manticoresearch/.translation-cache/Searching/Options.md.json

{
    "1605614aafa5d2f36701204327fd1e20f80e18d79ceab69bdf7e49c149cec972": {
        "original": "You can also enforce a guaranteed groupby/aggregate accuracy mode using the [accurate_aggregation](../Searching/Options.md#accurate_aggregation) option.\n\n### max_query_time\nSets the maximum search query time in milliseconds. Must be a non-negative integer. The default value is 0, which means \"do not limit.\" Local search queries will be stopped once the specified time has elapsed. Note that if you're performing a search that queries multiple local tables, this limit applies to each table separately. Be aware that this may slightly increase the query's response time due to the overhead caused by constantly tracking whether it's time to stop the query.\n\n### max_predicted_time\nInteger. Maximum predicted search time; see [predicted_time_costs](../Server_settings/Searchd.md#predicted_time_costs).\n\n### morphology\n`none` allows replacing all query terms with their exact forms if the table was built with [index_exact_words](../Creating_a_table/NLP_and_tokenization/Morphology.md#index_exact_words) enabled. This is useful for preventing stemming or lemmatizing query terms.\n\n### not_terms_only_allowed\n<!-- example not_terms_only_allowed -->\n`0` or `1` allows standalone [negation](../Searching/Full_text_matching/Operators.md#Negation-operator) for the query. The default is 0. See also the corresponding [global setting](../Server_settings/Searchd.md#not_terms_only_allowed).\n\n<!-- request SQL -->\nCODE_BLOCK_9\n<!-- end -->\n\n### ranker\nChoose from the following options:\n* `proximity_bm25`\n* `bm25`\n* `none`\n* `wordcount`\n* `proximity`\n* `matchany`\n* `fieldmask`\n* `sph04`\n* `expr`\n* `export`\n\nFor more details on each ranker, refer to [Search results ranking](../Searching/Sorting_and_ranking.md#Available-built-in-rankers).\n\n### rand_seed\nAllows you to specify a specific integer seed value for an `ORDER BY RAND()` query, for example: `... OPTION rand_seed=1234`. By default, a new and different seed value is autogenerated for every query.\n\n### retry_count\nInteger. Distributed retries count.\n\n### retry_delay\nInteger. Distributed retry delay, in milliseconds.\n\n### scroll\n\nString. A scroll token for paginating results using the [Scroll pagination approach](../Searching/Pagination.md#Scroll-Search-Option).\n\n### sort_method\n* `pq` - priority queue, set by default\n* `kbuffer` - provides faster sorting for already pre-sorted data, e.g., table data sorted by id\nThe result set is the same in both cases; choosing one option or the other may simply improve (or worsen) performance.\n\n### threads\nLimits the max number of threads used for current query processing. Default - no limit (the query can occupy all [threads](../Server_settings/Searchd.md#threads) as defined globally).\nFor a batch of queries, the option must be attached to the very first query in the batch, and it is then applied when the working queue is created and is effective for the entire batch. This option has the same meaning as the option [max_threads_per_query](../Server_settings/Searchd.md#max_threads_per_query), but is applied only to the current query or batch of queries.\n\n### token_filter\nQuoted, colon-separated string of `library name:plugin name:optional string of settings`. A query-time token filter is created for each search when full-text is invoked by every table involved, allowing you to implement a custom tokenizer that generates tokens according to custom rules.\nCODE_BLOCK_10\n### expansion_limit\nRestricts the maximum number of expanded keywords for a single wildcard, with a default value of 0 indicating no limit. For additional details, refer to [expansion_limit](../Server_settings/Searchd.md#expansion_limit).\n\n## Query optimizer hints\n\n<!-- example options_force -->\n\nIn rare cases, Manticore's built-in query analyzer may be incorrect in understanding a query and determining whether a docid index, secondary indexes, or columnar scan should be used. To override the query optimizer's decisions, you can use the following hints in your query:\n\n* `/*+ DocidIndex(id) */`  to force the use of a docid index, `/*+ NO_DocidIndex(id) */` to tell the optimizer to ignore it\n* `/*+ SecondaryIndex(<attr_name1>[, <attr_nameN>]) */` to force the use of a secondary index (if available), `/*+ NO_SecondaryIndex(id) */`  to tell the optimizer to ignore it\n* `/*+ ColumnarScan(<attr_name1>[, <attr_nameN>]) */`  to force the use of a columnar scan (if the attribute is columnar), `/*+ NO_ColumnarScan(id) */` to tell the optimizer to ignore it\n\nNote that when executing a full-text query with filters, the query optimizer decides between intersecting the results of the full-text tree with the filter results or using a standard match-then-filter approach. Specifying *any* hint will force the daemon to use the code path that performs the intersection of the full-text tree results with the filter results.\n\nFor more information on how the query optimizer works, refer to the [Cost based optimizer](../Searching/Cost_based_optimizer.md) page.\n\n<!-- request SQL -->\n\nCODE_BLOCK_11\n\n<!-- end -->\n\n<!-- example comments -->\nWhen using a MySQL/MariaDB client, make sure to include the `--comments` flag to enable the hints in your queries.\n\n<!-- request mysql -->\nCODE_BLOCK_12\n<!-- end -->\n\n<!-- proofread -->\n\n",
        "translations": {
            "chinese": "\u60a8\u8fd8\u53ef\u4ee5\u4f7f\u7528 [accurate_aggregation](../Searching/Options.md#accurate_aggregation) \u9009\u9879\u5f3a\u5236\u6267\u884c\u4fdd\u969c\u7684 groupby/\u805a\u5408\u51c6\u786e\u6a21\u5f0f\u3002\n\n### max_query_time\n\u8bbe\u7f6e\u6700\u5927\u641c\u7d22\u67e5\u8be2\u65f6\u95f4\uff0c\u5355\u4f4d\u4e3a\u6beb\u79d2\u3002\u5fc5\u987b\u662f\u975e\u8d1f\u6574\u6570\u3002\u9ed8\u8ba4\u503c\u4e3a 0\uff0c\u8868\u793a\u201c\u4e0d\u9650\u5236\u201d\u3002\u672c\u5730\u641c\u7d22\u67e5\u8be2\u5c06\u5728\u6307\u5b9a\u65f6\u95f4\u7ed3\u675f\u540e\u505c\u6b62\u3002\u8bf7\u6ce8\u610f\uff0c\u5982\u679c\u60a8\u6267\u884c\u7684\u662f\u67e5\u8be2\u591a\u4e2a\u672c\u5730\u8868\u7684\u641c\u7d22\uff0c\u5219\u6b64\u9650\u5236\u5206\u522b\u9002\u7528\u4e8e\u6bcf\u4e2a\u8868\u3002\u9700\u6ce8\u610f\uff0c\u7531\u4e8e\u4e0d\u65ad\u68c0\u67e5\u662f\u5426\u5e94\u505c\u6b62\u67e5\u8be2\u7684\u5f00\u9500\uff0c\u8fd9\u53ef\u80fd\u4f1a\u7a0d\u5fae\u589e\u52a0\u67e5\u8be2\u7684\u54cd\u5e94\u65f6\u95f4\u3002\n\n### max_predicted_time\n\u6574\u6570\u3002\u6700\u5927\u9884\u6d4b\u641c\u7d22\u65f6\u95f4\uff1b\u8be6\u89c1 [predicted_time_costs](../Server_settings/Searchd.md#predicted_time_costs)\u3002\n\n### morphology\n`none` \u5141\u8bb8\u7528\u5b83\u4eec\u7684\u7cbe\u786e\u5f62\u5f0f\u66ff\u6362\u6240\u6709\u67e5\u8be2\u8bcd\uff0c\u5982\u679c\u8868\u683c\u662f\u4f7f\u7528\u542f\u7528\u7684 [index_exact_words](../Creating_a_table/NLP_and_tokenization/Morphology.md#index_exact_words) \u6784\u5efa\u7684\u3002\u8fd9\u5bf9\u4e8e\u9632\u6b62\u67e5\u8be2\u8bcd\u88ab\u8bcd\u5e72\u5316\u6216\u8bcd\u5f62\u8fd8\u539f\u975e\u5e38\u6709\u7528\u3002\n\n### not_terms_only_allowed\n<!-- example not_terms_only_allowed -->\n`0` \u6216 `1` \u5141\u8bb8\u67e5\u8be2\u4e2d\u4f7f\u7528\u72ec\u7acb\u7684[\u5426\u5b9a](../Searching/Full_text_matching/Operators.md#Negation-operator)\u64cd\u4f5c\u7b26\u3002\u9ed8\u8ba4\u503c\u662f 0\u3002\u53e6\u8bf7\u53c2\u89c1\u76f8\u5e94\u7684[\u5168\u5c40\u8bbe\u7f6e](../Server_settings/Searchd.md#not_terms_only_allowed)\u3002\n\n<!-- request SQL -->\nCODE_BLOCK_9\n<!-- end -->\n\n### ranker\n\u53ef\u4ece\u4ee5\u4e0b\u9009\u9879\u4e2d\u9009\u62e9\uff1a\n* `proximity_bm25`\n* `bm25`\n* `none`\n* `wordcount`\n* `proximity`\n* `matchany`\n* `fieldmask`\n* `sph04`\n* `expr`\n* `export`\n\n\u6709\u5173\u6bcf\u4e2a\u6392\u5e8f\u5668\u7684\u66f4\u591a\u8be6\u7ec6\u4fe1\u606f\uff0c\u8bf7\u53c2\u9605 [\u641c\u7d22\u7ed3\u679c\u6392\u540d](../Searching/Sorting_and_ranking.md#Available-built-in-rankers)\u3002\n\n### rand_seed\n\u5141\u8bb8\u60a8\u4e3a `ORDER BY RAND()` \u67e5\u8be2\u6307\u5b9a\u7279\u5b9a\u7684\u6574\u6570\u79cd\u5b50\u503c\uff0c\u4f8b\u5982\uff1a`... OPTION rand_seed=1234`\u3002\u9ed8\u8ba4\u60c5\u51b5\u4e0b\uff0c\u6bcf\u4e2a\u67e5\u8be2\u90fd\u4f1a\u81ea\u52a8\u751f\u6210\u4e00\u4e2a\u65b0\u7684\u4e0d\u540c\u7684\u79cd\u5b50\u503c\u3002\n\n### retry_count\n\u6574\u6570\u3002\u5206\u5e03\u5f0f\u91cd\u8bd5\u6b21\u6570\u3002\n\n### retry_delay\n\u6574\u6570\u3002\u5206\u5e03\u5f0f\u91cd\u8bd5\u5ef6\u8fdf\uff0c\u5355\u4f4d\u4e3a\u6beb\u79d2\u3002\n\n### scroll\n\n\u5b57\u7b26\u4e32\u3002\u4f7f\u7528[\u6eda\u52a8\u5206\u9875\u65b9\u6cd5](../Searching/Pagination.md#Scroll-Search-Option)\u8fdb\u884c\u7ed3\u679c\u5206\u9875\u7684\u6eda\u52a8\u4ee4\u724c\u3002\n\n### sort_method\n* `pq` - \u4f18\u5148\u961f\u5217\uff0c\u9ed8\u8ba4\u8bbe\u7f6e\n* `kbuffer` - \u5bf9\u5df2\u9884\u6392\u5e8f\u7684\u6570\u636e\u63d0\u4f9b\u66f4\u5feb\u7684\u6392\u5e8f\uff0c\u4f8b\u5982\u6309 id \u6392\u5e8f\u7684\u8868\u6570\u636e\n\u4e24\u79cd\u60c5\u51b5\u4e0b\u7684\u7ed3\u679c\u96c6\u662f\u76f8\u540c\u7684\uff1b\u9009\u62e9\u5176\u4e2d\u4e00\u4e2a\u9009\u9879\u53ef\u80fd\u4ec5\u4ec5\u662f\u6539\u5584\uff08\u6216\u6076\u5316\uff09\u6027\u80fd\u3002\n\n### threads\n\u9650\u5236\u5f53\u524d\u67e5\u8be2\u5904\u7406\u4f7f\u7528\u7684\u6700\u5927\u7ebf\u7a0b\u6570\u3002\u9ed8\u8ba4 - \u65e0\u9650\u5236\uff08\u67e5\u8be2\u53ef\u4ee5\u4f7f\u7528\u6240\u6709\u5168\u5c40\u5b9a\u4e49\u7684 [threads](../Server_settings/Searchd.md#threads)\uff09\u3002\n\u5bf9\u4e8e\u4e00\u6279\u67e5\u8be2\uff0c\u8be5\u9009\u9879\u5fc5\u987b\u9644\u52a0\u4e8e\u8be5\u6279\u4e2d\u7684\u7b2c\u4e00\u4e2a\u67e5\u8be2\uff0c\u7136\u540e\u5728\u521b\u5efa\u5de5\u4f5c\u961f\u5217\u65f6\u5e94\u7528\uff0c\u5e76\u5bf9\u6574\u4e2a\u6279\u6b21\u751f\u6548\u3002\u6b64\u9009\u9879\u4e0e [max_threads_per_query](../Server_settings/Searchd.md#max_threads_per_query) \u5177\u6709\u76f8\u540c\u542b\u4e49\uff0c\u4f46\u4ec5\u5e94\u7528\u4e8e\u5f53\u524d\u67e5\u8be2\u6216\u67e5\u8be2\u6279\u6b21\u3002\n\n### token_filter\n\u5e26\u5f15\u53f7\u7684\u3001\u7528\u5192\u53f7\u5206\u9694\u7684\u5b57\u7b26\u4e32\u683c\u5f0f\u4e3a `library name:plugin name:optional string of settings`\u3002\u6bcf\u5f53\u6d89\u53ca\u7684\u6bcf\u4e2a\u8868\u8c03\u7528\u5168\u6587\u641c\u7d22\u65f6\uff0c\u90fd\u4f1a\u4e3a\u8be5\u67e5\u8be2\u521b\u5efa\u4e00\u4e2a\u67e5\u8be2\u65f6\u4ee4\u724c\u8fc7\u6ee4\u5668\uff0c\u5141\u8bb8\u60a8\u5b9e\u73b0\u6839\u636e\u81ea\u5b9a\u4e49\u89c4\u5219\u751f\u6210\u4ee4\u724c\u7684\u81ea\u5b9a\u4e49\u5206\u8bcd\u5668\u3002\nCODE_BLOCK_10\n### expansion_limit\n\u9650\u5236\u5355\u4e2a\u901a\u914d\u7b26\u7684\u6700\u5927\u6269\u5c55\u5173\u952e\u5b57\u6570\u91cf\uff0c\u9ed8\u8ba4\u503c\u4e3a 0\uff0c\u8868\u793a\u65e0\u9650\u5236\u3002\u66f4\u591a\u8be6\u7ec6\u4fe1\u606f\uff0c\u8bf7\u53c2\u9605 [expansion_limit](../Server_settings/Searchd.md#expansion_limit)\u3002\n\n## \u67e5\u8be2\u4f18\u5316\u5668\u63d0\u793a\n\n<!-- example options_force -->\n\n\u5728\u6781\u5c11\u6570\u60c5\u51b5\u4e0b\uff0cManticore \u5185\u7f6e\u7684\u67e5\u8be2\u5206\u6790\u5668\u53ef\u80fd\u65e0\u6cd5\u6b63\u786e\u7406\u89e3\u67e5\u8be2\u5e76\u786e\u5b9a\u5e94\u4f7f\u7528 docid \u7d22\u5f15\u3001\u4e8c\u7ea7\u7d22\u5f15\u8fd8\u662f\u5217\u626b\u63cf\u3002\u4e3a\u4e86\u8986\u76d6\u67e5\u8be2\u4f18\u5316\u5668\u7684\u51b3\u7b56\uff0c\u60a8\u53ef\u4ee5\u5728\u67e5\u8be2\u4e2d\u4f7f\u7528\u4ee5\u4e0b\u63d0\u793a\uff1a\n\n* `/*+ DocidIndex(id) */`  \u5f3a\u5236\u4f7f\u7528 docid \u7d22\u5f15\uff0c`/*+ NO_DocidIndex(id) */`  \u544a\u8bc9\u4f18\u5316\u5668\u5ffd\u7565\u5b83\n* `/*+ SecondaryIndex(<attr_name1>[, <attr_nameN>]) */`  \u5f3a\u5236\u4f7f\u7528\u4e8c\u7ea7\u7d22\u5f15\uff08\u5982\u679c\u53ef\u7528\uff09\uff0c`/*+ NO_SecondaryIndex(id) */`  \u544a\u8bc9\u4f18\u5316\u5668\u5ffd\u7565\u5b83\n* `/*+ ColumnarScan(<attr_name1>[, <attr_nameN>]) */`  \u5f3a\u5236\u4f7f\u7528\u5217\u626b\u63cf\uff08\u5982\u679c\u5c5e\u6027\u4e3a\u5217\u5f0f\uff09\uff0c`/*+ NO_ColumnarScan(id) */` \u544a\u8bc9\u4f18\u5316\u5668\u5ffd\u7565\u5b83\n\n\u8bf7\u6ce8\u610f\uff0c\u5f53\u6267\u884c\u5e26\u6709\u8fc7\u6ee4\u5668\u7684\u5168\u6587\u67e5\u8be2\u65f6\uff0c\u67e5\u8be2\u4f18\u5316\u5668\u4f1a\u51b3\u5b9a\u662f\u5c06\u5168\u6587\u6811\u7ed3\u679c\u4e0e\u8fc7\u6ee4\u5668\u7ed3\u679c\u8fdb\u884c\u4ea4\u96c6\uff0c\u8fd8\u662f\u4f7f\u7528\u6807\u51c6\u7684\u5339\u914d\u540e\u8fc7\u6ee4\u65b9\u6cd5\u3002\u6307\u5b9a*\u4efb\u4f55*\u63d0\u793a\u5c06\u5f3a\u5236\u5b88\u62a4\u8fdb\u7a0b\u4f7f\u7528\u6267\u884c\u5168\u6587\u6811\u7ed3\u679c\u4e0e\u8fc7\u6ee4\u5668\u7ed3\u679c\u4ea4\u96c6\u7684\u4ee3\u7801\u8def\u5f84\u3002\n\n\u6709\u5173\u67e5\u8be2\u4f18\u5316\u5668\u5de5\u4f5c\u539f\u7406\u7684\u66f4\u591a\u4fe1\u606f\uff0c\u8bf7\u53c2\u9605[\u57fa\u4e8e\u6210\u672c\u7684\u4f18\u5316\u5668](../Searching/Cost_based_optimizer.md)\u9875\u9762\u3002\n\n<!-- request SQL -->\n\nCODE_BLOCK_11\n\n<!-- end -->\n\n<!-- example comments -->\n\u4f7f\u7528 MySQL/MariaDB \u5ba2\u6237\u7aef\u65f6\uff0c\u8bf7\u786e\u4fdd\u6dfb\u52a0 `--comments` \u6807\u5fd7\u4ee5\u542f\u7528\u67e5\u8be2\u4e2d\u7684\u63d0\u793a\u3002\n\n<!-- request mysql -->\nCODE_BLOCK_12\n<!-- end -->\n\n<!-- proofread -->",
            "russian": "\u0412\u044b \u0442\u0430\u043a\u0436\u0435 \u043c\u043e\u0436\u0435\u0442\u0435 \u043f\u0440\u0438\u043c\u0435\u043d\u0438\u0442\u044c \u0440\u0435\u0436\u0438\u043c \u0433\u0430\u0440\u0430\u043d\u0442\u0438\u0440\u043e\u0432\u0430\u043d\u043d\u043e\u0439 \u0442\u043e\u0447\u043d\u043e\u0441\u0442\u0438 \u0433\u0440\u0443\u043f\u043f\u0438\u0440\u043e\u0432\u043a\u0438/\u0430\u0433\u0440\u0435\u0433\u0430\u0446\u0438\u0438 \u0441 \u043f\u043e\u043c\u043e\u0449\u044c\u044e \u043e\u043f\u0446\u0438\u0438 [accurate_aggregation](../Searching/Options.md#accurate_aggregation).\n\n### max_query_time\n\u0423\u0441\u0442\u0430\u043d\u0430\u0432\u043b\u0438\u0432\u0430\u0435\u0442 \u043c\u0430\u043a\u0441\u0438\u043c\u0430\u043b\u044c\u043d\u043e\u0435 \u0432\u0440\u0435\u043c\u044f \u0432\u044b\u043f\u043e\u043b\u043d\u0435\u043d\u0438\u044f \u043f\u043e\u0438\u0441\u043a\u043e\u0432\u043e\u0433\u043e \u0437\u0430\u043f\u0440\u043e\u0441\u0430 \u0432 \u043c\u0438\u043b\u043b\u0438\u0441\u0435\u043a\u0443\u043d\u0434\u0430\u0445. \u0414\u043e\u043b\u0436\u043d\u043e \u0431\u044b\u0442\u044c \u043d\u0435\u043e\u0442\u0440\u0438\u0446\u0430\u0442\u0435\u043b\u044c\u043d\u044b\u043c \u0446\u0435\u043b\u044b\u043c \u0447\u0438\u0441\u043b\u043e\u043c. \u0417\u043d\u0430\u0447\u0435\u043d\u0438\u0435 \u043f\u043e \u0443\u043c\u043e\u043b\u0447\u0430\u043d\u0438\u044e \u2014 0, \u0447\u0442\u043e \u043e\u0437\u043d\u0430\u0447\u0430\u0435\u0442 \u00ab\u043d\u0435 \u043e\u0433\u0440\u0430\u043d\u0438\u0447\u0438\u0432\u0430\u0442\u044c\u0441\u044f\u00bb. \u041b\u043e\u043a\u0430\u043b\u044c\u043d\u044b\u0435 \u043f\u043e\u0438\u0441\u043a\u043e\u0432\u044b\u0435 \u0437\u0430\u043f\u0440\u043e\u0441\u044b \u0431\u0443\u0434\u0443\u0442 \u043f\u0440\u0435\u0440\u0432\u0430\u043d\u044b \u043f\u043e\u0441\u043b\u0435 \u0438\u0441\u0442\u0435\u0447\u0435\u043d\u0438\u044f \u0437\u0430\u0434\u0430\u043d\u043d\u043e\u0433\u043e \u0432\u0440\u0435\u043c\u0435\u043d\u0438. \u041e\u0431\u0440\u0430\u0442\u0438\u0442\u0435 \u0432\u043d\u0438\u043c\u0430\u043d\u0438\u0435, \u0447\u0442\u043e \u0435\u0441\u043b\u0438 \u0432\u044b \u0432\u044b\u043f\u043e\u043b\u043d\u044f\u0435\u0442\u0435 \u043f\u043e\u0438\u0441\u043a, \u043e\u0431\u0440\u0430\u0449\u0430\u044e\u0449\u0438\u0439\u0441\u044f \u043a \u043d\u0435\u0441\u043a\u043e\u043b\u044c\u043a\u0438\u043c \u043b\u043e\u043a\u0430\u043b\u044c\u043d\u044b\u043c \u0442\u0430\u0431\u043b\u0438\u0446\u0430\u043c, \u044d\u0442\u043e \u043e\u0433\u0440\u0430\u043d\u0438\u0447\u0435\u043d\u0438\u0435 \u043f\u0440\u0438\u043c\u0435\u043d\u044f\u0435\u0442\u0441\u044f \u043a \u043a\u0430\u0436\u0434\u043e\u0439 \u0442\u0430\u0431\u043b\u0438\u0446\u0435 \u043e\u0442\u0434\u0435\u043b\u044c\u043d\u043e. \u0411\u0443\u0434\u044c\u0442\u0435 \u0433\u043e\u0442\u043e\u0432\u044b \u043a \u0442\u043e\u043c\u0443, \u0447\u0442\u043e \u044d\u0442\u043e \u043c\u043e\u0436\u0435\u0442 \u043d\u0435\u043c\u043d\u043e\u0433\u043e \u0443\u0432\u0435\u043b\u0438\u0447\u0438\u0442\u044c \u0432\u0440\u0435\u043c\u044f \u043e\u0442\u043a\u043b\u0438\u043a\u0430 \u0437\u0430\u043f\u0440\u043e\u0441\u0430 \u0438\u0437-\u0437\u0430 \u043d\u0430\u043a\u043b\u0430\u0434\u043d\u044b\u0445 \u0440\u0430\u0441\u0445\u043e\u0434\u043e\u0432, \u0441\u0432\u044f\u0437\u0430\u043d\u043d\u044b\u0445 \u0441 \u043f\u043e\u0441\u0442\u043e\u044f\u043d\u043d\u044b\u043c \u043e\u0442\u0441\u043b\u0435\u0436\u0438\u0432\u0430\u043d\u0438\u0435\u043c \u043c\u043e\u043c\u0435\u043d\u0442\u0430, \u043a\u043e\u0433\u0434\u0430 \u043d\u0443\u0436\u043d\u043e \u043e\u0441\u0442\u0430\u043d\u043e\u0432\u0438\u0442\u044c \u0437\u0430\u043f\u0440\u043e\u0441.\n\n### max_predicted_time\n\u0426\u0435\u043b\u043e\u0435 \u0447\u0438\u0441\u043b\u043e. \u041c\u0430\u043a\u0441\u0438\u043c\u0430\u043b\u044c\u043d\u043e\u0435 \u043f\u0440\u043e\u0433\u043d\u043e\u0437\u0438\u0440\u0443\u0435\u043c\u043e\u0435 \u0432\u0440\u0435\u043c\u044f \u043f\u043e\u0438\u0441\u043a\u0430; \u0441\u043c\u043e\u0442\u0440\u0438\u0442\u0435 [predicted_time_costs](../Server_settings/Searchd.md#predicted_time_costs).\n\n### morphology\n`none` \u043f\u043e\u0437\u0432\u043e\u043b\u044f\u0435\u0442 \u0437\u0430\u043c\u0435\u043d\u044f\u0442\u044c \u0432\u0441\u0435 \u0442\u0435\u0440\u043c\u0438\u043d\u044b \u0437\u0430\u043f\u0440\u043e\u0441\u0430 \u0438\u0445 \u0442\u043e\u0447\u043d\u044b\u043c\u0438 \u0444\u043e\u0440\u043c\u0430\u043c\u0438, \u0435\u0441\u043b\u0438 \u0442\u0430\u0431\u043b\u0438\u0446\u0430 \u0431\u044b\u043b\u0430 \u0441\u043e\u0437\u0434\u0430\u043d\u0430 \u0441 \u0432\u043a\u043b\u044e\u0447\u0451\u043d\u043d\u043e\u0439 \u043e\u043f\u0446\u0438\u0435\u0439 [index_exact_words](../Creating_a_table/NLP_and_tokenization/Morphology.md#index_exact_words). \u042d\u0442\u043e \u043f\u043e\u043b\u0435\u0437\u043d\u043e \u0434\u043b\u044f \u043f\u0440\u0435\u0434\u043e\u0442\u0432\u0440\u0430\u0449\u0435\u043d\u0438\u044f \u0441\u0442\u0435\u043c\u043c\u0438\u043d\u0433\u0430 \u0438\u043b\u0438 \u043b\u0435\u043c\u043c\u0430\u0442\u0438\u0437\u0430\u0446\u0438\u0438 \u0442\u0435\u0440\u043c\u0438\u043d\u043e\u0432 \u0437\u0430\u043f\u0440\u043e\u0441\u0430.\n\n### not_terms_only_allowed\n<!-- example not_terms_only_allowed -->\n`0` \u0438\u043b\u0438 `1` \u0440\u0430\u0437\u0440\u0435\u0448\u0430\u0435\u0442 \u0441\u0430\u043c\u043e\u0441\u0442\u043e\u044f\u0442\u0435\u043b\u044c\u043d\u043e\u0435 [\u043e\u0442\u0440\u0438\u0446\u0430\u043d\u0438\u0435](../Searching/Full_text_matching/Operators.md#Negation-operator) \u0434\u043b\u044f \u0437\u0430\u043f\u0440\u043e\u0441\u0430. \u0417\u043d\u0430\u0447\u0435\u043d\u0438\u0435 \u043f\u043e \u0443\u043c\u043e\u043b\u0447\u0430\u043d\u0438\u044e \u2014 0. \u0421\u043c. \u0442\u0430\u043a\u0436\u0435 \u0441\u043e\u043e\u0442\u0432\u0435\u0442\u0441\u0442\u0432\u0443\u044e\u0449\u0443\u044e [\u0433\u043b\u043e\u0431\u0430\u043b\u044c\u043d\u0443\u044e \u043d\u0430\u0441\u0442\u0440\u043e\u0439\u043a\u0443](../Server_settings/Searchd.md#not_terms_only_allowed).\n\n<!-- request SQL -->\nCODE_BLOCK_9\n<!-- end -->\n\n### ranker\n\u0412\u044b\u0431\u0435\u0440\u0438\u0442\u0435 \u043e\u0434\u0438\u043d \u0438\u0437 \u0441\u043b\u0435\u0434\u0443\u044e\u0449\u0438\u0445 \u0432\u0430\u0440\u0438\u0430\u043d\u0442\u043e\u0432:\n* `proximity_bm25`\n* `bm25`\n* `none`\n* `wordcount`\n* `proximity`\n* `matchany`\n* `fieldmask`\n* `sph04`\n* `expr`\n* `export`\n\n\u041f\u043e\u0434\u0440\u043e\u0431\u043d\u0435\u0435 \u043e \u043a\u0430\u0436\u0434\u043e\u043c \u0440\u0430\u043d\u0436\u0438\u0440\u043e\u0432\u0449\u0438\u043a\u0435 \u0441\u043c\u043e\u0442\u0440\u0438\u0442\u0435 \u0432 \u0440\u0430\u0437\u0434\u0435\u043b\u0435 [\u0420\u0430\u043d\u0436\u0438\u0440\u043e\u0432\u0430\u043d\u0438\u0435 \u0440\u0435\u0437\u0443\u043b\u044c\u0442\u0430\u0442\u043e\u0432 \u043f\u043e\u0438\u0441\u043a\u0430](../Searching/Sorting_and_ranking.md#Available-built-in-rankers).\n\n### rand_seed\n\u041f\u043e\u0437\u0432\u043e\u043b\u044f\u0435\u0442 \u0443\u043a\u0430\u0437\u0430\u0442\u044c \u043a\u043e\u043d\u043a\u0440\u0435\u0442\u043d\u043e\u0435 \u0437\u043d\u0430\u0447\u0435\u043d\u0438\u0435 \u043d\u0430\u0447\u0430\u043b\u044c\u043d\u043e\u0433\u043e \u00ab\u0441\u0435\u043c\u0435\u043d\u0438\u00bb \u0434\u043b\u044f \u0437\u0430\u043f\u0440\u043e\u0441\u0430 `ORDER BY RAND()`, \u043d\u0430\u043f\u0440\u0438\u043c\u0435\u0440: `... OPTION rand_seed=1234`. \u041f\u043e \u0443\u043c\u043e\u043b\u0447\u0430\u043d\u0438\u044e \u0434\u043b\u044f \u043a\u0430\u0436\u0434\u043e\u0433\u043e \u0437\u0430\u043f\u0440\u043e\u0441\u0430 \u0430\u0432\u0442\u043e\u043c\u0430\u0442\u0438\u0447\u0435\u0441\u043a\u0438 \u0441\u043e\u0437\u0434\u0430\u0451\u0442\u0441\u044f \u043d\u043e\u0432\u043e\u0435 \u0438\u043d\u043e\u0435 \u0437\u043d\u0430\u0447\u0435\u043d\u0438\u0435.\n\n### retry_count\n\u0426\u0435\u043b\u043e\u0435 \u0447\u0438\u0441\u043b\u043e. \u041a\u043e\u043b\u0438\u0447\u0435\u0441\u0442\u0432\u043e \u043f\u043e\u0432\u0442\u043e\u0440\u043d\u044b\u0445 \u043f\u043e\u043f\u044b\u0442\u043e\u043a \u0432 \u0440\u0430\u0441\u043f\u0440\u0435\u0434\u0435\u043b\u0451\u043d\u043d\u043e\u043c \u0440\u0435\u0436\u0438\u043c\u0435.\n\n### retry_delay\n\u0426\u0435\u043b\u043e\u0435 \u0447\u0438\u0441\u043b\u043e. \u0417\u0430\u0434\u0435\u0440\u0436\u043a\u0430 \u043c\u0435\u0436\u0434\u0443 \u043f\u043e\u043f\u044b\u0442\u043a\u0430\u043c\u0438 \u0432 \u0440\u0430\u0441\u043f\u0440\u0435\u0434\u0435\u043b\u0451\u043d\u043d\u043e\u043c \u0440\u0435\u0436\u0438\u043c\u0435, \u0432 \u043c\u0438\u043b\u043b\u0438\u0441\u0435\u043a\u0443\u043d\u0434\u0430\u0445.\n\n### scroll\n\n\u0421\u0442\u0440\u043e\u043a\u0430. \u0422\u043e\u043a\u0435\u043d scroll \u0434\u043b\u044f \u043f\u043e\u044d\u0442\u0430\u043f\u043d\u043e\u0433\u043e \u043f\u043e\u043b\u0443\u0447\u0435\u043d\u0438\u044f \u0440\u0435\u0437\u0443\u043b\u044c\u0442\u0430\u0442\u043e\u0432 \u0441 \u043f\u043e\u043c\u043e\u0449\u044c\u044e [Scroll pagination approach](../Searching/Pagination.md#Scroll-Search-Option).\n\n### sort_method\n* `pq` - \u043e\u0447\u0435\u0440\u0435\u0434\u044c \u0441 \u043f\u0440\u0438\u043e\u0440\u0438\u0442\u0435\u0442\u043e\u043c, \u0438\u0441\u043f\u043e\u043b\u044c\u0437\u0443\u0435\u0442\u0441\u044f \u043f\u043e \u0443\u043c\u043e\u043b\u0447\u0430\u043d\u0438\u044e\n* `kbuffer` - \u043e\u0431\u0435\u0441\u043f\u0435\u0447\u0438\u0432\u0430\u0435\u0442 \u0431\u043e\u043b\u0435\u0435 \u0431\u044b\u0441\u0442\u0440\u0443\u044e \u0441\u043e\u0440\u0442\u0438\u0440\u043e\u0432\u043a\u0443 \u0434\u043b\u044f \u0443\u0436\u0435 \u0447\u0430\u0441\u0442\u0438\u0447\u043d\u043e \u043e\u0442\u0441\u043e\u0440\u0442\u0438\u0440\u043e\u0432\u0430\u043d\u043d\u044b\u0445 \u0434\u0430\u043d\u043d\u044b\u0445, \u043d\u0430\u043f\u0440\u0438\u043c\u0435\u0440, \u0434\u043b\u044f \u0434\u0430\u043d\u043d\u044b\u0445 \u0442\u0430\u0431\u043b\u0438\u0446\u044b, \u043e\u0442\u0441\u043e\u0440\u0442\u0438\u0440\u043e\u0432\u0430\u043d\u043d\u044b\u0445 \u043f\u043e id\n\u041d\u0430\u0431\u043e\u0440 \u0440\u0435\u0437\u0443\u043b\u044c\u0442\u0430\u0442\u043e\u0432 \u0432 \u043e\u0431\u043e\u0438\u0445 \u0441\u043b\u0443\u0447\u0430\u044f\u0445 \u043e\u0434\u0438\u043d\u0430\u043a\u043e\u0432; \u0432\u044b\u0431\u043e\u0440 \u043e\u0434\u043d\u043e\u0433\u043e \u0438\u0437 \u0432\u0430\u0440\u0438\u0430\u043d\u0442\u043e\u0432 \u043c\u043e\u0436\u0435\u0442 \u043b\u0438\u0448\u044c \u0443\u043b\u0443\u0447\u0448\u0438\u0442\u044c (\u0438\u043b\u0438 \u0443\u0445\u0443\u0434\u0448\u0438\u0442\u044c) \u043f\u0440\u043e\u0438\u0437\u0432\u043e\u0434\u0438\u0442\u0435\u043b\u044c\u043d\u043e\u0441\u0442\u044c.\n\n### threads\n\u041e\u0433\u0440\u0430\u043d\u0438\u0447\u0438\u0432\u0430\u0435\u0442 \u043c\u0430\u043a\u0441\u0438\u043c\u0430\u043b\u044c\u043d\u043e\u0435 \u0447\u0438\u0441\u043b\u043e \u043f\u043e\u0442\u043e\u043a\u043e\u0432, \u0438\u0441\u043f\u043e\u043b\u044c\u0437\u0443\u0435\u043c\u044b\u0445 \u0434\u043b\u044f \u043e\u0431\u0440\u0430\u0431\u043e\u0442\u043a\u0438 \u0442\u0435\u043a\u0443\u0449\u0435\u0433\u043e \u0437\u0430\u043f\u0440\u043e\u0441\u0430. \u041f\u043e \u0443\u043c\u043e\u043b\u0447\u0430\u043d\u0438\u044e \u2014 \u0431\u0435\u0437 \u043e\u0433\u0440\u0430\u043d\u0438\u0447\u0435\u043d\u0438\u0439 (\u0437\u0430\u043f\u0440\u043e\u0441 \u043c\u043e\u0436\u0435\u0442 \u0438\u0441\u043f\u043e\u043b\u044c\u0437\u043e\u0432\u0430\u0442\u044c \u0432\u0441\u0435 [\u043f\u043e\u0442\u043e\u043a\u0438](../Server_settings/Searchd.md#threads), \u0443\u0441\u0442\u0430\u043d\u043e\u0432\u043b\u0435\u043d\u043d\u044b\u0435 \u0433\u043b\u043e\u0431\u0430\u043b\u044c\u043d\u043e).\n\u0414\u043b\u044f \u043f\u0430\u043a\u0435\u0442\u0430 \u0437\u0430\u043f\u0440\u043e\u0441\u043e\u0432 \u043e\u043f\u0446\u0438\u044f \u0434\u043e\u043b\u0436\u043d\u0430 \u0431\u044b\u0442\u044c \u043f\u0440\u0438\u043c\u0435\u043d\u0435\u043d\u0430 \u043a \u043f\u0435\u0440\u0432\u043e\u043c\u0443 \u0437\u0430\u043f\u0440\u043e\u0441\u0443 \u0432 \u043f\u0430\u043a\u0435\u0442\u0435, \u043f\u043e\u0441\u043b\u0435 \u0447\u0435\u0433\u043e \u043e\u043d\u0430 \u043f\u0440\u0438\u043c\u0435\u043d\u044f\u0435\u0442\u0441\u044f \u043f\u0440\u0438 \u0441\u043e\u0437\u0434\u0430\u043d\u0438\u0438 \u0440\u0430\u0431\u043e\u0447\u0435\u0439 \u043e\u0447\u0435\u0440\u0435\u0434\u0438 \u0438 \u0434\u0435\u0439\u0441\u0442\u0432\u0443\u0435\u0442 \u043d\u0430 \u0432\u0435\u0441\u044c \u043f\u0430\u043a\u0435\u0442. \u042d\u0442\u0430 \u043e\u043f\u0446\u0438\u044f \u044d\u043a\u0432\u0438\u0432\u0430\u043b\u0435\u043d\u0442\u043d\u0430 \u043e\u043f\u0446\u0438\u0438 [max_threads_per_query](../Server_settings/Searchd.md#max_threads_per_query), \u043d\u043e \u043f\u0440\u0438\u043c\u0435\u043d\u044f\u0435\u0442\u0441\u044f \u0442\u043e\u043b\u044c\u043a\u043e \u043a \u0442\u0435\u043a\u0443\u0449\u0435\u043c\u0443 \u0437\u0430\u043f\u0440\u043e\u0441\u0443 \u0438\u043b\u0438 \u043f\u0430\u043a\u0435\u0442\u0443 \u0437\u0430\u043f\u0440\u043e\u0441\u043e\u0432.\n\n### token_filter\n\u0417\u043d\u0430\u0447\u0435\u043d\u0438\u0435 \u0432 \u043a\u0430\u0432\u044b\u0447\u043a\u0430\u0445, \u0441\u0442\u0440\u043e\u043a\u0430 \u0441 \u0440\u0430\u0437\u0434\u0435\u043b\u0438\u0442\u0435\u043b\u0435\u043c \u0434\u0432\u043e\u0435\u0442\u043e\u0447\u0438\u0435\u043c \u0432 \u0444\u043e\u0440\u043c\u0430\u0442\u0435 `\u0438\u043c\u044f_\u0431\u0438\u0431\u043b\u0438\u043e\u0442\u0435\u043a\u0438:\u0438\u043c\u044f_\u043f\u043b\u0430\u0433\u0438\u043d\u0430:\u043d\u0435\u043e\u0431\u044f\u0437\u0430\u0442\u0435\u043b\u044c\u043d\u0430\u044f_\u0441\u0442\u0440\u043e\u043a\u0430_\u043d\u0430\u0441\u0442\u0440\u043e\u0435\u043a`. \u041f\u0440\u0438 \u0432\u044b\u0437\u043e\u0432\u0435 \u043f\u043e\u043b\u043d\u043e\u0442\u0435\u043a\u0441\u0442\u043e\u0432\u043e\u0433\u043e \u043f\u043e\u0438\u0441\u043a\u0430 \u0434\u043b\u044f \u043a\u0430\u0436\u0434\u043e\u0439 \u0437\u0430\u0434\u0435\u0439\u0441\u0442\u0432\u043e\u0432\u0430\u043d\u043d\u043e\u0439 \u0442\u0430\u0431\u043b\u0438\u0446\u044b \u0441\u043e\u0437\u0434\u0430\u0451\u0442\u0441\u044f \u0444\u0438\u043b\u044c\u0442\u0440 \u0442\u043e\u043a\u0435\u043d\u043e\u0432 \u0432 \u0440\u0435\u0436\u0438\u043c\u0435 \u0432\u044b\u043f\u043e\u043b\u043d\u0435\u043d\u0438\u044f \u0437\u0430\u043f\u0440\u043e\u0441\u0430, \u0447\u0442\u043e \u043f\u043e\u0437\u0432\u043e\u043b\u044f\u0435\u0442 \u0440\u0435\u0430\u043b\u0438\u0437\u043e\u0432\u0430\u0442\u044c \u0441\u043e\u0431\u0441\u0442\u0432\u0435\u043d\u043d\u044b\u0439 \u0442\u043e\u043a\u0435\u043d\u0438\u0437\u0430\u0442\u043e\u0440, \u0433\u0435\u043d\u0435\u0440\u0438\u0440\u0443\u044e\u0449\u0438\u0439 \u0442\u043e\u043a\u0435\u043d\u044b \u043f\u043e \u043f\u043e\u043b\u044c\u0437\u043e\u0432\u0430\u0442\u0435\u043b\u044c\u0441\u043a\u0438\u043c \u043f\u0440\u0430\u0432\u0438\u043b\u0430\u043c.\nCODE_BLOCK_10\n### expansion_limit\n\u041e\u0433\u0440\u0430\u043d\u0438\u0447\u0438\u0432\u0430\u0435\u0442 \u043c\u0430\u043a\u0441\u0438\u043c\u0430\u043b\u044c\u043d\u043e\u0435 \u0447\u0438\u0441\u043b\u043e \u0440\u0430\u0441\u0448\u0438\u0440\u0435\u043d\u043d\u044b\u0445 \u043a\u043b\u044e\u0447\u0435\u0432\u044b\u0445 \u0441\u043b\u043e\u0432 \u0434\u043b\u044f \u043e\u0434\u043d\u043e\u0433\u043e \u043f\u043e\u0434\u0441\u0442\u0430\u043d\u043e\u0432\u043e\u0447\u043d\u043e\u0433\u043e \u0437\u043d\u0430\u043a\u0430, \u043f\u043e \u0443\u043c\u043e\u043b\u0447\u0430\u043d\u0438\u044e 0 \u043e\u0437\u043d\u0430\u0447\u0430\u0435\u0442 \u043e\u0442\u0441\u0443\u0442\u0441\u0442\u0432\u0438\u0435 \u043e\u0433\u0440\u0430\u043d\u0438\u0447\u0435\u043d\u0438\u0439. \u0414\u043e\u043f\u043e\u043b\u043d\u0438\u0442\u0435\u043b\u044c\u043d\u0443\u044e \u0438\u043d\u0444\u043e\u0440\u043c\u0430\u0446\u0438\u044e \u0441\u043c. \u0432 \u0440\u0430\u0437\u0434\u0435\u043b\u0435 [expansion_limit](../Server_settings/Searchd.md#expansion_limit).\n\n## \u041f\u043e\u0434\u0441\u043a\u0430\u0437\u043a\u0438 \u043e\u043f\u0442\u0438\u043c\u0438\u0437\u0430\u0442\u043e\u0440\u0430 \u0437\u0430\u043f\u0440\u043e\u0441\u043e\u0432\n\n<!-- example options_force -->\n\n\u0412 \u0440\u0435\u0434\u043a\u0438\u0445 \u0441\u043b\u0443\u0447\u0430\u044f\u0445 \u0432\u0441\u0442\u0440\u043e\u0435\u043d\u043d\u044b\u0439 \u0430\u043d\u0430\u043b\u0438\u0437\u0430\u0442\u043e\u0440 \u0437\u0430\u043f\u0440\u043e\u0441\u043e\u0432 Manticore \u043c\u043e\u0436\u0435\u0442 \u043e\u0448\u0438\u0431\u043e\u0447\u043d\u043e \u0438\u043d\u0442\u0435\u0440\u043f\u0440\u0435\u0442\u0438\u0440\u043e\u0432\u0430\u0442\u044c \u0437\u0430\u043f\u0440\u043e\u0441 \u0438 \u043e\u043f\u0440\u0435\u0434\u0435\u043b\u0438\u0442\u044c, \u0441\u043b\u0435\u0434\u0443\u0435\u0442 \u043b\u0438 \u0438\u0441\u043f\u043e\u043b\u044c\u0437\u043e\u0432\u0430\u0442\u044c \u0438\u043d\u0434\u0435\u043a\u0441 docid, \u0432\u0442\u043e\u0440\u0438\u0447\u043d\u044b\u0435 \u0438\u043d\u0434\u0435\u043a\u0441\u044b \u0438\u043b\u0438 \u043f\u043e\u0441\u043a\u043e\u043b\u043e\u043d\u043d\u044b\u0439 \u0441\u043a\u0430\u043d. \u0427\u0442\u043e\u0431\u044b \u043f\u0435\u0440\u0435\u043e\u043f\u0440\u0435\u0434\u0435\u043b\u0438\u0442\u044c \u0440\u0435\u0448\u0435\u043d\u0438\u044f \u043e\u043f\u0442\u0438\u043c\u0438\u0437\u0430\u0442\u043e\u0440\u0430 \u0437\u0430\u043f\u0440\u043e\u0441\u043e\u0432, \u043c\u043e\u0436\u043d\u043e \u0438\u0441\u043f\u043e\u043b\u044c\u0437\u043e\u0432\u0430\u0442\u044c \u0441\u043b\u0435\u0434\u0443\u044e\u0449\u0438\u0435 \u043f\u043e\u0434\u0441\u043a\u0430\u0437\u043a\u0438 \u0432 \u0432\u0430\u0448\u0435\u043c \u0437\u0430\u043f\u0440\u043e\u0441\u0435:\n\n* `/*+ DocidIndex(id) */` \u2014 \u043f\u0440\u0438\u043d\u0443\u0434\u0438\u0442\u0435\u043b\u044c\u043d\u043e \u0438\u0441\u043f\u043e\u043b\u044c\u0437\u043e\u0432\u0430\u0442\u044c \u0438\u043d\u0434\u0435\u043a\u0441 docid, `/*+ NO_DocidIndex(id) */` \u2014 \u0443\u043a\u0430\u0437\u0430\u0442\u044c \u043e\u043f\u0442\u0438\u043c\u0438\u0437\u0430\u0442\u043e\u0440\u0443 \u0438\u0433\u043d\u043e\u0440\u0438\u0440\u043e\u0432\u0430\u0442\u044c \u0435\u0433\u043e\n* `/*+ SecondaryIndex(<attr_name1>[, <attr_nameN>]) */` \u2014 \u043f\u0440\u0438\u043d\u0443\u0434\u0438\u0442\u0435\u043b\u044c\u043d\u043e \u0438\u0441\u043f\u043e\u043b\u044c\u0437\u043e\u0432\u0430\u0442\u044c \u0432\u0442\u043e\u0440\u0438\u0447\u043d\u044b\u0439 \u0438\u043d\u0434\u0435\u043a\u0441 (\u0435\u0441\u043b\u0438 \u0434\u043e\u0441\u0442\u0443\u043f\u0435\u043d), `/*+ NO_SecondaryIndex(id) */` \u2014 \u0443\u043a\u0430\u0437\u0430\u0442\u044c \u043e\u043f\u0442\u0438\u043c\u0438\u0437\u0430\u0442\u043e\u0440\u0443 \u0438\u0433\u043d\u043e\u0440\u0438\u0440\u043e\u0432\u0430\u0442\u044c \u0435\u0433\u043e\n* `/*+ ColumnarScan(<attr_name1>[, <attr_nameN>]) */` \u2014 \u043f\u0440\u0438\u043d\u0443\u0434\u0438\u0442\u0435\u043b\u044c\u043d\u043e \u0438\u0441\u043f\u043e\u043b\u044c\u0437\u043e\u0432\u0430\u0442\u044c \u043f\u043e\u0441\u043a\u043e\u043b\u043e\u043d\u043d\u044b\u0439 \u0441\u043a\u0430\u043d (\u0435\u0441\u043b\u0438 \u0430\u0442\u0440\u0438\u0431\u0443\u0442 \u043a\u043e\u043b\u043e\u043d\u043d\u044b\u0439), `/*+ NO_ColumnarScan(id) */` \u2014 \u0443\u043a\u0430\u0437\u0430\u0442\u044c \u043e\u043f\u0442\u0438\u043c\u0438\u0437\u0430\u0442\u043e\u0440\u0443 \u0438\u0433\u043d\u043e\u0440\u0438\u0440\u043e\u0432\u0430\u0442\u044c \u0435\u0433\u043e\n\n\u041e\u0431\u0440\u0430\u0442\u0438\u0442\u0435 \u0432\u043d\u0438\u043c\u0430\u043d\u0438\u0435, \u0447\u0442\u043e \u043f\u0440\u0438 \u0432\u044b\u043f\u043e\u043b\u043d\u0435\u043d\u0438\u0438 \u043f\u043e\u043b\u043d\u043e\u0442\u0435\u043a\u0441\u0442\u043e\u0432\u043e\u0433\u043e \u0437\u0430\u043f\u0440\u043e\u0441\u0430 \u0441 \u0444\u0438\u043b\u044c\u0442\u0440\u0430\u043c\u0438 \u043e\u043f\u0442\u0438\u043c\u0438\u0437\u0430\u0442\u043e\u0440 \u0437\u0430\u043f\u0440\u043e\u0441\u0430 \u0432\u044b\u0431\u0438\u0440\u0430\u0435\u0442 \u043c\u0435\u0436\u0434\u0443 \u043f\u0435\u0440\u0435\u0441\u0435\u0447\u0435\u043d\u0438\u0435\u043c \u0440\u0435\u0437\u0443\u043b\u044c\u0442\u0430\u0442\u043e\u0432 \u043f\u043e\u043b\u043d\u043e\u0442\u0435\u043a\u0441\u0442\u043e\u0432\u043e\u0433\u043e \u0434\u0435\u0440\u0435\u0432\u0430 \u0441 \u0440\u0435\u0437\u0443\u043b\u044c\u0442\u0430\u0442\u0430\u043c\u0438 \u0444\u0438\u043b\u044c\u0442\u0440\u0430 \u0438\u043b\u0438 \u0441\u0442\u0430\u043d\u0434\u0430\u0440\u0442\u043d\u044b\u043c \u043f\u043e\u0434\u0445\u043e\u0434\u043e\u043c \u00ab\u0441\u043d\u0430\u0447\u0430\u043b\u0430 \u0441\u043e\u0432\u043f\u0430\u0434\u0435\u043d\u0438\u0435, \u0437\u0430\u0442\u0435\u043c \u0444\u0438\u043b\u044c\u0442\u0440\u00bb. \u0423\u043a\u0430\u0437\u0430\u043d\u0438\u0435 *\u043b\u044e\u0431\u043e\u0439* \u043f\u043e\u0434\u0441\u043a\u0430\u0437\u043a\u0438 \u0437\u0430\u0441\u0442\u0430\u0432\u0438\u0442 \u0434\u0435\u043c\u043e\u043d \u0438\u0441\u043f\u043e\u043b\u044c\u0437\u043e\u0432\u0430\u0442\u044c \u043f\u0443\u0442\u044c \u043a\u043e\u0434\u0430, \u043a\u043e\u0442\u043e\u0440\u044b\u0439 \u0432\u044b\u043f\u043e\u043b\u043d\u044f\u0435\u0442 \u043f\u0435\u0440\u0435\u0441\u0435\u0447\u0435\u043d\u0438\u0435 \u0440\u0435\u0437\u0443\u043b\u044c\u0442\u0430\u0442\u043e\u0432 \u043f\u043e\u043b\u043d\u043e\u0442\u0435\u043a\u0441\u0442\u043e\u0432\u043e\u0433\u043e \u0434\u0435\u0440\u0435\u0432\u0430 \u0441 \u0444\u0438\u043b\u044c\u0442\u0440\u0443\u044e\u0449\u0438\u043c\u0438 \u0440\u0435\u0437\u0443\u043b\u044c\u0442\u0430\u0442\u0430\u043c\u0438.\n\n\u041f\u043e\u0434\u0440\u043e\u0431\u043d\u0435\u0435 \u043e \u0440\u0430\u0431\u043e\u0442\u0435 \u043e\u043f\u0442\u0438\u043c\u0438\u0437\u0430\u0442\u043e\u0440\u0430 \u0437\u0430\u043f\u0440\u043e\u0441\u043e\u0432 \u0441\u043c\u043e\u0442\u0440\u0438\u0442\u0435 \u043d\u0430 \u0441\u0442\u0440\u0430\u043d\u0438\u0446\u0435 [\u041e\u043f\u0442\u0438\u043c\u0438\u0437\u0430\u0442\u043e\u0440 \u043d\u0430 \u043e\u0441\u043d\u043e\u0432\u0435 \u0441\u0442\u043e\u0438\u043c\u043e\u0441\u0442\u0438](../Searching/Cost_based_optimizer.md).\n\n<!-- request SQL -->\n\nCODE_BLOCK_11\n\n<!-- end -->\n\n<!-- example comments -->\n\u041f\u0440\u0438 \u0438\u0441\u043f\u043e\u043b\u044c\u0437\u043e\u0432\u0430\u043d\u0438\u0438 \u043a\u043b\u0438\u0435\u043d\u0442\u0430 MySQL/MariaDB \u043d\u0435 \u0437\u0430\u0431\u0443\u0434\u044c\u0442\u0435 \u0432\u043a\u043b\u044e\u0447\u0438\u0442\u044c \u0444\u043b\u0430\u0433 `--comments`, \u0447\u0442\u043e\u0431\u044b \u043f\u043e\u0434\u0441\u043a\u0430\u0437\u043a\u0438 \u0431\u044b\u043b\u0438 \u0430\u043a\u0442\u0438\u0432\u043d\u044b \u0432 \u0432\u0430\u0448\u0438\u0445 \u0437\u0430\u043f\u0440\u043e\u0441\u0430\u0445.\n\n<!-- request mysql -->\nCODE_BLOCK_12\n<!-- end -->\n\n<!-- proofread -->"
        },
        "is_code_or_comment": false,
        "model": "openai:gpt-4.1-mini",
        "updated_at": 1766339819
    },
    "bf1fec3abf43e91fdfd1443419be99e445f4893963ebd626ee2f27c61e53ed6a": {
        "original": "# Search options\n\nThe SQL [SELECT](../Searching/Full_text_matching/Basic_usage.md#SQL) clause and the HTTP [/search](../Searching/Full_text_matching/Basic_usage.md#HTTP-JSON) endpoint support a number of options that can be used to fine-tune search behavior.\n\n## OPTION\n\n### General syntax\n\n<!-- example options -->\n\n**SQL**:\n\nCODE_BLOCK_0\n\n**HTTP**:\nCODE_BLOCK_1\n\n\n<!-- intro -->\nSQL:\n<!-- request SQL -->\nCODE_BLOCK_2\n\n<!-- response SQL -->\nCODE_BLOCK_3\n\n<!-- intro -->\nJSON:\n<!-- request JSON -->\n\nCODE_BLOCK_4\n\n<!-- response JSON -->\n\nCODE_BLOCK_5\n\n<!-- end -->\n\nSupported options are:\n\n### accurate_aggregation\nInteger. Enables or disables guaranteed aggregate accuracy when running groupby queries in multiple threads. Default is 0.\n\nWhen running a groupby query, it can be run in parallel on a plain table with several pseudo shards (if `pseudo_sharding` is on). A similar approach works on RT tables. Each shard/chunk executes the query, but the number of groups is limited by `max_matches`. If the result sets from different shards/chunks have different groups, the group counts and aggregates may be inaccurate. Note that Manticore tries to increase `max_matches` up to [`max_matches_increase_threshold`](../Searching/Options.md#max_matches_increase_threshold) based on the number of unique values of the groupby attribute (retrieved from secondary indexes). If it succeeds, there will be no loss in accuracy.\n\nHowever, if the number of unique values of the groupby attribute is high, further increasing `max_matches` may not be a good strategy because it can lead to a loss in performance and higher memory usage. Setting `accurate_aggregation` to 1 forces groupby searches to run in a single thread, which fixes the accuracy issue. Note that running in a single thread is only enforced when `max_matches` cannot be set high enough; otherwise, searches with `accurate_aggregation=1` will still run in multiple threads.\n\nOverall, setting `accurate_aggregation` to 1 ensures group count and aggregate accuracy in RT tables and plain tables with `pseudo_sharding=1`. The drawback is that searches will run slower since they will be forced to operate in a single thread.\n\nHowever, if we have an RT table and a plain table containing the same data, and we run a query with `accurate_aggregation=1`, we might still receive different results. This occurs because the daemon might choose different `max_matches` settings for the RT and plain table due to the [`max_matches_increase_threshold`](../Searching/Options.md#max_matches_increase_threshold) setting.\n\n### agent_query_timeout\nInteger. Max time in milliseconds to wait for remote queries to complete, see [this section](../Creating_a_table/Creating_a_distributed_table/Remote_tables.md#agent_query_timeout).\n\n### boolean_simplify\n`0` or `1` (`1` by default). `boolean_simplify=1` enables [simplifying the query](../Searching/Full_text_matching/Boolean_optimization.md) to speed it up.\n\nThis option can also be set globally in the [searchd configuration](../Server_settings/Searchd.md#boolean_simplify) to change the default behavior for all queries. The per-query option will override the global setting.\n\n### comment\nString, user comment that gets copied to a query log file.\n\n### cutoff\nInteger. Specifies the maximum number of matches to process. If not set, Manticore will select an appropriate value automatically.\n\n<!-- example cutoff_aggregation -->\n\n* `N = 0`: Disables the limit on the number of matches.\n* `N > 0`: Instructs Manticore to stop processing results as soon as it finds `N` matching documents.\n* Not set: Manticore decides the threshold automatically.\n\nWhen Manticore cannot determine the exact count of matching documents, the `total_relation` field in the query [meta information](../Node_info_and_management/SHOW_META.md#SHOW-META) will show `gte`, which stands for **Greater Than or Equal to**. This indicates that the actual count of matches is at least the reported `total_found` (in SQL) or `hits.total` (in JSON). When the count is exact, `total_relation` will display `eq`.\n\nNote: Using `cutoff` in aggregation queries is not recommended because it can produce inaccurate or incomplete results.\n\n<!-- request Example -->\n\nUsing `cutoff` in aggregation queries can lead to incorrect or misleading results, as shown in the following example:\nCODE_BLOCK_6\n\nCompare it with the same query without `cutoff`:\nCODE_BLOCK_7\n\n<!-- end -->\n\n### distinct_precision_threshold\nInteger. Default is `3500`. This option sets the threshold below which counts returned by `count distinct` are guaranteed to be exact within a plain table.\n\nAccepted values range from `500` to `15500`. Values outside this range will be clamped.\n\nWhen this option is set to 0, it enables an algorithm that ensures exact counts. This algorithm collects `{group, value}` pairs, sorts them, and periodically eliminates duplicates. The result is precise counts within a plain table. However, this approach is not suitable for high-cardinality datasets due to its high memory consumption and slow query execution.\n\nWhen `distinct_precision_threshold` is set to a value greater than `0`, Manticore employs a different algorithm. It loads counts into a hash table and returns the size of the table. If the hash table becomes too large, its contents are moved into a `HyperLogLog` data structure. At this point, the counts become approximate because HyperLogLog is a probabilistic algorithm. This approach maintains a fixed maximum memory usage per group, but there is a tradeoff in count accuracy.\n\nThe accuracy of the `HyperLogLog` and the threshold for converting from the hash table to HyperLogLog are derived from the `distinct_precision_threshold` setting. It's important to use this option with caution since doubling its value will also double the maximum memory required to calculate counts. The maximum memory usage can be roughly estimated using this formula: `64 * max_matches * distinct_precision_threshold`, although in practice, count calculations often use less memory than the worst-case scenario.",
        "translations": {
            "chinese": "# \u641c\u7d22\u9009\u9879\n\nSQL \u7684 [SELECT](../Searching/Full_text_matching/Basic_usage.md#SQL) \u5b50\u53e5\u548c HTTP \u7684 [/search](../Searching/Full_text_matching/Basic_usage.md#HTTP-JSON) \u7aef\u70b9\u652f\u6301\u591a\u4e2a\u9009\u9879\uff0c\u53ef\u4ee5\u7528\u6765\u5fae\u8c03\u641c\u7d22\u884c\u4e3a\u3002\n\n## OPTION\n\n### \u901a\u7528\u8bed\u6cd5\n\n<!-- example options -->\n\n**SQL**:\n\nCODE_BLOCK_0\n\n**HTTP**:\nCODE_BLOCK_1\n\n\n<!-- intro -->\nSQL:\n<!-- request SQL -->\nCODE_BLOCK_2\n\n<!-- response SQL -->\nCODE_BLOCK_3\n\n<!-- intro -->\nJSON:\n<!-- request JSON -->\n\nCODE_BLOCK_4\n\n<!-- response JSON -->\n\nCODE_BLOCK_5\n\n<!-- end -->\n\n\u652f\u6301\u7684\u9009\u9879\u6709\uff1a\n\n### accurate_aggregation\n\u6574\u6570\u7c7b\u578b\u3002\u5728\u591a\u7ebf\u7a0b\u8fd0\u884c groupby \u67e5\u8be2\u65f6\u542f\u7528\u6216\u7981\u7528\u4fdd\u8bc1\u805a\u5408\u7ed3\u679c\u7684\u51c6\u786e\u6027\u3002\u9ed8\u8ba4\u503c\u4e3a 0\u3002\n\n\u8fd0\u884c groupby \u67e5\u8be2\u65f6\uff0c\u53ef\u4ee5\u5728\u666e\u901a\u8868\u4e0a\u5e76\u884c\u6267\u884c\u591a\u4e2a\u4f2a\u5206\u7247\uff08\u5982\u679c\u542f\u7528\u4e86 `pseudo_sharding`\uff09\u3002\u7c7b\u4f3c\u7684\u65b9\u6cd5\u4e5f\u9002\u7528\u4e8e RT \u8868\u3002\u6bcf\u4e2a\u5206\u7247/\u5757\u90fd\u4f1a\u6267\u884c\u67e5\u8be2\uff0c\u4f46\u5206\u7ec4\u6570\u53d7\u5230 `max_matches` \u7684\u9650\u5236\u3002\u5982\u679c\u4e0d\u540c\u5206\u7247/\u5757\u7684\u7ed3\u679c\u96c6\u4e2d\u7684\u5206\u7ec4\u4e0d\u540c\uff0c\u5219\u5206\u7ec4\u8ba1\u6570\u548c\u805a\u5408\u53ef\u80fd\u4e0d\u51c6\u786e\u3002\u6ce8\u610f Manticore \u4f1a\u5c1d\u8bd5\u57fa\u4e8e\u4ece\u4e8c\u7ea7\u7d22\u5f15\u83b7\u53d6\u7684 groupby \u5c5e\u6027\u7684\u552f\u4e00\u503c\u6570\u91cf\uff0c\u5c06 `max_matches` \u589e\u52a0\u5230 [`max_matches_increase_threshold`](../Searching/Options.md#max_matches_increase_threshold) \u4e4b\u4e0a\u3002\u5982\u679c\u6210\u529f\uff0c\u5219\u4e0d\u4f1a\u4e22\u5931\u51c6\u786e\u6027\u3002\n\n\u4f46\u662f\uff0c\u5982\u679c groupby \u5c5e\u6027\u7684\u552f\u4e00\u503c\u6570\u91cf\u5f88\u9ad8\uff0c\u8fdb\u4e00\u6b65\u589e\u52a0 `max_matches` \u53ef\u80fd\u4e0d\u662f\u4e00\u4e2a\u597d\u7684\u7b56\u7565\uff0c\u56e0\u4e3a\u8fd9\u53ef\u80fd\u5bfc\u81f4\u6027\u80fd\u4e0b\u964d\u548c\u66f4\u9ad8\u7684\u5185\u5b58\u4f7f\u7528\u3002\u5c06 `accurate_aggregation` \u8bbe\u7f6e\u4e3a 1 \u4f1a\u5f3a\u5236 groupby \u67e5\u8be2\u5728\u5355\u7ebf\u7a0b\u4e2d\u8fd0\u884c\uff0c\u4ece\u800c\u89e3\u51b3\u51c6\u786e\u6027\u95ee\u9898\u3002\u9700\u8981\u6ce8\u610f\u7684\u662f\uff0c\u53ea\u6709\u5728\u65e0\u6cd5\u5c06 `max_matches` \u8bbe\u7f6e\u5f97\u8db3\u591f\u9ad8\u65f6\uff0c\u624d\u5f3a\u5236\u5355\u7ebf\u7a0b\u8fd0\u884c\uff1b\u5426\u5219\uff0c\u8bbe\u7f6e\u4e86 `accurate_aggregation=1` \u7684\u67e5\u8be2\u4ecd\u5c06\u5728\u591a\u7ebf\u7a0b\u4e2d\u8fd0\u884c\u3002\n\n\u603b\u4f53\u6765\u8bf4\uff0c\u5c06 `accurate_aggregation` \u8bbe\u4e3a 1 \u53ef\u4ee5\u4fdd\u8bc1 RT \u8868\u548c\u542f\u7528\u4e86 `pseudo_sharding=1` \u7684\u666e\u901a\u8868\u4e2d\u5206\u7ec4\u8ba1\u6570\u548c\u805a\u5408\u7684\u51c6\u786e\u6027\u3002\u7f3a\u70b9\u662f\u67e5\u8be2\u901f\u5ea6\u4f1a\u53d8\u6162\uff0c\u56e0\u4e3a\u5f3a\u5236\u4f7f\u7528\u5355\u7ebf\u7a0b\u6267\u884c\u3002\n\n\u4f46\u662f\uff0c\u5982\u679c\u540c\u65f6\u5b58\u5728\u542b\u6709\u76f8\u540c\u6570\u636e\u7684 RT \u8868\u548c\u666e\u901a\u8868\uff0c\u5e76\u5bf9\u8fd9\u4e24\u4e2a\u8868\u6267\u884c\u5e26\u6709 `accurate_aggregation=1` \u7684\u67e5\u8be2\uff0c\u7ed3\u679c\u4ecd\u53ef\u80fd\u4e0d\u540c\u3002\u8fd9\u662f\u56e0\u4e3a\u5b88\u62a4\u8fdb\u7a0b\u53ef\u80fd\u4f1a\u56e0 [`max_matches_increase_threshold`](../Searching/Options.md#max_matches_increase_threshold) \u8bbe\u7f6e\u7684\u4e0d\u540c\u800c\u4e3a RT \u8868\u548c\u666e\u901a\u8868\u9009\u62e9\u4e0d\u540c\u7684 `max_matches` \u914d\u7f6e\u3002\n\n### agent_query_timeout\n\u6574\u6570\u7c7b\u578b\u3002\u7b49\u5f85\u8fdc\u7a0b\u67e5\u8be2\u5b8c\u6210\u7684\u6700\u957f\u65f6\u95f4\uff08\u6beb\u79d2\uff09\uff0c\u8be6\u89c1[\u6b64\u90e8\u5206](../Creating_a_table/Creating_a_distributed_table/Remote_tables.md#agent_query_timeout)\u3002\n\n### boolean_simplify\n`0` \u6216 `1`\uff08\u9ed8\u8ba4\u503c\u4e3a `1`\uff09\u3002`boolean_simplify=1` \u542f\u7528[\u7b80\u5316\u67e5\u8be2](../Searching/Full_text_matching/Boolean_optimization.md)\u4ee5\u52a0\u901f\u67e5\u8be2\u3002\n\n\u6b64\u9009\u9879\u4e5f\u53ef\u4ee5\u5728 [searchd \u914d\u7f6e](../Server_settings/Searchd.md#boolean_simplify) \u5168\u5c40\u8bbe\u7f6e\uff0c\u4ee5\u6539\u53d8\u6240\u6709\u67e5\u8be2\u7684\u9ed8\u8ba4\u884c\u4e3a\u3002\u6bcf\u4e2a\u67e5\u8be2\u4e2d\u7684\u8be5\u9009\u9879\u4f1a\u8986\u76d6\u5168\u5c40\u8bbe\u7f6e\u3002\n\n### comment\n\u5b57\u7b26\u4e32\u7c7b\u578b\uff0c\u7528\u6237\u6ce8\u91ca\uff0c\u4f1a\u88ab\u590d\u5236\u5230\u67e5\u8be2\u65e5\u5fd7\u6587\u4ef6\u3002\n\n### cutoff\n\u6574\u6570\u7c7b\u578b\u3002\u6307\u5b9a\u5904\u7406\u7684\u6700\u5927\u5339\u914d\u6570\u3002\u5982\u679c\u672a\u8bbe\u7f6e\uff0cManticore \u4f1a\u81ea\u52a8\u9009\u62e9\u4e00\u4e2a\u9002\u5f53\u7684\u503c\u3002\n\n<!-- example cutoff_aggregation -->\n\n* `N = 0`: \u7981\u7528\u5339\u914d\u6570\u91cf\u7684\u9650\u5236\u3002\n* `N > 0`: \u6307\u793a Manticore \u5728\u627e\u5230 `N` \u4e2a\u5339\u914d\u6587\u6863\u540e\u505c\u6b62\u5904\u7406\u7ed3\u679c\u3002\n* \u672a\u8bbe\u7f6e\uff1aManticore \u81ea\u52a8\u51b3\u5b9a\u9608\u503c\u3002\n\n\u5f53 Manticore \u65e0\u6cd5\u786e\u5b9a\u5339\u914d\u6587\u6863\u7684\u51c6\u786e\u6570\u91cf\u65f6\uff0c\u67e5\u8be2\u7684[\u5143\u4fe1\u606f](../Node_info_and_management/SHOW_META.md#SHOW-META)\u4e2d\u7684 `total_relation` \u5b57\u6bb5\u4f1a\u663e\u793a `gte`\uff0c\u8868\u793a**\u5927\u4e8e\u6216\u7b49\u4e8e**\u3002\u8fd9\u610f\u5473\u7740\u5b9e\u9645\u5339\u914d\u6570\u81f3\u5c11\u662f\u62a5\u544a\u7684 `total_found`\uff08SQL\u4e2d\uff09\u6216 `hits.total`\uff08JSON\u4e2d\uff09\u3002\u5f53\u8ba1\u6570\u662f\u51c6\u786e\u7684\uff0c`total_relation` \u4f1a\u663e\u793a `eq`\u3002\n\n\u6ce8\u610f\uff1a\u4e0d\u5efa\u8bae\u5728\u805a\u5408\u67e5\u8be2\u4e2d\u4f7f\u7528 `cutoff`\uff0c\u56e0\u4e3a\u5b83\u53ef\u80fd\u4f1a\u4ea7\u751f\u4e0d\u51c6\u786e\u6216\u4e0d\u5b8c\u6574\u7684\u7ed3\u679c\u3002\n\n<!-- request Example -->\n\n\u5728\u805a\u5408\u67e5\u8be2\u4e2d\u4f7f\u7528 `cutoff` \u53ef\u80fd\u5bfc\u81f4\u4e0d\u6b63\u786e\u6216\u8bef\u5bfc\u6027\u7684\u7ed3\u679c\uff0c\u5982\u4e0b\u9762\u793a\u4f8b\u6240\u793a\uff1a\nCODE_BLOCK_6\n\n\u4e0e\u672a\u4f7f\u7528 `cutoff` \u7684\u76f8\u540c\u67e5\u8be2\u5bf9\u6bd4\uff1a\nCODE_BLOCK_7\n\n<!-- end -->\n\n### distinct_precision_threshold\n\u6574\u6570\u7c7b\u578b\u3002\u9ed8\u8ba4\u503c\u4e3a `3500`\u3002\u6b64\u9009\u9879\u8bbe\u7f6e\u4e86\u5728\u666e\u901a\u8868\u4e2d `count distinct` \u8fd4\u56de\u8ba1\u6570\u4fdd\u8bc1\u51c6\u786e\u7684\u9608\u503c\u3002\n\n\u63a5\u53d7\u7684\u53d6\u503c\u8303\u56f4\u4e3a `500` \u5230 `15500`\uff0c\u8d85\u51fa\u8303\u56f4\u7684\u503c\u5c06\u88ab\u5939\u7d27\u3002\n\n\u5f53\u8be5\u9009\u9879\u8bbe\u7f6e\u4e3a 0 \u65f6\uff0c\u542f\u7528\u4e00\u79cd\u786e\u4fdd\u51c6\u786e\u8ba1\u6570\u7684\u7b97\u6cd5\u3002\u8be5\u7b97\u6cd5\u6536\u96c6 `{group, value}` \u952e\u503c\u5bf9\uff0c\u5bf9\u5176\u6392\u5e8f\uff0c\u5b9a\u671f\u53bb\u9664\u91cd\u590d\u9879\u3002\u7ed3\u679c\u662f\u5728\u666e\u901a\u8868\u4e2d\u83b7\u5f97\u7cbe\u786e\u8ba1\u6570\u3002\u4f46\u7531\u4e8e\u5176\u9ad8\u5185\u5b58\u6d88\u8017\u548c\u67e5\u8be2\u6267\u884c\u7f13\u6162\uff0c\u8fd9\u79cd\u65b9\u6cd5\u4e0d\u9002\u7528\u4e8e\u9ad8\u57fa\u6570\u6570\u636e\u96c6\u3002\n\n\u5f53 `distinct_precision_threshold` \u8bbe\u7f6e\u4e3a\u5927\u4e8e 0 \u7684\u503c\u65f6\uff0cManticore \u4f7f\u7528\u53e6\u4e00\u79cd\u7b97\u6cd5\u3002\u5b83\u5148\u5c06\u8ba1\u6570\u52a0\u8f7d\u5230\u54c8\u5e0c\u8868\u4e2d\uff0c\u5e76\u8fd4\u56de\u8be5\u8868\u7684\u5927\u5c0f\u3002\u5982\u679c\u54c8\u5e0c\u8868\u53d8\u5f97\u8fc7\u5927\uff0c\u5219\u5176\u5185\u5bb9\u5c06\u88ab\u8f6c\u79fb\u5230 `HyperLogLog` \u6570\u636e\u7ed3\u6784\u4e2d\u3002\u6b64\u65f6\u8ba1\u6570\u53d8\u4e3a\u8fd1\u4f3c\uff0c\u56e0\u4e3a HyperLogLog \u662f\u6982\u7387\u7b97\u6cd5\u3002\u8be5\u65b9\u6cd5\u4fdd\u8bc1\u4e86\u6bcf\u4e2a\u5206\u7ec4\u7684\u6700\u5927\u5185\u5b58\u4f7f\u7528\u56fa\u5b9a\uff0c\u4f46\u4f1a\u5728\u8ba1\u6570\u51c6\u786e\u6027\u4e0a\u6709\u6240\u6298\u8877\u3002\n\n`HyperLogLog` \u7684\u51c6\u786e\u6027\u53ca\u4ece\u54c8\u5e0c\u8868\u8f6c\u6362\u4e3a HyperLogLog \u7684\u9608\u503c\u5747\u7531 `distinct_precision_threshold` \u8bbe\u7f6e\u51b3\u5b9a\u3002\u4f7f\u7528\u6b64\u9009\u9879\u65f6\u9700\u8c28\u614e\uff0c\u56e0\u4e3a\u8be5\u503c\u52a0\u500d\u4e5f\u4f1a\u4f7f\u8ba1\u7b97\u8ba1\u6570\u65f6\u6240\u9700\u7684\u6700\u5927\u5185\u5b58\u52a0\u500d\u3002\u6700\u5927\u5185\u5b58\u4f7f\u7528\u91cf\u5927\u81f4\u53ef\u6309\u516c\u5f0f\u4f30\u7b97\uff1a`64 * max_matches * distinct_precision_threshold`\uff0c\u5c3d\u7ba1\u5b9e\u9645\u4e0a\u8ba1\u6570\u8ba1\u7b97\u901a\u5e38\u4f7f\u7528\u7684\u5185\u5b58\u6bd4\u7406\u8bba\u6700\u5927\u503c\u8981\u5c11\u3002",
            "russian": "# \u041e\u043f\u0446\u0438\u0438 \u043f\u043e\u0438\u0441\u043a\u0430\n\nSQL [SELECT](../Searching/Full_text_matching/Basic_usage.md#SQL) \u043e\u043f\u0435\u0440\u0430\u0442\u043e\u0440 \u0438 HTTP [/search](../Searching/Full_text_matching/Basic_usage.md#HTTP-JSON) \u044d\u043d\u0434\u043f\u043e\u0438\u043d\u0442 \u043f\u043e\u0434\u0434\u0435\u0440\u0436\u0438\u0432\u0430\u044e\u0442 \u0440\u044f\u0434 \u043e\u043f\u0446\u0438\u0439, \u043a\u043e\u0442\u043e\u0440\u044b\u0435 \u043c\u043e\u0436\u043d\u043e \u0438\u0441\u043f\u043e\u043b\u044c\u0437\u043e\u0432\u0430\u0442\u044c \u0434\u043b\u044f \u0442\u043e\u043d\u043a\u043e\u0439 \u043d\u0430\u0441\u0442\u0440\u043e\u0439\u043a\u0438 \u043f\u043e\u0432\u0435\u0434\u0435\u043d\u0438\u044f \u043f\u043e\u0438\u0441\u043a\u0430.\n\n## OPTION\n\n### \u041e\u0431\u0449\u0438\u0439 \u0441\u0438\u043d\u0442\u0430\u043a\u0441\u0438\u0441\n\n<!-- example options -->\n\n**SQL**:\n\nCODE_BLOCK_0\n\n**HTTP**:\nCODE_BLOCK_1\n\n\n<!-- intro -->\nSQL:\n<!-- request SQL -->\nCODE_BLOCK_2\n\n<!-- response SQL -->\nCODE_BLOCK_3\n\n<!-- intro -->\nJSON:\n<!-- request JSON -->\n\nCODE_BLOCK_4\n\n<!-- response JSON -->\n\nCODE_BLOCK_5\n\n<!-- end -->\n\n\u041f\u043e\u0434\u0434\u0435\u0440\u0436\u0438\u0432\u0430\u0435\u043c\u044b\u0435 \u043e\u043f\u0446\u0438\u0438:\n\n### accurate_aggregation\n\u0426\u0435\u043b\u043e\u0435 \u0447\u0438\u0441\u043b\u043e. \u0412\u043a\u043b\u044e\u0447\u0430\u0435\u0442 \u0438\u043b\u0438 \u043e\u0442\u043a\u043b\u044e\u0447\u0430\u0435\u0442 \u0433\u0430\u0440\u0430\u043d\u0442\u0438\u0440\u043e\u0432\u0430\u043d\u043d\u0443\u044e \u0442\u043e\u0447\u043d\u043e\u0441\u0442\u044c \u0430\u0433\u0440\u0435\u0433\u0430\u0442\u043e\u0432 \u043f\u0440\u0438 \u0432\u044b\u043f\u043e\u043b\u043d\u0435\u043d\u0438\u0438 \u0437\u0430\u043f\u0440\u043e\u0441\u043e\u0432 groupby \u0432 \u043d\u0435\u0441\u043a\u043e\u043b\u044c\u043a\u0438\u0445 \u043f\u043e\u0442\u043e\u043a\u0430\u0445. \u041f\u043e \u0443\u043c\u043e\u043b\u0447\u0430\u043d\u0438\u044e 0.\n\n\u041f\u0440\u0438 \u0432\u044b\u043f\u043e\u043b\u043d\u0435\u043d\u0438\u0438 \u0437\u0430\u043f\u0440\u043e\u0441\u0430 groupby \u043e\u043d \u043c\u043e\u0436\u0435\u0442 \u0431\u044b\u0442\u044c \u0437\u0430\u043f\u0443\u0449\u0435\u043d \u043f\u0430\u0440\u0430\u043b\u043b\u0435\u043b\u044c\u043d\u043e \u043f\u043e \u043f\u0440\u043e\u0441\u0442\u043e\u0439 \u0442\u0430\u0431\u043b\u0438\u0446\u0435 \u0441 \u043d\u0435\u0441\u043a\u043e\u043b\u044c\u043a\u0438\u043c\u0438 \u043f\u0441\u0435\u0432\u0434\u043e-\u0448\u0430\u0440\u0434\u0430\u043c\u0438 (\u0435\u0441\u043b\u0438 \u0432\u043a\u043b\u044e\u0447\u0435\u043d `pseudo_sharding`). \u041f\u043e\u0445\u043e\u0436\u0438\u0439 \u043f\u043e\u0434\u0445\u043e\u0434 \u0440\u0430\u0431\u043e\u0442\u0430\u0435\u0442 \u0438 \u0434\u043b\u044f RT \u0442\u0430\u0431\u043b\u0438\u0446. \u041a\u0430\u0436\u0434\u044b\u0439 \u0448\u0430\u0440\u0434/\u0447\u0430\u043d\u043a \u0432\u044b\u043f\u043e\u043b\u043d\u044f\u0435\u0442 \u0437\u0430\u043f\u0440\u043e\u0441, \u043d\u043e \u043a\u043e\u043b\u0438\u0447\u0435\u0441\u0442\u0432\u043e \u0433\u0440\u0443\u043f\u043f \u043e\u0433\u0440\u0430\u043d\u0438\u0447\u0435\u043d\u043e `max_matches`. \u0415\u0441\u043b\u0438 \u0440\u0435\u0437\u0443\u043b\u044c\u0442\u0438\u0440\u0443\u044e\u0449\u0438\u0435 \u043d\u0430\u0431\u043e\u0440\u044b \u0438\u0437 \u0440\u0430\u0437\u043d\u044b\u0445 \u0448\u0430\u0440\u0434\u043e\u0432/\u0447\u0430\u043d\u043a\u043e\u0432 \u0441\u043e\u0434\u0435\u0440\u0436\u0430\u0442 \u0440\u0430\u0437\u043d\u044b\u0435 \u0433\u0440\u0443\u043f\u043f\u044b, \u043f\u043e\u0434\u0441\u0447\u0451\u0442\u044b \u0433\u0440\u0443\u043f\u043f \u0438 \u0430\u0433\u0440\u0435\u0433\u0430\u0442\u044b \u043c\u043e\u0433\u0443\u0442 \u0431\u044b\u0442\u044c \u043d\u0435\u0442\u043e\u0447\u043d\u044b\u043c\u0438. \u041e\u0431\u0440\u0430\u0442\u0438\u0442\u0435 \u0432\u043d\u0438\u043c\u0430\u043d\u0438\u0435, \u0447\u0442\u043e Manticore \u043f\u044b\u0442\u0430\u0435\u0442\u0441\u044f \u0443\u0432\u0435\u043b\u0438\u0447\u0438\u0442\u044c `max_matches` \u0434\u043e [`max_matches_increase_threshold`](../Searching/Options.md#max_matches_increase_threshold) \u043d\u0430 \u043e\u0441\u043d\u043e\u0432\u0435 \u043a\u043e\u043b\u0438\u0447\u0435\u0441\u0442\u0432\u0430 \u0443\u043d\u0438\u043a\u0430\u043b\u044c\u043d\u044b\u0445 \u0437\u043d\u0430\u0447\u0435\u043d\u0438\u0439 \u0430\u0442\u0440\u0438\u0431\u0443\u0442\u0430 groupby (\u0438\u0437\u0432\u043b\u0435\u0447\u0451\u043d\u043d\u044b\u0445 \u0438\u0437 \u0432\u0442\u043e\u0440\u0438\u0447\u043d\u044b\u0445 \u0438\u043d\u0434\u0435\u043a\u0441\u043e\u0432). \u0415\u0441\u043b\u0438 \u044d\u0442\u043e \u0443\u0434\u0430\u0451\u0442\u0441\u044f, \u043f\u043e\u0442\u0435\u0440\u044c \u0442\u043e\u0447\u043d\u043e\u0441\u0442\u0438 \u043d\u0435 \u0431\u0443\u0434\u0435\u0442.\n\n\u041e\u0434\u043d\u0430\u043a\u043e, \u0435\u0441\u043b\u0438 \u043a\u043e\u043b\u0438\u0447\u0435\u0441\u0442\u0432\u043e \u0443\u043d\u0438\u043a\u0430\u043b\u044c\u043d\u044b\u0445 \u0437\u043d\u0430\u0447\u0435\u043d\u0438\u0439 \u0430\u0442\u0440\u0438\u0431\u0443\u0442\u0430 groupby \u0432\u0435\u043b\u0438\u043a\u043e, \u0434\u0430\u043b\u044c\u043d\u0435\u0439\u0448\u0435\u0435 \u0443\u0432\u0435\u043b\u0438\u0447\u0435\u043d\u0438\u0435 `max_matches` \u043c\u043e\u0436\u0435\u0442 \u0431\u044b\u0442\u044c \u043f\u043b\u043e\u0445\u043e\u0439 \u0441\u0442\u0440\u0430\u0442\u0435\u0433\u0438\u0435\u0439, \u0442\u0430\u043a \u043a\u0430\u043a \u044d\u0442\u043e \u0432\u0435\u0434\u0451\u0442 \u043a \u043f\u043e\u0442\u0435\u0440\u0435 \u043f\u0440\u043e\u0438\u0437\u0432\u043e\u0434\u0438\u0442\u0435\u043b\u044c\u043d\u043e\u0441\u0442\u0438 \u0438 \u0431\u043e\u043b\u044c\u0448\u0435\u043c\u0443 \u0438\u0441\u043f\u043e\u043b\u044c\u0437\u043e\u0432\u0430\u043d\u0438\u044e \u043f\u0430\u043c\u044f\u0442\u0438. \u0423\u0441\u0442\u0430\u043d\u043e\u0432\u043a\u0430 `accurate_aggregation` \u0432 1 \u0437\u0430\u0441\u0442\u0430\u0432\u043b\u044f\u0435\u0442 groupby-\u0437\u0430\u043f\u0440\u043e\u0441\u044b \u0432\u044b\u043f\u043e\u043b\u043d\u044f\u0442\u044c\u0441\u044f \u0432 \u043e\u0434\u043d\u043e\u043c \u043f\u043e\u0442\u043e\u043a\u0435, \u0447\u0442\u043e \u0440\u0435\u0448\u0430\u0435\u0442 \u043f\u0440\u043e\u0431\u043b\u0435\u043c\u0443 \u0442\u043e\u0447\u043d\u043e\u0441\u0442\u0438. \u0423\u0447\u0442\u0438\u0442\u0435, \u0447\u0442\u043e \u0432\u044b\u043f\u043e\u043b\u043d\u0435\u043d\u0438\u0435 \u0432 \u043e\u0434\u043d\u043e\u043c \u043f\u043e\u0442\u043e\u043a\u0435 \u043f\u0440\u0438\u043c\u0435\u043d\u044f\u0435\u0442\u0441\u044f \u0442\u043e\u043b\u044c\u043a\u043e \u043a\u043e\u0433\u0434\u0430 \u043d\u0435\u043b\u044c\u0437\u044f \u0443\u0441\u0442\u0430\u043d\u043e\u0432\u0438\u0442\u044c `max_matches` \u0434\u043e\u0441\u0442\u0430\u0442\u043e\u0447\u043d\u043e \u0432\u044b\u0441\u043e\u043a\u0438\u043c; \u0438\u043d\u0430\u0447\u0435 \u0437\u0430\u043f\u0440\u043e\u0441\u044b \u0441 `accurate_aggregation=1` \u0432\u0441\u0451 \u0435\u0449\u0451 \u0431\u0443\u0434\u0443\u0442 \u0432\u044b\u043f\u043e\u043b\u043d\u044f\u0442\u044c\u0441\u044f \u0432 \u043d\u0435\u0441\u043a\u043e\u043b\u044c\u043a\u0438\u0445 \u043f\u043e\u0442\u043e\u043a\u0430\u0445.\n\n\u0412 \u0446\u0435\u043b\u043e\u043c, \u0443\u0441\u0442\u0430\u043d\u043e\u0432\u043a\u0430 `accurate_aggregation` \u0432 1 \u043e\u0431\u0435\u0441\u043f\u0435\u0447\u0438\u0432\u0430\u0435\u0442 \u0442\u043e\u0447\u043d\u043e\u0441\u0442\u044c \u043f\u043e\u0434\u0441\u0447\u0451\u0442\u0430 \u0433\u0440\u0443\u043f\u043f \u0438 \u0430\u0433\u0440\u0435\u0433\u0430\u0442\u043e\u0432 \u0432 RT \u0442\u0430\u0431\u043b\u0438\u0446\u0430\u0445 \u0438 \u043f\u0440\u043e\u0441\u0442\u044b\u0445 \u0442\u0430\u0431\u043b\u0438\u0446\u0430\u0445 \u0441 `pseudo_sharding=1`. \u041d\u0435\u0434\u043e\u0441\u0442\u0430\u0442\u043e\u043a \u2014 \u0437\u0430\u043f\u0440\u043e\u0441\u044b \u0431\u0443\u0434\u0443\u0442 \u0432\u044b\u043f\u043e\u043b\u043d\u044f\u0442\u044c\u0441\u044f \u043c\u0435\u0434\u043b\u0435\u043d\u043d\u0435\u0435, \u0442\u0430\u043a \u043a\u0430\u043a \u0431\u0443\u0434\u0443\u0442 \u043f\u0440\u0438\u043d\u0443\u0434\u0438\u0442\u0435\u043b\u044c\u043d\u043e \u0440\u0430\u0431\u043e\u0442\u0430\u0442\u044c \u0432 \u043e\u0434\u043d\u043e\u043c \u043f\u043e\u0442\u043e\u043a\u0435.\n\n\u041e\u0434\u043d\u0430\u043a\u043e, \u0435\u0441\u043b\u0438 \u0443 \u043d\u0430\u0441 \u0435\u0441\u0442\u044c RT \u0442\u0430\u0431\u043b\u0438\u0446\u0430 \u0438 \u043f\u0440\u043e\u0441\u0442\u0430\u044f \u0442\u0430\u0431\u043b\u0438\u0446\u0430 \u0441 \u043e\u0434\u0438\u043d\u0430\u043a\u043e\u0432\u044b\u043c\u0438 \u0434\u0430\u043d\u043d\u044b\u043c\u0438, \u0438 \u043c\u044b \u0437\u0430\u043f\u0443\u0441\u043a\u0430\u0435\u043c \u0437\u0430\u043f\u0440\u043e\u0441 \u0441 `accurate_aggregation=1`, \u043c\u044b \u0432\u0441\u0451 \u0440\u0430\u0432\u043d\u043e \u043c\u043e\u0436\u0435\u043c \u043f\u043e\u043b\u0443\u0447\u0438\u0442\u044c \u0440\u0430\u0437\u043d\u044b\u0435 \u0440\u0435\u0437\u0443\u043b\u044c\u0442\u0430\u0442\u044b. \u042d\u0442\u043e \u043f\u0440\u043e\u0438\u0441\u0445\u043e\u0434\u0438\u0442 \u0438\u0437-\u0437\u0430 \u0442\u043e\u0433\u043e, \u0447\u0442\u043e \u0434\u0435\u043c\u043e\u043d \u043c\u043e\u0436\u0435\u0442 \u0432\u044b\u0431\u0440\u0430\u0442\u044c \u0440\u0430\u0437\u043d\u044b\u0435 \u043d\u0430\u0441\u0442\u0440\u043e\u0439\u043a\u0438 `max_matches` \u0434\u043b\u044f RT \u0438 \u043f\u0440\u043e\u0441\u0442\u043e\u0439 \u0442\u0430\u0431\u043b\u0438\u0446\u044b \u0438\u0437-\u0437\u0430 \u043f\u0430\u0440\u0430\u043c\u0435\u0442\u0440\u0430 [`max_matches_increase_threshold`](../Searching/Options.md#max_matches_increase_threshold).\n\n### agent_query_timeout\n\u0426\u0435\u043b\u043e\u0435 \u0447\u0438\u0441\u043b\u043e. \u041c\u0430\u043a\u0441\u0438\u043c\u0430\u043b\u044c\u043d\u043e\u0435 \u0432\u0440\u0435\u043c\u044f \u0432 \u043c\u0438\u043b\u043b\u0438\u0441\u0435\u043a\u0443\u043d\u0434\u0430\u0445 \u043e\u0436\u0438\u0434\u0430\u043d\u0438\u044f \u0437\u0430\u0432\u0435\u0440\u0448\u0435\u043d\u0438\u044f \u0443\u0434\u0430\u043b\u0451\u043d\u043d\u044b\u0445 \u0437\u0430\u043f\u0440\u043e\u0441\u043e\u0432, \u0441\u043c. [\u044d\u0442\u043e\u0442 \u0440\u0430\u0437\u0434\u0435\u043b](../Creating_a_table/Creating_a_distributed_table/Remote_tables.md#agent_query_timeout).\n\n### boolean_simplify\n`0` \u0438\u043b\u0438 `1` (\u043f\u043e \u0443\u043c\u043e\u043b\u0447\u0430\u043d\u0438\u044e `1`). `boolean_simplify=1` \u0432\u043a\u043b\u044e\u0447\u0430\u0435\u0442 [\u0443\u043f\u0440\u043e\u0449\u0435\u043d\u0438\u0435 \u0437\u0430\u043f\u0440\u043e\u0441\u0430](../Searching/Full_text_matching/Boolean_optimization.md) \u0434\u043b\u044f \u0443\u0441\u043a\u043e\u0440\u0435\u043d\u0438\u044f \u043f\u043e\u0438\u0441\u043a\u0430.\n\n\u042d\u0442\u0443 \u043e\u043f\u0446\u0438\u044e \u0442\u0430\u043a\u0436\u0435 \u043c\u043e\u0436\u043d\u043e \u0437\u0430\u0434\u0430\u0442\u044c \u0433\u043b\u043e\u0431\u0430\u043b\u044c\u043d\u043e \u0432 [\u043a\u043e\u043d\u0444\u0438\u0433\u0443\u0440\u0430\u0446\u0438\u0438 searchd](../Server_settings/Searchd.md#boolean_simplify) \u0434\u043b\u044f \u0438\u0437\u043c\u0435\u043d\u0435\u043d\u0438\u044f \u043f\u043e\u0432\u0435\u0434\u0435\u043d\u0438\u044f \u043f\u043e \u0443\u043c\u043e\u043b\u0447\u0430\u043d\u0438\u044e \u0434\u043b\u044f \u0432\u0441\u0435\u0445 \u0437\u0430\u043f\u0440\u043e\u0441\u043e\u0432. \u041e\u043f\u0446\u0438\u044f \u043d\u0430 \u0443\u0440\u043e\u0432\u043d\u0435 \u0437\u0430\u043f\u0440\u043e\u0441\u0430 \u043f\u0435\u0440\u0435\u043e\u043f\u0440\u0435\u0434\u0435\u043b\u0438\u0442 \u0433\u043b\u043e\u0431\u0430\u043b\u044c\u043d\u0443\u044e \u043d\u0430\u0441\u0442\u0440\u043e\u0439\u043a\u0443.\n\n### comment\n\u0421\u0442\u0440\u043e\u043a\u0430, \u043a\u043e\u043c\u043c\u0435\u043d\u0442\u0430\u0440\u0438\u0439 \u043f\u043e\u043b\u044c\u0437\u043e\u0432\u0430\u0442\u0435\u043b\u044f, \u043a\u043e\u0442\u043e\u0440\u044b\u0439 \u043a\u043e\u043f\u0438\u0440\u0443\u0435\u0442\u0441\u044f \u0432 \u0444\u0430\u0439\u043b \u0436\u0443\u0440\u043d\u0430\u043b\u0430 \u0437\u0430\u043f\u0440\u043e\u0441\u043e\u0432.\n\n### cutoff\n\u0426\u0435\u043b\u043e\u0435 \u0447\u0438\u0441\u043b\u043e. \u0423\u043a\u0430\u0437\u044b\u0432\u0430\u0435\u0442 \u043c\u0430\u043a\u0441\u0438\u043c\u0430\u043b\u044c\u043d\u043e\u0435 \u043a\u043e\u043b\u0438\u0447\u0435\u0441\u0442\u0432\u043e \u0441\u043e\u0432\u043f\u0430\u0434\u0435\u043d\u0438\u0439 \u0434\u043b\u044f \u043e\u0431\u0440\u0430\u0431\u043e\u0442\u043a\u0438. \u0415\u0441\u043b\u0438 \u043d\u0435 \u0437\u0430\u0434\u0430\u043d\u043e, Manticore \u0432\u044b\u0431\u0435\u0440\u0435\u0442 \u043f\u043e\u0434\u0445\u043e\u0434\u044f\u0449\u0435\u0435 \u0437\u043d\u0430\u0447\u0435\u043d\u0438\u0435 \u0430\u0432\u0442\u043e\u043c\u0430\u0442\u0438\u0447\u0435\u0441\u043a\u0438.\n\n<!-- example cutoff_aggregation -->\n\n* `N = 0`: \u041e\u0442\u043a\u043b\u044e\u0447\u0430\u0435\u0442 \u043e\u0433\u0440\u0430\u043d\u0438\u0447\u0435\u043d\u0438\u0435 \u043d\u0430 \u043a\u043e\u043b\u0438\u0447\u0435\u0441\u0442\u0432\u043e \u0441\u043e\u0432\u043f\u0430\u0434\u0435\u043d\u0438\u0439.\n* `N > 0`: \u0417\u0430\u0441\u0442\u0430\u0432\u043b\u044f\u0435\u0442 Manticore \u043e\u0441\u0442\u0430\u043d\u043e\u0432\u0438\u0442\u044c \u043e\u0431\u0440\u0430\u0431\u043e\u0442\u043a\u0443 \u0440\u0435\u0437\u0443\u043b\u044c\u0442\u0430\u0442\u043e\u0432, \u043a\u0430\u043a \u0442\u043e\u043b\u044c\u043a\u043e \u0431\u0443\u0434\u0435\u0442 \u043d\u0430\u0439\u0434\u0435\u043d\u043e `N` \u0441\u043e\u0432\u043f\u0430\u0434\u0430\u044e\u0449\u0438\u0445 \u0434\u043e\u043a\u0443\u043c\u0435\u043d\u0442\u043e\u0432.\n* \u041d\u0435 \u0437\u0430\u0434\u0430\u043d\u043e: Manticore \u0430\u0432\u0442\u043e\u043c\u0430\u0442\u0438\u0447\u0435\u0441\u043a\u0438 \u0440\u0435\u0448\u0430\u0435\u0442 \u043f\u043e\u0440\u043e\u0433\u043e\u0432\u043e\u0435 \u0437\u043d\u0430\u0447\u0435\u043d\u0438\u0435.\n\n\u041a\u043e\u0433\u0434\u0430 Manticore \u043d\u0435 \u043c\u043e\u0436\u0435\u0442 \u043e\u043f\u0440\u0435\u0434\u0435\u043b\u0438\u0442\u044c \u0442\u043e\u0447\u043d\u043e\u0435 \u043a\u043e\u043b\u0438\u0447\u0435\u0441\u0442\u0432\u043e \u0441\u043e\u0432\u043f\u0430\u0434\u0430\u044e\u0449\u0438\u0445 \u0434\u043e\u043a\u0443\u043c\u0435\u043d\u0442\u043e\u0432, \u043f\u043e\u043b\u0435 `total_relation` \u0432 [\u043c\u0435\u0442\u0430\u0438\u043d\u0444\u043e\u0440\u043c\u0430\u0446\u0438\u0438](../Node_info_and_management/SHOW_META.md#SHOW-META) \u0437\u0430\u043f\u0440\u043e\u0441\u0430 \u0431\u0443\u0434\u0435\u0442 \u043f\u043e\u043a\u0430\u0437\u044b\u0432\u0430\u0442\u044c `gte`, \u0447\u0442\u043e \u043e\u0437\u043d\u0430\u0447\u0430\u0435\u0442 **\u0411\u043e\u043b\u044c\u0448\u0435 \u0438\u043b\u0438 \u0440\u0430\u0432\u043d\u043e**. \u042d\u0442\u043e \u0443\u043a\u0430\u0437\u044b\u0432\u0430\u0435\u0442, \u0447\u0442\u043e \u0444\u0430\u043a\u0442\u0438\u0447\u0435\u0441\u043a\u043e\u0435 \u043a\u043e\u043b\u0438\u0447\u0435\u0441\u0442\u0432\u043e \u0441\u043e\u0432\u043f\u0430\u0434\u0435\u043d\u0438\u0439 \u043a\u0430\u043a \u043c\u0438\u043d\u0438\u043c\u0443\u043c \u0440\u0430\u0432\u043d\u043e \u0441\u043e\u043e\u0431\u0449\u0451\u043d\u043d\u043e\u043c\u0443 `total_found` (\u0432 SQL) \u0438\u043b\u0438 `hits.total` (\u0432 JSON). \u0415\u0441\u043b\u0438 \u043a\u043e\u043b\u0438\u0447\u0435\u0441\u0442\u0432\u043e \u0442\u043e\u0447\u043d\u043e\u0435, `total_relation` \u0431\u0443\u0434\u0435\u0442 \u0440\u0430\u0432\u043d\u043e `eq`.\n\n\u041f\u0440\u0438\u043c\u0435\u0447\u0430\u043d\u0438\u0435: \u0418\u0441\u043f\u043e\u043b\u044c\u0437\u043e\u0432\u0430\u043d\u0438\u0435 `cutoff` \u0432 \u0430\u0433\u0440\u0435\u0433\u0430\u0442\u043d\u044b\u0445 \u0437\u0430\u043f\u0440\u043e\u0441\u0430\u0445 \u043d\u0435 \u0440\u0435\u043a\u043e\u043c\u0435\u043d\u0434\u0443\u0435\u0442\u0441\u044f, \u0442\u0430\u043a \u043a\u0430\u043a \u043e\u043d\u043e \u043c\u043e\u0436\u0435\u0442 \u043f\u0440\u0438\u0432\u043e\u0434\u0438\u0442\u044c \u043a \u043d\u0435\u0442\u043e\u0447\u043d\u044b\u043c \u0438\u043b\u0438 \u043d\u0435\u043f\u043e\u043b\u043d\u044b\u043c \u0440\u0435\u0437\u0443\u043b\u044c\u0442\u0430\u0442\u0430\u043c.\n\n<!-- request Example -->\n\n\u0418\u0441\u043f\u043e\u043b\u044c\u0437\u043e\u0432\u0430\u043d\u0438\u0435 `cutoff` \u0432 \u0430\u0433\u0440\u0435\u0433\u0430\u0442\u043d\u044b\u0445 \u0437\u0430\u043f\u0440\u043e\u0441\u0430\u0445 \u043c\u043e\u0436\u0435\u0442 \u043f\u0440\u0438\u0432\u0435\u0441\u0442\u0438 \u043a \u043d\u0435\u043f\u0440\u0430\u0432\u0438\u043b\u044c\u043d\u044b\u043c \u0438\u043b\u0438 \u0432\u0432\u043e\u0434\u044f\u0449\u0438\u043c \u0432 \u0437\u0430\u0431\u043b\u0443\u0436\u0434\u0435\u043d\u0438\u0435 \u0440\u0435\u0437\u0443\u043b\u044c\u0442\u0430\u0442\u0430\u043c, \u0447\u0442\u043e \u043f\u043e\u043a\u0430\u0437\u0430\u043d\u043e \u0432 \u0441\u043b\u0435\u0434\u0443\u044e\u0449\u0435\u043c \u043f\u0440\u0438\u043c\u0435\u0440\u0435:\nCODE_BLOCK_6\n\n\u0421\u0440\u0430\u0432\u043d\u0438\u0442\u0435 \u0441 \u0442\u0435\u043c \u0436\u0435 \u0437\u0430\u043f\u0440\u043e\u0441\u043e\u043c \u0431\u0435\u0437 `cutoff`:\nCODE_BLOCK_7\n\n<!-- end -->\n\n### distinct_precision_threshold\n\u0426\u0435\u043b\u043e\u0435 \u0447\u0438\u0441\u043b\u043e. \u0417\u043d\u0430\u0447\u0435\u043d\u0438\u0435 \u043f\u043e \u0443\u043c\u043e\u043b\u0447\u0430\u043d\u0438\u044e `3500`. \u042d\u0442\u0430 \u043e\u043f\u0446\u0438\u044f \u0437\u0430\u0434\u0430\u0451\u0442 \u043f\u043e\u0440\u043e\u0433, \u043d\u0438\u0436\u0435 \u043a\u043e\u0442\u043e\u0440\u043e\u0433\u043e \u043f\u043e\u0434\u0441\u0447\u0451\u0442\u044b \u0432\u043e\u0437\u0432\u0440\u0430\u0449\u0430\u0435\u043c\u044b\u0435 `count distinct` \u0433\u0430\u0440\u0430\u043d\u0442\u0438\u0440\u043e\u0432\u0430\u043d\u043d\u043e \u0442\u043e\u0447\u043d\u044b \u0432 \u043f\u0440\u0435\u0434\u0435\u043b\u0430\u0445 \u043f\u0440\u043e\u0441\u0442\u043e\u0439 \u0442\u0430\u0431\u043b\u0438\u0446\u044b.\n\n\u0414\u043e\u043f\u0443\u0441\u0442\u0438\u043c\u044b\u0435 \u0437\u043d\u0430\u0447\u0435\u043d\u0438\u044f \u043e\u0442 `500` \u0434\u043e `15500`. \u0417\u043d\u0430\u0447\u0435\u043d\u0438\u044f \u0432\u043d\u0435 \u044d\u0442\u043e\u0433\u043e \u0434\u0438\u0430\u043f\u0430\u0437\u043e\u043d\u0430 \u0431\u0443\u0434\u0443\u0442 \u043f\u0440\u0438\u0432\u0435\u0434\u0435\u043d\u044b \u043a \u0431\u043b\u0438\u0436\u0430\u0439\u0448\u0435\u043c\u0443 \u043f\u0440\u0435\u0434\u0435\u043b\u0443.\n\n\u0415\u0441\u043b\u0438 \u043e\u043f\u0446\u0438\u044f \u0443\u0441\u0442\u0430\u043d\u043e\u0432\u043b\u0435\u043d\u0430 \u0432 0, \u0432\u043a\u043b\u044e\u0447\u0430\u0435\u0442\u0441\u044f \u0430\u043b\u0433\u043e\u0440\u0438\u0442\u043c, \u043e\u0431\u0435\u0441\u043f\u0435\u0447\u0438\u0432\u0430\u044e\u0449\u0438\u0439 \u0442\u043e\u0447\u043d\u044b\u0435 \u043f\u043e\u0434\u0441\u0447\u0451\u0442\u044b. \u042d\u0442\u043e\u0442 \u0430\u043b\u0433\u043e\u0440\u0438\u0442\u043c \u0441\u043e\u0431\u0438\u0440\u0430\u0435\u0442 \u043f\u0430\u0440\u044b `{group, value}`, \u0441\u043e\u0440\u0442\u0438\u0440\u0443\u0435\u0442 \u0438\u0445 \u0438 \u043f\u0435\u0440\u0438\u043e\u0434\u0438\u0447\u0435\u0441\u043a\u0438 \u0443\u0434\u0430\u043b\u044f\u0435\u0442 \u0434\u0443\u0431\u043b\u0438\u043a\u0430\u0442\u044b. \u0412 \u0440\u0435\u0437\u0443\u043b\u044c\u0442\u0430\u0442\u0435 \u043f\u043e\u0434\u0441\u0447\u0451\u0442\u044b \u0432 \u043f\u0440\u043e\u0441\u0442\u043e\u0439 \u0442\u0430\u0431\u043b\u0438\u0446\u0435 \u043f\u043e\u043b\u0443\u0447\u0430\u044e\u0442\u0441\u044f \u0442\u043e\u0447\u043d\u044b\u043c\u0438. \u041e\u0434\u043d\u0430\u043a\u043e \u0434\u0430\u043d\u043d\u044b\u0439 \u043f\u043e\u0434\u0445\u043e\u0434 \u043d\u0435 \u043f\u043e\u0434\u0445\u043e\u0434\u0438\u0442 \u0434\u043b\u044f \u043d\u0430\u0431\u043e\u0440\u043e\u0432 \u0434\u0430\u043d\u043d\u044b\u0445 \u0441 \u0432\u044b\u0441\u043e\u043a\u043e\u0439 \u043a\u0430\u0440\u0434\u0438\u043d\u0430\u043b\u044c\u043d\u043e\u0441\u0442\u044c\u044e \u0438\u0437-\u0437\u0430 \u0432\u044b\u0441\u043e\u043a\u043e\u0433\u043e \u043f\u043e\u0442\u0440\u0435\u0431\u043b\u0435\u043d\u0438\u044f \u043f\u0430\u043c\u044f\u0442\u0438 \u0438 \u043c\u0435\u0434\u043b\u0435\u043d\u043d\u043e\u0433\u043e \u0432\u044b\u043f\u043e\u043b\u043d\u0435\u043d\u0438\u044f \u0437\u0430\u043f\u0440\u043e\u0441\u043e\u0432.\n\n\u0415\u0441\u043b\u0438 `distinct_precision_threshold` \u0443\u0441\u0442\u0430\u043d\u043e\u0432\u043b\u0435\u043d \u0431\u043e\u043b\u044c\u0448\u0435 0, Manticore \u0438\u0441\u043f\u043e\u043b\u044c\u0437\u0443\u0435\u0442 \u0434\u0440\u0443\u0433\u043e\u0439 \u0430\u043b\u0433\u043e\u0440\u0438\u0442\u043c. \u041e\u043d \u0437\u0430\u0433\u0440\u0443\u0436\u0430\u0435\u0442 \u043f\u043e\u0434\u0441\u0447\u0451\u0442\u044b \u0432 \u0445\u044d\u0448-\u0442\u0430\u0431\u043b\u0438\u0446\u0443 \u0438 \u0432\u043e\u0437\u0432\u0440\u0430\u0449\u0430\u0435\u0442 \u0440\u0430\u0437\u043c\u0435\u0440 \u0442\u0430\u0431\u043b\u0438\u0446\u044b. \u0415\u0441\u043b\u0438 \u0445\u044d\u0448-\u0442\u0430\u0431\u043b\u0438\u0446\u0430 \u0441\u0442\u0430\u043d\u043e\u0432\u0438\u0442\u0441\u044f \u0441\u043b\u0438\u0448\u043a\u043e\u043c \u0431\u043e\u043b\u044c\u0448\u043e\u0439, \u0435\u0451 \u0441\u043e\u0434\u0435\u0440\u0436\u0438\u043c\u043e\u0435 \u043f\u0435\u0440\u0435\u043d\u043e\u0441\u0438\u0442\u0441\u044f \u0432 \u0441\u0442\u0440\u0443\u043a\u0442\u0443\u0440\u0443 \u0434\u0430\u043d\u043d\u044b\u0445 `HyperLogLog`. \u041d\u0430 \u044d\u0442\u043e\u043c \u044d\u0442\u0430\u043f\u0435 \u043f\u043e\u0434\u0441\u0447\u0451\u0442\u044b \u0441\u0442\u0430\u043d\u043e\u0432\u044f\u0442\u0441\u044f \u043f\u0440\u0438\u0431\u043b\u0438\u0436\u0435\u043d\u043d\u044b\u043c\u0438, \u0442\u0430\u043a \u043a\u0430\u043a HyperLogLog \u2014 \u0432\u0435\u0440\u043e\u044f\u0442\u043d\u043e\u0441\u0442\u043d\u044b\u0439 \u0430\u043b\u0433\u043e\u0440\u0438\u0442\u043c. \u0422\u0430\u043a\u043e\u0439 \u043f\u043e\u0434\u0445\u043e\u0434 \u043f\u043e\u0434\u0434\u0435\u0440\u0436\u0438\u0432\u0430\u0435\u0442 \u0444\u0438\u043a\u0441\u0438\u0440\u043e\u0432\u0430\u043d\u043d\u043e\u0435 \u043c\u0430\u043a\u0441\u0438\u043c\u0430\u043b\u044c\u043d\u043e\u0435 \u0438\u0441\u043f\u043e\u043b\u044c\u0437\u043e\u0432\u0430\u043d\u0438\u0435 \u043f\u0430\u043c\u044f\u0442\u0438 \u043d\u0430 \u0433\u0440\u0443\u043f\u043f\u0443, \u043d\u043e \u0441 \u043a\u043e\u043c\u043f\u0440\u043e\u043c\u0438\u0441\u0441\u043e\u043c \u0432 \u0442\u043e\u0447\u043d\u043e\u0441\u0442\u0438.\n\n\u0422\u043e\u0447\u043d\u043e\u0441\u0442\u044c `HyperLogLog` \u0438 \u043f\u043e\u0440\u043e\u0433 \u0434\u043b\u044f \u043f\u0435\u0440\u0435\u0445\u043e\u0434\u0430 \u0438\u0437 \u0445\u044d\u0448-\u0442\u0430\u0431\u043b\u0438\u0446\u044b \u0432 HyperLogLog \u0432\u044b\u0432\u043e\u0434\u044f\u0442\u0441\u044f \u0438\u0437 \u043d\u0430\u0441\u0442\u0440\u043e\u0439\u043a\u0438 `distinct_precision_threshold`. \u0412\u0430\u0436\u043d\u043e \u0438\u0441\u043f\u043e\u043b\u044c\u0437\u043e\u0432\u0430\u0442\u044c \u044d\u0442\u0443 \u043e\u043f\u0446\u0438\u044e \u0441 \u043e\u0441\u0442\u043e\u0440\u043e\u0436\u043d\u043e\u0441\u0442\u044c\u044e, \u0442\u0430\u043a \u043a\u0430\u043a \u0443\u0434\u0432\u043e\u0435\u043d\u0438\u0435 \u0435\u0451 \u0437\u043d\u0430\u0447\u0435\u043d\u0438\u044f \u0442\u0430\u043a\u0436\u0435 \u0443\u0434\u0432\u043e\u0438\u0442 \u043c\u0430\u043a\u0441\u0438\u043c\u0430\u043b\u044c\u043d\u044b\u0439 \u043e\u0431\u044a\u0451\u043c \u043f\u0430\u043c\u044f\u0442\u0438, \u043d\u0435\u043e\u0431\u0445\u043e\u0434\u0438\u043c\u044b\u0439 \u0434\u043b\u044f \u043f\u043e\u0434\u0441\u0447\u0451\u0442\u043e\u0432. \u041c\u0430\u043a\u0441\u0438\u043c\u0430\u043b\u044c\u043d\u043e\u0435 \u0438\u0441\u043f\u043e\u043b\u044c\u0437\u043e\u0432\u0430\u043d\u0438\u0435 \u043f\u0430\u043c\u044f\u0442\u0438 \u043c\u043e\u0436\u043d\u043e \u043f\u0440\u0438\u043c\u0435\u0440\u043d\u043e \u043e\u0446\u0435\u043d\u0438\u0442\u044c \u043f\u043e \u0444\u043e\u0440\u043c\u0443\u043b\u0435: `64 * max_matches * distinct_precision_threshold`, \u0445\u043e\u0442\u044f \u043d\u0430 \u043f\u0440\u0430\u043a\u0442\u0438\u043a\u0435 \u043f\u043e\u0434\u0441\u0447\u0451\u0442\u044b \u0447\u0430\u0441\u0442\u043e \u0438\u0441\u043f\u043e\u043b\u044c\u0437\u0443\u044e\u0442 \u043c\u0435\u043d\u044c\u0448\u0435 \u043f\u0430\u043c\u044f\u0442\u0438, \u0447\u0435\u043c \u0432 \u0445\u0443\u0434\u0448\u0435\u043c \u0441\u043b\u0443\u0447\u0430\u0435."
        },
        "is_code_or_comment": false,
        "model": "openai:gpt-4.1-mini",
        "updated_at": 1766339820
    },
    "a4c868a366e86ef9cb2247bd2c9551d3b56361aa60c3979c5c22c5369d43f5bc": {
        "original": "### expand_keywords\n`0` or `1` (`0` by default). Expands keywords with exact forms and/or stars when possible. Refer to [expand_keywords](../Creating_a_table/NLP_and_tokenization/Wildcard_searching_settings.md#expand_keywords) for more details.\n\n### field_weights\nNamed integer list (per-field user weights for ranking).\n\nExample:\nCODE_BLOCK_8\n\n### global_idf\nUse global statistics (frequencies) from the [global_idf](../Creating_a_table/NLP_and_tokenization/Low-level_tokenization.md#global_idf) file for IDF computations.\n\n### idf\nQuoted, comma-separated list of IDF computation flags. Known flags are:\n\n* `normalized`: BM25 variant, idf = log((N-n+1)/n), as per Robertson et al\n* `plain`: plain variant, idf = log(N/n), as per Sparck-Jones\n* `tfidf_normalized`: additionally divide IDF by query word count, so that `TF*IDF` fits into [0, 1] range\n* `tfidf_unnormalized`: do not additionally divide IDF by query word count where N is the collection size and n is the number of matched documents\n\nThe historically default IDF (Inverse Document Frequency) in Manticore is equivalent to `OPTION idf='normalized,tfidf_normalized'`, and those normalizations may cause several undesired effects.\n\nFirst, `idf=normalized` causes keyword penalization. For instance, if you search for `the | something` and `the` occurs in more than 50% of the documents, then documents with both keywords `the` and `something` will get less weight than documents with just one keyword `something`. Using `OPTION idf=plain` avoids this. Plain IDF varies in `[0, log(N)]` range, and keywords are never penalized; while the normalized IDF varies in `[-log(N), log(N)]` range, and too frequent keywords are penalized.\n\nSecond, `idf=tfidf_normalized` leads to IDF drift across queries. Historically, IDF was also divided by the query keyword count, ensuring the entire `sum(tf*idf)` across all keywords remained within the [0,1] range. However, this meant that queries like `word1` and `word1 | nonmatchingword2` would assign different weights to the exact same result set, as the IDFs for both `word1` and `nonmatchingword2` would be divided by 2. Using `OPTION idf='tfidf_unnormalized'` resolves this issue. Keep in mind that BM25, BM25A, BM25F() ranking factors will be adjusted accordingly when you disable this normalization.\n\nIDF flags can be combined; `plain` and `normalized` are mutually exclusive; `tfidf_unnormalized` and `tfidf_normalized` are also mutually exclusive; and unspecified flags in such mutually exclusive groups default to their original settings. This means `OPTION idf=plain` is the same as specifying `OPTION idf='plain,tfidf_normalized'` in its entirety.\n\n### jieba_mode\nSpecifies the Jieba segmentation mode for the query.\n\nWhen using Jieba Chinese segmentation, it can sometimes help to use different segmentation modes for tokenizing the documents and the query. For a complete list of modes, refer to [jieba_mode](../Creating_a_table/NLP_and_tokenization/Morphology.md#jieba_mode).\n\n### index_weights\nNamed integer list. Per-table user weights for ranking.\n\n### local_df\n`0` or `1`, automatically sum DFs over all local parts of a distributed table, ensuring consistent (and accurate) IDF across a locally sharded table. Enabled by default for disk chunks of the RT table. Query terms with wildcards are ignored.\n\n### low_priority\n`0` or `1` (`0` by default). Setting `low_priority=1` executes the query with a lower priority, rescheduling its jobs 10 times less frequently than other queries with normal priority.\n\n### max_matches\nInteger. Per-query max matches value.\n\nThe maximum number of matches that the server retains in RAM for each table and can return to the client. The default is 1000.\n\nIntroduced to control and limit RAM usage, the `max_matches` setting determines how many matches will be kept in RAM while searching each table. Every match found is still processed, but only the best N of them will be retained in memory and returned to the client in the end. For example, suppose a table contains 2,000,000 matches for a query. It's rare that you would need to retrieve all of them. Instead, you need to scan all of them but only choose the \"best\" 500, for instance, based on some criteria (e.g., sorted by relevance, price, or other factors) and display those 500 matches to the end user in pages of 20 to 100 matches. Tracking only the best 500 matches is much more RAM and CPU efficient than keeping all 2,000,000 matches, sorting them, and then discarding everything but the first 20 needed for the search results page. `max_matches` controls the N in that \"best N\" amount.\n\nThis parameter significantly impacts per-query RAM and CPU usage. Values of 1,000 to 10,000 are generally acceptable, but higher limits should be used with caution. Carelessly increasing max_matches to 1,000,000 means that `searchd` will have to allocate and initialize a 1-million-entry matches buffer for every query. This will inevitably increase per-query RAM usage and, in some cases, can noticeably affect performance.\n\nRefer to [max_matches_increase_threshold](../Searching/Options.md#max_matches_increase_threshold) for additional information on how it can influence the behavior of the `max_matches` option.\n\n### max_matches_increase_threshold\n\nInteger. Sets the threshold that `max_matches` can be increased to. Default is 16384.\n\nManticore may increase `max_matches` to enhance groupby and/or aggregation accuracy when `pseudo_sharding` is enabled, and if it detects that the number of unique values of the groupby attribute is less than this threshold. Loss of accuracy may occur when pseudo-sharding executes the query in multiple threads or when an RT table conducts parallel searches in disk chunks.\n\nIf the number of unique values of the groupby attribute is less than the threshold, `max_matches` will be set to this number. Otherwise, the default `max_matches` will be used.\n\nIf `max_matches` was explicitly set in query options, this threshold has no effect.\n\nKeep in mind that if this threshold is set too high, it will result in increased memory consumption and general performance degradation.",
        "translations": {
            "chinese": "### expand_keywords\n`0` \u6216 `1`\uff08\u9ed8\u8ba4\u503c\u4e3a `0`\uff09\u3002\u5728\u53ef\u80fd\u7684\u60c5\u51b5\u4e0b\u6269\u5c55\u5173\u952e\u8bcd\u4e3a\u7cbe\u786e\u5f62\u5f0f\u548c/\u6216\u901a\u914d\u7b26\u3002\u8be6\u60c5\u8bf7\u53c2\u89c1 [expand_keywords](../Creating_a_table/NLP_and_tokenization/Wildcard_searching_settings.md#expand_keywords)\u3002\n\n### field_weights\n\u547d\u540d\u7684\u6574\u6570\u5217\u8868\uff08\u6309\u5b57\u6bb5\u7684\u7528\u6237\u6743\u91cd\uff0c\u7528\u4e8e\u6392\u540d\uff09\u3002\n\n\u793a\u4f8b\uff1a\nCODE_BLOCK_8\n\n### global_idf\n\u4f7f\u7528 [global_idf](../Creating_a_table/NLP_and_tokenization/Low-level_tokenization.md#global_idf) \u6587\u4ef6\u4e2d\u7684\u5168\u5c40\u7edf\u8ba1\u6570\u636e\uff08\u9891\u7387\uff09\u8fdb\u884c IDF \u8ba1\u7b97\u3002\n\n### idf\n\u5e26\u5f15\u53f7\u7684\u3001\u7528\u9017\u53f7\u5206\u9694\u7684 IDF \u8ba1\u7b97\u6807\u5fd7\u5217\u8868\u3002\u5df2\u77e5\u6807\u5fd7\u5305\u62ec\uff1a\n\n* `normalized`\uff1aBM25 \u53d8\u4f53\uff0cidf = log((N-n+1)/n)\uff0c\u6839\u636e Robertson \u7b49\u4eba\n* `plain`\uff1a\u7eaf\u53d8\u4f53\uff0cidf = log(N/n)\uff0c\u6839\u636e Sparck-Jones\n* `tfidf_normalized`\uff1a\u989d\u5916\u6309\u67e5\u8be2\u8bcd\u6570\u9664\u4ee5 IDF\uff0c\u4f7f `TF*IDF` \u9002\u5408\u4e8e [0, 1] \u8303\u56f4\u5185\n* `tfidf_unnormalized`\uff1a\u4e0d\u989d\u5916\u6309\u67e5\u8be2\u8bcd\u6570\u9664\u4ee5 IDF\uff0c\u5176\u4e2d N \u662f\u96c6\u5408\u5927\u5c0f\uff0cn \u662f\u5339\u914d\u6587\u6863\u6570\n\nManticore \u5386\u53f2\u9ed8\u8ba4\u7684\u9006\u6587\u6863\u9891\u7387\uff08IDF\uff09\u7b49\u4ef7\u4e8e `OPTION idf='normalized,tfidf_normalized'`\uff0c\u8fd9\u4e9b\u5f52\u4e00\u5316\u53ef\u80fd\u5bfc\u81f4\u82e5\u5e72\u4e0d\u671f\u671b\u7684\u6548\u679c\u3002\n\n\u9996\u5148\uff0c`idf=normalized` \u4f1a\u5bfc\u81f4\u5173\u952e\u8bcd\u60e9\u7f5a\u3002\u4f8b\u5982\uff0c\u5982\u679c\u641c\u7d22 `the | something` \u4e14 `the` \u51fa\u73b0\u5728\u8d85\u8fc7 50% \u7684\u6587\u6863\u4e2d\uff0c\u5219\u540c\u65f6\u542b\u6709 `the` \u548c `something` \u4e24\u4e2a\u5173\u952e\u8bcd\u7684\u6587\u6863\u6743\u91cd\u4f1a\u4f4e\u4e8e\u53ea\u542b\u6709\u4e00\u4e2a\u5173\u952e\u8bcd `something` \u7684\u6587\u6863\u3002\u4f7f\u7528 `OPTION idf=plain` \u53ef\u907f\u514d\u6b64\u95ee\u9898\u3002\u7eaf IDF \u53d8\u52a8\u8303\u56f4\u4e3a `[0, log(N)]`\uff0c\u5173\u952e\u8bcd\u4e0d\u4f1a\u88ab\u60e9\u7f5a\uff1b\u800c\u5f52\u4e00\u5316\u7684 IDF \u53d8\u52a8\u8303\u56f4\u4e3a `[-log(N), log(N)]`\uff0c\u8fc7\u4e8e\u9891\u7e41\u7684\u5173\u952e\u8bcd\u4f1a\u88ab\u60e9\u7f5a\u3002\n\n\u5176\u6b21\uff0c`idf=tfidf_normalized` \u4f1a\u5bfc\u81f4 IDF \u5728\u67e5\u8be2\u95f4\u6f02\u79fb\u3002\u5386\u53f2\u4e0a\uff0cIDF \u8fd8\u4f1a\u88ab\u67e5\u8be2\u5173\u952e\u8bcd\u6570\u91cf\u9664\u4ee5\uff0c\u786e\u4fdd\u6240\u6709\u5173\u952e\u8bcd\u7684 `sum(tf*idf)` \u4fdd\u6301\u5728 [0,1] \u8303\u56f4\u5185\u3002\u7136\u800c\uff0c\u8fd9\u610f\u5473\u7740\u50cf `word1` \u548c `word1 | nonmatchingword2` \u8fd9\u6837\u7684\u67e5\u8be2\u4f1a\u7ed9\u540c\u4e00\u7ed3\u679c\u96c6\u5206\u914d\u4e0d\u540c\u6743\u91cd\uff0c\u56e0\u4e3a `word1` \u548c `nonmatchingword2` \u7684 IDF \u90fd\u88ab\u9664\u4ee5\u4e86 2\u3002\u4f7f\u7528 `OPTION idf='tfidf_unnormalized'` \u53ef\u89e3\u51b3\u6b64\u95ee\u9898\u3002\u8bf7\u8bb0\u4f4f\uff0c\u5f53\u60a8\u7981\u7528\u6b64\u5f52\u4e00\u5316\u65f6\uff0cBM25\u3001BM25A\u3001BM25F() \u6392\u540d\u56e0\u5b50\u5c06\u76f8\u5e94\u8c03\u6574\u3002\n\nIDF \u6807\u5fd7\u53ef\u4ee5\u7ec4\u5408\uff1b`plain` \u548c `normalized` \u4e92\u65a5\uff1b`tfidf_unnormalized` \u548c `tfidf_normalized` \u4e5f\u4e92\u65a5\uff1b\u5728\u6b64\u7c7b\u4e92\u65a5\u7ec4\u4e2d\u672a\u6307\u5b9a\u7684\u6807\u5fd7\u9ed8\u8ba4\u4e3a\u5176\u539f\u59cb\u8bbe\u7f6e\u3002\u8fd9\u610f\u5473\u7740 `OPTION idf=plain` \u7b49\u540c\u4e8e\u5b8c\u6574\u6307\u5b9a `OPTION idf='plain,tfidf_normalized'`\u3002\n\n### jieba_mode\n\u6307\u5b9a\u67e5\u8be2\u7684 Jieba \u5206\u8bcd\u6a21\u5f0f\u3002\n\n\u4f7f\u7528 Jieba \u4e2d\u6587\u5206\u8bcd\u65f6\uff0c\u6587\u6863\u548c\u67e5\u8be2\u7684\u5206\u8bcd\u6a21\u5f0f\u53ef\u80fd\u4e0d\u540c\uff0c\u4ece\u800c\u5e26\u6765\u5e2e\u52a9\u3002\u5b8c\u6574\u6a21\u5f0f\u5217\u8868\u8bf7\u53c2\u89c1 [jieba_mode](../Creating_a_table/NLP_and_tokenization/Morphology.md#jieba_mode)\u3002\n\n### index_weights\n\u547d\u540d\u7684\u6574\u6570\u5217\u8868\u3002\u6309\u8868\u7684\u7528\u6237\u6743\u91cd\uff0c\u7528\u4e8e\u6392\u540d\u3002\n\n### local_df\n`0` \u6216 `1`\uff0c\u81ea\u52a8\u5bf9\u5206\u5e03\u5f0f\u8868\u7684\u6240\u6709\u672c\u5730\u90e8\u5206\u6c47\u603b\u6587\u6863\u9891\u7387\uff0c\u786e\u4fdd\u5c40\u90e8\u5206\u7247\u8868\u4e2d\u7684 IDF \u4e00\u81f4\u4e14\u51c6\u786e\u3002\u9ed8\u8ba4\u5728 RT \u8868\u7684\u78c1\u76d8\u533a\u5757\u542f\u7528\u3002\u5e26\u901a\u914d\u7b26\u7684\u67e5\u8be2\u8bcd\u88ab\u5ffd\u7565\u3002\n\n### low_priority\n`0` \u6216 `1`\uff08\u9ed8\u8ba4\u503c\u4e3a `0`\uff09\u3002\u8bbe\u7f6e `low_priority=1` \u4ee5\u8f83\u4f4e\u4f18\u5148\u7ea7\u6267\u884c\u67e5\u8be2\uff0c\u5176\u4f5c\u4e1a\u8c03\u5ea6\u9891\u7387\u6bd4\u6b63\u5e38\u4f18\u5148\u7ea7\u67e5\u8be2\u4f4e 10 \u500d\u3002\n\n### max_matches\n\u6574\u6570\u3002\u6bcf\u4e2a\u67e5\u8be2\u7684\u6700\u5927\u5339\u914d\u6570\u503c\u3002\n\n\u670d\u52a1\u5668\u4e3a\u6bcf\u4e2a\u8868\u4fdd\u7559\u5728 RAM \u4e2d\u7684\u6700\u5927\u5339\u914d\u6570\uff0c\u5e76\u53ef\u8fd4\u56de\u7ed9\u5ba2\u6237\u7aef\u3002\u9ed8\u8ba4\u503c\u4e3a 1000\u3002\n\n\u6b64\u8bbe\u7f6e\u7528\u4e8e\u63a7\u5236\u548c\u9650\u5236\u5185\u5b58\u4f7f\u7528\u91cf\u3002`max_matches` \u786e\u5b9a\u5728\u641c\u7d22\u6bcf\u4e2a\u8868\u65f6\u4fdd\u7559\u5728\u5185\u5b58\u4e2d\u7684\u5339\u914d\u6570\u91cf\u3002\u6bcf\u4e2a\u5339\u914d\u90fd\u4f1a\u88ab\u5904\u7406\uff0c\u4f46\u53ea\u6709\u6700\u4f18\u7684 N \u4e2a\u5339\u914d\u4f1a\u88ab\u4fdd\u5b58\u5728\u5185\u5b58\u4e2d\uff0c\u5e76\u6700\u7ec8\u8fd4\u56de\u7ed9\u5ba2\u6237\u7aef\u3002\u4f8b\u5982\uff0c\u5047\u8bbe\u67d0\u8868\u9488\u5bf9\u4e00\u4e2a\u67e5\u8be2\u6709 2,000,000 \u4e2a\u5339\u914d\u3002\u60a8\u5f88\u5c11\u9700\u8981\u68c0\u7d22\u5168\u90e8\u5339\u914d\u3002\u76f8\u53cd\uff0c\u60a8\u9700\u8981\u626b\u63cf\u6240\u6709\u5339\u914d\uff0c\u4f46\u53ea\u9009\u62e9\u201c\u6700\u4f18\u201d\u7684 500 \u4e2a\uff08\u57fa\u4e8e\u67d0\u4e9b\u6807\u51c6\uff0c\u4f8b\u5982\u76f8\u5173\u6027\u3001\u4ef7\u683c\u6216\u5176\u4ed6\u56e0\u7d20\uff09\uff0c\u5e76\u5206\u9875\u663e\u793a\u8fd9 500 \u4e2a\u5339\u914d\uff0c\u5355\u9875 20 \u5230 100 \u6761\u3002\u4ec5\u8ddf\u8e2a\u6700\u4f18\u7684 500 \u4e2a\u5339\u914d\u6bd4\u4fdd\u7559\u5168\u90e8 2,000,000 \u4e2a\u5339\u914d\u4e14\u6392\u5e8f\uff0c\u7136\u540e\u4e22\u5f03\u9664\u524d20\u4e2a\u7ed3\u679c\u5916\u7684\u7ed3\u679c\u8981\u9ad8\u6548\u5f97\u591a\u3002`max_matches` \u63a7\u5236\u8fd9\u4e2a\u201c\u6700\u4f18 N \u6570\u91cf\u201d\u3002\n\n\u6b64\u53c2\u6570\u663e\u8457\u5f71\u54cd\u6bcf\u4e2a\u67e5\u8be2\u7684\u5185\u5b58\u548c CPU \u4f7f\u7528\u3002\u901a\u5e38 1,000 \u5230 10,000 \u7684\u503c\u662f\u53ef\u63a5\u53d7\u7684\uff0c\u4f46\u8fc7\u9ad8\u503c\u9700\u8981\u8c28\u614e\u4f7f\u7528\u3002\u4efb\u610f\u589e\u52a0 max_matches \u5230 1,000,000 \u610f\u5473\u7740 `searchd` \u4f1a\u4e3a\u6bcf\u4e2a\u67e5\u8be2\u5206\u914d\u548c\u521d\u59cb\u5316\u4e00\u4e2a\u5305\u542b\u4e00\u767e\u4e07\u6761\u76ee\u7684\u5339\u914d\u7f13\u51b2\u533a\uff0c\u8fd9\u5fc5\u7136\u589e\u52a0\u6bcf\u67e5\u8be2\u7684\u5185\u5b58\u4f7f\u7528\uff0c\u6709\u65f6\u4f1a\u660e\u663e\u5f71\u54cd\u6027\u80fd\u3002\n\n\u6709\u5173\u5176\u5982\u4f55\u5f71\u54cd `max_matches` \u9009\u9879\u884c\u4e3a\u7684\u9644\u52a0\u4fe1\u606f\uff0c\u8bf7\u53c2\u89c1 [max_matches_increase_threshold](../Searching/Options.md#max_matches_increase_threshold)\u3002\n\n### max_matches_increase_threshold\n\n\u6574\u6570\u3002\u8bbe\u7f6e\u53ef\u589e\u52a0\u7684 `max_matches` \u9608\u503c\u3002\u9ed8\u8ba4\u503c\u662f 16384\u3002\n\n\u5f53\u542f\u7528 `pseudo_sharding` \u5e76\u4e14\u68c0\u6d4b\u5230 groupby \u5c5e\u6027\u552f\u4e00\u503c\u6570\u91cf\u5c0f\u4e8e\u6b64\u9608\u503c\u65f6\uff0cManticore \u53ef\u80fd\u4f1a\u589e\u5927 `max_matches` \u4ee5\u63d0\u9ad8 groupby \u548c/\u6216\u805a\u5408\u7684\u51c6\u786e\u6027\u3002\u7cbe\u5ea6\u635f\u5931\u53ef\u80fd\u51fa\u73b0\u5728 pseudo-sharding \u5728\u591a\u7ebf\u7a0b\u4e2d\u6267\u884c\u67e5\u8be2\uff0c\u6216 RT \u8868\u5bf9\u78c1\u76d8\u533a\u5757\u8fdb\u884c\u5e76\u884c\u641c\u7d22\u65f6\u3002\n\n\u5982\u679c groupby \u5c5e\u6027\u7684\u552f\u4e00\u503c\u6570\u91cf\u5c0f\u4e8e\u6b64\u9608\u503c\uff0c\u5219 `max_matches` \u4f1a\u88ab\u8bbe\u7f6e\u4e3a\u8be5\u6570\u91cf\u3002\u5426\u5219\uff0c\u4f7f\u7528\u9ed8\u8ba4\u7684 `max_matches`\u3002\n\n\u5982\u679c\u67e5\u8be2\u9009\u9879\u4e2d\u663e\u5f0f\u8bbe\u7f6e\u4e86 `max_matches`\uff0c\u6b64\u9608\u503c\u65e0\u6548\u3002\n\n\u8bf7\u6ce8\u610f\uff0c\u9608\u503c\u8bbe\u7f6e\u8fc7\u9ad8\u4f1a\u5bfc\u81f4\u5185\u5b58\u4f7f\u7528\u589e\u52a0\u548c\u6574\u4f53\u6027\u80fd\u4e0b\u964d\u3002",
            "russian": "### expand_keywords\n`0` \u0438\u043b\u0438 `1` (\u043f\u043e \u0443\u043c\u043e\u043b\u0447\u0430\u043d\u0438\u044e `0`). \u0420\u0430\u0441\u0448\u0438\u0440\u044f\u0435\u0442 \u043a\u043b\u044e\u0447\u0435\u0432\u044b\u0435 \u0441\u043b\u043e\u0432\u0430 \u0442\u043e\u0447\u043d\u044b\u043c\u0438 \u0444\u043e\u0440\u043c\u0430\u043c\u0438 \u0438/\u0438\u043b\u0438 \u0437\u0432\u0451\u0437\u0434\u043e\u0447\u043a\u0430\u043c\u0438, \u0435\u0441\u043b\u0438 \u044d\u0442\u043e \u0432\u043e\u0437\u043c\u043e\u0436\u043d\u043e. \u041f\u043e\u0434\u0440\u043e\u0431\u043d\u043e\u0441\u0442\u0438 \u0441\u043c\u043e\u0442\u0440\u0438\u0442\u0435 \u0432 [expand_keywords](../Creating_a_table/NLP_and_tokenization/Wildcard_searching_settings.md#expand_keywords).\n\n### field_weights\n\u0418\u043c\u0435\u043d\u043e\u0432\u0430\u043d\u043d\u044b\u0439 \u0441\u043f\u0438\u0441\u043e\u043a \u0446\u0435\u043b\u044b\u0445 \u0447\u0438\u0441\u0435\u043b (\u0432\u0435\u0441\u0430 \u043f\u043e\u043b\u044c\u0437\u043e\u0432\u0430\u0442\u0435\u043b\u044f \u0434\u043b\u044f \u0440\u0430\u043d\u0436\u0438\u0440\u043e\u0432\u0430\u043d\u0438\u044f \u043f\u043e \u043f\u043e\u043b\u044f\u043c).\n\n\u041f\u0440\u0438\u043c\u0435\u0440:\nCODE_BLOCK_8\n\n### global_idf\n\u0418\u0441\u043f\u043e\u043b\u044c\u0437\u043e\u0432\u0430\u0442\u044c \u0433\u043b\u043e\u0431\u0430\u043b\u044c\u043d\u0443\u044e \u0441\u0442\u0430\u0442\u0438\u0441\u0442\u0438\u043a\u0443 (\u0447\u0430\u0441\u0442\u043e\u0442\u044b) \u0438\u0437 \u0444\u0430\u0439\u043b\u0430 [global_idf](../Creating_a_table/NLP_and_tokenization/Low-level_tokenization.md#global_idf) \u0434\u043b\u044f \u0432\u044b\u0447\u0438\u0441\u043b\u0435\u043d\u0438\u0439 IDF.\n\n### idf\n\u041a\u0430\u0432\u044b\u0447\u043a\u0430\u043c\u0438, \u0447\u0435\u0440\u0435\u0437 \u0437\u0430\u043f\u044f\u0442\u0443\u044e \u043f\u0435\u0440\u0435\u0447\u0438\u0441\u043b\u0435\u043d\u043d\u044b\u0435 \u0444\u043b\u0430\u0433\u0438 \u0432\u044b\u0447\u0438\u0441\u043b\u0435\u043d\u0438\u044f IDF. \u0418\u0437\u0432\u0435\u0441\u0442\u043d\u044b\u0435 \u0444\u043b\u0430\u0433\u0438:\n\n* `normalized`: \u0432\u0430\u0440\u0438\u0430\u043d\u0442 BM25, idf = log((N-n+1)/n), \u0441\u043e\u0433\u043b\u0430\u0441\u043d\u043e Robertson et al\n* `plain`: \u043f\u0440\u043e\u0441\u0442\u043e\u0439 \u0432\u0430\u0440\u0438\u0430\u043d\u0442, idf = log(N/n), \u0441\u043e\u0433\u043b\u0430\u0441\u043d\u043e Sparck-Jones\n* `tfidf_normalized`: \u0434\u043e\u043f\u043e\u043b\u043d\u0438\u0442\u0435\u043b\u044c\u043d\u043e \u0434\u0435\u043b\u0438\u0442\u044c IDF \u043d\u0430 \u043a\u043e\u043b\u0438\u0447\u0435\u0441\u0442\u0432\u043e \u0441\u043b\u043e\u0432 \u0437\u0430\u043f\u0440\u043e\u0441\u0430, \u0447\u0442\u043e\u0431\u044b `TF*IDF` \u043d\u0430\u0445\u043e\u0434\u0438\u043b\u0441\u044f \u0432 \u0434\u0438\u0430\u043f\u0430\u0437\u043e\u043d\u0435 [0, 1]\n* `tfidf_unnormalized`: \u043d\u0435 \u0434\u0435\u043b\u0438\u0442\u044c \u0434\u043e\u043f\u043e\u043b\u043d\u0438\u0442\u0435\u043b\u044c\u043d\u043e IDF \u043d\u0430 \u043a\u043e\u043b\u0438\u0447\u0435\u0441\u0442\u0432\u043e \u0441\u043b\u043e\u0432 \u0437\u0430\u043f\u0440\u043e\u0441\u0430, \u0433\u0434\u0435 N \u2014 \u0440\u0430\u0437\u043c\u0435\u0440 \u043a\u043e\u043b\u043b\u0435\u043a\u0446\u0438\u0438, \u0430 n \u2014 \u043a\u043e\u043b\u0438\u0447\u0435\u0441\u0442\u0432\u043e \u0441\u043e\u0432\u043f\u0430\u0434\u0430\u044e\u0449\u0438\u0445 \u0434\u043e\u043a\u0443\u043c\u0435\u043d\u0442\u043e\u0432\n\n\u0418\u0441\u0442\u043e\u0440\u0438\u0447\u0435\u0441\u043a\u0438 \u0438\u0441\u043f\u043e\u043b\u044c\u0437\u0443\u0435\u043c\u044b\u0439 \u043f\u043e \u0443\u043c\u043e\u043b\u0447\u0430\u043d\u0438\u044e IDF (\u043e\u0431\u0440\u0430\u0442\u043d\u0430\u044f \u0447\u0430\u0441\u0442\u043e\u0442\u0430 \u0434\u043e\u043a\u0443\u043c\u0435\u043d\u0442\u0430) \u0432 Manticore \u044d\u043a\u0432\u0438\u0432\u0430\u043b\u0435\u043d\u0442\u0435\u043d `OPTION idf='normalized,tfidf_normalized'`, \u0438 \u044d\u0442\u0438 \u043d\u043e\u0440\u043c\u0430\u043b\u0438\u0437\u0430\u0446\u0438\u0438 \u043c\u043e\u0433\u0443\u0442 \u0432\u044b\u0437\u044b\u0432\u0430\u0442\u044c \u043d\u0435\u0441\u043a\u043e\u043b\u044c\u043a\u043e \u043d\u0435\u0436\u0435\u043b\u0430\u0442\u0435\u043b\u044c\u043d\u044b\u0445 \u044d\u0444\u0444\u0435\u043a\u0442\u043e\u0432.\n\n\u0412\u043e-\u043f\u0435\u0440\u0432\u044b\u0445, `idf=normalized` \u043f\u0440\u0438\u0432\u043e\u0434\u0438\u0442 \u043a \u0448\u0442\u0440\u0430\u0444\u043e\u0432\u0430\u043d\u0438\u044e \u043a\u043b\u044e\u0447\u0435\u0432\u044b\u0445 \u0441\u043b\u043e\u0432. \u041d\u0430\u043f\u0440\u0438\u043c\u0435\u0440, \u0435\u0441\u043b\u0438 \u0432\u044b \u0438\u0449\u0435\u0442\u0435 `the | something` \u0438 `the` \u0432\u0441\u0442\u0440\u0435\u0447\u0430\u0435\u0442\u0441\u044f \u0431\u043e\u043b\u0435\u0435 \u0447\u0435\u043c \u0432 50% \u0434\u043e\u043a\u0443\u043c\u0435\u043d\u0442\u043e\u0432, \u0442\u043e\u0433\u0434\u0430 \u0434\u043e\u043a\u0443\u043c\u0435\u043d\u0442\u044b \u0441 \u0434\u0432\u0443\u043c\u044f \u043a\u043b\u044e\u0447\u0435\u0432\u044b\u043c\u0438 \u0441\u043b\u043e\u0432\u0430\u043c\u0438 `the` \u0438 `something` \u0431\u0443\u0434\u0443\u0442 \u0438\u043c\u0435\u0442\u044c \u043c\u0435\u043d\u044c\u0448\u0438\u0439 \u0432\u0435\u0441, \u0447\u0435\u043c \u0434\u043e\u043a\u0443\u043c\u0435\u043d\u0442\u044b \u0441 \u043e\u0434\u043d\u0438\u043c \u043a\u043b\u044e\u0447\u0435\u0432\u044b\u043c \u0441\u043b\u043e\u0432\u043e\u043c `something`. \u0418\u0441\u043f\u043e\u043b\u044c\u0437\u043e\u0432\u0430\u043d\u0438\u0435 `OPTION idf=plain` \u044d\u0442\u043e \u0438\u0437\u0431\u0435\u0433\u0430\u0435\u0442. \u041f\u0440\u043e\u0441\u0442\u043e\u0439 IDF \u0432\u0430\u0440\u044c\u0438\u0440\u0443\u0435\u0442\u0441\u044f \u0432 \u0434\u0438\u0430\u043f\u0430\u0437\u043e\u043d\u0435 `[0, log(N)]`, \u0438 \u043a\u043b\u044e\u0447\u0435\u0432\u044b\u0435 \u0441\u043b\u043e\u0432\u0430 \u043d\u0438\u043a\u043e\u0433\u0434\u0430 \u043d\u0435 \u0448\u0442\u0440\u0430\u0444\u0443\u044e\u0442\u0441\u044f; \u0430 \u043d\u043e\u0440\u043c\u0430\u043b\u0438\u0437\u043e\u0432\u0430\u043d\u043d\u044b\u0439 IDF \u0432\u0430\u0440\u044c\u0438\u0440\u0443\u0435\u0442\u0441\u044f \u0432 \u0434\u0438\u0430\u043f\u0430\u0437\u043e\u043d\u0435 `[-log(N), log(N)]`, \u0438 \u0441\u043b\u0438\u0448\u043a\u043e\u043c \u0447\u0430\u0441\u0442\u043e\u0442\u043d\u044b\u0435 \u043a\u043b\u044e\u0447\u0435\u0432\u044b\u0435 \u0441\u043b\u043e\u0432\u0430 \u0448\u0442\u0440\u0430\u0444\u0443\u044e\u0442\u0441\u044f.\n\n\u0412\u043e-\u0432\u0442\u043e\u0440\u044b\u0445, `idf=tfidf_normalized` \u043f\u0440\u0438\u0432\u043e\u0434\u0438\u0442 \u043a \u0434\u0440\u0435\u0439\u0444\u0443 IDF \u043c\u0435\u0436\u0434\u0443 \u0437\u0430\u043f\u0440\u043e\u0441\u0430\u043c\u0438. \u0418\u0441\u0442\u043e\u0440\u0438\u0447\u0435\u0441\u043a\u0438 IDF \u0442\u0430\u043a\u0436\u0435 \u0434\u0435\u043b\u0438\u043b\u0441\u044f \u043d\u0430 \u043a\u043e\u043b\u0438\u0447\u0435\u0441\u0442\u0432\u043e \u043a\u043b\u044e\u0447\u0435\u0432\u044b\u0445 \u0441\u043b\u043e\u0432 \u0432 \u0437\u0430\u043f\u0440\u043e\u0441\u0435, \u0433\u0430\u0440\u0430\u043d\u0442\u0438\u0440\u0443\u044f, \u0447\u0442\u043e \u0441\u0443\u043c\u043c\u0430 \u043f\u043e \u0432\u0441\u0435\u043c \u043a\u043b\u044e\u0447\u0435\u0432\u044b\u043c \u0441\u043b\u043e\u0432\u0430\u043c `sum(tf*idf)` \u043e\u0441\u0442\u0430\u0432\u0430\u043b\u0430\u0441\u044c \u0432 \u0434\u0438\u0430\u043f\u0430\u0437\u043e\u043d\u0435 [0,1]. \u041e\u0434\u043d\u0430\u043a\u043e \u044d\u0442\u043e \u043e\u0437\u043d\u0430\u0447\u0430\u043b\u043e, \u0447\u0442\u043e \u0437\u0430\u043f\u0440\u043e\u0441\u044b, \u043d\u0430\u043f\u0440\u0438\u043c\u0435\u0440, `word1` \u0438 `word1 | nonmatchingword2` \u043f\u0440\u0438\u0441\u0432\u0430\u0438\u0432\u0430\u043b\u0438 \u0440\u0430\u0437\u043d\u044b\u0439 \u0432\u0435\u0441 \u0430\u0431\u0441\u043e\u043b\u044e\u0442\u043d\u043e \u043e\u0434\u0438\u043d\u0430\u043a\u043e\u0432\u043e\u043c\u0443 \u043c\u043d\u043e\u0436\u0435\u0441\u0442\u0432\u0443 \u0440\u0435\u0437\u0443\u043b\u044c\u0442\u0430\u0442\u043e\u0432, \u0442\u0430\u043a \u043a\u0430\u043a IDF \u0434\u043b\u044f \u043e\u0431\u043e\u0438\u0445 \u0441\u043b\u043e\u0432 \u0434\u0435\u043b\u0438\u043b\u043e\u0441\u044c \u043d\u0430 2. \u0418\u0441\u043f\u043e\u043b\u044c\u0437\u043e\u0432\u0430\u043d\u0438\u0435 `OPTION idf='tfidf_unnormalized'` \u0440\u0435\u0448\u0430\u0435\u0442 \u044d\u0442\u0443 \u043f\u0440\u043e\u0431\u043b\u0435\u043c\u0443. \u0418\u043c\u0435\u0439\u0442\u0435 \u0432 \u0432\u0438\u0434\u0443, \u0447\u0442\u043e \u0444\u0430\u043a\u0442\u043e\u0440\u044b \u0440\u0430\u043d\u0436\u0438\u0440\u043e\u0432\u0430\u043d\u0438\u044f BM25, BM25A, BM25F() \u0431\u0443\u0434\u0443\u0442 \u0441\u043e\u043e\u0442\u0432\u0435\u0442\u0441\u0442\u0432\u0435\u043d\u043d\u043e \u0441\u043a\u043e\u0440\u0440\u0435\u043a\u0442\u0438\u0440\u043e\u0432\u0430\u043d\u044b \u043f\u0440\u0438 \u043e\u0442\u043a\u043b\u044e\u0447\u0435\u043d\u0438\u0438 \u044d\u0442\u043e\u0439 \u043d\u043e\u0440\u043c\u0430\u043b\u0438\u0437\u0430\u0446\u0438\u0438.\n\n\u0424\u043b\u0430\u0433\u0438 IDF \u043c\u043e\u0433\u0443\u0442 \u043a\u043e\u043c\u0431\u0438\u043d\u0438\u0440\u043e\u0432\u0430\u0442\u044c\u0441\u044f; `plain` \u0438 `normalized` \u0432\u0437\u0430\u0438\u043c\u043e\u0438\u0441\u043a\u043b\u044e\u0447\u0430\u044e\u0449\u0438\u0435; `tfidf_unnormalized` \u0438 `tfidf_normalized` \u0442\u0430\u043a\u0436\u0435 \u0432\u0437\u0430\u0438\u043c\u043e\u0438\u0441\u043a\u043b\u044e\u0447\u0430\u044e\u0449\u0438\u0435; \u043d\u0435\u0443\u043a\u0430\u0437\u0430\u043d\u043d\u044b\u0435 \u0444\u043b\u0430\u0433\u0438 \u0432 \u0442\u0430\u043a\u0438\u0445 \u0432\u0437\u0430\u0438\u043c\u043e\u0438\u0441\u043a\u043b\u044e\u0447\u0430\u044e\u0449\u0438\u0445 \u0433\u0440\u0443\u043f\u043f\u0430\u0445 \u043f\u0440\u0438\u043d\u0438\u043c\u0430\u044e\u0442 \u0437\u043d\u0430\u0447\u0435\u043d\u0438\u044f \u043f\u043e \u0443\u043c\u043e\u043b\u0447\u0430\u043d\u0438\u044e. \u042d\u0442\u043e \u043e\u0437\u043d\u0430\u0447\u0430\u0435\u0442, \u0447\u0442\u043e `OPTION idf=plain` \u044d\u043a\u0432\u0438\u0432\u0430\u043b\u0435\u043d\u0442\u0435\u043d \u043f\u043e\u043b\u043d\u043e\u043c\u0443 \u0443\u043a\u0430\u0437\u0430\u043d\u0438\u044e `OPTION idf='plain,tfidf_normalized'`.\n\n### jieba_mode\n\u0417\u0430\u0434\u0430\u0435\u0442 \u0440\u0435\u0436\u0438\u043c \u0441\u0435\u0433\u043c\u0435\u043d\u0442\u0430\u0446\u0438\u0438 Jieba \u0434\u043b\u044f \u0437\u0430\u043f\u0440\u043e\u0441\u0430.\n\n\u041f\u0440\u0438 \u0438\u0441\u043f\u043e\u043b\u044c\u0437\u043e\u0432\u0430\u043d\u0438\u0438 \u043a\u0438\u0442\u0430\u0439\u0441\u043a\u043e\u0439 \u0441\u0435\u0433\u043c\u0435\u043d\u0442\u0430\u0446\u0438\u0438 Jieba \u0438\u043d\u043e\u0433\u0434\u0430 \u043f\u043e\u043b\u0435\u0437\u043d\u043e \u043f\u0440\u0438\u043c\u0435\u043d\u044f\u0442\u044c \u0440\u0430\u0437\u043d\u044b\u0435 \u0440\u0435\u0436\u0438\u043c\u044b \u0441\u0435\u0433\u043c\u0435\u043d\u0442\u0430\u0446\u0438\u0438 \u0434\u043b\u044f \u0442\u043e\u043a\u0435\u043d\u0438\u0437\u0430\u0446\u0438\u0438 \u0434\u043e\u043a\u0443\u043c\u0435\u043d\u0442\u043e\u0432 \u0438 \u0437\u0430\u043f\u0440\u043e\u0441\u0430. \u041f\u043e\u043b\u043d\u044b\u0439 \u0441\u043f\u0438\u0441\u043e\u043a \u0440\u0435\u0436\u0438\u043c\u043e\u0432 \u0441\u043c\u043e\u0442\u0440\u0438\u0442\u0435 \u0432 [jieba_mode](../Creating_a_table/NLP_and_tokenization/Morphology.md#jieba_mode).\n\n### index_weights\n\u0418\u043c\u0435\u043d\u043e\u0432\u0430\u043d\u043d\u044b\u0439 \u0441\u043f\u0438\u0441\u043e\u043a \u0446\u0435\u043b\u044b\u0445 \u0447\u0438\u0441\u0435\u043b. \u0412\u0435\u0441\u0430 \u043f\u043e\u043b\u044c\u0437\u043e\u0432\u0430\u0442\u0435\u043b\u044f \u0434\u043b\u044f \u0440\u0430\u043d\u0436\u0438\u0440\u043e\u0432\u0430\u043d\u0438\u044f \u043f\u043e \u0442\u0430\u0431\u043b\u0438\u0446\u0430\u043c.\n\n### local_df\n`0` \u0438\u043b\u0438 `1`, \u0430\u0432\u0442\u043e\u043c\u0430\u0442\u0438\u0447\u0435\u0441\u043a\u0438 \u0441\u0443\u043c\u043c\u0438\u0440\u0443\u0435\u0442 DFs \u043f\u043e \u0432\u0441\u0435\u043c \u043b\u043e\u043a\u0430\u043b\u044c\u043d\u044b\u043c \u0447\u0430\u0441\u0442\u044f\u043c \u0440\u0430\u0441\u043f\u0440\u0435\u0434\u0435\u043b\u0435\u043d\u043d\u043e\u0439 \u0442\u0430\u0431\u043b\u0438\u0446\u044b, \u043e\u0431\u0435\u0441\u043f\u0435\u0447\u0438\u0432\u0430\u044f \u0441\u043e\u0433\u043b\u0430\u0441\u043e\u0432\u0430\u043d\u043d\u044b\u0439 (\u0438 \u0442\u043e\u0447\u043d\u044b\u0439) IDF \u0434\u043b\u044f \u043b\u043e\u043a\u0430\u043b\u044c\u043d\u043e \u0448\u0430\u0440\u0434\u0438\u0440\u043e\u0432\u0430\u043d\u043d\u043e\u0439 \u0442\u0430\u0431\u043b\u0438\u0446\u044b. \u041f\u043e \u0443\u043c\u043e\u043b\u0447\u0430\u043d\u0438\u044e \u0432\u043a\u043b\u044e\u0447\u0435\u043d\u043e \u0434\u043b\u044f \u0434\u0438\u0441\u043a\u043e\u0432\u044b\u0445 \u0447\u0430\u0441\u0442\u0435\u0439 RT-\u0442\u0430\u0431\u043b\u0438\u0446\u044b. \u0422\u0435\u0440\u043c\u0438\u043d\u044b \u0437\u0430\u043f\u0440\u043e\u0441\u0430 \u0441\u043e \u0437\u0432\u0451\u0437\u0434\u043e\u0447\u043a\u0430\u043c\u0438 \u0438\u0433\u043d\u043e\u0440\u0438\u0440\u0443\u044e\u0442\u0441\u044f.\n\n### low_priority\n`0` \u0438\u043b\u0438 `1` (\u043f\u043e \u0443\u043c\u043e\u043b\u0447\u0430\u043d\u0438\u044e `0`). \u0423\u0441\u0442\u0430\u043d\u043e\u0432\u043a\u0430 `low_priority=1` \u0432\u044b\u043f\u043e\u043b\u043d\u044f\u0435\u0442 \u0437\u0430\u043f\u0440\u043e\u0441 \u0441 \u0431\u043e\u043b\u0435\u0435 \u043d\u0438\u0437\u043a\u0438\u043c \u043f\u0440\u0438\u043e\u0440\u0438\u0442\u0435\u0442\u043e\u043c, \u043f\u0435\u0440\u0435\u0441\u043c\u0430\u0442\u0440\u0438\u0432\u0430\u044f \u0437\u0430\u0434\u0430\u043d\u0438\u044f \u0434\u043b\u044f \u043d\u0435\u0433\u043e \u0432 10 \u0440\u0430\u0437 \u0440\u0435\u0436\u0435, \u0447\u0435\u043c \u0434\u043b\u044f \u0437\u0430\u043f\u0440\u043e\u0441\u043e\u0432 \u0441 \u043e\u0431\u044b\u0447\u043d\u044b\u043c \u043f\u0440\u0438\u043e\u0440\u0438\u0442\u0435\u0442\u043e\u043c.\n\n### max_matches\n\u0426\u0435\u043b\u043e\u0435 \u0447\u0438\u0441\u043b\u043e. \u041c\u0430\u043a\u0441\u0438\u043c\u0430\u043b\u044c\u043d\u043e\u0435 \u043a\u043e\u043b\u0438\u0447\u0435\u0441\u0442\u0432\u043e \u0441\u043e\u0432\u043f\u0430\u0434\u0435\u043d\u0438\u0439, \u0441\u043e\u0445\u0440\u0430\u043d\u044f\u0435\u043c\u044b\u0445 \u0434\u043b\u044f \u043a\u0430\u0436\u0434\u043e\u0433\u043e \u0437\u0430\u043f\u0440\u043e\u0441\u0430.\n\n\u041c\u0430\u043a\u0441\u0438\u043c\u0430\u043b\u044c\u043d\u043e\u0435 \u043a\u043e\u043b\u0438\u0447\u0435\u0441\u0442\u0432\u043e \u0441\u043e\u0432\u043f\u0430\u0434\u0435\u043d\u0438\u0439, \u043a\u043e\u0442\u043e\u0440\u044b\u0435 \u0441\u0435\u0440\u0432\u0435\u0440 \u0441\u043e\u0445\u0440\u0430\u043d\u044f\u0435\u0442 \u0432 \u041e\u0417\u0423 \u0434\u043b\u044f \u043a\u0430\u0436\u0434\u043e\u0439 \u0442\u0430\u0431\u043b\u0438\u0446\u044b \u0438 \u043c\u043e\u0436\u0435\u0442 \u0432\u0435\u0440\u043d\u0443\u0442\u044c \u043a\u043b\u0438\u0435\u043d\u0442\u0443. \u041f\u043e \u0443\u043c\u043e\u043b\u0447\u0430\u043d\u0438\u044e 1000.\n\n\u0412\u0432\u0435\u0434\u0435\u043d\u043e \u0434\u043b\u044f \u043a\u043e\u043d\u0442\u0440\u043e\u043b\u044f \u0438 \u043e\u0433\u0440\u0430\u043d\u0438\u0447\u0435\u043d\u0438\u044f \u0438\u0441\u043f\u043e\u043b\u044c\u0437\u043e\u0432\u0430\u043d\u0438\u044f \u041e\u0417\u0423, \u043d\u0430\u0441\u0442\u0440\u043e\u0439\u043a\u0430 `max_matches` \u043e\u043f\u0440\u0435\u0434\u0435\u043b\u044f\u0435\u0442, \u0441\u043a\u043e\u043b\u044c\u043a\u043e \u0441\u043e\u0432\u043f\u0430\u0434\u0435\u043d\u0438\u0439 \u0431\u0443\u0434\u0435\u0442 \u0445\u0440\u0430\u043d\u0438\u0442\u044c\u0441\u044f \u0432 \u041e\u0417\u0423 \u043f\u0440\u0438 \u043f\u043e\u0438\u0441\u043a\u0435 \u043f\u043e \u043a\u0430\u0436\u0434\u043e\u0439 \u0442\u0430\u0431\u043b\u0438\u0446\u0435. \u0412\u0441\u0435 \u043d\u0430\u0439\u0434\u0435\u043d\u043d\u044b\u0435 \u0441\u043e\u0432\u043f\u0430\u0434\u0435\u043d\u0438\u044f \u043e\u0431\u0440\u0430\u0431\u0430\u0442\u044b\u0432\u0430\u044e\u0442\u0441\u044f, \u043d\u043e \u0432 \u043f\u0430\u043c\u044f\u0442\u044c \u0441\u043e\u0445\u0440\u0430\u043d\u044f\u044e\u0442\u0441\u044f \u0438 \u0432 \u0438\u0442\u043e\u0433\u0435 \u043a\u043b\u0438\u0435\u043d\u0442\u0443 \u0432\u043e\u0437\u0432\u0440\u0430\u0449\u0430\u044e\u0442\u0441\u044f \u0442\u043e\u043b\u044c\u043a\u043e \u043b\u0443\u0447\u0448\u0438\u0435 N \u0438\u0437 \u043d\u0438\u0445. \u041d\u0430\u043f\u0440\u0438\u043c\u0435\u0440, \u043f\u0440\u0435\u0434\u043f\u043e\u043b\u043e\u0436\u0438\u043c, \u0447\u0442\u043e \u0442\u0430\u0431\u043b\u0438\u0446\u0430 \u0441\u043e\u0434\u0435\u0440\u0436\u0438\u0442 2 000 000 \u0441\u043e\u0432\u043f\u0430\u0434\u0435\u043d\u0438\u0439 \u0434\u043b\u044f \u0437\u0430\u043f\u0440\u043e\u0441\u0430. \u0420\u0435\u0434\u043a\u043e \u0431\u044b\u0432\u0430\u0435\u0442 \u043d\u0443\u0436\u043d\u044b\u043c \u043f\u043e\u043b\u0443\u0447\u0438\u0442\u044c \u0438\u0445 \u0432\u0441\u0435. \u0412\u043c\u0435\u0441\u0442\u043e \u044d\u0442\u043e\u0433\u043e \u043d\u0443\u0436\u043d\u043e \u043f\u0440\u043e\u0441\u043c\u043e\u0442\u0440\u0435\u0442\u044c \u0432\u0441\u0435 \u0441\u043e\u0432\u043f\u0430\u0434\u0435\u043d\u0438\u044f, \u043d\u043e \u0432\u044b\u0431\u0440\u0430\u0442\u044c \u00ab\u043b\u0443\u0447\u0448\u0438\u0435\u00bb 500, \u043d\u0430\u043f\u0440\u0438\u043c\u0435\u0440, \u043f\u043e \u043a\u0430\u043a\u043e\u043c\u0443-\u0442\u043e \u043a\u0440\u0438\u0442\u0435\u0440\u0438\u044e (\u0441\u043e\u0440\u0442\u0438\u0440\u043e\u0432\u043a\u0430 \u043f\u043e \u0440\u0435\u043b\u0435\u0432\u0430\u043d\u0442\u043d\u043e\u0441\u0442\u0438, \u0446\u0435\u043d\u0435 \u0438\u043b\u0438 \u0434\u0440\u0443\u0433\u0438\u043c \u0444\u0430\u043a\u0442\u043e\u0440\u0430\u043c), \u0438 \u043f\u043e\u043a\u0430\u0437\u0430\u0442\u044c \u0432\u043e \u0432\u0441\u043f\u043b\u044b\u0432\u0430\u044e\u0449\u0438\u0445 \u0441\u0442\u0440\u0430\u043d\u0438\u0446\u0430\u0445 \u0434\u043b\u044f \u043f\u043e\u043b\u044c\u0437\u043e\u0432\u0430\u0442\u0435\u043b\u044f \u043f\u043e 20\u2013100 \u0441\u043e\u0432\u043f\u0430\u0434\u0435\u043d\u0438\u0439. \u041e\u0442\u0441\u043b\u0435\u0436\u0438\u0432\u0430\u043d\u0438\u0435 \u0442\u043e\u043b\u044c\u043a\u043e \u043b\u0443\u0447\u0448\u0438\u0445 500 \u0441\u043e\u0432\u043f\u0430\u0434\u0435\u043d\u0438\u0439 \u0433\u043e\u0440\u0430\u0437\u0434\u043e \u044d\u0444\u0444\u0435\u043a\u0442\u0438\u0432\u043d\u0435\u0435 \u0441 \u0442\u043e\u0447\u043a\u0438 \u0437\u0440\u0435\u043d\u0438\u044f \u041e\u0417\u0423 \u0438 \u0426\u041f, \u0447\u0435\u043c \u0445\u0440\u0430\u043d\u0435\u043d\u0438\u0435 \u0432\u0441\u0435\u0445 2 000 000, \u0441\u043e\u0440\u0442\u0438\u0440\u043e\u0432\u043a\u0430 \u0438 \u0437\u0430\u0442\u0435\u043c \u043e\u0442\u0431\u0440\u0430\u0441\u044b\u0432\u0430\u043d\u0438\u0435 \u0432\u0441\u0435\u0433\u043e, \u043a\u0440\u043e\u043c\u0435 \u043f\u0435\u0440\u0432\u044b\u0445 20 \u0434\u043b\u044f \u0441\u0442\u0440\u0430\u043d\u0438\u0446\u044b \u0440\u0435\u0437\u0443\u043b\u044c\u0442\u0430\u0442\u043e\u0432 \u043f\u043e\u0438\u0441\u043a\u0430. \u041f\u0430\u0440\u0430\u043c\u0435\u0442\u0440 `max_matches` \u043a\u043e\u043d\u0442\u0440\u043e\u043b\u0438\u0440\u0443\u0435\u0442 \u043a\u043e\u043b\u0438\u0447\u0435\u0441\u0442\u0432\u043e N \u0432 \u044d\u0442\u043e\u043c \u00ab\u043b\u0443\u0447\u0448\u0438\u0435 N\u00bb.\n\n\u042d\u0442\u043e\u0442 \u043f\u0430\u0440\u0430\u043c\u0435\u0442\u0440 \u0441\u0443\u0449\u0435\u0441\u0442\u0432\u0435\u043d\u043d\u043e \u0432\u043b\u0438\u044f\u0435\u0442 \u043d\u0430 \u0438\u0441\u043f\u043e\u043b\u044c\u0437\u043e\u0432\u0430\u043d\u0438\u0435 \u041e\u0417\u0423 \u0438 \u0426\u041f \u0434\u043b\u044f \u043a\u0430\u0436\u0434\u043e\u0433\u043e \u0437\u0430\u043f\u0440\u043e\u0441\u0430. \u041e\u0431\u044b\u0447\u043d\u043e \u043f\u0440\u0438\u0435\u043c\u043b\u0435\u043c\u044b \u0437\u043d\u0430\u0447\u0435\u043d\u0438\u044f \u043e\u0442 1000 \u0434\u043e 10000, \u043d\u043e \u0431\u043e\u043b\u0435\u0435 \u0432\u044b\u0441\u043e\u043a\u0438\u0435 \u043b\u0438\u043c\u0438\u0442\u044b \u0441\u043b\u0435\u0434\u0443\u0435\u0442 \u0438\u0441\u043f\u043e\u043b\u044c\u0437\u043e\u0432\u0430\u0442\u044c \u0441 \u043e\u0441\u0442\u043e\u0440\u043e\u0436\u043d\u043e\u0441\u0442\u044c\u044e. \u041d\u0435\u0431\u0440\u0435\u0436\u043d\u043e\u0435 \u0443\u0432\u0435\u043b\u0435\u0447\u0435\u043d\u0438\u0435 max_matches \u0434\u043e 1 000 000 \u043e\u0437\u043d\u0430\u0447\u0430\u0435\u0442, \u0447\u0442\u043e `searchd` \u043f\u043e\u0442\u0440\u0435\u0431\u0443\u0435\u0442\u0441\u044f \u0432\u044b\u0434\u0435\u043b\u0438\u0442\u044c \u0438 \u0438\u043d\u0438\u0446\u0438\u0430\u043b\u0438\u0437\u0438\u0440\u043e\u0432\u0430\u0442\u044c \u0431\u0443\u0444\u0435\u0440 \u0441\u043e\u0432\u043f\u0430\u0434\u0435\u043d\u0438\u0439 \u0441 1 \u043c\u0438\u043b\u043b\u0438\u043e\u043d\u043e\u043c \u0437\u0430\u043f\u0438\u0441\u0435\u0439 \u0434\u043b\u044f \u043a\u0430\u0436\u0434\u043e\u0433\u043e \u0437\u0430\u043f\u0440\u043e\u0441\u0430. \u042d\u0442\u043e \u043d\u0435\u0438\u0437\u0431\u0435\u0436\u043d\u043e \u0443\u0432\u0435\u043b\u0438\u0447\u0438\u0442 \u0438\u0441\u043f\u043e\u043b\u044c\u0437\u043e\u0432\u0430\u043d\u0438\u0435 \u041e\u0417\u0423 \u043d\u0430 \u0437\u0430\u043f\u0440\u043e\u0441 \u0438, \u0432 \u043d\u0435\u043a\u043e\u0442\u043e\u0440\u044b\u0445 \u0441\u043b\u0443\u0447\u0430\u044f\u0445, \u043c\u043e\u0436\u0435\u0442 \u0437\u0430\u043c\u0435\u0442\u043d\u043e \u043f\u043e\u0432\u043b\u0438\u044f\u0442\u044c \u043d\u0430 \u043f\u0440\u043e\u0438\u0437\u0432\u043e\u0434\u0438\u0442\u0435\u043b\u044c\u043d\u043e\u0441\u0442\u044c.\n\n\u0414\u043e\u043f\u043e\u043b\u043d\u0438\u0442\u0435\u043b\u044c\u043d\u0443\u044e \u0438\u043d\u0444\u043e\u0440\u043c\u0430\u0446\u0438\u044e \u043e \u0432\u043b\u0438\u044f\u043d\u0438\u0438 \u043f\u0430\u0440\u0430\u043c\u0435\u0442\u0440\u0430 `max_matches` \u0441\u043c\u043e\u0442\u0440\u0438\u0442\u0435 \u0432 [max_matches_increase_threshold](../Searching/Options.md#max_matches_increase_threshold).\n\n### max_matches_increase_threshold\n\n\u0426\u0435\u043b\u043e\u0435 \u0447\u0438\u0441\u043b\u043e. \u0423\u0441\u0442\u0430\u043d\u0430\u0432\u043b\u0438\u0432\u0430\u0435\u0442 \u043f\u043e\u0440\u043e\u0433, \u0434\u043e \u043a\u043e\u0442\u043e\u0440\u043e\u0433\u043e \u043c\u043e\u0436\u043d\u043e \u0443\u0432\u0435\u043b\u0438\u0447\u0438\u0442\u044c `max_matches`. \u041f\u043e \u0443\u043c\u043e\u043b\u0447\u0430\u043d\u0438\u044e 16384.\n\nManticore \u043c\u043e\u0436\u0435\u0442 \u0443\u0432\u0435\u043b\u0438\u0447\u0438\u0442\u044c `max_matches` \u0434\u043b\u044f \u043f\u043e\u0432\u044b\u0448\u0435\u043d\u0438\u044f \u0442\u043e\u0447\u043d\u043e\u0441\u0442\u0438 \u0433\u0440\u0443\u043f\u043f\u0438\u0440\u043e\u0432\u043a\u0438 \u0438/\u0438\u043b\u0438 \u0430\u0433\u0440\u0435\u0433\u0430\u0446\u0438\u0438 \u043f\u0440\u0438 \u0432\u043a\u043b\u044e\u0447\u0435\u043d\u043d\u043e\u043c `pseudo_sharding`, \u0435\u0441\u043b\u0438 \u043e\u0431\u043d\u0430\u0440\u0443\u0436\u0435\u043d\u043e, \u0447\u0442\u043e \u043a\u043e\u043b\u0438\u0447\u0435\u0441\u0442\u0432\u043e \u0443\u043d\u0438\u043a\u0430\u043b\u044c\u043d\u044b\u0445 \u0437\u043d\u0430\u0447\u0435\u043d\u0438\u0439 \u0430\u0442\u0440\u0438\u0431\u0443\u0442\u0430 \u0433\u0440\u0443\u043f\u043f\u0438\u0440\u043e\u0432\u043a\u0438 \u043c\u0435\u043d\u044c\u0448\u0435 \u044d\u0442\u043e\u0433\u043e \u043f\u043e\u0440\u043e\u0433\u0430. \u041f\u043e\u0442\u0435\u0440\u044f \u0442\u043e\u0447\u043d\u043e\u0441\u0442\u0438 \u043c\u043e\u0436\u0435\u0442 \u043f\u0440\u043e\u0438\u0437\u043e\u0439\u0442\u0438 \u043f\u0440\u0438 \u0432\u044b\u043f\u043e\u043b\u043d\u0435\u043d\u0438\u0438 \u0437\u0430\u043f\u0440\u043e\u0441\u0430 \u0432 \u043d\u0435\u0441\u043a\u043e\u043b\u044c\u043a\u0438\u0445 \u043f\u043e\u0442\u043e\u043a\u0430\u0445 \u0447\u0435\u0440\u0435\u0437 \u043f\u0441\u0435\u0432\u0434\u043e-\u0448\u0430\u0440\u0434\u0438\u043d\u0433 \u0438\u043b\u0438 \u043f\u0440\u0438 \u043f\u0430\u0440\u0430\u043b\u043b\u0435\u043b\u044c\u043d\u043e\u043c \u043f\u043e\u0438\u0441\u043a\u0435 \u0432 \u0434\u0438\u0441\u043a\u043e\u0432\u044b\u0445 \u0447\u0430\u0441\u0442\u044f\u0445 RT-\u0442\u0430\u0431\u043b\u0438\u0446\u044b.\n\n\u0415\u0441\u043b\u0438 \u043a\u043e\u043b\u0438\u0447\u0435\u0441\u0442\u0432\u043e \u0443\u043d\u0438\u043a\u0430\u043b\u044c\u043d\u044b\u0445 \u0437\u043d\u0430\u0447\u0435\u043d\u0438\u0439 \u0430\u0442\u0440\u0438\u0431\u0443\u0442\u0430 \u0433\u0440\u0443\u043f\u043f\u0438\u0440\u043e\u0432\u043a\u0438 \u043c\u0435\u043d\u044c\u0448\u0435 \u043f\u043e\u0440\u043e\u0433\u0430, `max_matches` \u0431\u0443\u0434\u0435\u0442 \u0443\u0441\u0442\u0430\u043d\u043e\u0432\u043b\u0435\u043d\u043e \u0432 \u044d\u0442\u043e \u0437\u043d\u0430\u0447\u0435\u043d\u0438\u0435. \u0412 \u043f\u0440\u043e\u0442\u0438\u0432\u043d\u043e\u043c \u0441\u043b\u0443\u0447\u0430\u0435 \u0431\u0443\u0434\u0435\u0442 \u0438\u0441\u043f\u043e\u043b\u044c\u0437\u043e\u0432\u0430\u043d\u043e \u0437\u043d\u0430\u0447\u0435\u043d\u0438\u0435 `max_matches` \u043f\u043e \u0443\u043c\u043e\u043b\u0447\u0430\u043d\u0438\u044e.\n\n\u0415\u0441\u043b\u0438 `max_matches` \u0431\u044b\u043b \u044f\u0432\u043d\u043e \u0437\u0430\u0434\u0430\u043d \u0432 \u043e\u043f\u0446\u0438\u044f\u0445 \u0437\u0430\u043f\u0440\u043e\u0441\u0430, \u044d\u0442\u043e\u0442 \u043f\u043e\u0440\u043e\u0433 \u043d\u0435 \u0434\u0435\u0439\u0441\u0442\u0432\u0443\u0435\u0442.\n\n\u0418\u043c\u0435\u0439\u0442\u0435 \u0432 \u0432\u0438\u0434\u0443, \u0447\u0442\u043e \u0441\u043b\u0438\u0448\u043a\u043e\u043c \u0432\u044b\u0441\u043e\u043a\u043e\u0435 \u0437\u043d\u0430\u0447\u0435\u043d\u0438\u0435 \u044d\u0442\u043e\u0433\u043e \u043f\u043e\u0440\u043e\u0433\u0430 \u043f\u0440\u0438\u0432\u0435\u0434\u0435\u0442 \u043a \u0443\u0432\u0435\u043b\u0438\u0447\u0435\u043d\u0438\u044e \u043f\u043e\u0442\u0440\u0435\u0431\u043b\u0435\u043d\u0438\u044f \u043f\u0430\u043c\u044f\u0442\u0438 \u0438 \u043e\u0431\u0449\u0435\u043c\u0443 \u0441\u043d\u0438\u0436\u0435\u043d\u0438\u044e \u043f\u0440\u043e\u0438\u0437\u0432\u043e\u0434\u0438\u0442\u0435\u043b\u044c\u043d\u043e\u0441\u0442\u0438."
        },
        "is_code_or_comment": false,
        "model": "openai:gpt-4.1-mini",
        "updated_at": 1766339822
    },
    "fbf8be458cc7f31f9b48cb78b43b34c91a2e93cfd9e0a3a2441703fc617e0bf9": {
        "original": "# Search options\n\nThe SQL [SELECT](../Searching/Full_text_matching/Basic_usage.md#SQL) clause and the HTTP [/search](../Searching/Full_text_matching/Basic_usage.md#HTTP-JSON) endpoint support a number of options that can be used to fine-tune search behavior.\n\n## OPTION\n\n### General syntax\n\n<!-- example options -->\n\n**SQL**:\n\nCODE_BLOCK_0\n\n**HTTP**:\nCODE_BLOCK_1\n\n<!-- intro -->\nSQL:\n<!-- request SQL -->\nCODE_BLOCK_2\n\n<!-- response SQL -->\nCODE_BLOCK_3\n\n<!-- intro -->\nJSON:\n<!-- request JSON -->\n\nCODE_BLOCK_4\n\n<!-- response JSON -->\n\nCODE_BLOCK_5\n\n<!-- end -->\n\nSupported options are:\n\n### accurate_aggregation\nInteger. Enables or disables guaranteed aggregate accuracy when running groupby queries in multiple threads. Default is 0.\n\nWhen running a groupby query, it can be run in parallel on a plain table with several pseudo shards (if `pseudo_sharding` is on). A similar approach works on RT tables. Each shard/chunk executes the query, but the number of groups is limited by `max_matches`. If the result sets from different shards/chunks have different groups, the group counts and aggregates may be inaccurate. Note that Manticore tries to increase `max_matches` up to [`max_matches_increase_threshold`](../Searching/Options.md#max_matches_increase_threshold) based on the number of unique values of the groupby attribute (retrieved from secondary indexes). If it succeeds, there will be no loss in accuracy.\n\nHowever, if the number of unique values of the groupby attribute is high, further increasing `max_matches` may not be a good strategy because it can lead to a loss in performance and higher memory usage. Setting `accurate_aggregation` to 1 forces groupby searches to run in a single thread, which fixes the accuracy issue. Note that running in a single thread is only enforced when `max_matches` cannot be set high enough; otherwise, searches with `accurate_aggregation=1` will still run in multiple threads.\n\nOverall, setting `accurate_aggregation` to 1 ensures group count and aggregate accuracy in RT tables and plain tables with `pseudo_sharding=1`. The drawback is that searches will run slower since they will be forced to operate in a single thread.\n\nHowever, if we have an RT table and a plain table containing the same data, and we run a query with `accurate_aggregation=1`, we might still receive different results. This occurs because the daemon might choose different `max_matches` settings for the RT and plain table due to the [`max_matches_increase_threshold`](../Searching/Options.md#max_matches_increase_threshold) setting.\n\n### agent_query_timeout\nInteger. Max time in milliseconds to wait for remote queries to complete, see [this section](../Creating_a_table/Creating_a_distributed_table/Remote_tables.md#agent_query_timeout).\n\n### boolean_simplify\n`0` or `1` (`1` by default). `boolean_simplify=1` enables [simplifying the query](../Searching/Full_text_matching/Boolean_optimization.md) to speed it up.\n\nThis option can also be set globally in the [searchd configuration](../Server_settings/Searchd.md#boolean_simplify) to change the default behavior for all queries. The per-query option will override the global setting.\n\n### comment\nString, user comment that gets copied to a query log file.\n\n### cutoff\nInteger. Specifies the maximum number of matches to process. If not set, Manticore will select an appropriate value automatically.\n\n<!-- example cutoff_aggregation -->\n\n* `N = 0`: Disables the limit on the number of matches.\n* `N > 0`: Instructs Manticore to stop processing results as soon as it finds `N` matching documents.\n* Not set: Manticore decides the threshold automatically.\n\nWhen Manticore cannot determine the exact count of matching documents, the `total_relation` field in the query [meta information](../Node_info_and_management/SHOW_META.md#SHOW-META) will show `gte`, which stands for **Greater Than or Equal to**. This indicates that the actual count of matches is at least the reported `total_found` (in SQL) or `hits.total` (in JSON). When the count is exact, `total_relation` will display `eq`.\n\nNote: Using `cutoff` in aggregation queries is not recommended because it can produce inaccurate or incomplete results.\n\n<!-- request Example -->\n\nUsing `cutoff` in aggregation queries can lead to incorrect or misleading results, as shown in the following example:\nCODE_BLOCK_6\n\nCompare it with the same query without `cutoff`:\nCODE_BLOCK_7\n\n<!-- end -->\n\n### distinct_precision_threshold\nInteger. Default is `3500`. This option sets the threshold below which counts returned by `count distinct` are guaranteed to be exact within a plain table.\n\nAccepted values range from `500` to `15500`. Values outside this range will be clamped.\n\nWhen this option is set to 0, it enables an algorithm that ensures exact counts. This algorithm collects `{group, value}` pairs, sorts them, and periodically eliminates duplicates. The result is precise counts within a plain table. However, this approach is not suitable for high-cardinality datasets due to its high memory consumption and slow query execution.\n\nWhen `distinct_precision_threshold` is set to a value greater than `0`, Manticore employs a different algorithm. It loads counts into a hash table and returns the size of the table. If the hash table becomes too large, its contents are moved into a `HyperLogLog` data structure. At this point, the counts become approximate because HyperLogLog is a probabilistic algorithm. This approach maintains a fixed maximum memory usage per group, but there is a tradeoff in count accuracy.\n\nThe accuracy of the `HyperLogLog` and the threshold for converting from the hash table to HyperLogLog are derived from the `distinct_precision_threshold` setting. It's important to use this option with caution since doubling its value will also double the maximum memory required to calculate counts. The maximum memory usage can be roughly estimated using this formula: `64 * max_matches * distinct_precision_threshold`, although in practice, count calculations often use less memory than the worst-case scenario.",
        "translations": {
            "chinese": "# \u641c\u7d22\u9009\u9879\n\nSQL [SELECT](../Searching/Full_text_matching/Basic_usage.md#SQL) \u5b50\u53e5\u548c HTTP [/search](../Searching/Full_text_matching/Basic_usage.md#HTTP-JSON) \u7aef\u70b9\u652f\u6301\u8bb8\u591a\u9009\u9879\uff0c\u53ef\u7528\u4e8e\u5fae\u8c03\u641c\u7d22\u884c\u4e3a\u3002\n\n## OPTION\n\n### \u4e00\u822c\u8bed\u6cd5\n\n<!-- example options -->\n\n**SQL**:\n\nCODE_BLOCK_0\n\n**HTTP**:\nCODE_BLOCK_1\n\n<!-- intro -->\nSQL:\n<!-- request SQL -->\nCODE_BLOCK_2\n\n<!-- response SQL -->\nCODE_BLOCK_3\n\n<!-- intro -->\nJSON:\n<!-- request JSON -->\n\nCODE_BLOCK_4\n\n<!-- response JSON -->\n\nCODE_BLOCK_5\n\n<!-- end -->\n\n\u652f\u6301\u7684\u9009\u9879\u5305\u62ec\uff1a\n\n### accurate_aggregation\n\u6574\u6570\u3002\u542f\u7528\u6216\u7981\u7528\u5728\u591a\u7ebf\u7a0b\u8fd0\u884c groupby \u67e5\u8be2\u65f6\u7684\u4fdd\u8bc1\u805a\u5408\u51c6\u786e\u6027\u3002\u9ed8\u8ba4\u503c\u4e3a 0\u3002\n\n\u5f53\u8fd0\u884c groupby \u67e5\u8be2\u65f6\uff0c\u53ef\u4ee5\u5728\u666e\u901a\u8868\u4e0a\u4f7f\u7528\u591a\u4e2a\u4f2a\u5206\u7247\u5e76\u884c\u8fd0\u884c\uff08\u5982\u679c `pseudo_sharding` \u5f00\u542f\uff09\u3002\u7c7b\u4f3c\u7684\u65b9\u6cd5\u9002\u7528\u4e8e RT \u8868\u3002\u6bcf\u4e2a\u5206\u7247/\u5757\u6267\u884c\u67e5\u8be2\uff0c\u4f46\u7ec4\u7684\u6570\u91cf\u53d7 `max_matches` \u9650\u5236\u3002\u5982\u679c\u4e0d\u540c\u5206\u7247/\u5757\u7684\u7ed3\u679c\u96c6\u5305\u542b\u4e0d\u540c\u7684\u7ec4\uff0c\u7ec4\u8ba1\u6570\u548c\u805a\u5408\u53ef\u80fd\u4f1a\u4e0d\u51c6\u786e\u3002\u6ce8\u610f Manticore \u4f1a\u6839\u636e groupby \u5c5e\u6027\u7684\u552f\u4e00\u503c\u6570\u91cf\uff08\u4ece\u4e8c\u7ea7\u7d22\u5f15\u4e2d\u68c0\u7d22\uff09\u5c06 `max_matches` \u589e\u52a0\u5230 [`max_matches_increase_threshold`](../Searching/Options.md#max_matches_increase_threshold)\u3002\u5982\u679c\u6210\u529f\uff0c\u5c06\u4e0d\u4f1a\u51fa\u73b0\u51c6\u786e\u6027\u635f\u5931\u3002\n\n\u7136\u800c\uff0c\u5982\u679c groupby \u5c5e\u6027\u7684\u552f\u4e00\u503c\u6570\u91cf\u5f88\u9ad8\uff0c\u8fdb\u4e00\u6b65\u589e\u52a0 `max_matches` \u53ef\u80fd\u4e0d\u662f\u4e00\u4e2a\u597d\u7b56\u7565\uff0c\u56e0\u4e3a\u5b83\u53ef\u80fd\u5bfc\u81f4\u6027\u80fd\u4e0b\u964d\u548c\u5185\u5b58\u4f7f\u7528\u589e\u52a0\u3002\u5c06 `accurate_aggregation` \u8bbe\u7f6e\u4e3a 1 \u4f1a\u5f3a\u5236 groupby \u641c\u7d22\u5728\u5355\u7ebf\u7a0b\u4e2d\u8fd0\u884c\uff0c\u4ece\u800c\u89e3\u51b3\u51c6\u786e\u6027\u95ee\u9898\u3002\u6ce8\u610f\uff0c\u4ec5\u5f53 `max_matches` \u65e0\u6cd5\u8bbe\u7f6e\u5f97\u8db3\u591f\u9ad8\u65f6\uff0c\u624d\u4f1a\u5f3a\u5236\u5355\u7ebf\u7a0b\u8fd0\u884c\uff1b\u5426\u5219\uff0c\u5e26\u6709 `accurate_aggregation=1` \u7684\u641c\u7d22\u4ecd\u4f1a\u5728\u591a\u7ebf\u7a0b\u4e2d\u8fd0\u884c\u3002\n\n\u603b\u4f53\u800c\u8a00\uff0c\u5c06 `accurate_aggregation` \u8bbe\u7f6e\u4e3a 1 \u53ef\u786e\u4fdd RT \u8868\u548c `pseudo_sharding=1` \u7684\u666e\u901a\u8868\u4e2d\u7684\u7ec4\u8ba1\u6570\u548c\u805a\u5408\u51c6\u786e\u6027\u3002\u7f3a\u70b9\u662f\u641c\u7d22\u4f1a\u53d8\u6162\uff0c\u56e0\u4e3a\u5b83\u4eec\u5c06\u88ab\u5f3a\u5236\u5728\u5355\u7ebf\u7a0b\u4e2d\u8fd0\u884c\u3002\n\n\u7136\u800c\uff0c\u5982\u679c\u6211\u4eec\u6709\u4e00\u4e2a RT \u8868\u548c\u4e00\u4e2a\u5305\u542b\u76f8\u540c\u6570\u636e\u7684\u666e\u901a\u8868\uff0c\u5e76\u8fd0\u884c\u5e26\u6709 `accurate_aggregation=1` \u7684\u67e5\u8be2\uff0c\u6211\u4eec\u4ecd\u53ef\u80fd\u6536\u5230\u4e0d\u540c\u7684\u7ed3\u679c\u3002\u8fd9\u662f\u56e0\u4e3a\u5b88\u62a4\u8fdb\u7a0b\u53ef\u80fd\u4f1a\u6839\u636e [`max_matches_increase_threshold`](../Searching/Options.md#max_matches_increase_threshold) \u8bbe\u7f6e\u4e3a RT \u8868\u548c\u666e\u901a\u8868\u9009\u62e9\u4e0d\u540c\u7684 `max_matches` \u503c\u3002\n\n### agent_query_timeout\n\u6574\u6570\u3002\u7b49\u5f85\u8fdc\u7a0b\u67e5\u8be2\u5b8c\u6210\u7684\u6700\u5927\u65f6\u95f4\uff08\u4ee5\u6beb\u79d2\u4e3a\u5355\u4f4d\uff09\uff0c\u8bf7\u53c2\u89c1 [\u6b64\u90e8\u5206](../Creating_a_table/Creating_a_distributed_table/Remote_tables.md#agent_query_timeout)\u3002\n\n### boolean_simplify\n`0` \u6216 `1`\uff08\u9ed8\u8ba4\u4e3a `1`\uff09\u3002`boolean_simplify=1` \u542f\u7528 [\u67e5\u8be2\u7b80\u5316](../Searching/Full_text_matching/Boolean_optimization.md) \u4ee5\u52a0\u5feb\u901f\u5ea6\u3002\n\n\u6b64\u9009\u9879\u4e5f\u53ef\u4ee5\u5728 [searchd \u914d\u7f6e](../Server_settings/Searchd.md#boolean_simplify) \u4e2d\u5168\u5c40\u8bbe\u7f6e\uff0c\u4ee5\u66f4\u6539\u6240\u6709\u67e5\u8be2\u7684\u9ed8\u8ba4\u884c\u4e3a\u3002\u6bcf\u4e2a\u67e5\u8be2\u7684\u9009\u9879\u5c06\u8986\u76d6\u5168\u5c40\u8bbe\u7f6e\u3002\n\n### comment\n\u5b57\u7b26\u4e32\uff0c\u7528\u6237\u8bc4\u8bba\u4f1a\u88ab\u590d\u5236\u5230\u67e5\u8be2\u65e5\u5fd7\u6587\u4ef6\u4e2d\u3002\n\n### cutoff\n\u6574\u6570\u3002\u6307\u5b9a\u8981\u5904\u7406\u7684\u6700\u5927\u5339\u914d\u6570\u3002\u5982\u679c\u672a\u8bbe\u7f6e\uff0cManticore \u5c06\u81ea\u52a8\u9009\u62e9\u4e00\u4e2a\u9002\u5f53\u7684\u503c\u3002\n\n<!-- example cutoff_aggregation -->\n\n* `N = 0`\uff1a\u7981\u7528\u5339\u914d\u6570\u7684\u9650\u5236\u3002\n* `N > 0`\uff1a\u6307\u793a Manticore \u5728\u627e\u5230 `N` \u4e2a\u5339\u914d\u6587\u6863\u540e\u7acb\u5373\u505c\u6b62\u5904\u7406\u7ed3\u679c\u3002\n* \u672a\u8bbe\u7f6e\uff1aManticore \u81ea\u52a8\u51b3\u5b9a\u9608\u503c\u3002\n\n\u5f53 Manticore \u65e0\u6cd5\u786e\u5b9a\u5339\u914d\u6587\u6863\u7684\u786e\u5207\u6570\u91cf\u65f6\uff0c\u67e5\u8be2 [\u5143\u4fe1\u606f](../Node_info_and_management/SHOW_META.md#SHOW-META) \u4e2d\u7684 `total_relation` \u5b57\u6bb5\u5c06\u663e\u793a `gte`\uff0c\u8868\u793a **\u5927\u4e8e\u6216\u7b49\u4e8e**\u3002\u8fd9\u8868\u660e\u5b9e\u9645\u5339\u914d\u6570\u81f3\u5c11\u4e3a\u62a5\u544a\u7684 `total_found`\uff08\u5728 SQL \u4e2d\uff09\u6216 `hits.total`\uff08\u5728 JSON \u4e2d\uff09\u3002\u5f53\u8ba1\u6570\u51c6\u786e\u65f6\uff0c`total_relation` \u5c06\u663e\u793a `eq`\u3002\n\n\u6ce8\u610f\uff1a\u5728\u805a\u5408\u67e5\u8be2\u4e2d\u4f7f\u7528 `cutoff` \u4e0d\u63a8\u8350\uff0c\u56e0\u4e3a\u5b83\u53ef\u80fd\u5bfc\u81f4\u4e0d\u51c6\u786e\u6216\u4e0d\u5b8c\u6574\u7684\u7ed3\u679c\u3002\n\n<!-- request Example -->\n\n\u5728\u805a\u5408\u67e5\u8be2\u4e2d\u4f7f\u7528 `cutoff` \u53ef\u80fd\u5bfc\u81f4\u4e0d\u6b63\u786e\u6216\u8bef\u5bfc\u6027\u7684\u7ed3\u679c\uff0c\u5982\u4e0b\u4f8b\u6240\u793a\uff1a\nCODE_BLOCK_6\n\n\u4e0e\u4e0d\u4f7f\u7528 `cutoff` \u7684\u76f8\u540c\u67e5\u8be2\u8fdb\u884c\u6bd4\u8f83\uff1a\nCODE_BLOCK_7\n\n<!-- end -->\n\n### distinct_precision_threshold\n\u6574\u6570\u3002\u9ed8\u8ba4\u503c\u4e3a `3500`\u3002\u6b64\u9009\u9879\u8bbe\u7f6e\u5728\u666e\u901a\u8868\u4e2d `count distinct` \u8fd4\u56de\u7684\u8ba1\u6570\u4fdd\u8bc1\u7cbe\u786e\u7684\u9608\u503c\u3002\n\n\u63a5\u53d7\u7684\u503c\u8303\u56f4\u4e3a `500` \u5230 `15500`\u3002\u8d85\u51fa\u6b64\u8303\u56f4\u7684\u503c\u5c06\u88ab\u9650\u5236\u3002\n\n\u5f53\u6b64\u9009\u9879\u8bbe\u7f6e\u4e3a 0 \u65f6\uff0c\u5b83\u542f\u7528\u4e00\u79cd\u786e\u4fdd\u7cbe\u786e\u8ba1\u6570\u7684\u7b97\u6cd5\u3002\u8be5\u7b97\u6cd5\u6536\u96c6 `{group, value}` \u5bf9\uff0c\u5bf9\u5176\u8fdb\u884c\u6392\u5e8f\uff0c\u5e76\u5b9a\u671f\u6d88\u9664\u91cd\u590d\u9879\u3002\u7ed3\u679c\u662f\u5728\u666e\u901a\u8868\u4e2d\u7cbe\u786e\u7684\u8ba1\u6570\u3002\u7136\u800c\uff0c\u7531\u4e8e\u5176\u9ad8\u5185\u5b58\u6d88\u8017\u548c\u6162\u67e5\u8be2\u6267\u884c\uff0c\u8fd9\u79cd\u65b9\u6cd5\u4e0d\u9002\u5408\u9ad8\u57fa\u6570\u6570\u636e\u96c6\u3002\n\n\u5f53 `distinct_precision_threshold` \u8bbe\u7f6e\u4e3a\u5927\u4e8e `0` \u7684\u503c\u65f6\uff0cManticore \u91c7\u7528\u4e0d\u540c\u7684\u7b97\u6cd5\u3002\u5b83\u5c06\u8ba1\u6570\u52a0\u8f7d\u5230\u54c8\u5e0c\u8868\u4e2d\u5e76\u8fd4\u56de\u8868\u7684\u5927\u5c0f\u3002\u5982\u679c\u54c8\u5e0c\u8868\u53d8\u5f97\u592a\u5927\uff0c\u5176\u5185\u5bb9\u5c06\u88ab\u79fb\u52a8\u5230 `HyperLogLog` \u6570\u636e\u7ed3\u6784\u4e2d\u3002\u6b64\u65f6\uff0c\u8ba1\u6570\u53d8\u5f97\u8fd1\u4f3c\uff0c\u56e0\u4e3a HyperLogLog \u662f\u4e00\u79cd\u6982\u7387\u7b97\u6cd5\u3002\u8fd9\u79cd\u65b9\u6cd5\u4fdd\u6301\u6bcf\u7ec4\u7684\u6700\u5927\u5185\u5b58\u4f7f\u7528\u91cf\u56fa\u5b9a\uff0c\u4f46\u8ba1\u6570\u51c6\u786e\u6027\u5b58\u5728\u6743\u8861\u3002\n\n`HyperLogLog` \u7684\u7cbe\u5ea6\u548c\u4ece\u54c8\u5e0c\u8868\u8f6c\u6362\u5230 HyperLogLog \u7684\u9608\u503c\u6e90\u81ea `distinct_precision_threshold` \u8bbe\u7f6e\u3002\u4f7f\u7528\u6b64\u9009\u9879\u65f6\u9700\u8c28\u614e\uff0c\u56e0\u4e3a\u5c06\u5176\u503c\u52a0\u500d\u4e5f\u4f1a\u4f7f\u8ba1\u7b97\u8ba1\u6570\u6240\u9700\u7684\u6700\u5927\u5185\u5b58\u52a0\u500d\u3002\u6700\u5927\u5185\u5b58\u4f7f\u7528\u91cf\u53ef\u4ee5\u5927\u81f4\u901a\u8fc7\u6b64\u516c\u5f0f\u4f30\u7b97\uff1a`64 * max_matches * distinct_precision_threshold`\uff0c\u5c3d\u7ba1\u5728\u5b9e\u8df5\u4e2d\uff0c\u8ba1\u6570\u8ba1\u7b97\u901a\u5e38\u4f7f\u7528\u7684\u5185\u5b58\u5c11\u4e8e\u6700\u574f\u60c5\u51b5\u4e0b\u7684\u5185\u5b58\u3002",
            "russian": "# \u041f\u0430\u0440\u0430\u043c\u0435\u0442\u0440\u044b \u043f\u043e\u0438\u0441\u043a\u0430\n\nSQL-\u043f\u0440\u0435\u0434\u043b\u043e\u0436\u0435\u043d\u0438\u0435 [SELECT](../Searching/Full_text_matching/Basic_usage.md#SQL) \u0438 HTTP-\u044d\u043d\u0434\u043f\u043e\u0438\u043d\u0442 [/search](../Searching/Full_text_matching/Basic_usage.md#HTTP-JSON) \u043f\u043e\u0434\u0434\u0435\u0440\u0436\u0438\u0432\u0430\u044e\u0442 \u0440\u044f\u0434 \u043e\u043f\u0446\u0438\u0439, \u043a\u043e\u0442\u043e\u0440\u044b\u0435 \u043c\u043e\u0436\u043d\u043e \u0438\u0441\u043f\u043e\u043b\u044c\u0437\u043e\u0432\u0430\u0442\u044c \u0434\u043b\u044f \u0442\u043e\u043d\u043a\u043e\u0439 \u043d\u0430\u0441\u0442\u0440\u043e\u0439\u043a\u0438 \u043f\u043e\u0432\u0435\u0434\u0435\u043d\u0438\u044f \u043f\u043e\u0438\u0441\u043a\u0430.\n\n## OPTION\n\n### \u041e\u0431\u0449\u0438\u0439 \u0441\u0438\u043d\u0442\u0430\u043a\u0441\u0438\u0441\n\n<!-- example options -->\n\n**SQL**:\n\nCODE_BLOCK_0\n\n**HTTP**:\nCODE_BLOCK_1\n\n<!-- intro -->\nSQL:\n<!-- request SQL -->\nCODE_BLOCK_2\n\n<!-- response SQL -->\nCODE_BLOCK_3\n\n<!-- intro -->\nJSON:\n<!-- request JSON -->\n\nCODE_BLOCK_4\n\n<!-- response JSON -->\n\nCODE_BLOCK_5\n\n<!-- end -->\n\n\u041f\u043e\u0434\u0434\u0435\u0440\u0436\u0438\u0432\u0430\u0435\u043c\u044b\u0435 \u043e\u043f\u0446\u0438\u0438:\n\n### accurate_aggregation\n\u0426\u0435\u043b\u043e\u0435 \u0447\u0438\u0441\u043b\u043e. \u0412\u043a\u043b\u044e\u0447\u0430\u0435\u0442 \u0438\u043b\u0438 \u043e\u0442\u043a\u043b\u044e\u0447\u0430\u0435\u0442 \u0433\u0430\u0440\u0430\u043d\u0442\u0438\u0440\u043e\u0432\u0430\u043d\u043d\u0443\u044e \u0442\u043e\u0447\u043d\u043e\u0441\u0442\u044c \u0430\u0433\u0440\u0435\u0433\u0430\u0446\u0438\u0438 \u043f\u0440\u0438 \u0432\u044b\u043f\u043e\u043b\u043d\u0435\u043d\u0438\u0438 \u0433\u0440\u0443\u043f\u043f\u043e\u0432\u044b\u0445 \u0437\u0430\u043f\u0440\u043e\u0441\u043e\u0432 \u0432 \u043d\u0435\u0441\u043a\u043e\u043b\u044c\u043a\u0438\u0445 \u043f\u043e\u0442\u043e\u043a\u0430\u0445. \u041f\u043e \u0443\u043c\u043e\u043b\u0447\u0430\u043d\u0438\u044e 0.\n\n\u041f\u0440\u0438 \u0432\u044b\u043f\u043e\u043b\u043d\u0435\u043d\u0438\u0438 \u0433\u0440\u0443\u043f\u043f\u043e\u0432\u043e\u0433\u043e \u0437\u0430\u043f\u0440\u043e\u0441\u0430 \u043e\u043d \u043c\u043e\u0436\u0435\u0442 \u0432\u044b\u043f\u043e\u043b\u043d\u044f\u0442\u044c\u0441\u044f \u043f\u0430\u0440\u0430\u043b\u043b\u0435\u043b\u044c\u043d\u043e \u043d\u0430 \u043e\u0431\u044b\u0447\u043d\u043e\u0439 \u0442\u0430\u0431\u043b\u0438\u0446\u0435 \u0441 \u043d\u0435\u0441\u043a\u043e\u043b\u044c\u043a\u0438\u043c\u0438 \u043f\u0441\u0435\u0432\u0434\u043e\u0448\u0430\u0440\u0434\u0430\u043c\u0438 (\u0435\u0441\u043b\u0438 \u0432\u043a\u043b\u044e\u0447\u0435\u043d `pseudo_sharding`). \u0410\u043d\u0430\u043b\u043e\u0433\u0438\u0447\u043d\u044b\u0439 \u043f\u043e\u0434\u0445\u043e\u0434 \u0440\u0430\u0431\u043e\u0442\u0430\u0435\u0442 \u043d\u0430 RT-\u0442\u0430\u0431\u043b\u0438\u0446\u0430\u0445. \u041a\u0430\u0436\u0434\u044b\u0439 \u0448\u0430\u0440\u0434/\u0447\u0430\u043d\u043a \u0432\u044b\u043f\u043e\u043b\u043d\u044f\u0435\u0442 \u0437\u0430\u043f\u0440\u043e\u0441, \u043d\u043e \u043a\u043e\u043b\u0438\u0447\u0435\u0441\u0442\u0432\u043e \u0433\u0440\u0443\u043f\u043f \u043e\u0433\u0440\u0430\u043d\u0438\u0447\u0435\u043d\u043e `max_matches`. \u0415\u0441\u043b\u0438 \u0440\u0435\u0437\u0443\u043b\u044c\u0442\u0438\u0440\u0443\u044e\u0449\u0438\u0435 \u043d\u0430\u0431\u043e\u0440\u044b \u0438\u0437 \u0440\u0430\u0437\u043d\u044b\u0445 \u0448\u0430\u0440\u0434\u043e\u0432/\u0447\u0430\u043d\u043a\u043e\u0432 \u0441\u043e\u0434\u0435\u0440\u0436\u0430\u0442 \u0440\u0430\u0437\u043d\u044b\u0435 \u0433\u0440\u0443\u043f\u043f\u044b, \u043f\u043e\u0434\u0441\u0447\u0435\u0442 \u0433\u0440\u0443\u043f\u043f \u0438 \u0430\u0433\u0440\u0435\u0433\u0430\u0442\u044b \u043c\u043e\u0433\u0443\u0442 \u0431\u044b\u0442\u044c \u043d\u0435\u0442\u043e\u0447\u043d\u044b\u043c\u0438. \u041e\u0431\u0440\u0430\u0442\u0438\u0442\u0435 \u0432\u043d\u0438\u043c\u0430\u043d\u0438\u0435, \u0447\u0442\u043e Manticore \u043f\u044b\u0442\u0430\u0435\u0442\u0441\u044f \u0443\u0432\u0435\u043b\u0438\u0447\u0438\u0442\u044c `max_matches` \u0434\u043e [`max_matches_increase_threshold`](../Searching/Options.md#max_matches_increase_threshold) \u043d\u0430 \u043e\u0441\u043d\u043e\u0432\u0435 \u043a\u043e\u043b\u0438\u0447\u0435\u0441\u0442\u0432\u0430 \u0443\u043d\u0438\u043a\u0430\u043b\u044c\u043d\u044b\u0445 \u0437\u043d\u0430\u0447\u0435\u043d\u0438\u0439 \u0433\u0440\u0443\u043f\u043f\u0438\u0440\u0443\u044e\u0449\u0435\u0433\u043e \u0430\u0442\u0440\u0438\u0431\u0443\u0442\u0430 (\u043f\u043e\u043b\u0443\u0447\u0435\u043d\u043d\u044b\u0445 \u0438\u0437 \u0432\u0442\u043e\u0440\u0438\u0447\u043d\u044b\u0445 \u0438\u043d\u0434\u0435\u043a\u0441\u043e\u0432). \u0415\u0441\u043b\u0438 \u044d\u0442\u043e \u0443\u0434\u0430\u0435\u0442\u0441\u044f, \u043f\u043e\u0442\u0435\u0440\u0438 \u0442\u043e\u0447\u043d\u043e\u0441\u0442\u0438 \u043d\u0435 \u0431\u0443\u0434\u0435\u0442.\n\n\u041e\u0434\u043d\u0430\u043a\u043e, \u0435\u0441\u043b\u0438 \u043a\u043e\u043b\u0438\u0447\u0435\u0441\u0442\u0432\u043e \u0443\u043d\u0438\u043a\u0430\u043b\u044c\u043d\u044b\u0445 \u0437\u043d\u0430\u0447\u0435\u043d\u0438\u0439 \u0433\u0440\u0443\u043f\u043f\u0438\u0440\u0443\u044e\u0449\u0435\u0433\u043e \u0430\u0442\u0440\u0438\u0431\u0443\u0442\u0430 \u0432\u0435\u043b\u0438\u043a\u043e, \u0434\u0430\u043b\u044c\u043d\u0435\u0439\u0448\u0435\u0435 \u0443\u0432\u0435\u043b\u0438\u0447\u0435\u043d\u0438\u0435 `max_matches` \u043c\u043e\u0436\u0435\u0442 \u0431\u044b\u0442\u044c \u043d\u0435 \u043b\u0443\u0447\u0448\u0435\u0439 \u0441\u0442\u0440\u0430\u0442\u0435\u0433\u0438\u0435\u0439, \u0442\u0430\u043a \u043a\u0430\u043a \u044d\u0442\u043e \u043c\u043e\u0436\u0435\u0442 \u043f\u0440\u0438\u0432\u0435\u0441\u0442\u0438 \u043a \u043f\u043e\u0442\u0435\u0440\u0435 \u043f\u0440\u043e\u0438\u0437\u0432\u043e\u0434\u0438\u0442\u0435\u043b\u044c\u043d\u043e\u0441\u0442\u0438 \u0438 \u0443\u0432\u0435\u043b\u0438\u0447\u0435\u043d\u0438\u044e \u0438\u0441\u043f\u043e\u043b\u044c\u0437\u043e\u0432\u0430\u043d\u0438\u044f \u043f\u0430\u043c\u044f\u0442\u0438. \u0423\u0441\u0442\u0430\u043d\u043e\u0432\u043a\u0430 `accurate_aggregation` \u0432 1 \u0437\u0430\u0441\u0442\u0430\u0432\u043b\u044f\u0435\u0442 \u0433\u0440\u0443\u043f\u043f\u043e\u0432\u044b\u0435 \u043f\u043e\u0438\u0441\u043a\u0438 \u0432\u044b\u043f\u043e\u043b\u043d\u044f\u0442\u044c\u0441\u044f \u0432 \u043e\u0434\u043d\u043e\u043c \u043f\u043e\u0442\u043e\u043a\u0435, \u0447\u0442\u043e \u0440\u0435\u0448\u0430\u0435\u0442 \u043f\u0440\u043e\u0431\u043b\u0435\u043c\u0443 \u0442\u043e\u0447\u043d\u043e\u0441\u0442\u0438. \u041e\u0431\u0440\u0430\u0442\u0438\u0442\u0435 \u0432\u043d\u0438\u043c\u0430\u043d\u0438\u0435, \u0447\u0442\u043e \u0432\u044b\u043f\u043e\u043b\u043d\u0435\u043d\u0438\u0435 \u0432 \u043e\u0434\u043d\u043e\u043c \u043f\u043e\u0442\u043e\u043a\u0435 \u043f\u0440\u0438\u043c\u0435\u043d\u044f\u0435\u0442\u0441\u044f \u0442\u043e\u043b\u044c\u043a\u043e \u0442\u043e\u0433\u0434\u0430, \u043a\u043e\u0433\u0434\u0430 `max_matches` \u043d\u0435 \u043c\u043e\u0436\u0435\u0442 \u0431\u044b\u0442\u044c \u0443\u0441\u0442\u0430\u043d\u043e\u0432\u043b\u0435\u043d \u0434\u043e\u0441\u0442\u0430\u0442\u043e\u0447\u043d\u043e \u0432\u044b\u0441\u043e\u043a\u0438\u043c; \u0432 \u043f\u0440\u043e\u0442\u0438\u0432\u043d\u043e\u043c \u0441\u043b\u0443\u0447\u0430\u0435 \u043f\u043e\u0438\u0441\u043a\u0438 \u0441 `accurate_aggregation=1` \u0432\u0441\u0435 \u0440\u0430\u0432\u043d\u043e \u0431\u0443\u0434\u0443\u0442 \u0432\u044b\u043f\u043e\u043b\u043d\u044f\u0442\u044c\u0441\u044f \u0432 \u043d\u0435\u0441\u043a\u043e\u043b\u044c\u043a\u0438\u0445 \u043f\u043e\u0442\u043e\u043a\u0430\u0445.\n\n\u0412 \u0446\u0435\u043b\u043e\u043c, \u0443\u0441\u0442\u0430\u043d\u043e\u0432\u043a\u0430 `accurate_aggregation` \u0432 1 \u0433\u0430\u0440\u0430\u043d\u0442\u0438\u0440\u0443\u0435\u0442 \u0442\u043e\u0447\u043d\u043e\u0441\u0442\u044c \u043f\u043e\u0434\u0441\u0447\u0435\u0442\u0430 \u0433\u0440\u0443\u043f\u043f \u0438 \u0430\u0433\u0440\u0435\u0433\u0430\u0442\u043e\u0432 \u0432 RT-\u0442\u0430\u0431\u043b\u0438\u0446\u0430\u0445 \u0438 \u043e\u0431\u044b\u0447\u043d\u044b\u0445 \u0442\u0430\u0431\u043b\u0438\u0446\u0430\u0445 \u0441 `pseudo_sharding=1`. \u041d\u0435\u0434\u043e\u0441\u0442\u0430\u0442\u043e\u043a \u0432 \u0442\u043e\u043c, \u0447\u0442\u043e \u043f\u043e\u0438\u0441\u043a\u0438 \u0431\u0443\u0434\u0443\u0442 \u0432\u044b\u043f\u043e\u043b\u043d\u044f\u0442\u044c\u0441\u044f \u043c\u0435\u0434\u043b\u0435\u043d\u043d\u0435\u0435, \u0442\u0430\u043a \u043a\u0430\u043a \u043e\u043d\u0438 \u0431\u0443\u0434\u0443\u0442 \u0432\u044b\u043d\u0443\u0436\u0434\u0435\u043d\u044b \u0440\u0430\u0431\u043e\u0442\u0430\u0442\u044c \u0432 \u043e\u0434\u043d\u043e\u043c \u043f\u043e\u0442\u043e\u043a\u0435.\n\n\u041e\u0434\u043d\u0430\u043a\u043e, \u0435\u0441\u043b\u0438 \u0443 \u043d\u0430\u0441 \u0435\u0441\u0442\u044c RT-\u0442\u0430\u0431\u043b\u0438\u0446\u0430 \u0438 \u043e\u0431\u044b\u0447\u043d\u0430\u044f \u0442\u0430\u0431\u043b\u0438\u0446\u0430, \u0441\u043e\u0434\u0435\u0440\u0436\u0430\u0449\u0438\u0435 \u043e\u0434\u043d\u0438 \u0438 \u0442\u0435 \u0436\u0435 \u0434\u0430\u043d\u043d\u044b\u0435, \u0438 \u043c\u044b \u0432\u044b\u043f\u043e\u043b\u043d\u044f\u0435\u043c \u0437\u0430\u043f\u0440\u043e\u0441 \u0441 `accurate_aggregation=1`, \u043c\u044b \u0432\u0441\u0435 \u0440\u0430\u0432\u043d\u043e \u043c\u043e\u0436\u0435\u043c \u043f\u043e\u043b\u0443\u0447\u0438\u0442\u044c \u0440\u0430\u0437\u043d\u044b\u0435 \u0440\u0435\u0437\u0443\u043b\u044c\u0442\u0430\u0442\u044b. \u042d\u0442\u043e \u043f\u0440\u043e\u0438\u0441\u0445\u043e\u0434\u0438\u0442 \u043f\u043e\u0442\u043e\u043c\u0443, \u0447\u0442\u043e \u0434\u0435\u043c\u043e\u043d \u043c\u043e\u0436\u0435\u0442 \u0432\u044b\u0431\u0440\u0430\u0442\u044c \u0440\u0430\u0437\u043d\u044b\u0435 \u043d\u0430\u0441\u0442\u0440\u043e\u0439\u043a\u0438 `max_matches` \u0434\u043b\u044f RT-\u0442\u0430\u0431\u043b\u0438\u0446\u044b \u0438 \u043e\u0431\u044b\u0447\u043d\u043e\u0439 \u0442\u0430\u0431\u043b\u0438\u0446\u044b \u0438\u0437-\u0437\u0430 \u043d\u0430\u0441\u0442\u0440\u043e\u0439\u043a\u0438 [`max_matches_increase_threshold`](../Searching/Options.md#max_matches_increase_threshold).\n\n### agent_query_timeout\n\u0426\u0435\u043b\u043e\u0435 \u0447\u0438\u0441\u043b\u043e. \u041c\u0430\u043a\u0441\u0438\u043c\u0430\u043b\u044c\u043d\u043e\u0435 \u0432\u0440\u0435\u043c\u044f \u0432 \u043c\u0438\u043b\u043b\u0438\u0441\u0435\u043a\u0443\u043d\u0434\u0430\u0445 \u043e\u0436\u0438\u0434\u0430\u043d\u0438\u044f \u0437\u0430\u0432\u0435\u0440\u0448\u0435\u043d\u0438\u044f \u0443\u0434\u0430\u043b\u0435\u043d\u043d\u044b\u0445 \u0437\u0430\u043f\u0440\u043e\u0441\u043e\u0432, \u0441\u043c. [\u044d\u0442\u043e\u0442 \u0440\u0430\u0437\u0434\u0435\u043b](../Creating_a_table/Creating_a_distributed_table/Remote_tables.md#agent_query_timeout).\n\n### boolean_simplify\n`0` \u0438\u043b\u0438 `1` (\u043f\u043e \u0443\u043c\u043e\u043b\u0447\u0430\u043d\u0438\u044e `1`). `boolean_simplify=1` \u0432\u043a\u043b\u044e\u0447\u0430\u0435\u0442 [\u0443\u043f\u0440\u043e\u0449\u0435\u043d\u0438\u0435 \u0437\u0430\u043f\u0440\u043e\u0441\u0430](../Searching/Full_text_matching/Boolean_optimization.md) \u0434\u043b\u044f \u0443\u0441\u043a\u043e\u0440\u0435\u043d\u0438\u044f \u0435\u0433\u043e \u0432\u044b\u043f\u043e\u043b\u043d\u0435\u043d\u0438\u044f.\n\n\u042d\u0442\u0430 \u043e\u043f\u0446\u0438\u044f \u0442\u0430\u043a\u0436\u0435 \u043c\u043e\u0436\u0435\u0442 \u0431\u044b\u0442\u044c \u0443\u0441\u0442\u0430\u043d\u043e\u0432\u043b\u0435\u043d\u0430 \u0433\u043b\u043e\u0431\u0430\u043b\u044c\u043d\u043e \u0432 [\u043a\u043e\u043d\u0444\u0438\u0433\u0443\u0440\u0430\u0446\u0438\u0438 searchd](../Server_settings/Searchd.md#boolean_simplify) \u0434\u043b\u044f \u0438\u0437\u043c\u0435\u043d\u0435\u043d\u0438\u044f \u043f\u043e\u0432\u0435\u0434\u0435\u043d\u0438\u044f \u043f\u043e \u0443\u043c\u043e\u043b\u0447\u0430\u043d\u0438\u044e \u0434\u043b\u044f \u0432\u0441\u0435\u0445 \u0437\u0430\u043f\u0440\u043e\u0441\u043e\u0432. \u041e\u043f\u0446\u0438\u044f \u043d\u0430 \u0443\u0440\u043e\u0432\u043d\u0435 \u0437\u0430\u043f\u0440\u043e\u0441\u0430 \u043f\u0435\u0440\u0435\u043e\u043f\u0440\u0435\u0434\u0435\u043b\u0438\u0442 \u0433\u043b\u043e\u0431\u0430\u043b\u044c\u043d\u0443\u044e \u043d\u0430\u0441\u0442\u0440\u043e\u0439\u043a\u0443.\n\n### comment\n\u0421\u0442\u0440\u043e\u043a\u0430, \u043f\u043e\u043b\u044c\u0437\u043e\u0432\u0430\u0442\u0435\u043b\u044c\u0441\u043a\u0438\u0439 \u043a\u043e\u043c\u043c\u0435\u043d\u0442\u0430\u0440\u0438\u0439, \u043a\u043e\u0442\u043e\u0440\u044b\u0439 \u043a\u043e\u043f\u0438\u0440\u0443\u0435\u0442\u0441\u044f \u0432 \u0444\u0430\u0439\u043b \u0436\u0443\u0440\u043d\u0430\u043b\u0430 \u0437\u0430\u043f\u0440\u043e\u0441\u043e\u0432.\n\n### cutoff\n\u0426\u0435\u043b\u043e\u0435 \u0447\u0438\u0441\u043b\u043e. \u041e\u043f\u0440\u0435\u0434\u0435\u043b\u044f\u0435\u0442 \u043c\u0430\u043a\u0441\u0438\u043c\u0430\u043b\u044c\u043d\u043e\u0435 \u043a\u043e\u043b\u0438\u0447\u0435\u0441\u0442\u0432\u043e \u0441\u043e\u0432\u043f\u0430\u0434\u0435\u043d\u0438\u0439 \u0434\u043b\u044f \u043e\u0431\u0440\u0430\u0431\u043e\u0442\u043a\u0438. \u0415\u0441\u043b\u0438 \u043d\u0435 \u0443\u0441\u0442\u0430\u043d\u043e\u0432\u043b\u0435\u043d\u043e, Manticore \u0430\u0432\u0442\u043e\u043c\u0430\u0442\u0438\u0447\u0435\u0441\u043a\u0438 \u0432\u044b\u0431\u0435\u0440\u0435\u0442 \u043f\u043e\u0434\u0445\u043e\u0434\u044f\u0449\u0435\u0435 \u0437\u043d\u0430\u0447\u0435\u043d\u0438\u0435.\n\n<!-- example cutoff_aggregation -->\n\n* `N = 0`: \u041e\u0442\u043a\u043b\u044e\u0447\u0430\u0435\u0442 \u043e\u0433\u0440\u0430\u043d\u0438\u0447\u0435\u043d\u0438\u0435 \u043d\u0430 \u043a\u043e\u043b\u0438\u0447\u0435\u0441\u0442\u0432\u043e \u0441\u043e\u0432\u043f\u0430\u0434\u0435\u043d\u0438\u0439.\n* `N > 0`: \u0423\u043a\u0430\u0437\u044b\u0432\u0430\u0435\u0442 Manticore \u043e\u0441\u0442\u0430\u043d\u043e\u0432\u0438\u0442\u044c \u043e\u0431\u0440\u0430\u0431\u043e\u0442\u043a\u0443 \u0440\u0435\u0437\u0443\u043b\u044c\u0442\u0430\u0442\u043e\u0432, \u043a\u0430\u043a \u0442\u043e\u043b\u044c\u043a\u043e \u0431\u0443\u0434\u0435\u0442 \u043d\u0430\u0439\u0434\u0435\u043d\u043e `N` \u0441\u043e\u043e\u0442\u0432\u0435\u0442\u0441\u0442\u0432\u0443\u044e\u0449\u0438\u0445 \u0434\u043e\u043a\u0443\u043c\u0435\u043d\u0442\u043e\u0432.\n* \u041d\u0435 \u0443\u0441\u0442\u0430\u043d\u043e\u0432\u043b\u0435\u043d\u043e: Manticore \u043e\u043f\u0440\u0435\u0434\u0435\u043b\u044f\u0435\u0442 \u043f\u043e\u0440\u043e\u0433 \u0430\u0432\u0442\u043e\u043c\u0430\u0442\u0438\u0447\u0435\u0441\u043a\u0438.\n\n\u041a\u043e\u0433\u0434\u0430 Manticore \u043d\u0435 \u043c\u043e\u0436\u0435\u0442 \u043e\u043f\u0440\u0435\u0434\u0435\u043b\u0438\u0442\u044c \u0442\u043e\u0447\u043d\u043e\u0435 \u043a\u043e\u043b\u0438\u0447\u0435\u0441\u0442\u0432\u043e \u0441\u043e\u043e\u0442\u0432\u0435\u0442\u0441\u0442\u0432\u0443\u044e\u0449\u0438\u0445 \u0434\u043e\u043a\u0443\u043c\u0435\u043d\u0442\u043e\u0432, \u043f\u043e\u043b\u0435 `total_relation` \u0432 [\u043c\u0435\u0442\u0430\u0438\u043d\u0444\u043e\u0440\u043c\u0430\u0446\u0438\u0438](../Node_info_and_management/SHOW_META.md#SHOW-META) \u0437\u0430\u043f\u0440\u043e\u0441\u0430 \u0431\u0443\u0434\u0435\u0442 \u043f\u043e\u043a\u0430\u0437\u044b\u0432\u0430\u0442\u044c `gte`, \u0447\u0442\u043e \u043e\u0437\u043d\u0430\u0447\u0430\u0435\u0442 **\u0411\u043e\u043b\u044c\u0448\u0435 \u0438\u043b\u0438 \u0420\u0430\u0432\u043d\u043e**. \u042d\u0442\u043e \u0443\u043a\u0430\u0437\u044b\u0432\u0430\u0435\u0442, \u0447\u0442\u043e \u0444\u0430\u043a\u0442\u0438\u0447\u0435\u0441\u043a\u043e\u0435 \u043a\u043e\u043b\u0438\u0447\u0435\u0441\u0442\u0432\u043e \u0441\u043e\u0432\u043f\u0430\u0434\u0435\u043d\u0438\u0439 \u0441\u043e\u0441\u0442\u0430\u0432\u043b\u044f\u0435\u0442 \u043f\u043e \u043c\u0435\u043d\u044c\u0448\u0435\u0439 \u043c\u0435\u0440\u0435 \u0443\u043a\u0430\u0437\u0430\u043d\u043d\u043e\u0435 `total_found` (\u0432 SQL) \u0438\u043b\u0438 `hits.total` (\u0432 JSON). \u041a\u043e\u0433\u0434\u0430 \u043a\u043e\u043b\u0438\u0447\u0435\u0441\u0442\u0432\u043e \u0442\u043e\u0447\u043d\u043e\u0435, `total_relation` \u0431\u0443\u0434\u0435\u0442 \u043e\u0442\u043e\u0431\u0440\u0430\u0436\u0430\u0442\u044c `eq`.\n\n\u041f\u0440\u0438\u043c\u0435\u0447\u0430\u043d\u0438\u0435: \u0418\u0441\u043f\u043e\u043b\u044c\u0437\u043e\u0432\u0430\u043d\u0438\u0435 `cutoff` \u0432 \u0430\u0433\u0440\u0435\u0433\u0430\u0446\u0438\u043e\u043d\u043d\u044b\u0445 \u0437\u0430\u043f\u0440\u043e\u0441\u0430\u0445 \u043d\u0435 \u0440\u0435\u043a\u043e\u043c\u0435\u043d\u0434\u0443\u0435\u0442\u0441\u044f, \u0442\u0430\u043a \u043a\u0430\u043a \u044d\u0442\u043e \u043c\u043e\u0436\u0435\u0442 \u043f\u0440\u0438\u0432\u0435\u0441\u0442\u0438 \u043a \u043d\u0435\u0442\u043e\u0447\u043d\u044b\u043c \u0438\u043b\u0438 \u043d\u0435\u043f\u043e\u043b\u043d\u044b\u043c \u0440\u0435\u0437\u0443\u043b\u044c\u0442\u0430\u0442\u0430\u043c.\n\n<!-- request Example -->\n\n\u0418\u0441\u043f\u043e\u043b\u044c\u0437\u043e\u0432\u0430\u043d\u0438\u0435 `cutoff` \u0432 \u0430\u0433\u0440\u0435\u0433\u0430\u0446\u0438\u043e\u043d\u043d\u044b\u0445 \u0437\u0430\u043f\u0440\u043e\u0441\u0430\u0445 \u043c\u043e\u0436\u0435\u0442 \u043f\u0440\u0438\u0432\u0435\u0441\u0442\u0438 \u043a \u043d\u0435\u043a\u043e\u0440\u0440\u0435\u043a\u0442\u043d\u044b\u043c \u0438\u043b\u0438 \u0432\u0432\u043e\u0434\u044f\u0449\u0438\u043c \u0432 \u0437\u0430\u0431\u043b\u0443\u0436\u0434\u0435\u043d\u0438\u0435 \u0440\u0435\u0437\u0443\u043b\u044c\u0442\u0430\u0442\u0430\u043c, \u043a\u0430\u043a \u043f\u043e\u043a\u0430\u0437\u0430\u043d\u043e \u0432 \u0441\u043b\u0435\u0434\u0443\u044e\u0449\u0435\u043c \u043f\u0440\u0438\u043c\u0435\u0440\u0435:\nCODE_BLOCK_6\n\n\u0421\u0440\u0430\u0432\u043d\u0438\u0442\u0435 \u0441 \u0442\u0435\u043c \u0436\u0435 \u0437\u0430\u043f\u0440\u043e\u0441\u043e\u043c \u0431\u0435\u0437 `cutoff`:\nCODE_BLOCK_7\n\n<!-- end -->\n\n### distinct_precision_threshold\n\u0426\u0435\u043b\u043e\u0435 \u0447\u0438\u0441\u043b\u043e. \u041f\u043e \u0443\u043c\u043e\u043b\u0447\u0430\u043d\u0438\u044e `3500`. \u042d\u0442\u0430 \u043e\u043f\u0446\u0438\u044f \u0443\u0441\u0442\u0430\u043d\u0430\u0432\u043b\u0438\u0432\u0430\u0435\u0442 \u043f\u043e\u0440\u043e\u0433, \u043d\u0438\u0436\u0435 \u043a\u043e\u0442\u043e\u0440\u043e\u0433\u043e \u043a\u043e\u043b\u0438\u0447\u0435\u0441\u0442\u0432\u0430, \u0432\u043e\u0437\u0432\u0440\u0430\u0449\u0430\u0435\u043c\u044b\u0435 `count distinct`, \u0433\u0430\u0440\u0430\u043d\u0442\u0438\u0440\u043e\u0432\u0430\u043d\u043d\u043e \u0442\u043e\u0447\u043d\u044b \u0432 \u043f\u0440\u0435\u0434\u0435\u043b\u0430\u0445 \u043e\u0431\u044b\u0447\u043d\u043e\u0439 \u0442\u0430\u0431\u043b\u0438\u0446\u044b.\n\n\u0414\u043e\u043f\u0443\u0441\u0442\u0438\u043c\u044b\u0435 \u0437\u043d\u0430\u0447\u0435\u043d\u0438\u044f \u0432 \u0434\u0438\u0430\u043f\u0430\u0437\u043e\u043d\u0435 \u043e\u0442 `500` \u0434\u043e `15500`. \u0417\u043d\u0430\u0447\u0435\u043d\u0438\u044f \u0432\u043d\u0435 \u044d\u0442\u043e\u0433\u043e \u0434\u0438\u0430\u043f\u0430\u0437\u043e\u043d\u0430 \u0431\u0443\u0434\u0443\u0442 \u043e\u0433\u0440\u0430\u043d\u0438\u0447\u0435\u043d\u044b.\n\n\u041a\u043e\u0433\u0434\u0430 \u044d\u0442\u0430 \u043e\u043f\u0446\u0438\u044f \u0443\u0441\u0442\u0430\u043d\u043e\u0432\u043b\u0435\u043d\u0430 \u0432 0, \u0432\u043a\u043b\u044e\u0447\u0430\u0435\u0442\u0441\u044f \u0430\u043b\u0433\u043e\u0440\u0438\u0442\u043c, \u0433\u0430\u0440\u0430\u043d\u0442\u0438\u0440\u0443\u044e\u0449\u0438\u0439 \u0442\u043e\u0447\u043d\u044b\u0435 \u043f\u043e\u0434\u0441\u0447\u0435\u0442\u044b. \u042d\u0442\u043e\u0442 \u0430\u043b\u0433\u043e\u0440\u0438\u0442\u043c \u0441\u043e\u0431\u0438\u0440\u0430\u0435\u0442 \u043f\u0430\u0440\u044b `{\u0433\u0440\u0443\u043f\u043f\u0430, \u0437\u043d\u0430\u0447\u0435\u043d\u0438\u0435}`, \u0441\u043e\u0440\u0442\u0438\u0440\u0443\u0435\u0442 \u0438\u0445 \u0438 \u043f\u0435\u0440\u0438\u043e\u0434\u0438\u0447\u0435\u0441\u043a\u0438 \u0443\u0434\u0430\u043b\u044f\u0435\u0442 \u0434\u0443\u0431\u043b\u0438\u043a\u0430\u0442\u044b. \u0420\u0435\u0437\u0443\u043b\u044c\u0442\u0430\u0442 \u2014 \u0442\u043e\u0447\u043d\u044b\u0435 \u043f\u043e\u0434\u0441\u0447\u0435\u0442\u044b \u0432 \u043f\u0440\u0435\u0434\u0435\u043b\u0430\u0445 \u043e\u0431\u044b\u0447\u043d\u043e\u0439 \u0442\u0430\u0431\u043b\u0438\u0446\u044b. \u041e\u0434\u043d\u0430\u043a\u043e \u044d\u0442\u043e\u0442 \u043f\u043e\u0434\u0445\u043e\u0434 \u043d\u0435 \u043f\u043e\u0434\u0445\u043e\u0434\u0438\u0442 \u0434\u043b\u044f \u043d\u0430\u0431\u043e\u0440\u043e\u0432 \u0434\u0430\u043d\u043d\u044b\u0445 \u0441 \u0432\u044b\u0441\u043e\u043a\u043e\u0439 \u043a\u0430\u0440\u0434\u0438\u043d\u0430\u043b\u044c\u043d\u043e\u0441\u0442\u044c\u044e \u0438\u0437-\u0437\u0430 \u0432\u044b\u0441\u043e\u043a\u043e\u0433\u043e \u043f\u043e\u0442\u0440\u0435\u0431\u043b\u0435\u043d\u0438\u044f \u043f\u0430\u043c\u044f\u0442\u0438 \u0438 \u043c\u0435\u0434\u043b\u0435\u043d\u043d\u043e\u0433\u043e \u0432\u044b\u043f\u043e\u043b\u043d\u0435\u043d\u0438\u044f \u0437\u0430\u043f\u0440\u043e\u0441\u0430.\n\n\u041a\u043e\u0433\u0434\u0430 `distinct_precision_threshold` \u0443\u0441\u0442\u0430\u043d\u043e\u0432\u043b\u0435\u043d \u0432 \u0437\u043d\u0430\u0447\u0435\u043d\u0438\u0435 \u0431\u043e\u043b\u044c\u0448\u0435 `0`, Manticore \u0438\u0441\u043f\u043e\u043b\u044c\u0437\u0443\u0435\u0442 \u0434\u0440\u0443\u0433\u043e\u0439 \u0430\u043b\u0433\u043e\u0440\u0438\u0442\u043c. \u041e\u043d \u0437\u0430\u0433\u0440\u0443\u0436\u0430\u0435\u0442 \u043f\u043e\u0434\u0441\u0447\u0435\u0442\u044b \u0432 \u0445\u0435\u0448-\u0442\u0430\u0431\u043b\u0438\u0446\u0443 \u0438 \u0432\u043e\u0437\u0432\u0440\u0430\u0449\u0430\u0435\u0442 \u0440\u0430\u0437\u043c\u0435\u0440 \u0442\u0430\u0431\u043b\u0438\u0446\u044b. \u0415\u0441\u043b\u0438 \u0445\u0435\u0448-\u0442\u0430\u0431\u043b\u0438\u0446\u0430 \u0441\u0442\u0430\u043d\u043e\u0432\u0438\u0442\u0441\u044f \u0441\u043b\u0438\u0448\u043a\u043e\u043c \u0431\u043e\u043b\u044c\u0448\u043e\u0439, \u0435\u0435 \u0441\u043e\u0434\u0435\u0440\u0436\u0438\u043c\u043e\u0435 \u043f\u0435\u0440\u0435\u043c\u0435\u0449\u0430\u0435\u0442\u0441\u044f \u0432 \u0441\u0442\u0440\u0443\u043a\u0442\u0443\u0440\u0443 \u0434\u0430\u043d\u043d\u044b\u0445 `HyperLogLog`. \u041d\u0430 \u044d\u0442\u043e\u043c \u044d\u0442\u0430\u043f\u0435 \u043f\u043e\u0434\u0441\u0447\u0435\u0442\u044b \u0441\u0442\u0430\u043d\u043e\u0432\u044f\u0442\u0441\u044f \u043f\u0440\u0438\u0431\u043b\u0438\u0437\u0438\u0442\u0435\u043b\u044c\u043d\u044b\u043c\u0438, \u043f\u043e\u0441\u043a\u043e\u043b\u044c\u043a\u0443 HyperLogLog \u2014 \u044d\u0442\u043e \u0432\u0435\u0440\u043e\u044f\u0442\u043d\u043e\u0441\u0442\u043d\u044b\u0439 \u0430\u043b\u0433\u043e\u0440\u0438\u0442\u043c. \u042d\u0442\u043e\u0442 \u043f\u043e\u0434\u0445\u043e\u0434 \u043f\u043e\u0434\u0434\u0435\u0440\u0436\u0438\u0432\u0430\u0435\u0442 \u0444\u0438\u043a\u0441\u0438\u0440\u043e\u0432\u0430\u043d\u043d\u043e\u0435 \u043c\u0430\u043a\u0441\u0438\u043c\u0430\u043b\u044c\u043d\u043e\u0435 \u0438\u0441\u043f\u043e\u043b\u044c\u0437\u043e\u0432\u0430\u043d\u0438\u0435 \u043f\u0430\u043c\u044f\u0442\u0438 \u043d\u0430 \u0433\u0440\u0443\u043f\u043f\u0443, \u043d\u043e \u0435\u0441\u0442\u044c \u043a\u043e\u043c\u043f\u0440\u043e\u043c\u0438\u0441\u0441 \u0432 \u0442\u043e\u0447\u043d\u043e\u0441\u0442\u0438 \u043f\u043e\u0434\u0441\u0447\u0435\u0442\u043e\u0432.\n\n\u0422\u043e\u0447\u043d\u043e\u0441\u0442\u044c `HyperLogLog` \u0438 \u043f\u043e\u0440\u043e\u0433 \u043f\u0440\u0435\u043e\u0431\u0440\u0430\u0437\u043e\u0432\u0430\u043d\u0438\u044f \u0438\u0437 \u0445\u0435\u0448-\u0442\u0430\u0431\u043b\u0438\u0446\u044b \u0432 HyperLogLog \u043e\u043f\u0440\u0435\u0434\u0435\u043b\u044f\u044e\u0442\u0441\u044f \u043d\u0430\u0441\u0442\u0440\u043e\u0439\u043a\u043e\u0439 `distinct_precision_threshold`. \u0412\u0430\u0436\u043d\u043e \u0438\u0441\u043f\u043e\u043b\u044c\u0437\u043e\u0432\u0430\u0442\u044c \u044d\u0442\u0443 \u043e\u043f\u0446\u0438\u044e \u0441 \u043e\u0441\u0442\u043e\u0440\u043e\u0436\u043d\u043e\u0441\u0442\u044c\u044e, \u043f\u043e\u0441\u043a\u043e\u043b\u044c\u043a\u0443 \u0443\u0434\u0432\u043e\u0435\u043d\u0438\u0435 \u0435\u0435 \u0437\u043d\u0430\u0447\u0435\u043d\u0438\u044f \u0442\u0430\u043a\u0436\u0435 \u0443\u0434\u0432\u043e\u0438\u0442 \u043c\u0430\u043a\u0441\u0438\u043c\u0430\u043b\u044c\u043d\u044b\u0439 \u043e\u0431\u044a\u0435\u043c \u043f\u0430\u043c\u044f\u0442\u0438, \u043d\u0435\u043e\u0431\u0445\u043e\u0434\u0438\u043c\u044b\u0439 \u0434\u043b\u044f \u0432\u044b\u0447\u0438\u0441\u043b\u0435\u043d\u0438\u044f \u043f\u043e\u0434\u0441\u0447\u0435\u0442\u043e\u0432. \u041c\u0430\u043a\u0441\u0438\u043c\u0430\u043b\u044c\u043d\u043e\u0435 \u0438\u0441\u043f\u043e\u043b\u044c\u0437\u043e\u0432\u0430\u043d\u0438\u0435 \u043f\u0430\u043c\u044f\u0442\u0438 \u043c\u043e\u0436\u043d\u043e \u043f\u0440\u0438\u0431\u043b\u0438\u0437\u0438\u0442\u0435\u043b\u044c\u043d\u043e \u043e\u0446\u0435\u043d\u0438\u0442\u044c \u043f\u043e \u0444\u043e\u0440\u043c\u0443\u043b\u0435: `64 * max_matches * distinct_precision_threshold`, \u0445\u043e\u0442\u044f \u043d\u0430 \u043f\u0440\u0430\u043a\u0442\u0438\u043a\u0435 \u0432\u044b\u0447\u0438\u0441\u043b\u0435\u043d\u0438\u044f \u043f\u043e\u0434\u0441\u0447\u0435\u0442\u043e\u0432 \u0447\u0430\u0441\u0442\u043e \u0438\u0441\u043f\u043e\u043b\u044c\u0437\u0443\u044e\u0442 \u043c\u0435\u043d\u044c\u0448\u0435 \u043f\u0430\u043c\u044f\u0442\u0438, \u0447\u0435\u043c \u0432 \u0445\u0443\u0434\u0448\u0435\u043c \u0441\u043b\u0443\u0447\u0430\u0435."
        },
        "is_code_or_comment": false,
        "model": "qwen/qwen3-14b",
        "updated_at": 1768541870
    },
    "__meta": {
        "source_text": "# Search options\n\nThe SQL [SELECT](../Searching/Full_text_matching/Basic_usage.md#SQL) clause and the HTTP [/search](../Searching/Full_text_matching/Basic_usage.md#HTTP-JSON) endpoint support a number of options that can be used to fine-tune search behavior.\n\n## OPTION\n\n### General syntax\n\n<!-- example options -->\n\n**SQL**:\n\n```sql\nSELECT ... [OPTION <optionname>=<value> [ , ... ]] [/*+ [NO_][ColumnarScan|DocidIndex|SecondaryIndex(<attribute>[,...])]] /*]\n```\n\n**HTTP**:\n```json\nPOST /search\n{\n    \"table\" : \"table_name\",\n    \"options\":\n    {\n        \"optionname\": \"value\",\n        \"optionname2\": <value2>\n    }\n}\n```\n\n\n<!-- intro -->\nSQL:\n<!-- request SQL -->\n```sql\nSELECT * FROM test WHERE MATCH('@title hello @body world')\nOPTION ranker=bm25, max_matches=3000,\nfield_weights=(title=10, body=3), agent_query_timeout=10000\n```\n\n<!-- response SQL -->\n```sql\n+------+-------+-------+\n| id   | title | body  |\n+------+-------+-------+\n|    1 | hello | world |\n+------+-------+-------+\n1 row in set (0.00 sec)\n```\n\n<!-- intro -->\nJSON:\n<!-- request JSON -->\n\n```json\nPOST /search\n{\n    \"table\" : \"test\",\n    \"query\": {\n      \"match\": {\n        \"title\": \"hello\"\n      },\n      \"match\": {\n        \"body\": \"world\"\n      }\n    },\n    \"options\":\n    {\n        \"ranker\": \"bm25\",\n        \"max_matches\": 3000,\n        \"field_weights\": {\n            \"title\": 10,\n            \"body\": 3\n        },\n        \"agent_query_timeout\": 10000\n    }\n}\n```\n\n<!-- response JSON -->\n\n```json\n{\n  \"took\": 0,\n  \"timed_out\": false,\n  \"hits\": {\n    \"total\": 1,\n    \"total_relation\": \"eq\",\n    \"hits\": [\n      {\n        \"_id\": 1,\n        \"_score\": 10500,\n        \"_source\": {\n          \"title\": \"hello\",\n          \"body\": \"world\"\n        }\n      }\n    ]\n  }\n}\n```\n\n<!-- end -->\n\nSupported options are:\n\n### accurate_aggregation\nInteger. Enables or disables guaranteed aggregate accuracy when running groupby queries in multiple threads. Default is 0.\n\nWhen running a groupby query, it can be run in parallel on a plain table with several pseudo shards (if `pseudo_sharding` is on). A similar approach works on RT tables. Each shard/chunk executes the query, but the number of groups is limited by `max_matches`. If the result sets from different shards/chunks have different groups, the group counts and aggregates may be inaccurate. Note that Manticore tries to increase `max_matches` up to [`max_matches_increase_threshold`](../Searching/Options.md#max_matches_increase_threshold) based on the number of unique values of the groupby attribute (retrieved from secondary indexes). If it succeeds, there will be no loss in accuracy.\n\nHowever, if the number of unique values of the groupby attribute is high, further increasing `max_matches` may not be a good strategy because it can lead to a loss in performance and higher memory usage. Setting `accurate_aggregation` to 1 forces groupby searches to run in a single thread, which fixes the accuracy issue. Note that running in a single thread is only enforced when `max_matches` cannot be set high enough; otherwise, searches with `accurate_aggregation=1` will still run in multiple threads.\n\nOverall, setting `accurate_aggregation` to 1 ensures group count and aggregate accuracy in RT tables and plain tables with `pseudo_sharding=1`. The drawback is that searches will run slower since they will be forced to operate in a single thread.\n\nHowever, if we have an RT table and a plain table containing the same data, and we run a query with `accurate_aggregation=1`, we might still receive different results. This occurs because the daemon might choose different `max_matches` settings for the RT and plain table due to the [`max_matches_increase_threshold`](../Searching/Options.md#max_matches_increase_threshold) setting.\n\n### agent_query_timeout\nInteger. Max time in milliseconds to wait for remote queries to complete, see [this section](../Creating_a_table/Creating_a_distributed_table/Remote_tables.md#agent_query_timeout).\n\n### boolean_simplify\n`0` or `1` (`1` by default). `boolean_simplify=1` enables [simplifying the query](../Searching/Full_text_matching/Boolean_optimization.md) to speed it up.\n\nThis option can also be set globally in the [searchd configuration](../Server_settings/Searchd.md#boolean_simplify) to change the default behavior for all queries. The per-query option will override the global setting.\n\n### comment\nString, user comment that gets copied to a query log file.\n\n### cutoff\nInteger. Specifies the maximum number of matches to process. If not set, Manticore will select an appropriate value automatically.\n\n<!-- example cutoff_aggregation -->\n\n* `N = 0`: Disables the limit on the number of matches.\n* `N > 0`: Instructs Manticore to stop processing results as soon as it finds `N` matching documents.\n* Not set: Manticore decides the threshold automatically.\n\nWhen Manticore cannot determine the exact count of matching documents, the `total_relation` field in the query [meta information](../Node_info_and_management/SHOW_META.md#SHOW-META) will show `gte`, which stands for **Greater Than or Equal to**. This indicates that the actual count of matches is at least the reported `total_found` (in SQL) or `hits.total` (in JSON). When the count is exact, `total_relation` will display `eq`.\n\nNote: Using `cutoff` in aggregation queries is not recommended because it can produce inaccurate or incomplete results.\n\n<!-- request Example -->\n\nUsing `cutoff` in aggregation queries can lead to incorrect or misleading results, as shown in the following example:\n```\ndrop table if exists t\n--------------\n\nQuery OK, 0 rows affected (0.02 sec)\n\n--------------\ncreate table t(a int)\n--------------\n\nQuery OK, 0 rows affected (0.04 sec)\n\n--------------\ninsert into t(a) values(1),(2),(3),(1),(2),(3)\n--------------\n\nQuery OK, 6 rows affected (0.00 sec)\n\n--------------\nselect avg(a) from t option cutoff=1 facet a\n--------------\n\n+----------+\n| avg(a)   |\n+----------+\n| 1.000000 |\n+----------+\n1 row in set (0.00 sec)\n--- 1 out of 1 results in 0ms ---\n\n+------+----------+\n| a    | count(*) |\n+------+----------+\n|    1 |        1 |\n+------+----------+\n1 row in set (0.00 sec)\n--- 1 out of 1 results in 0ms ---\n```\n\nCompare it with the same query without `cutoff`:\n```\n--------------\nselect avg(a) from t facet a\n--------------\n\n+----------+\n| avg(a)   |\n+----------+\n| 2.000000 |\n+----------+\n1 row in set (0.00 sec)\n--- 1 out of 1 results in 0ms ---\n\n+------+----------+\n| a    | count(*) |\n+------+----------+\n|    1 |        2 |\n|    2 |        2 |\n|    3 |        2 |\n+------+----------+\n3 rows in set (0.00 sec)\n--- 3 out of 3 results in 0ms ---\n```\n\n<!-- end -->\n\n### distinct_precision_threshold\nInteger. Default is `3500`. This option sets the threshold below which counts returned by `count distinct` are guaranteed to be exact within a plain table.\n\nAccepted values range from `500` to `15500`. Values outside this range will be clamped.\n\nWhen this option is set to 0, it enables an algorithm that ensures exact counts. This algorithm collects `{group, value}` pairs, sorts them, and periodically eliminates duplicates. The result is precise counts within a plain table. However, this approach is not suitable for high-cardinality datasets due to its high memory consumption and slow query execution.\n\nWhen `distinct_precision_threshold` is set to a value greater than `0`, Manticore employs a different algorithm. It loads counts into a hash table and returns the size of the table. If the hash table becomes too large, its contents are moved into a `HyperLogLog` data structure. At this point, the counts become approximate because HyperLogLog is a probabilistic algorithm. This approach maintains a fixed maximum memory usage per group, but there is a tradeoff in count accuracy.\n\nThe accuracy of the `HyperLogLog` and the threshold for converting from the hash table to HyperLogLog are derived from the `distinct_precision_threshold` setting. It's important to use this option with caution since doubling its value will also double the maximum memory required to calculate counts. The maximum memory usage can be roughly estimated using this formula: `64 * max_matches * distinct_precision_threshold`, although in practice, count calculations often use less memory than the worst-case scenario.\n\n### expand_keywords\n`0` or `1` (`0` by default). Expands keywords with exact forms and/or stars when possible. Refer to [expand_keywords](../Creating_a_table/NLP_and_tokenization/Wildcard_searching_settings.md#expand_keywords) for more details.\n\n### expand_blended\n`0`, `off`, `1`, or any combination of `blend_mode` options (`0` by default). Expands blended keywords (tokens that contain characters configured via [blend_chars](../Creating_a_table/NLP_and_tokenization/Low-level_tokenization.md#blend_chars)) into their constituent variants during query parsing. When enabled, keywords like \"well-being\" (if `-` is configured in `blend_chars`) are expanded into variants such as \"well-being\", \"wellbeing\", \"well\", and \"being\", which are then grouped into OR subtrees in the query tree.\n\nThe supported values are:\n* `0` or `off` - Blended expansion is disabled (default). Blended keywords are processed normally without expansion.\n* `1` - Blended expansion is enabled and uses the table's [blend_mode](../Creating_a_table/NLP_and_tokenization/Low-level_tokenization.md#blend_mode) setting to determine which variants to generate.\n* Any blend mode option(s) - Blended expansion is enabled with the specified blend mode(s), overriding the table's `blend_mode` setting.\n\nRefer to [blend_mode](../Creating_a_table/NLP_and_tokenization/Low-level_tokenization.md#blend_mode) for more details on options.\n\n### field_weights\nNamed integer list (per-field user weights for ranking).\n\nExample:\n```sql\nSELECT ... OPTION field_weights=(title=10, body=3)\n```\n\n### global_idf\nUse global statistics (frequencies) from the [global_idf](../Creating_a_table/NLP_and_tokenization/Low-level_tokenization.md#global_idf) file for IDF computations.\n\n### idf\nQuoted, comma-separated list of IDF computation flags. Known flags are:\n\n* `normalized`: BM25 variant, idf = log((N-n+1)/n), as per Robertson et al\n* `plain`: plain variant, idf = log(N/n), as per Sparck-Jones\n* `tfidf_normalized`: additionally divide IDF by query word count, so that `TF*IDF` fits into [0, 1] range\n* `tfidf_unnormalized`: do not additionally divide IDF by query word count where N is the collection size and n is the number of matched documents\n\nThe historically default IDF (Inverse Document Frequency) in Manticore is equivalent to `OPTION idf='normalized,tfidf_normalized'`, and those normalizations may cause several undesired effects.\n\nFirst, `idf=normalized` causes keyword penalization. For instance, if you search for `the | something` and `the` occurs in more than 50% of the documents, then documents with both keywords `the` and `something` will get less weight than documents with just one keyword `something`. Using `OPTION idf=plain` avoids this. Plain IDF varies in `[0, log(N)]` range, and keywords are never penalized; while the normalized IDF varies in `[-log(N), log(N)]` range, and too frequent keywords are penalized.\n\nSecond, `idf=tfidf_normalized` leads to IDF drift across queries. Historically, IDF was also divided by the query keyword count, ensuring the entire `sum(tf*idf)` across all keywords remained within the [0,1] range. However, this meant that queries like `word1` and `word1 | nonmatchingword2` would assign different weights to the exact same result set, as the IDFs for both `word1` and `nonmatchingword2` would be divided by 2. Using `OPTION idf='tfidf_unnormalized'` resolves this issue. Keep in mind that BM25, BM25A, BM25F() ranking factors will be adjusted accordingly when you disable this normalization.\n\nIDF flags can be combined; `plain` and `normalized` are mutually exclusive; `tfidf_unnormalized` and `tfidf_normalized` are also mutually exclusive; and unspecified flags in such mutually exclusive groups default to their original settings. This means `OPTION idf=plain` is the same as specifying `OPTION idf='plain,tfidf_normalized'` in its entirety.\n\n### jieba_mode\nSpecifies the Jieba segmentation mode for the query.\n\nWhen using Jieba Chinese segmentation, it can sometimes help to use different segmentation modes for tokenizing the documents and the query. For a complete list of modes, refer to [jieba_mode](../Creating_a_table/NLP_and_tokenization/Morphology.md#jieba_mode).\n\n### index_weights\nNamed integer list. Per-table user weights for ranking.\n\n### local_df\n`0` or `1`, automatically sum DFs over all local parts of a distributed table, ensuring consistent (and accurate) IDF across a locally sharded table. Enabled by default for disk chunks of the RT table. Query terms with wildcards are ignored.\n\n### low_priority\n`0` or `1` (`0` by default). Setting `low_priority=1` executes the query with a lower priority, rescheduling its jobs 10 times less frequently than other queries with normal priority.\n\n### max_matches\nInteger. Per-query max matches value.\n\nThe maximum number of matches that the server retains in RAM for each table and can return to the client. The default is 1000.\n\nIntroduced to control and limit RAM usage, the `max_matches` setting determines how many matches will be kept in RAM while searching each table. Every match found is still processed, but only the best N of them will be retained in memory and returned to the client in the end. For example, suppose a table contains 2,000,000 matches for a query. It's rare that you would need to retrieve all of them. Instead, you need to scan all of them but only choose the \"best\" 500, for instance, based on some criteria (e.g., sorted by relevance, price, or other factors) and display those 500 matches to the end user in pages of 20 to 100 matches. Tracking only the best 500 matches is much more RAM and CPU efficient than keeping all 2,000,000 matches, sorting them, and then discarding everything but the first 20 needed for the search results page. `max_matches` controls the N in that \"best N\" amount.\n\nThis parameter significantly impacts per-query RAM and CPU usage. Values of 1,000 to 10,000 are generally acceptable, but higher limits should be used with caution. Carelessly increasing max_matches to 1,000,000 means that `searchd` will have to allocate and initialize a 1-million-entry matches buffer for every query. This will inevitably increase per-query RAM usage and, in some cases, can noticeably affect performance.\n\nRefer to [max_matches_increase_threshold](../Searching/Options.md#max_matches_increase_threshold) for additional information on how it can influence the behavior of the `max_matches` option.\n\n### max_matches_increase_threshold\n\nInteger. Sets the threshold that `max_matches` can be increased to. Default is 16384.\n\nManticore may increase `max_matches` to enhance groupby and/or aggregation accuracy when `pseudo_sharding` is enabled, and if it detects that the number of unique values of the groupby attribute is less than this threshold. Loss of accuracy may occur when pseudo-sharding executes the query in multiple threads or when an RT table conducts parallel searches in disk chunks.\n\nIf the number of unique values of the groupby attribute is less than the threshold, `max_matches` will be set to this number. Otherwise, the default `max_matches` will be used.\n\nIf `max_matches` was explicitly set in query options, this threshold has no effect.\n\nKeep in mind that if this threshold is set too high, it will result in increased memory consumption and general performance degradation.\n\nYou can also enforce a guaranteed groupby/aggregate accuracy mode using the [accurate_aggregation](../Searching/Options.md#accurate_aggregation) option.\n\n### max_query_time\nSets the maximum search query time in milliseconds. Must be a non-negative integer. The default value is 0, which means \"do not limit.\" Local search queries will be stopped once the specified time has elapsed. Note that if you're performing a search that queries multiple local tables, this limit applies to each table separately. Be aware that this may slightly increase the query's response time due to the overhead caused by constantly tracking whether it's time to stop the query.\n\n### max_predicted_time\nInteger. Maximum predicted search time; see [predicted_time_costs](../Server_settings/Searchd.md#predicted_time_costs).\n\n### morphology\n`none` allows replacing all query terms with their exact forms if the table was built with [index_exact_words](../Creating_a_table/NLP_and_tokenization/Morphology.md#index_exact_words) enabled. This is useful for preventing stemming or lemmatizing query terms.\n\n### not_terms_only_allowed\n<!-- example not_terms_only_allowed -->\n`0` or `1` allows standalone [negation](../Searching/Full_text_matching/Operators.md#Negation-operator) for the query. The default is 0. See also the corresponding [global setting](../Server_settings/Searchd.md#not_terms_only_allowed).\n\n<!-- request SQL -->\n```sql\nMySQL [(none)]> select * from tbl where match('-donald');\nERROR 1064 (42000): index t: query error: query is non-computable (single NOT operator)\nMySQL [(none)]> select * from t where match('-donald') option not_terms_only_allowed=1;\n+---------------------+-----------+\n| id                  | field     |\n+---------------------+-----------+\n| 1658178727135150081 | smth else |\n+---------------------+-----------+\n```\n<!-- end -->\n\n### ranker\nChoose from the following options:\n* `proximity_bm25`\n* `bm25`\n* `none`\n* `wordcount`\n* `proximity`\n* `matchany`\n* `fieldmask`\n* `sph04`\n* `expr`\n* `export`\n\nFor more details on each ranker, refer to [Search results ranking](../Searching/Sorting_and_ranking.md#Available-built-in-rankers).\n\n### rand_seed\nAllows you to specify a specific integer seed value for an `ORDER BY RAND()` query, for example: `... OPTION rand_seed=1234`. By default, a new and different seed value is autogenerated for every query.\n\n### retry_count\nInteger. Distributed retries count.\n\n### retry_delay\nInteger. Distributed retry delay, in milliseconds.\n\n### scroll\n\nString. A scroll token for paginating results using the [Scroll pagination approach](../Searching/Pagination.md#Scroll-Search-Option).\n\n### sort_method\n* `pq` - priority queue, set by default\n* `kbuffer` - provides faster sorting for already pre-sorted data, e.g., table data sorted by id\nThe result set is the same in both cases; choosing one option or the other may simply improve (or worsen) performance.\n\n### threads\nLimits the max number of threads used for current query processing. Default - no limit (the query can occupy all [threads](../Server_settings/Searchd.md#threads) as defined globally).\nFor a batch of queries, the option must be attached to the very first query in the batch, and it is then applied when the working queue is created and is effective for the entire batch. This option has the same meaning as the option [max_threads_per_query](../Server_settings/Searchd.md#max_threads_per_query), but is applied only to the current query or batch of queries.\n\n### token_filter\nQuoted, colon-separated string of `library name:plugin name:optional string of settings`. A query-time token filter is created for each search when full-text is invoked by every table involved, allowing you to implement a custom tokenizer that generates tokens according to custom rules.\n```sql\nSELECT * FROM index WHERE MATCH ('yes@no') OPTION token_filter='mylib.so:blend:@'\n```\n### expansion_limit\nRestricts the maximum number of expanded keywords for a single wildcard, with a default value of 0 indicating no limit. For additional details, refer to [expansion_limit](../Server_settings/Searchd.md#expansion_limit).\n\n## Query optimizer hints\n\n<!-- example options_force -->\n\nIn rare cases, Manticore's built-in query analyzer may be incorrect in understanding a query and determining whether a docid index, secondary indexes, or columnar scan should be used. To override the query optimizer's decisions, you can use the following hints in your query:\n\n* `/*+ DocidIndex(id) */`  to force the use of a docid index, `/*+ NO_DocidIndex(id) */` to tell the optimizer to ignore it\n* `/*+ SecondaryIndex(<attr_name1>[, <attr_nameN>]) */` to force the use of a secondary index (if available), `/*+ NO_SecondaryIndex(id) */`  to tell the optimizer to ignore it\n* `/*+ ColumnarScan(<attr_name1>[, <attr_nameN>]) */`  to force the use of a columnar scan (if the attribute is columnar), `/*+ NO_ColumnarScan(id) */` to tell the optimizer to ignore it\n\nNote that when executing a full-text query with filters, the query optimizer decides between intersecting the results of the full-text tree with the filter results or using a standard match-then-filter approach. Specifying *any* hint will force the daemon to use the code path that performs the intersection of the full-text tree results with the filter results.\n\nFor more information on how the query optimizer works, refer to the [Cost based optimizer](../Searching/Cost_based_optimizer.md) page.\n\n<!-- request SQL -->\n\n```sql\nSELECT * FROM students where age > 21 /*+ SecondaryIndex(age) */\n```\n\n<!-- end -->\n\n<!-- example comments -->\nWhen using a MySQL/MariaDB client, make sure to include the `--comments` flag to enable the hints in your queries.\n\n<!-- request mysql -->\n```bash\nmysql -P9306 -h0 --comments\n```\n<!-- end -->\n\n<!-- proofread -->\n\n",
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        "original": "Note that when executing a full-text query with filters, the query optimizer decides between intersecting the results of the full-text tree with the filter results or using a standard match-then-filter approach. Specifying *any* hint will force the daemon to use the code path that performs the intersection of the full-text tree results with the filter results.\n\nFor more information on how the query optimizer works, refer to the [Cost based optimizer](../Searching/Cost_based_optimizer.md) page.\n\n<!-- request SQL -->\n\nCODE_BLOCK_11\n\n<!-- end -->\n\n<!-- example comments -->\nWhen using a MySQL/MariaDB client, make sure to include the `--comments` flag to enable the hints in your queries.\n\n<!-- request mysql -->\nCODE_BLOCK_12\n<!-- end -->\n\n<!-- proofread -->\n\n",
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    "85e1671e890799af45b99434149da78fc5f4af2d77b5799298b13c1ccb03631c": {
        "original": "This parameter significantly impacts per-query RAM and CPU usage. Values of 1,000 to 10,000 are generally acceptable, but higher limits should be used with caution. Carelessly increasing max_matches to 1,000,000 means that `searchd` will have to allocate and initialize a 1-million-entry matches buffer for every query. This will inevitably increase per-query RAM usage and, in some cases, can noticeably affect performance.\n\nRefer to [max_matches_increase_threshold](../Searching/Options.md#max_matches_increase_threshold) for additional information on how it can influence the behavior of the `max_matches` option.\n\n### max_matches_increase_threshold\n\nInteger. Sets the threshold that `max_matches` can be increased to. Default is 16384.\n\nManticore may increase `max_matches` to enhance groupby and/or aggregation accuracy when `pseudo_sharding` is enabled, and if it detects that the number of unique values of the groupby attribute is less than this threshold. Loss of accuracy may occur when pseudo-sharding executes the query in multiple threads or when an RT table conducts parallel searches in disk chunks.\n\nIf the number of unique values of the groupby attribute is less than the threshold, `max_matches` will be set to this number. Otherwise, the default `max_matches` will be used.\n\nIf `max_matches` was explicitly set in query options, this threshold has no effect.\n\nKeep in mind that if this threshold is set too high, it will result in increased memory consumption and general performance degradation.\n\nYou can also enforce a guaranteed groupby/aggregate accuracy mode using the [accurate_aggregation](../Searching/Options.md#accurate_aggregation) option.\n\n### max_query_time\nSets the maximum search query time in milliseconds. Must be a non-negative integer. The default value is 0, which means \"do not limit.\" Local search queries will be stopped once the specified time has elapsed. Note that if you're performing a search that queries multiple local tables, this limit applies to each table separately. Be aware that this may slightly increase the query's response time due to the overhead caused by constantly tracking whether it's time to stop the query.\n\n### max_predicted_time\nInteger. Maximum predicted search time; see [predicted_time_costs](../Server_settings/Searchd.md#predicted_time_costs).\n\n### morphology\n`none` allows replacing all query terms with their exact forms if the table was built with [index_exact_words](../Creating_a_table/NLP_and_tokenization/Morphology.md#index_exact_words) enabled. This is useful for preventing stemming or lemmatizing query terms.\n\n### not_terms_only_allowed\n<!-- example not_terms_only_allowed -->\n`0` or `1` allows standalone [negation](../Searching/Full_text_matching/Operators.md#Negation-operator) for the query. The default is 0. See also the corresponding [global setting](../Server_settings/Searchd.md#not_terms_only_allowed).\n\n<!-- request SQL -->\nCODE_BLOCK_9\n<!-- end -->\n\n### ranker\nChoose from the following options:\n* `proximity_bm25`\n* `bm25`\n* `none`\n* `wordcount`\n* `proximity`\n* `matchany`\n* `fieldmask`\n* `sph04`\n* `expr`\n* `export`\n\nFor more details on each ranker, refer to [Search results ranking](../Searching/Sorting_and_ranking.md#Available-built-in-rankers).\n\n### rand_seed\nAllows you to specify a specific integer seed value for an `ORDER BY RAND()` query, for example: `... OPTION rand_seed=1234`. By default, a new and different seed value is autogenerated for every query.\n\n### retry_count\nInteger. Distributed retries count.\n\n### retry_delay\nInteger. Distributed retry delay, in milliseconds.\n\n### scroll\n\nString. A scroll token for paginating results using the [Scroll pagination approach](../Searching/Pagination.md#Scroll-Search-Option).\n\n### sort_method\n* `pq` - priority queue, set by default\n* `kbuffer` - provides faster sorting for already pre-sorted data, e.g., table data sorted by id\nThe result set is the same in both cases; choosing one option or the other may simply improve (or worsen) performance.\n\n### threads\nLimits the max number of threads used for current query processing. Default - no limit (the query can occupy all [threads](../Server_settings/Searchd.md#threads) as defined globally).\nFor a batch of queries, the option must be attached to the very first query in the batch, and it is then applied when the working queue is created and is effective for the entire batch. This option has the same meaning as the option [max_threads_per_query](../Server_settings/Searchd.md#max_threads_per_query), but is applied only to the current query or batch of queries.\n\n### token_filter\nQuoted, colon-separated string of `library name:plugin name:optional string of settings`. A query-time token filter is created for each search when full-text is invoked by every table involved, allowing you to implement a custom tokenizer that generates tokens according to custom rules.\nCODE_BLOCK_10\n### expansion_limit\nRestricts the maximum number of expanded keywords for a single wildcard, with a default value of 0 indicating no limit. For additional details, refer to [expansion_limit](../Server_settings/Searchd.md#expansion_limit).\n\n## Query optimizer hints\n\n<!-- example options_force -->\n\nIn rare cases, Manticore's built-in query analyzer may be incorrect in understanding a query and determining whether a docid index, secondary indexes, or columnar scan should be used. To override the query optimizer's decisions, you can use the following hints in your query:\n\n* `/*+ DocidIndex(id) */`  to force the use of a docid index, `/*+ NO_DocidIndex(id) */` to tell the optimizer to ignore it\n* `/*+ SecondaryIndex(<attr_name1>[, <attr_nameN>]) */` to force the use of a secondary index (if available), `/*+ NO_SecondaryIndex(id) */`  to tell the optimizer to ignore it\n* `/*+ ColumnarScan(<attr_name1>[, <attr_nameN>]) */`  to force the use of a columnar scan (if the attribute is columnar), `/*+ NO_ColumnarScan(id) */` to tell the optimizer to ignore it",
        "translations": {
            "chinese": "\u6b64\u53c2\u6570\u4f1a\u663e\u8457\u5f71\u54cd\u6bcf\u4e2a\u67e5\u8be2\u7684RAM\u548cCPU\u4f7f\u7528\u91cf\u3002\u503c\u57281,000\u523010,000\u4e4b\u95f4\u901a\u5e38\u662f\u53ef\u4ee5\u63a5\u53d7\u7684\uff0c\u4f46\u63d0\u9ad8\u9650\u5236\u65f6\u5e94\u8c28\u614e\u4f7f\u7528\u3002\u968f\u610f\u5c06max_matches\u589e\u52a0\u52301,000,000\u610f\u5473\u7740`searchd`\u5fc5\u987b\u4e3a\u6bcf\u4e2a\u67e5\u8be2\u5206\u914d\u5e76\u521d\u59cb\u5316\u4e00\u4e2a\u5305\u542b100\u4e07\u6761\u5339\u914d\u9879\u7684\u7f13\u51b2\u533a\u3002\u8fd9\u4e0d\u53ef\u907f\u514d\u5730\u4f1a\u589e\u52a0\u6bcf\u4e2a\u67e5\u8be2\u7684RAM\u4f7f\u7528\u91cf\uff0c\u5e76\u4e14\u5728\u67d0\u4e9b\u60c5\u51b5\u4e0b\u53ef\u80fd\u660e\u663e\u5f71\u54cd\u6027\u80fd\u3002\n\n\u6709\u5173\u5b83\u5982\u4f55\u5f71\u54cd`max_matches`\u9009\u9879\u884c\u4e3a\u7684\u66f4\u591a\u4fe1\u606f\uff0c\u8bf7\u53c2\u9605[max_matches_increase_threshold](../Searching/Options.md#max_matches_increase_threshold)\u3002\n\n### max_matches_increase_threshold\n\n\u6574\u6570\u3002\u8bbe\u7f6e`max_matches`\u53ef\u4ee5\u589e\u52a0\u7684\u9608\u503c\u3002\u9ed8\u8ba4\u503c\u4e3a16384\u3002\n\n\u5f53\u542f\u7528`pseudo_sharding`\u4e14\u68c0\u6d4b\u5230\u5206\u7ec4\u5c5e\u6027\u7684\u552f\u4e00\u503c\u6570\u91cf\u5c0f\u4e8e\u6b64\u9608\u503c\u65f6\uff0cManticore\u53ef\u80fd\u4f1a\u589e\u52a0`max_matches`\u4ee5\u63d0\u9ad8\u5206\u7ec4\u548c/\u6216\u805a\u5408\u7684\u51c6\u786e\u6027\u3002\u5f53\u4f2a\u5206\u7247\u5728\u591a\u4e2a\u7ebf\u7a0b\u4e2d\u6267\u884c\u67e5\u8be2\u6216RT\u8868\u5728\u78c1\u76d8\u5757\u4e2d\u8fdb\u884c\u5e76\u884c\u641c\u7d22\u65f6\uff0c\u53ef\u80fd\u4f1a\u53d1\u751f\u51c6\u786e\u6027\u4e0b\u964d\u3002\n\n\u5982\u679c\u5206\u7ec4\u5c5e\u6027\u7684\u552f\u4e00\u503c\u6570\u91cf\u5c0f\u4e8e\u9608\u503c\uff0c`max_matches`\u5c06\u8bbe\u7f6e\u4e3a\u8be5\u6570\u91cf\u3002\u5426\u5219\uff0c\u5c06\u4f7f\u7528\u9ed8\u8ba4\u7684`max_matches`\u3002\n\n\u5982\u679c\u5728\u67e5\u8be2\u9009\u9879\u4e2d\u663e\u5f0f\u8bbe\u7f6e\u4e86`max_matches`\uff0c\u5219\u6b64\u9608\u503c\u65e0\u6548\u3002\n\n\u8bf7\u6ce8\u610f\uff0c\u5982\u679c\u6b64\u9608\u503c\u8bbe\u7f6e\u5f97\u8fc7\u9ad8\uff0c\u4f1a\u5bfc\u81f4\u5185\u5b58\u6d88\u8017\u589e\u52a0\u548c\u6574\u4f53\u6027\u80fd\u4e0b\u964d\u3002\n\n\u60a8\u8fd8\u53ef\u4ee5\u4f7f\u7528[accurate_aggregation](../Searching/Options.md#accurate_aggregation)\u9009\u9879\u5f3a\u5236\u542f\u7528\u4fdd\u8bc1\u7684\u5206\u7ec4/\u805a\u5408\u51c6\u786e\u6027\u6a21\u5f0f\u3002\n\n### max_query_time\n\u8bbe\u7f6e\u6700\u5927\u641c\u7d22\u67e5\u8be2\u65f6\u95f4\uff08\u4ee5\u6beb\u79d2\u4e3a\u5355\u4f4d\uff09\u3002\u5fc5\u987b\u662f\u975e\u8d1f\u6574\u6570\u3002\u9ed8\u8ba4\u503c\u4e3a0\uff0c\u8868\u793a\u201c\u4e0d\u9650\u5236\u201d\u3002\u672c\u5730\u641c\u7d22\u67e5\u8be2\u4e00\u65e6\u8fbe\u5230\u6307\u5b9a\u65f6\u95f4\u5c31\u4f1a\u505c\u6b62\u3002\u8bf7\u6ce8\u610f\uff0c\u5982\u679c\u60a8\u6267\u884c\u7684\u641c\u7d22\u67e5\u8be2\u4e86\u591a\u4e2a\u672c\u5730\u8868\uff0c\u6b64\u9650\u5236\u9002\u7528\u4e8e\u6bcf\u4e2a\u8868\u3002\u8bf7\u6ce8\u610f\uff0c\u7531\u4e8e\u4e0d\u65ad\u8ddf\u8e2a\u662f\u5426\u9700\u8981\u505c\u6b62\u67e5\u8be2\u6240\u4ea7\u751f\u7684\u5f00\u9500\uff0c\u8fd9\u53ef\u80fd\u4f1a\u7565\u5fae\u589e\u52a0\u67e5\u8be2\u7684\u54cd\u5e94\u65f6\u95f4\u3002\n\n### max_predicted_time\n\u6574\u6570\u3002\u6700\u5927\u9884\u6d4b\u641c\u7d22\u65f6\u95f4\uff1b\u8bf7\u53c2\u9605[predicted_time_costs](../Server_settings/Searchd.md#predicted_time_costs)\u3002\n\n### morphology\n`none`\u5141\u8bb8\u5728\u8868\u4f7f\u7528[index_exact_words](../Creating_a_table/NLP_and_tokenization/Morphology.md#index_exact_words)\u542f\u7528\u65f6\uff0c\u5c06\u6240\u6709\u67e5\u8be2\u672f\u8bed\u66ff\u6362\u4e3a\u5b83\u4eec\u7684\u786e\u5207\u5f62\u5f0f\u3002\u8fd9\u5bf9\u4e8e\u9632\u6b62\u5bf9\u67e5\u8be2\u672f\u8bed\u8fdb\u884c\u8bcd\u5e72\u63d0\u53d6\u6216\u8bcd\u5f62\u8fd8\u539f\u5f88\u6709\u7528\u3002\n\n### not_terms_only_allowed\n<!-- example not_terms_only_allowed -->\n`0`\u6216`1`\u5141\u8bb8\u67e5\u8be2\u4e2d\u4f7f\u7528\u72ec\u7acb\u7684[\u5426\u5b9a](../Searching/Full_text_matching/Operators.md#Negation-operator)\u3002\u9ed8\u8ba4\u503c\u4e3a0\u3002\u53e6\u8bf7\u53c2\u9605\u76f8\u5e94\u7684[\u5168\u5c40\u8bbe\u7f6e](../Server_settings/Searchd.md#not_terms_only_allowed)\u3002\n\n<!-- request SQL -->\nCODE_BLOCK_9\n<!-- end -->\n\n### ranker\n\u4ece\u4ee5\u4e0b\u9009\u9879\u4e2d\u9009\u62e9\uff1a\n* `proximity_bm25`\n* `bm25`\n* `none`\n* `wordcount`\n* `proximity`\n* `matchany`\n* `fieldmask`\n* `sph04`\n* `expr`\n* `export`\n\n\u6709\u5173\u6bcf\u4e2a\u6392\u5e8f\u5668\u7684\u66f4\u591a\u8be6\u7ec6\u4fe1\u606f\uff0c\u8bf7\u53c2\u9605[\u641c\u7d22\u7ed3\u679c\u6392\u5e8f](../Searching/Sorting_and_ranking.md#Available-built-in-rankers)\u3002\n\n### rand_seed\n\u5141\u8bb8\u60a8\u4e3a`ORDER BY RAND()`\u67e5\u8be2\u6307\u5b9a\u7279\u5b9a\u7684\u6574\u6570\u79cd\u5b50\u503c\uff0c\u4f8b\u5982\uff1a`... OPTION rand_seed=1234`\u3002\u9ed8\u8ba4\u60c5\u51b5\u4e0b\uff0c\u6bcf\u4e2a\u67e5\u8be2\u90fd\u4f1a\u81ea\u52a8\u751f\u6210\u4e00\u4e2a\u65b0\u7684\u4e14\u4e0d\u540c\u7684\u79cd\u5b50\u503c\u3002\n\n### retry_count\n\u6574\u6570\u3002\u5206\u5e03\u5f0f\u91cd\u8bd5\u6b21\u6570\u3002\n\n### retry_delay\n\u6574\u6570\u3002\u5206\u5e03\u5f0f\u91cd\u8bd5\u5ef6\u8fdf\uff08\u4ee5\u6beb\u79d2\u4e3a\u5355\u4f4d\uff09\u3002\n\n### scroll\n\n\u5b57\u7b26\u4e32\u3002\u7528\u4e8e\u4f7f\u7528[Scroll\u5206\u9875\u65b9\u6cd5](../Searching/Pagination.md#Scroll-Search-Option)\u5206\u9875\u7ed3\u679c\u7684\u6eda\u52a8\u4ee4\u724c\u3002\n\n### sort_method\n* `pq` - \u4f18\u5148\u961f\u5217\uff0c\u9ed8\u8ba4\u8bbe\u7f6e\n* `kbuffer` - \u4e3a\u5df2\u9884\u5148\u6392\u5e8f\u7684\u6570\u636e\uff08\u4f8b\u5982\u6309id\u6392\u5e8f\u7684\u8868\u6570\u636e\uff09\u63d0\u4f9b\u66f4\u5feb\u7684\u6392\u5e8f\n\u4e24\u79cd\u60c5\u51b5\u4e0b\u7ed3\u679c\u96c6\u76f8\u540c\uff1b\u9009\u62e9\u5176\u4e2d\u4e00\u4e2a\u9009\u9879\u53ef\u80fd\u4f1a\u7b80\u5355\u5730\u63d0\u9ad8\uff08\u6216\u964d\u4f4e\uff09\u6027\u80fd\u3002\n\n### threads\n\u9650\u5236\u5f53\u524d\u67e5\u8be2\u5904\u7406\u4f7f\u7528\u7684\u6700\u5927\u7ebf\u7a0b\u6570\u3002\u9ed8\u8ba4\u503c - \u65e0\u9650\u5236\uff08\u67e5\u8be2\u53ef\u4ee5\u5360\u7528\u5168\u5c40\u5b9a\u4e49\u7684[threads](../Server_settings/Searchd.md#threads)\u4e2d\u7684\u6240\u6709\u7ebf\u7a0b\uff09\u3002\n\u5bf9\u4e8e\u67e5\u8be2\u6279\u6b21\uff0c\u8be5\u9009\u9879\u5fc5\u987b\u9644\u52a0\u5230\u6279\u6b21\u4e2d\u7684\u7b2c\u4e00\u4e2a\u67e5\u8be2\uff0c\u5e76\u5728\u521b\u5efa\u5de5\u4f5c\u961f\u5217\u65f6\u5e94\u7528\uff0c\u5bf9\u6574\u4e2a\u6279\u6b21\u6709\u6548\u3002\u6b64\u9009\u9879\u4e0e\u9009\u9879[max_threads_per_query](../Server_settings/Searchd.md#max_threads_per_query)\u542b\u4e49\u76f8\u540c\uff0c\u4f46\u4ec5\u9002\u7528\u4e8e\u5f53\u524d\u67e5\u8be2\u6216\u67e5\u8be2\u6279\u6b21\u3002\n\n### token_filter\n\u7528\u5f15\u53f7\u62ec\u8d77\u7684\u3001\u4ee5\u5192\u53f7\u5206\u9694\u7684`library name:plugin name:optional string of settings`\u5b57\u7b26\u4e32\u3002\u5f53\u6bcf\u4e2a\u8868\u8c03\u7528\u5168\u6587\u641c\u7d22\u65f6\uff0c\u4e3a\u6bcf\u4e2a\u641c\u7d22\u521b\u5efa\u4e00\u4e2a\u67e5\u8be2\u65f6\u7684\u6807\u8bb0\u8fc7\u6ee4\u5668\uff0c\u5141\u8bb8\u60a8\u5b9e\u73b0\u81ea\u5b9a\u4e49\u5206\u8bcd\u5668\uff0c\u6839\u636e\u81ea\u5b9a\u4e49\u89c4\u5219\u751f\u6210\u6807\u8bb0\u3002\nCODE_BLOCK_10\n### expansion_limit\n\u9650\u5236\u5355\u4e2a\u901a\u914d\u7b26\u6269\u5c55\u7684\u5173\u952e\u5b57\u6700\u5927\u6570\u91cf\uff0c\u9ed8\u8ba4\u503c\u4e3a0\u8868\u793a\u65e0\u9650\u5236\u3002\u6709\u5173\u66f4\u591a\u8be6\u7ec6\u4fe1\u606f\uff0c\u8bf7\u53c2\u9605[expansion_limit](../Server_settings/Searchd.md#expansion_limit)\u3002\n\n## \u67e5\u8be2\u4f18\u5316\u5668\u63d0\u793a\n\n<!-- example options_force -->\n\n\u5728\u6781\u5c11\u6570\u60c5\u51b5\u4e0b\uff0cManticore\u5185\u7f6e\u7684\u67e5\u8be2\u5206\u6790\u5668\u53ef\u80fd\u65e0\u6cd5\u6b63\u786e\u7406\u89e3\u67e5\u8be2\u5e76\u786e\u5b9a\u662f\u5426\u5e94\u4f7f\u7528docid\u7d22\u5f15\u3001\u4e8c\u7ea7\u7d22\u5f15\u6216\u5217\u626b\u63cf\u3002\u8981\u8986\u76d6\u67e5\u8be2\u4f18\u5316\u5668\u7684\u51b3\u7b56\uff0c\u60a8\u53ef\u4ee5\u5728\u67e5\u8be2\u4e2d\u4f7f\u7528\u4ee5\u4e0b\u63d0\u793a\uff1a\n\n* `/*+ DocidIndex(id) */` \u5f3a\u5236\u4f7f\u7528docid\u7d22\u5f15\uff0c`/*+ NO_DocidIndex(id) */` \u544a\u8bc9\u4f18\u5316\u5668\u5ffd\u7565\u5b83\n* `/*+ SecondaryIndex(<attr_name1>[, <attr_nameN>]) */` \u5f3a\u5236\u4f7f\u7528\u4e8c\u7ea7\u7d22\u5f15\uff08\u5982\u679c\u53ef\u7528\uff09\uff0c`/*+ NO_SecondaryIndex(id) */` \u544a\u8bc9\u4f18\u5316\u5668\u5ffd\u7565\u5b83\n* `/*+ ColumnarScan(<attr_name1>[, <attr_nameN>]) */` \u5f3a\u5236\u4f7f\u7528\u5217\u626b\u63cf\uff08\u5982\u679c\u5c5e\u6027\u662f\u5217\u5f0f\u7684\uff09\uff0c`/*+ NO_ColumnarScan(id) */` \u544a\u8bc9\u4f18\u5316\u5668\u5ffd\u7565\u5b83",
            "russian": "\u042d\u0442\u043e\u0442 \u043f\u0430\u0440\u0430\u043c\u0435\u0442\u0440 \u0437\u043d\u0430\u0447\u0438\u0442\u0435\u043b\u044c\u043d\u043e \u0432\u043b\u0438\u044f\u0435\u0442 \u043d\u0430 \u0438\u0441\u043f\u043e\u043b\u044c\u0437\u043e\u0432\u0430\u043d\u0438\u0435 \u043e\u043f\u0435\u0440\u0430\u0442\u0438\u0432\u043d\u043e\u0439 \u043f\u0430\u043c\u044f\u0442\u0438 \u0438 \u043f\u0440\u043e\u0446\u0435\u0441\u0441\u043e\u0440\u0430 \u0434\u043b\u044f \u043a\u0430\u0436\u0434\u043e\u0433\u043e \u0437\u0430\u043f\u0440\u043e\u0441\u0430. \u0417\u043d\u0430\u0447\u0435\u043d\u0438\u044f \u043e\u0442 1 000 \u0434\u043e 10 000 \u043e\u0431\u044b\u0447\u043d\u043e \u043f\u0440\u0438\u0435\u043c\u043b\u0435\u043c\u044b, \u043d\u043e \u0431\u043e\u043b\u0435\u0435 \u0432\u044b\u0441\u043e\u043a\u0438\u0435 \u043b\u0438\u043c\u0438\u0442\u044b \u0441\u043b\u0435\u0434\u0443\u0435\u0442 \u0438\u0441\u043f\u043e\u043b\u044c\u0437\u043e\u0432\u0430\u0442\u044c \u0441 \u043e\u0441\u0442\u043e\u0440\u043e\u0436\u043d\u043e\u0441\u0442\u044c\u044e. \u0411\u0435\u0437\u0434\u0443\u043c\u043d\u043e\u0435 \u0443\u0432\u0435\u043b\u0438\u0447\u0435\u043d\u0438\u0435 max_matches \u0434\u043e 1 000 000 \u043e\u0437\u043d\u0430\u0447\u0430\u0435\u0442, \u0447\u0442\u043e `searchd` \u0434\u043e\u043b\u0436\u0435\u043d \u0431\u0443\u0434\u0435\u0442 \u0432\u044b\u0434\u0435\u043b\u044f\u0442\u044c \u0438 \u0438\u043d\u0438\u0446\u0438\u0430\u043b\u0438\u0437\u0438\u0440\u043e\u0432\u0430\u0442\u044c \u0431\u0443\u0444\u0435\u0440 \u0441\u043e\u0432\u043f\u0430\u0434\u0435\u043d\u0438\u0439 \u043d\u0430 1 \u043c\u0438\u043b\u043b\u0438\u043e\u043d \u0437\u0430\u043f\u0438\u0441\u0435\u0439 \u0434\u043b\u044f \u043a\u0430\u0436\u0434\u043e\u0433\u043e \u0437\u0430\u043f\u0440\u043e\u0441\u0430. \u042d\u0442\u043e \u043d\u0435\u0438\u0437\u0431\u0435\u0436\u043d\u043e \u0443\u0432\u0435\u043b\u0438\u0447\u0438\u0442 \u0438\u0441\u043f\u043e\u043b\u044c\u0437\u043e\u0432\u0430\u043d\u0438\u0435 \u043e\u043f\u0435\u0440\u0430\u0442\u0438\u0432\u043d\u043e\u0439 \u043f\u0430\u043c\u044f\u0442\u0438 \u043d\u0430 \u0437\u0430\u043f\u0440\u043e\u0441 \u0438, \u0432 \u043d\u0435\u043a\u043e\u0442\u043e\u0440\u044b\u0445 \u0441\u043b\u0443\u0447\u0430\u044f\u0445, \u043c\u043e\u0436\u0435\u0442 \u0437\u0430\u043c\u0435\u0442\u043d\u043e \u043f\u043e\u0432\u043b\u0438\u044f\u0442\u044c \u043d\u0430 \u043f\u0440\u043e\u0438\u0437\u0432\u043e\u0434\u0438\u0442\u0435\u043b\u044c\u043d\u043e\u0441\u0442\u044c.\n\n\u041e\u0431\u0440\u0430\u0442\u0438\u0442\u0435\u0441\u044c \u043a [max_matches_increase_threshold](../Searching/Options.md#max_matches_increase_threshold) \u0434\u043b\u044f \u043f\u043e\u043b\u0443\u0447\u0435\u043d\u0438\u044f \u0434\u043e\u043f\u043e\u043b\u043d\u0438\u0442\u0435\u043b\u044c\u043d\u043e\u0439 \u0438\u043d\u0444\u043e\u0440\u043c\u0430\u0446\u0438\u0438 \u043e \u0442\u043e\u043c, \u043a\u0430\u043a \u044d\u0442\u043e \u043c\u043e\u0436\u0435\u0442 \u043f\u043e\u0432\u043b\u0438\u044f\u0442\u044c \u043d\u0430 \u043f\u043e\u0432\u0435\u0434\u0435\u043d\u0438\u0435 \u043e\u043f\u0446\u0438\u0438 `max_matches`.\n\n### max_matches_increase_threshold\n\n\u0426\u0435\u043b\u043e\u0435 \u0447\u0438\u0441\u043b\u043e. \u0423\u0441\u0442\u0430\u043d\u0430\u0432\u043b\u0438\u0432\u0430\u0435\u0442 \u043f\u043e\u0440\u043e\u0433, \u0434\u043e \u043a\u043e\u0442\u043e\u0440\u043e\u0433\u043e \u043c\u043e\u0436\u043d\u043e \u0443\u0432\u0435\u043b\u0438\u0447\u0438\u0442\u044c `max_matches`. \u041f\u043e \u0443\u043c\u043e\u043b\u0447\u0430\u043d\u0438\u044e 16384.\n\nManticore \u043c\u043e\u0436\u0435\u0442 \u0443\u0432\u0435\u043b\u0438\u0447\u0438\u0442\u044c `max_matches` \u0434\u043b\u044f \u043f\u043e\u0432\u044b\u0448\u0435\u043d\u0438\u044f \u0442\u043e\u0447\u043d\u043e\u0441\u0442\u0438 \u0433\u0440\u0443\u043f\u043f\u0438\u0440\u043e\u0432\u043a\u0438 \u0438/\u0438\u043b\u0438 \u0430\u0433\u0440\u0435\u0433\u0430\u0446\u0438\u0438, \u043a\u043e\u0433\u0434\u0430 \u0432\u043a\u043b\u044e\u0447\u0435\u043d `pseudo_sharding`, \u0438 \u0435\u0441\u043b\u0438 \u043e\u043d \u043e\u0431\u043d\u0430\u0440\u0443\u0436\u0438\u0432\u0430\u0435\u0442, \u0447\u0442\u043e \u043a\u043e\u043b\u0438\u0447\u0435\u0441\u0442\u0432\u043e \u0443\u043d\u0438\u043a\u0430\u043b\u044c\u043d\u044b\u0445 \u0437\u043d\u0430\u0447\u0435\u043d\u0438\u0439 \u0430\u0442\u0440\u0438\u0431\u0443\u0442\u0430 \u0433\u0440\u0443\u043f\u043f\u0438\u0440\u043e\u0432\u043a\u0438 \u043c\u0435\u043d\u044c\u0448\u0435 \u044d\u0442\u043e\u0433\u043e \u043f\u043e\u0440\u043e\u0433\u0430. \u041f\u043e\u0442\u0435\u0440\u044f \u0442\u043e\u0447\u043d\u043e\u0441\u0442\u0438 \u043c\u043e\u0436\u0435\u0442 \u043f\u0440\u043e\u0438\u0437\u043e\u0439\u0442\u0438, \u043a\u043e\u0433\u0434\u0430 \u043f\u0441\u0435\u0432\u0434\u043e\u0448\u0430\u0440\u0434\u0438\u0440\u043e\u0432\u0430\u043d\u0438\u0435 \u0432\u044b\u043f\u043e\u043b\u043d\u044f\u0435\u0442 \u0437\u0430\u043f\u0440\u043e\u0441 \u0432 \u043d\u0435\u0441\u043a\u043e\u043b\u044c\u043a\u0438\u0445 \u043f\u043e\u0442\u043e\u043a\u0430\u0445 \u0438\u043b\u0438 \u043a\u043e\u0433\u0434\u0430 RT-\u0442\u0430\u0431\u043b\u0438\u0446\u0430 \u043f\u0440\u043e\u0432\u043e\u0434\u0438\u0442 \u043f\u0430\u0440\u0430\u043b\u043b\u0435\u043b\u044c\u043d\u044b\u0439 \u043f\u043e\u0438\u0441\u043a \u0432 \u0434\u0438\u0441\u043a\u043e\u0432\u044b\u0445 \u0447\u0430\u043d\u043a\u0430\u0445.\n\n\u0415\u0441\u043b\u0438 \u043a\u043e\u043b\u0438\u0447\u0435\u0441\u0442\u0432\u043e \u0443\u043d\u0438\u043a\u0430\u043b\u044c\u043d\u044b\u0445 \u0437\u043d\u0430\u0447\u0435\u043d\u0438\u0439 \u0430\u0442\u0440\u0438\u0431\u0443\u0442\u0430 \u0433\u0440\u0443\u043f\u043f\u0438\u0440\u043e\u0432\u043a\u0438 \u043c\u0435\u043d\u044c\u0448\u0435 \u043f\u043e\u0440\u043e\u0433\u0430, `max_matches` \u0431\u0443\u0434\u0435\u0442 \u0443\u0441\u0442\u0430\u043d\u043e\u0432\u043b\u0435\u043d\u043e \u0432 \u044d\u0442\u043e \u0447\u0438\u0441\u043b\u043e. \u0412 \u043f\u0440\u043e\u0442\u0438\u0432\u043d\u043e\u043c \u0441\u043b\u0443\u0447\u0430\u0435 \u0431\u0443\u0434\u0435\u0442 \u0438\u0441\u043f\u043e\u043b\u044c\u0437\u043e\u0432\u0430\u043d\u043e \u0437\u043d\u0430\u0447\u0435\u043d\u0438\u0435 `max_matches` \u043f\u043e \u0443\u043c\u043e\u043b\u0447\u0430\u043d\u0438\u044e.\n\n\u0415\u0441\u043b\u0438 `max_matches` \u0431\u044b\u043b\u043e \u044f\u0432\u043d\u043e \u0443\u0441\u0442\u0430\u043d\u043e\u0432\u043b\u0435\u043d\u043e \u0432 \u043f\u0430\u0440\u0430\u043c\u0435\u0442\u0440\u0430\u0445 \u0437\u0430\u043f\u0440\u043e\u0441\u0430, \u044d\u0442\u043e\u0442 \u043f\u043e\u0440\u043e\u0433 \u043d\u0435 \u0434\u0435\u0439\u0441\u0442\u0432\u0443\u0435\u0442.\n\n\u0418\u043c\u0435\u0439\u0442\u0435 \u0432 \u0432\u0438\u0434\u0443, \u0447\u0442\u043e \u0435\u0441\u043b\u0438 \u044d\u0442\u043e\u0442 \u043f\u043e\u0440\u043e\u0433 \u0443\u0441\u0442\u0430\u043d\u043e\u0432\u043b\u0435\u043d \u0441\u043b\u0438\u0448\u043a\u043e\u043c \u0432\u044b\u0441\u043e\u043a\u043e, \u044d\u0442\u043e \u043f\u0440\u0438\u0432\u0435\u0434\u0435\u0442 \u043a \u0443\u0432\u0435\u043b\u0438\u0447\u0435\u043d\u0438\u044e \u043f\u043e\u0442\u0440\u0435\u0431\u043b\u0435\u043d\u0438\u044f \u043f\u0430\u043c\u044f\u0442\u0438 \u0438 \u043e\u0431\u0449\u0435\u043c\u0443 \u0441\u043d\u0438\u0436\u0435\u043d\u0438\u044e \u043f\u0440\u043e\u0438\u0437\u0432\u043e\u0434\u0438\u0442\u0435\u043b\u044c\u043d\u043e\u0441\u0442\u0438.\n\n\u0412\u044b \u0442\u0430\u043a\u0436\u0435 \u043c\u043e\u0436\u0435\u0442\u0435 \u043f\u0440\u0438\u043d\u0443\u0434\u0438\u0442\u0435\u043b\u044c\u043d\u043e \u0432\u043a\u043b\u044e\u0447\u0438\u0442\u044c \u0440\u0435\u0436\u0438\u043c \u0433\u0430\u0440\u0430\u043d\u0442\u0438\u0440\u043e\u0432\u0430\u043d\u043d\u043e\u0439 \u0442\u043e\u0447\u043d\u043e\u0441\u0442\u0438 \u0433\u0440\u0443\u043f\u043f\u0438\u0440\u043e\u0432\u043a\u0438/\u0430\u0433\u0440\u0435\u0433\u0430\u0446\u0438\u0438 \u0441 \u043f\u043e\u043c\u043e\u0449\u044c\u044e \u043e\u043f\u0446\u0438\u0438 [accurate_aggregation](../Searching/Options.md#accurate_aggregation).\n\n### max_query_time\n\u0423\u0441\u0442\u0430\u043d\u0430\u0432\u043b\u0438\u0432\u0430\u0435\u0442 \u043c\u0430\u043a\u0441\u0438\u043c\u0430\u043b\u044c\u043d\u043e\u0435 \u0432\u0440\u0435\u043c\u044f \u0432\u044b\u043f\u043e\u043b\u043d\u0435\u043d\u0438\u044f \u043f\u043e\u0438\u0441\u043a\u043e\u0432\u043e\u0433\u043e \u0437\u0430\u043f\u0440\u043e\u0441\u0430 \u0432 \u043c\u0438\u043b\u043b\u0438\u0441\u0435\u043a\u0443\u043d\u0434\u0430\u0445. \u0414\u043e\u043b\u0436\u043d\u043e \u0431\u044b\u0442\u044c \u043d\u0435\u043e\u0442\u0440\u0438\u0446\u0430\u0442\u0435\u043b\u044c\u043d\u044b\u043c \u0446\u0435\u043b\u044b\u043c \u0447\u0438\u0441\u043b\u043e\u043c. \u0417\u043d\u0430\u0447\u0435\u043d\u0438\u0435 \u043f\u043e \u0443\u043c\u043e\u043b\u0447\u0430\u043d\u0438\u044e \u2014 0, \u0447\u0442\u043e \u043e\u0437\u043d\u0430\u0447\u0430\u0435\u0442 \u00ab\u043d\u0435 \u043e\u0433\u0440\u0430\u043d\u0438\u0447\u0438\u0432\u0430\u0442\u044c\u00bb. \u041b\u043e\u043a\u0430\u043b\u044c\u043d\u044b\u0435 \u043f\u043e\u0438\u0441\u043a\u043e\u0432\u044b\u0435 \u0437\u0430\u043f\u0440\u043e\u0441\u044b \u0431\u0443\u0434\u0443\u0442 \u043e\u0441\u0442\u0430\u043d\u043e\u0432\u043b\u0435\u043d\u044b, \u043a\u0430\u043a \u0442\u043e\u043b\u044c\u043a\u043e \u0438\u0441\u0442\u0435\u0447\u0435\u0442 \u0443\u043a\u0430\u0437\u0430\u043d\u043d\u043e\u0435 \u0432\u0440\u0435\u043c\u044f. \u041e\u0431\u0440\u0430\u0442\u0438\u0442\u0435 \u0432\u043d\u0438\u043c\u0430\u043d\u0438\u0435, \u0447\u0442\u043e \u0435\u0441\u043b\u0438 \u0432\u044b \u0432\u044b\u043f\u043e\u043b\u043d\u044f\u0435\u0442\u0435 \u043f\u043e\u0438\u0441\u043a, \u043a\u043e\u0442\u043e\u0440\u044b\u0439 \u0437\u0430\u043f\u0440\u0430\u0448\u0438\u0432\u0430\u0435\u0442 \u043d\u0435\u0441\u043a\u043e\u043b\u044c\u043a\u043e \u043b\u043e\u043a\u0430\u043b\u044c\u043d\u044b\u0445 \u0442\u0430\u0431\u043b\u0438\u0446, \u044d\u0442\u043e\u0442 \u043b\u0438\u043c\u0438\u0442 \u043f\u0440\u0438\u043c\u0435\u043d\u044f\u0435\u0442\u0441\u044f \u043a \u043a\u0430\u0436\u0434\u043e\u0439 \u0442\u0430\u0431\u043b\u0438\u0446\u0435 \u043e\u0442\u0434\u0435\u043b\u044c\u043d\u043e. \u0418\u043c\u0435\u0439\u0442\u0435 \u0432 \u0432\u0438\u0434\u0443, \u0447\u0442\u043e \u044d\u0442\u043e \u043c\u043e\u0436\u0435\u0442 \u043d\u0435\u043c\u043d\u043e\u0433\u043e \u0443\u0432\u0435\u043b\u0438\u0447\u0438\u0442\u044c \u0432\u0440\u0435\u043c\u044f \u043e\u0442\u043a\u043b\u0438\u043a\u0430 \u0437\u0430\u043f\u0440\u043e\u0441\u0430 \u0438\u0437-\u0437\u0430 \u043d\u0430\u043a\u043b\u0430\u0434\u043d\u044b\u0445 \u0440\u0430\u0441\u0445\u043e\u0434\u043e\u0432, \u0432\u044b\u0437\u0432\u0430\u043d\u043d\u044b\u0445 \u043f\u043e\u0441\u0442\u043e\u044f\u043d\u043d\u044b\u043c \u043e\u0442\u0441\u043b\u0435\u0436\u0438\u0432\u0430\u043d\u0438\u0435\u043c, \u043d\u0435 \u043f\u043e\u0440\u0430 \u043b\u0438 \u043e\u0441\u0442\u0430\u043d\u043e\u0432\u0438\u0442\u044c \u0437\u0430\u043f\u0440\u043e\u0441.\n\n### max_predicted_time\n\u0426\u0435\u043b\u043e\u0435 \u0447\u0438\u0441\u043b\u043e. \u041c\u0430\u043a\u0441\u0438\u043c\u0430\u043b\u044c\u043d\u043e\u0435 \u043f\u0440\u043e\u0433\u043d\u043e\u0437\u0438\u0440\u0443\u0435\u043c\u043e\u0435 \u0432\u0440\u0435\u043c\u044f \u043f\u043e\u0438\u0441\u043a\u0430; \u0441\u043c. [predicted_time_costs](../Server_settings/Searchd.md#predicted_time_costs).\n\n### morphology\n`none` \u043f\u043e\u0437\u0432\u043e\u043b\u044f\u0435\u0442 \u0437\u0430\u043c\u0435\u043d\u044f\u0442\u044c \u0432\u0441\u0435 \u0442\u0435\u0440\u043c\u0438\u043d\u044b \u0437\u0430\u043f\u0440\u043e\u0441\u0430 \u0438\u0445 \u0442\u043e\u0447\u043d\u044b\u043c\u0438 \u0444\u043e\u0440\u043c\u0430\u043c\u0438, \u0435\u0441\u043b\u0438 \u0442\u0430\u0431\u043b\u0438\u0446\u0430 \u0431\u044b\u043b\u0430 \u043f\u043e\u0441\u0442\u0440\u043e\u0435\u043d\u0430 \u0441 \u0432\u043a\u043b\u044e\u0447\u0435\u043d\u043d\u043e\u0439 \u043e\u043f\u0446\u0438\u0435\u0439 [index_exact_words](../Creating_a_table/NLP_and_tokenization/Morphology.md#index_exact_words). \u042d\u0442\u043e \u043f\u043e\u043b\u0435\u0437\u043d\u043e \u0434\u043b\u044f \u043f\u0440\u0435\u0434\u043e\u0442\u0432\u0440\u0430\u0449\u0435\u043d\u0438\u044f \u0441\u0442\u0435\u043c\u043c\u0438\u043d\u0433\u0430 \u0438\u043b\u0438 \u043b\u0435\u043c\u043c\u0430\u0442\u0438\u0437\u0430\u0446\u0438\u0438 \u0442\u0435\u0440\u043c\u0438\u043d\u043e\u0432 \u0437\u0430\u043f\u0440\u043e\u0441\u0430.\n\n### not_terms_only_allowed\n<!-- example not_terms_only_allowed -->\n`0` \u0438\u043b\u0438 `1` \u0440\u0430\u0437\u0440\u0435\u0448\u0430\u0435\u0442 \u0430\u0432\u0442\u043e\u043d\u043e\u043c\u043d\u043e\u0435 [\u043e\u0442\u0440\u0438\u0446\u0430\u043d\u0438\u0435](../Searching/Full_text_matching/Operators.md#Negation-operator) \u0434\u043b\u044f \u0437\u0430\u043f\u0440\u043e\u0441\u0430. \u041f\u043e \u0443\u043c\u043e\u043b\u0447\u0430\u043d\u0438\u044e 0. \u0421\u043c. \u0442\u0430\u043a\u0436\u0435 \u0441\u043e\u043e\u0442\u0432\u0435\u0442\u0441\u0442\u0432\u0443\u044e\u0449\u0443\u044e [\u0433\u043b\u043e\u0431\u0430\u043b\u044c\u043d\u0443\u044e \u043d\u0430\u0441\u0442\u0440\u043e\u0439\u043a\u0443](../Server_settings/Searchd.md#not_terms_only_allowed).\n\n<!-- request SQL -->\nCODE_BLOCK_9\n<!-- end -->\n\n### ranker\n\u0412\u044b\u0431\u0435\u0440\u0438\u0442\u0435 \u0438\u0437 \u0441\u043b\u0435\u0434\u0443\u044e\u0449\u0438\u0445 \u0432\u0430\u0440\u0438\u0430\u043d\u0442\u043e\u0432:\n* `proximity_bm25`\n* `bm25`\n* `none`\n* `wordcount`\n* `proximity`\n* `matchany`\n* `fieldmask`\n* `sph04`\n* `expr`\n* `export`\n\n\u0414\u043b\u044f \u043f\u043e\u043b\u0443\u0447\u0435\u043d\u0438\u044f \u0431\u043e\u043b\u0435\u0435 \u043f\u043e\u0434\u0440\u043e\u0431\u043d\u043e\u0439 \u0438\u043d\u0444\u043e\u0440\u043c\u0430\u0446\u0438\u0438 \u043e \u043a\u0430\u0436\u0434\u043e\u043c \u0440\u0430\u043d\u043a\u0435\u0440\u0435 \u043e\u0431\u0440\u0430\u0442\u0438\u0442\u0435\u0441\u044c \u043a [\u0420\u0430\u043d\u0436\u0438\u0440\u043e\u0432\u0430\u043d\u0438\u0435 \u0440\u0435\u0437\u0443\u043b\u044c\u0442\u0430\u0442\u043e\u0432 \u043f\u043e\u0438\u0441\u043a\u0430](../Searching/Sorting_and_ranking.md#Available-built-in-rankers).\n\n### rand_seed\n\u041f\u043e\u0437\u0432\u043e\u043b\u044f\u0435\u0442 \u0443\u043a\u0430\u0437\u0430\u0442\u044c \u043a\u043e\u043d\u043a\u0440\u0435\u0442\u043d\u043e\u0435 \u0446\u0435\u043b\u043e\u0447\u0438\u0441\u043b\u0435\u043d\u043d\u043e\u0435 \u0437\u043d\u0430\u0447\u0435\u043d\u0438\u0435 \u0441\u0438\u0434\u0430 \u0434\u043b\u044f \u0437\u0430\u043f\u0440\u043e\u0441\u0430 `ORDER BY RAND()`, \u043d\u0430\u043f\u0440\u0438\u043c\u0435\u0440: `... OPTION rand_seed=1234`. \u041f\u043e \u0443\u043c\u043e\u043b\u0447\u0430\u043d\u0438\u044e \u0434\u043b\u044f \u043a\u0430\u0436\u0434\u043e\u0433\u043e \u0437\u0430\u043f\u0440\u043e\u0441\u0430 \u0430\u0432\u0442\u043e\u043c\u0430\u0442\u0438\u0447\u0435\u0441\u043a\u0438 \u0433\u0435\u043d\u0435\u0440\u0438\u0440\u0443\u0435\u0442\u0441\u044f \u043d\u043e\u0432\u043e\u0435 \u0438 \u0440\u0430\u0437\u043d\u043e\u0435 \u0437\u043d\u0430\u0447\u0435\u043d\u0438\u0435 \u0441\u0438\u0434\u0430.\n\n### retry_count\n\u0426\u0435\u043b\u043e\u0435 \u0447\u0438\u0441\u043b\u043e. \u041a\u043e\u043b\u0438\u0447\u0435\u0441\u0442\u0432\u043e \u043f\u043e\u0432\u0442\u043e\u0440\u043d\u044b\u0445 \u043f\u043e\u043f\u044b\u0442\u043e\u043a \u0434\u043b\u044f \u0440\u0430\u0441\u043f\u0440\u0435\u0434\u0435\u043b\u0435\u043d\u043d\u043e\u0433\u043e \u043f\u043e\u0438\u0441\u043a\u0430.\n\n### retry_delay\n\u0426\u0435\u043b\u043e\u0435 \u0447\u0438\u0441\u043b\u043e. \u0417\u0430\u0434\u0435\u0440\u0436\u043a\u0430 \u043c\u0435\u0436\u0434\u0443 \u043f\u043e\u0432\u0442\u043e\u0440\u043d\u044b\u043c\u0438 \u043f\u043e\u043f\u044b\u0442\u043a\u0430\u043c\u0438 \u0434\u043b\u044f \u0440\u0430\u0441\u043f\u0440\u0435\u0434\u0435\u043b\u0435\u043d\u043d\u043e\u0433\u043e \u043f\u043e\u0438\u0441\u043a\u0430, \u0432 \u043c\u0438\u043b\u043b\u0438\u0441\u0435\u043a\u0443\u043d\u0434\u0430\u0445.\n\n### scroll\n\n\u0421\u0442\u0440\u043e\u043a\u0430. \u0422\u043e\u043a\u0435\u043d \u043f\u0440\u043e\u043a\u0440\u0443\u0442\u043a\u0438 \u0434\u043b\u044f \u043f\u043e\u0441\u0442\u0440\u0430\u043d\u0438\u0447\u043d\u043e\u0433\u043e \u0432\u044b\u0432\u043e\u0434\u0430 \u0440\u0435\u0437\u0443\u043b\u044c\u0442\u0430\u0442\u043e\u0432 \u0441 \u0438\u0441\u043f\u043e\u043b\u044c\u0437\u043e\u0432\u0430\u043d\u0438\u0435\u043c [\u041f\u043e\u0434\u0445\u043e\u0434\u0430 \u043a \u043f\u0430\u0433\u0438\u043d\u0430\u0446\u0438\u0438 Scroll](../Searching/Pagination.md#Scroll-Search-Option).\n\n### sort_method\n* `pq` - \u043e\u0447\u0435\u0440\u0435\u0434\u044c \u0441 \u043f\u0440\u0438\u043e\u0440\u0438\u0442\u0435\u0442\u043e\u043c, \u0443\u0441\u0442\u0430\u043d\u043e\u0432\u043b\u0435\u043d\u0430 \u043f\u043e \u0443\u043c\u043e\u043b\u0447\u0430\u043d\u0438\u044e\n* `kbuffer` - \u043e\u0431\u0435\u0441\u043f\u0435\u0447\u0438\u0432\u0430\u0435\u0442 \u0431\u043e\u043b\u0435\u0435 \u0431\u044b\u0441\u0442\u0440\u0443\u044e \u0441\u043e\u0440\u0442\u0438\u0440\u043e\u0432\u043a\u0443 \u0434\u043b\u044f \u0443\u0436\u0435 \u043f\u0440\u0435\u0434\u0432\u0430\u0440\u0438\u0442\u0435\u043b\u044c\u043d\u043e \u043e\u0442\u0441\u043e\u0440\u0442\u0438\u0440\u043e\u0432\u0430\u043d\u043d\u044b\u0445 \u0434\u0430\u043d\u043d\u044b\u0445, \u043d\u0430\u043f\u0440\u0438\u043c\u0435\u0440, \u0434\u0430\u043d\u043d\u044b\u0445 \u0442\u0430\u0431\u043b\u0438\u0446\u044b, \u043e\u0442\u0441\u043e\u0440\u0442\u0438\u0440\u043e\u0432\u0430\u043d\u043d\u044b\u0445 \u043f\u043e id\n\u0420\u0435\u0437\u0443\u043b\u044c\u0442\u0438\u0440\u0443\u044e\u0449\u0438\u0439 \u043d\u0430\u0431\u043e\u0440 \u043e\u0434\u0438\u043d\u0430\u043a\u043e\u0432 \u0432 \u043e\u0431\u043e\u0438\u0445 \u0441\u043b\u0443\u0447\u0430\u044f\u0445; \u0432\u044b\u0431\u043e\u0440 \u0442\u043e\u0433\u043e \u0438\u043b\u0438 \u0438\u043d\u043e\u0433\u043e \u0432\u0430\u0440\u0438\u0430\u043d\u0442\u0430 \u043c\u043e\u0436\u0435\u0442 \u043f\u0440\u043e\u0441\u0442\u043e \u0443\u043b\u0443\u0447\u0448\u0438\u0442\u044c (\u0438\u043b\u0438 \u0443\u0445\u0443\u0434\u0448\u0438\u0442\u044c) \u043f\u0440\u043e\u0438\u0437\u0432\u043e\u0434\u0438\u0442\u0435\u043b\u044c\u043d\u043e\u0441\u0442\u044c.\n\n### threads\n\u041e\u0433\u0440\u0430\u043d\u0438\u0447\u0438\u0432\u0430\u0435\u0442 \u043c\u0430\u043a\u0441\u0438\u043c\u0430\u043b\u044c\u043d\u043e\u0435 \u043a\u043e\u043b\u0438\u0447\u0435\u0441\u0442\u0432\u043e \u043f\u043e\u0442\u043e\u043a\u043e\u0432, \u0438\u0441\u043f\u043e\u043b\u044c\u0437\u0443\u0435\u043c\u044b\u0445 \u0434\u043b\u044f \u043e\u0431\u0440\u0430\u0431\u043e\u0442\u043a\u0438 \u0442\u0435\u043a\u0443\u0449\u0435\u0433\u043e \u0437\u0430\u043f\u0440\u043e\u0441\u0430. \u041f\u043e \u0443\u043c\u043e\u043b\u0447\u0430\u043d\u0438\u044e \u2014 \u0431\u0435\u0437 \u043e\u0433\u0440\u0430\u043d\u0438\u0447\u0435\u043d\u0438\u0439 (\u0437\u0430\u043f\u0440\u043e\u0441 \u043c\u043e\u0436\u0435\u0442 \u0437\u0430\u043d\u044f\u0442\u044c \u0432\u0441\u0435 [\u043f\u043e\u0442\u043e\u043a\u0438](../Server_settings/Searchd.md#threads), \u043e\u043f\u0440\u0435\u0434\u0435\u043b\u0435\u043d\u043d\u044b\u0435 \u0433\u043b\u043e\u0431\u0430\u043b\u044c\u043d\u043e).\n\u0414\u043b\u044f \u043f\u0430\u043a\u0435\u0442\u0430 \u0437\u0430\u043f\u0440\u043e\u0441\u043e\u0432 \u043e\u043f\u0446\u0438\u044f \u0434\u043e\u043b\u0436\u043d\u0430 \u0431\u044b\u0442\u044c \u043f\u0440\u0438\u043a\u0440\u0435\u043f\u043b\u0435\u043d\u0430 \u043a \u0441\u0430\u043c\u043e\u043c\u0443 \u043f\u0435\u0440\u0432\u043e\u043c\u0443 \u0437\u0430\u043f\u0440\u043e\u0441\u0443 \u0432 \u043f\u0430\u043a\u0435\u0442\u0435, \u0438 \u0437\u0430\u0442\u0435\u043c \u043e\u043d\u0430 \u043f\u0440\u0438\u043c\u0435\u043d\u044f\u0435\u0442\u0441\u044f \u043f\u0440\u0438 \u0441\u043e\u0437\u0434\u0430\u043d\u0438\u0438 \u0440\u0430\u0431\u043e\u0447\u0435\u0439 \u043e\u0447\u0435\u0440\u0435\u0434\u0438 \u0438 \u0434\u0435\u0439\u0441\u0442\u0432\u0443\u0435\u0442 \u043d\u0430 \u0432\u0435\u0441\u044c \u043f\u0430\u043a\u0435\u0442. \u042d\u0442\u0430 \u043e\u043f\u0446\u0438\u044f \u0438\u043c\u0435\u0435\u0442 \u0442\u043e\u0442 \u0436\u0435 \u0441\u043c\u044b\u0441\u043b, \u0447\u0442\u043e \u0438 \u043e\u043f\u0446\u0438\u044f [max_threads_per_query](../Server_settings/Searchd.md#max_threads_per_query), \u043d\u043e \u043f\u0440\u0438\u043c\u0435\u043d\u044f\u0435\u0442\u0441\u044f \u0442\u043e\u043b\u044c\u043a\u043e \u043a \u0442\u0435\u043a\u0443\u0449\u0435\u043c\u0443 \u0437\u0430\u043f\u0440\u043e\u0441\u0443 \u0438\u043b\u0438 \u043f\u0430\u043a\u0435\u0442\u0443 \u0437\u0430\u043f\u0440\u043e\u0441\u043e\u0432.\n\n### token_filter\n\u0417\u0430\u043a\u043b\u044e\u0447\u0435\u043d\u043d\u0430\u044f \u0432 \u043a\u0430\u0432\u044b\u0447\u043a\u0438 \u0441\u0442\u0440\u043e\u043a\u0430, \u0440\u0430\u0437\u0434\u0435\u043b\u0435\u043d\u043d\u0430\u044f \u0434\u0432\u043e\u0435\u0442\u043e\u0447\u0438\u044f\u043c\u0438: `\u0438\u043c\u044f \u0431\u0438\u0431\u043b\u0438\u043e\u0442\u0435\u043a\u0438:\u0438\u043c\u044f \u043f\u043b\u0430\u0433\u0438\u043d\u0430:\u043d\u0435\u043e\u0431\u044f\u0437\u0430\u0442\u0435\u043b\u044c\u043d\u0430\u044f \u0441\u0442\u0440\u043e\u043a\u0430 \u043d\u0430\u0441\u0442\u0440\u043e\u0435\u043a`. \u0424\u0438\u043b\u044c\u0442\u0440 \u0442\u043e\u043a\u0435\u043d\u043e\u0432 \u0432\u0440\u0435\u043c\u0435\u043d\u0438 \u0437\u0430\u043f\u0440\u043e\u0441\u0430 \u0441\u043e\u0437\u0434\u0430\u0435\u0442\u0441\u044f \u0434\u043b\u044f \u043a\u0430\u0436\u0434\u043e\u0433\u043e \u043f\u043e\u0438\u0441\u043a\u0430, \u043a\u043e\u0433\u0434\u0430 \u043f\u043e\u043b\u043d\u043e\u0442\u0435\u043a\u0441\u0442\u043e\u0432\u044b\u0439 \u043f\u043e\u0438\u0441\u043a \u0432\u044b\u0437\u044b\u0432\u0430\u0435\u0442\u0441\u044f \u043a\u0430\u0436\u0434\u043e\u0439 \u0437\u0430\u0434\u0435\u0439\u0441\u0442\u0432\u043e\u0432\u0430\u043d\u043d\u043e\u0439 \u0442\u0430\u0431\u043b\u0438\u0446\u0435\u0439, \u043f\u043e\u0437\u0432\u043e\u043b\u044f\u044f \u0440\u0435\u0430\u043b\u0438\u0437\u043e\u0432\u0430\u0442\u044c \u043f\u043e\u043b\u044c\u0437\u043e\u0432\u0430\u0442\u0435\u043b\u044c\u0441\u043a\u0438\u0439 \u0442\u043e\u043a\u0435\u043d\u0438\u0437\u0430\u0442\u043e\u0440, \u043a\u043e\u0442\u043e\u0440\u044b\u0439 \u0433\u0435\u043d\u0435\u0440\u0438\u0440\u0443\u0435\u0442 \u0442\u043e\u043a\u0435\u043d\u044b \u0432 \u0441\u043e\u043e\u0442\u0432\u0435\u0442\u0441\u0442\u0432\u0438\u0438 \u0441 \u043f\u043e\u043b\u044c\u0437\u043e\u0432\u0430\u0442\u0435\u043b\u044c\u0441\u043a\u0438\u043c\u0438 \u043f\u0440\u0430\u0432\u0438\u043b\u0430\u043c\u0438.\nCODE_BLOCK_10\n### expansion_limit\n\u041e\u0433\u0440\u0430\u043d\u0438\u0447\u0438\u0432\u0430\u0435\u0442 \u043c\u0430\u043a\u0441\u0438\u043c\u0430\u043b\u044c\u043d\u043e\u0435 \u043a\u043e\u043b\u0438\u0447\u0435\u0441\u0442\u0432\u043e \u0440\u0430\u0441\u0448\u0438\u0440\u0435\u043d\u043d\u044b\u0445 \u043a\u043b\u044e\u0447\u0435\u0432\u044b\u0445 \u0441\u043b\u043e\u0432 \u0434\u043b\u044f \u043e\u0434\u043d\u043e\u0433\u043e \u043f\u043e\u0434\u0441\u0442\u0430\u043d\u043e\u0432\u043e\u0447\u043d\u043e\u0433\u043e \u0437\u043d\u0430\u043a\u0430, \u0437\u043d\u0430\u0447\u0435\u043d\u0438\u0435 \u043f\u043e \u0443\u043c\u043e\u043b\u0447\u0430\u043d\u0438\u044e 0 \u043e\u0437\u043d\u0430\u0447\u0430\u0435\u0442 \u043e\u0442\u0441\u0443\u0442\u0441\u0442\u0432\u0438\u0435 \u043e\u0433\u0440\u0430\u043d\u0438\u0447\u0435\u043d\u0438\u0439. \u0414\u043b\u044f \u043f\u043e\u043b\u0443\u0447\u0435\u043d\u0438\u044f \u0434\u043e\u043f\u043e\u043b\u043d\u0438\u0442\u0435\u043b\u044c\u043d\u044b\u0445 \u0441\u0432\u0435\u0434\u0435\u043d\u0438\u0439 \u043e\u0431\u0440\u0430\u0442\u0438\u0442\u0435\u0441\u044c \u043a [expansion_limit](../Server_settings/Searchd.md#expansion_limit).\n\n## \u041f\u043e\u0434\u0441\u043a\u0430\u0437\u043a\u0438 \u043e\u043f\u0442\u0438\u043c\u0438\u0437\u0430\u0442\u043e\u0440\u0430 \u0437\u0430\u043f\u0440\u043e\u0441\u043e\u0432\n\n<!-- example options_force -->\n\n\u0412 \u0440\u0435\u0434\u043a\u0438\u0445 \u0441\u043b\u0443\u0447\u0430\u044f\u0445 \u0432\u0441\u0442\u0440\u043e\u0435\u043d\u043d\u044b\u0439 \u0430\u043d\u0430\u043b\u0438\u0437\u0430\u0442\u043e\u0440 \u0437\u0430\u043f\u0440\u043e\u0441\u043e\u0432 Manticore \u043c\u043e\u0436\u0435\u0442 \u043e\u0448\u0438\u0431\u0430\u0442\u044c\u0441\u044f \u0432 \u043f\u043e\u043d\u0438\u043c\u0430\u043d\u0438\u0438 \u0437\u0430\u043f\u0440\u043e\u0441\u0430 \u0438 \u043e\u043f\u0440\u0435\u0434\u0435\u043b\u0435\u043d\u0438\u0438 \u0442\u043e\u0433\u043e, \u0441\u043b\u0435\u0434\u0443\u0435\u0442 \u043b\u0438 \u0438\u0441\u043f\u043e\u043b\u044c\u0437\u043e\u0432\u0430\u0442\u044c \u0438\u043d\u0434\u0435\u043a\u0441 docid, \u0432\u0442\u043e\u0440\u0438\u0447\u043d\u044b\u0435 \u0438\u043d\u0434\u0435\u043a\u0441\u044b \u0438\u043b\u0438 \u043a\u043e\u043b\u043e\u043d\u043e\u0447\u043d\u043e\u0435 \u0441\u043a\u0430\u043d\u0438\u0440\u043e\u0432\u0430\u043d\u0438\u0435. \u0427\u0442\u043e\u0431\u044b \u043f\u0435\u0440\u0435\u043e\u043f\u0440\u0435\u0434\u0435\u043b\u0438\u0442\u044c \u0440\u0435\u0448\u0435\u043d\u0438\u044f \u043e\u043f\u0442\u0438\u043c\u0438\u0437\u0430\u0442\u043e\u0440\u0430 \u0437\u0430\u043f\u0440\u043e\u0441\u043e\u0432, \u0432\u044b \u043c\u043e\u0436\u0435\u0442\u0435 \u0438\u0441\u043f\u043e\u043b\u044c\u0437\u043e\u0432\u0430\u0442\u044c \u0441\u043b\u0435\u0434\u0443\u044e\u0449\u0438\u0435 \u043f\u043e\u0434\u0441\u043a\u0430\u0437\u043a\u0438 \u0432 \u0441\u0432\u043e\u0435\u043c \u0437\u0430\u043f\u0440\u043e\u0441\u0435:\n\n* `/*+ DocidIndex(id) */`  \u0434\u043b\u044f \u043f\u0440\u0438\u043d\u0443\u0434\u0438\u0442\u0435\u043b\u044c\u043d\u043e\u0433\u043e \u0438\u0441\u043f\u043e\u043b\u044c\u0437\u043e\u0432\u0430\u043d\u0438\u044f \u0438\u043d\u0434\u0435\u043a\u0441\u0430 docid, `/*+ NO_DocidIndex(id) */` \u0447\u0442\u043e\u0431\u044b \u0443\u043a\u0430\u0437\u0430\u0442\u044c \u043e\u043f\u0442\u0438\u043c\u0438\u0437\u0430\u0442\u043e\u0440\u0443 \u0438\u0433\u043d\u043e\u0440\u0438\u0440\u043e\u0432\u0430\u0442\u044c \u0435\u0433\u043e\n* `/*+ SecondaryIndex(<attr_name1>[, <attr_nameN>]) */` \u0434\u043b\u044f \u043f\u0440\u0438\u043d\u0443\u0434\u0438\u0442\u0435\u043b\u044c\u043d\u043e\u0433\u043e \u0438\u0441\u043f\u043e\u043b\u044c\u0437\u043e\u0432\u0430\u043d\u0438\u044f \u0432\u0442\u043e\u0440\u0438\u0447\u043d\u043e\u0433\u043e \u0438\u043d\u0434\u0435\u043a\u0441\u0430 (\u0435\u0441\u043b\u0438 \u0434\u043e\u0441\u0442\u0443\u043f\u0435\u043d), `/*+ NO_SecondaryIndex(id) */`  \u0447\u0442\u043e\u0431\u044b \u0443\u043a\u0430\u0437\u0430\u0442\u044c \u043e\u043f\u0442\u0438\u043c\u0438\u0437\u0430\u0442\u043e\u0440\u0443 \u0438\u0433\u043d\u043e\u0440\u0438\u0440\u043e\u0432\u0430\u0442\u044c \u0435\u0433\u043e\n* `/*+ ColumnarScan(<attr_name1>[, <attr_nameN>]) */`  \u0434\u043b\u044f \u043f\u0440\u0438\u043d\u0443\u0434\u0438\u0442\u0435\u043b\u044c\u043d\u043e\u0433\u043e \u0438\u0441\u043f\u043e\u043b\u044c\u0437\u043e\u0432\u0430\u043d\u0438\u044f \u043a\u043e\u043b\u043e\u043d\u043e\u0447\u043d\u043e\u0433\u043e \u0441\u043a\u0430\u043d\u0438\u0440\u043e\u0432\u0430\u043d\u0438\u044f (\u0435\u0441\u043b\u0438 \u0430\u0442\u0440\u0438\u0431\u0443\u0442 \u043a\u043e\u043b\u043e\u043d\u043e\u0447\u043d\u044b\u0439), `/*+ NO_ColumnarScan(id) */` \u0447\u0442\u043e\u0431\u044b \u0443\u043a\u0430\u0437\u0430\u0442\u044c \u043e\u043f\u0442\u0438\u043c\u0438\u0437\u0430\u0442\u043e\u0440\u0443 \u0438\u0433\u043d\u043e\u0440\u0438\u0440\u043e\u0432\u0430\u0442\u044c \u0435\u0433\u043e"
        },
        "is_code_or_comment": false,
        "model": "deepseek/deepseek-v3.2",
        "updated_at": 1768541941
    },
    "b8ebeb61587a144d71860c16027d112941183cd39b6f939604089f0433c94032": {
        "original": "### expand_keywords\n`0` or `1` (`0` by default). Expands keywords with exact forms and/or stars when possible. Refer to [expand_keywords](../Creating_a_table/NLP_and_tokenization/Wildcard_searching_settings.md#expand_keywords) for more details.\n\n### expand_blended\n`0`, `off`, `1`, or any combination of `blend_mode` options (`0` by default). Expands blended keywords (tokens that contain characters configured via [blend_chars](../Creating_a_table/NLP_and_tokenization/Low-level_tokenization.md#blend_chars)) into their constituent variants during query parsing. When enabled, keywords like \"well-being\" (if `-` is configured in `blend_chars`) are expanded into variants such as \"well-being\", \"wellbeing\", \"well\", and \"being\", which are then grouped into OR subtrees in the query tree.\n\nThe supported values are:\n* `0` or `off` - Blended expansion is disabled (default). Blended keywords are processed normally without expansion.\n* `1` - Blended expansion is enabled and uses the table's [blend_mode](../Creating_a_table/NLP_and_tokenization/Low-level_tokenization.md#blend_mode) setting to determine which variants to generate.\n* Any blend mode option(s) - Blended expansion is enabled with the specified blend mode(s), overriding the table's `blend_mode` setting.\n\nRefer to [blend_mode](../Creating_a_table/NLP_and_tokenization/Low-level_tokenization.md#blend_mode) for more details on options.\n\n### field_weights\nNamed integer list (per-field user weights for ranking).\n\nExample:\nCODE_BLOCK_8\n\n### global_idf\nUse global statistics (frequencies) from the [global_idf](../Creating_a_table/NLP_and_tokenization/Low-level_tokenization.md#global_idf) file for IDF computations.\n\n### idf\nQuoted, comma-separated list of IDF computation flags. Known flags are:\n\n* `normalized`: BM25 variant, idf = log((N-n+1)/n), as per Robertson et al\n* `plain`: plain variant, idf = log(N/n), as per Sparck-Jones\n* `tfidf_normalized`: additionally divide IDF by query word count, so that `TF*IDF` fits into [0, 1] range\n* `tfidf_unnormalized`: do not additionally divide IDF by query word count where N is the collection size and n is the number of matched documents\n\nThe historically default IDF (Inverse Document Frequency) in Manticore is equivalent to `OPTION idf='normalized,tfidf_normalized'`, and those normalizations may cause several undesired effects.\n\nFirst, `idf=normalized` causes keyword penalization. For instance, if you search for `the | something` and `the` occurs in more than 50% of the documents, then documents with both keywords `the` and `something` will get less weight than documents with just one keyword `something`. Using `OPTION idf=plain` avoids this. Plain IDF varies in `[0, log(N)]` range, and keywords are never penalized; while the normalized IDF varies in `[-log(N), log(N)]` range, and too frequent keywords are penalized.\n\nSecond, `idf=tfidf_normalized` leads to IDF drift across queries. Historically, IDF was also divided by the query keyword count, ensuring the entire `sum(tf*idf)` across all keywords remained within the [0,1] range. However, this meant that queries like `word1` and `word1 | nonmatchingword2` would assign different weights to the exact same result set, as the IDFs for both `word1` and `nonmatchingword2` would be divided by 2. Using `OPTION idf='tfidf_unnormalized'` resolves this issue. Keep in mind that BM25, BM25A, BM25F() ranking factors will be adjusted accordingly when you disable this normalization.\n\nIDF flags can be combined; `plain` and `normalized` are mutually exclusive; `tfidf_unnormalized` and `tfidf_normalized` are also mutually exclusive; and unspecified flags in such mutually exclusive groups default to their original settings. This means `OPTION idf=plain` is the same as specifying `OPTION idf='plain,tfidf_normalized'` in its entirety.\n\n### jieba_mode\nSpecifies the Jieba segmentation mode for the query.\n\nWhen using Jieba Chinese segmentation, it can sometimes help to use different segmentation modes for tokenizing the documents and the query. For a complete list of modes, refer to [jieba_mode](../Creating_a_table/NLP_and_tokenization/Morphology.md#jieba_mode).\n\n### index_weights\nNamed integer list. Per-table user weights for ranking.\n\n### local_df\n`0` or `1`, automatically sum DFs over all local parts of a distributed table, ensuring consistent (and accurate) IDF across a locally sharded table. Enabled by default for disk chunks of the RT table. Query terms with wildcards are ignored.\n\n### low_priority\n`0` or `1` (`0` by default). Setting `low_priority=1` executes the query with a lower priority, rescheduling its jobs 10 times less frequently than other queries with normal priority.\n\n### max_matches\nInteger. Per-query max matches value.\n\nThe maximum number of matches that the server retains in RAM for each table and can return to the client. The default is 1000.\n\nIntroduced to control and limit RAM usage, the `max_matches` setting determines how many matches will be kept in RAM while searching each table. Every match found is still processed, but only the best N of them will be retained in memory and returned to the client in the end. For example, suppose a table contains 2,000,000 matches for a query. It's rare that you would need to retrieve all of them. Instead, you need to scan all of them but only choose the \"best\" 500, for instance, based on some criteria (e.g., sorted by relevance, price, or other factors) and display those 500 matches to the end user in pages of 20 to 100 matches. Tracking only the best 500 matches is much more RAM and CPU efficient than keeping all 2,000,000 matches, sorting them, and then discarding everything but the first 20 needed for the search results page. `max_matches` controls the N in that \"best N\" amount.",
        "translations": {
            "chinese": "### expand_keywords\n`0` \u6216 `1`\uff08\u9ed8\u8ba4\u4e3a `0`\uff09\u3002\u5c3d\u53ef\u80fd\u6269\u5c55\u7cbe\u786e\u5f62\u5f0f\u548c/\u6216\u5e26\u661f\u53f7\u7684\u5173\u952e\u8bcd\u3002\u6709\u5173\u66f4\u591a\u8be6\u7ec6\u4fe1\u606f\uff0c\u8bf7\u53c2\u9605 [expand_keywords](../Creating_a_table/NLP_and_tokenization/Wildcard_searching_settings.md#expand_keywords)\u3002\n\n### expand_blended\n`0`\u3001`off`\u3001`1` \u6216\u4efb\u4f55 `blend_mode` \u9009\u9879\u7684\u7ec4\u5408\uff08\u9ed8\u8ba4\u4e3a `0`\uff09\u3002\u5728\u67e5\u8be2\u89e3\u6790\u671f\u95f4\uff0c\u5c06\u6df7\u5408\u5173\u952e\u8bcd\uff08\u5305\u542b\u901a\u8fc7 [blend_chars](../Creating_a_table/NLP_and_tokenization/Low-level_tokenization.md#blend_chars) \u914d\u7f6e\u7684\u5b57\u7b26\u7684\u6807\u8bb0\uff09\u6269\u5c55\u4e3a\u5176\u6784\u6210\u53d8\u4f53\u3002\u542f\u7528\u540e\uff0c\u50cf \"well-being\"\uff08\u5982\u679c `-` \u5728 `blend_chars` \u4e2d\u914d\u7f6e\uff09\u8fd9\u6837\u7684\u5173\u952e\u8bcd\u5c06\u88ab\u6269\u5c55\u4e3a \"well-being\"\u3001\"wellbeing\"\u3001\"well\" \u548c \"being\" \u7b49\u53d8\u4f53\uff0c\u7136\u540e\u5728\u67e5\u8be2\u6811\u4e2d\u88ab\u5206\u7ec4\u4e3a OR \u5b50\u6811\u3002\n\n\u652f\u6301\u7684\u503c\u4e3a\uff1a\n* `0` \u6216 `off` - \u7981\u7528\u6df7\u5408\u6269\u5c55\uff08\u9ed8\u8ba4\uff09\u3002\u6df7\u5408\u5173\u952e\u8bcd\u5c06\u6309\u6b63\u5e38\u65b9\u5f0f\u5904\u7406\uff0c\u4e0d\u8fdb\u884c\u6269\u5c55\u3002\n* `1` - \u542f\u7528\u6df7\u5408\u6269\u5c55\uff0c\u5e76\u4f7f\u7528\u8868\u7684 [blend_mode](../Creating_a_table/NLP_and_tokenization/Low-level_tokenization.md#blend_mode) \u8bbe\u7f6e\u6765\u786e\u5b9a\u751f\u6210\u54ea\u4e9b\u53d8\u4f53\u3002\n* \u4efb\u4f55\u6df7\u5408\u6a21\u5f0f\u9009\u9879 - \u542f\u7528\u6df7\u5408\u6269\u5c55\u5e76\u4f7f\u7528\u6307\u5b9a\u7684\u6df7\u5408\u6a21\u5f0f\uff0c\u8986\u76d6\u8868\u7684 `blend_mode` \u8bbe\u7f6e\u3002\n\n\u6709\u5173\u9009\u9879\u7684\u66f4\u591a\u8be6\u7ec6\u4fe1\u606f\uff0c\u8bf7\u53c2\u9605 [blend_mode](../Creating_a_table/NLP_and_tokenization/Low-level_tokenization.md#blend_mode)\u3002\n\n### field_weights\n\u547d\u540d\u6574\u6570\u5217\u8868\uff08\u6309\u5b57\u6bb5\u7684\u7528\u6237\u6743\u91cd\u7528\u4e8e\u6392\u5e8f\uff09\u3002\n\n\u793a\u4f8b\uff1a\nCODE_BLOCK_8\n\n### global_idf\n\u4f7f\u7528 [global_idf](../Creating_a_table/NLP_and_tokenization/Low-level_tokenization.md#global_idf) \u6587\u4ef6\u4e2d\u7684\u5168\u5c40\u7edf\u8ba1\u4fe1\u606f\uff08\u9891\u7387\uff09\u8fdb\u884c IDF \u8ba1\u7b97\u3002\n\n### idf\n\u5e26\u5f15\u53f7\u7684\u3001\u9017\u53f7\u5206\u9694\u7684 IDF \u8ba1\u7b97\u6807\u5fd7\u5217\u8868\u3002\u5df2\u77e5\u6807\u5fd7\u5305\u62ec\uff1a\n\n* `normalized`\uff1aBM25 \u53d8\u4f53\uff0cidf = log((N-n+1)/n)\uff0c\u5982 Robertson \u7b49\u4eba\u6240\u8ff0\n* `plain`\uff1a\u666e\u901a\u53d8\u4f53\uff0cidf = log(N/n)\uff0c\u5982 Sparck-Jones \u6240\u8ff0\n* `tfidf_normalized`\uff1a\u6b64\u5916\u5c06 IDF \u9664\u4ee5\u67e5\u8be2\u8bcd\u6570\uff0c\u4f7f `TF*IDF` \u4fdd\u6301\u5728 [0, 1] \u8303\u56f4\u5185\n* `tfidf_unnormalized`\uff1a\u4e0d\u5c06 IDF \u9664\u4ee5\u67e5\u8be2\u8bcd\u6570\uff0c\u5176\u4e2d N \u662f\u96c6\u5408\u5927\u5c0f\uff0cn \u662f\u5339\u914d\u6587\u6863\u6570\n\nManticore \u5386\u53f2\u9ed8\u8ba4\u7684 IDF\uff08\u9006\u6587\u6863\u9891\u7387\uff09\u7b49\u540c\u4e8e `OPTION idf='normalized,tfidf_normalized'`\uff0c\u8fd9\u4e9b\u5f52\u4e00\u5316\u53ef\u80fd\u4f1a\u5bfc\u81f4\u4e00\u4e9b\u4e0d\u826f\u5f71\u54cd\u3002\n\n\u9996\u5148\uff0c`idf=normalized` \u4f1a\u5bfc\u81f4\u5173\u952e\u8bcd\u60e9\u7f5a\u3002\u4f8b\u5982\uff0c\u5982\u679c\u4f60\u641c\u7d22 `the | something`\uff0c\u5e76\u4e14 `the` \u51fa\u73b0\u5728\u8d85\u8fc7 50% \u7684\u6587\u6863\u4e2d\uff0c\u90a3\u4e48\u540c\u65f6\u5305\u542b `the` \u548c `something` \u7684\u6587\u6863\u7684\u6743\u91cd\u5c06\u4f4e\u4e8e\u4ec5\u5305\u542b `something` \u7684\u6587\u6863\u3002\u4f7f\u7528 `OPTION idf=plain` \u53ef\u907f\u514d\u6b64\u95ee\u9898\u3002\u666e\u901a IDF \u7684\u8303\u56f4\u5728 [0, log(N)] \u5185\uff0c\u5173\u952e\u8bcd\u6c38\u8fdc\u4e0d\u4f1a\u88ab\u60e9\u7f5a\uff1b\u800c\u5f52\u4e00\u5316 IDF \u7684\u8303\u56f4\u5728 [-log(N), log(N)] \u5185\uff0c\u8fc7\u4e8e\u9891\u7e41\u7684\u5173\u952e\u8bcd\u4f1a\u88ab\u60e9\u7f5a\u3002\n\n\u5176\u6b21\uff0c`idf=tfidf_normalized` \u4f1a\u5bfc\u81f4 IDF \u5728\u67e5\u8be2\u4e4b\u95f4\u6f02\u79fb\u3002\u5386\u53f2\u4e0a\uff0cIDF \u4e5f\u4f1a\u9664\u4ee5\u67e5\u8be2\u5173\u952e\u8bcd\u6570\uff0c\u786e\u4fdd\u6240\u6709\u5173\u952e\u8bcd\u7684 `sum(tf*idf)` \u603b\u548c\u4fdd\u6301\u5728 [0,1] \u8303\u56f4\u5185\u3002\u7136\u800c\uff0c\u8fd9\u610f\u5473\u7740\u50cf `word1` \u548c `word1 | nonmatchingword2` \u8fd9\u6837\u7684\u67e5\u8be2\u4f1a\u4e3a\u5b8c\u5168\u76f8\u540c\u7684\u7ed3\u679c\u96c6\u5206\u914d\u4e0d\u540c\u7684\u6743\u91cd\uff0c\u56e0\u4e3a `word1` \u548c `nonmatchingword2` \u7684 IDF \u90fd\u4f1a\u88ab\u9664\u4ee5 2\u3002\u4f7f\u7528 `OPTION idf='tfidf_unnormalized'` \u53ef\u89e3\u51b3\u6b64\u95ee\u9898\u3002\u8bf7\u6ce8\u610f\uff0c\u5f53\u7981\u7528\u6b64\u5f52\u4e00\u5316\u65f6\uff0cBM25\u3001BM25A\u3001BM25F() \u6392\u540d\u56e0\u7d20\u5c06\u76f8\u5e94\u8c03\u6574\u3002\n\nIDF \u6807\u5fd7\u53ef\u4ee5\u7ec4\u5408\uff1b`plain` \u548c `normalized` \u4e92\u65a5\uff1b`tfidf_unnormalized` \u548c `tfidf_normalized` \u4e5f\u4e92\u65a5\uff1b\u672a\u6307\u5b9a\u7684\u6807\u5fd7\u5728\u8fd9\u4e9b\u4e92\u65a5\u7ec4\u4e2d\u9ed8\u8ba4\u4f7f\u7528\u5176\u539f\u59cb\u8bbe\u7f6e\u3002\u8fd9\u610f\u5473\u7740 `OPTION idf=plain` \u7b49\u540c\u4e8e\u5b8c\u6574\u6307\u5b9a `OPTION idf='plain,tfidf_normalized'`\u3002\n\n### jieba_mode\n\u6307\u5b9a\u67e5\u8be2\u7684 Jieba \u5206\u8bcd\u6a21\u5f0f\u3002\n\n\u5728\u4f7f\u7528 Jieba \u4e2d\u6587\u5206\u8bcd\u65f6\uff0c\u6709\u65f6\u9700\u8981\u4e3a\u6587\u6863\u548c\u67e5\u8be2\u4f7f\u7528\u4e0d\u540c\u7684\u5206\u8bcd\u6a21\u5f0f\u3002\u6709\u5173\u5b8c\u6574\u6a21\u5f0f\u5217\u8868\uff0c\u8bf7\u53c2\u9605 [jieba_mode](../Creating_a_table/NLP_and_tokenization/Morphology.md#jieba_mode)\u3002\n\n### index_weights\n\u547d\u540d\u6574\u6570\u5217\u8868\u3002\u6309\u8868\u7684\u7528\u6237\u6743\u91cd\u7528\u4e8e\u6392\u5e8f\u3002\n\n### local_df\n`0` \u6216 `1`\uff0c\u81ea\u52a8\u6c47\u603b\u5206\u5e03\u5f0f\u8868\u7684\u6240\u6709\u672c\u5730\u90e8\u5206\u7684 DF\uff0c\u786e\u4fdd\u672c\u5730\u5206\u7247\u8868\u7684 IDF \u4e00\u81f4\uff08\u4e14\u51c6\u786e\uff09\u3002\u9ed8\u8ba4\u542f\u7528\u7528\u4e8e RT \u8868\u7684\u78c1\u76d8\u5206\u7247\u3002\u5e26\u6709\u901a\u914d\u7b26\u7684\u67e5\u8be2\u672f\u8bed\u88ab\u5ffd\u7565\u3002\n\n### low_priority\n`0` \u6216 `1`\uff08\u9ed8\u8ba4\u4e3a `0`\uff09\u3002\u8bbe\u7f6e `low_priority=1` \u4ee5\u8f83\u4f4e\u4f18\u5148\u7ea7\u6267\u884c\u67e5\u8be2\uff0c\u5176\u4efb\u52a1\u91cd\u65b0\u8c03\u5ea6\u7684\u9891\u7387\u6bd4\u5176\u4ed6\u6b63\u5e38\u4f18\u5148\u7ea7\u67e5\u8be2\u4f4e 10 \u500d\u3002\n\n### max_matches\n\u6574\u6570\u3002\u6bcf\u67e5\u8be2\u6700\u5927\u5339\u914d\u503c\u3002\n\n\u670d\u52a1\u5668\u4e3a\u6bcf\u4e2a\u8868\u5728 RAM \u4e2d\u4fdd\u7559\u7684\u6700\u5927\u5339\u914d\u6570\uff0c\u5e76\u53ef\u8fd4\u56de\u7ed9\u5ba2\u6237\u7aef\u3002\u9ed8\u8ba4\u503c\u4e3a 1000\u3002\n\n\u5f15\u5165 `max_matches` \u8bbe\u7f6e\u662f\u4e3a\u4e86\u63a7\u5236\u548c\u9650\u5236 RAM \u4f7f\u7528\uff0c\u8be5\u8bbe\u7f6e\u51b3\u5b9a\u4e86\u5728\u641c\u7d22\u6bcf\u4e2a\u8868\u65f6\u5c06\u4fdd\u7559\u591a\u5c11\u5339\u914d\u9879\u5728 RAM \u4e2d\u3002\u6bcf\u4e2a\u627e\u5230\u7684\u5339\u914d\u9879\u4ecd\u4f1a\u88ab\u5904\u7406\uff0c\u4f46\u53ea\u6709\u6700\u4f73\u7684 N \u4e2a\u5339\u914d\u9879\u4f1a\u88ab\u4fdd\u7559\u5728\u5185\u5b58\u4e2d\uff0c\u5e76\u6700\u7ec8\u8fd4\u56de\u7ed9\u5ba2\u6237\u7aef\u3002\u4f8b\u5982\uff0c\u5047\u8bbe\u4e00\u4e2a\u8868\u5305\u542b 2,000,000 \u4e2a\u5339\u914d\u9879\u7528\u4e8e\u67d0\u4e2a\u67e5\u8be2\u3002\u5f88\u5c11\u9700\u8981\u68c0\u7d22\u6240\u6709\u5339\u914d\u9879\u3002\u76f8\u53cd\uff0c\u4f60\u9700\u8981\u626b\u63cf\u6240\u6709\u5339\u914d\u9879\uff0c\u4f46\u4ec5\u9009\u62e9\u57fa\u4e8e\u67d0\u4e9b\u6807\u51c6\uff08\u4f8b\u5982\u6309\u76f8\u5173\u6027\u3001\u4ef7\u683c\u6216\u5176\u4ed6\u56e0\u7d20\u6392\u5e8f\uff09\u7684\u201c\u6700\u4f73\u201d500 \u4e2a\u5339\u914d\u9879\uff0c\u5e76\u5c06\u8fd9 500 \u4e2a\u5339\u914d\u9879\u4ee5\u6bcf\u9875 20 \u5230 100 \u4e2a\u5339\u914d\u9879\u7684\u5f62\u5f0f\u663e\u793a\u7ed9\u6700\u7ec8\u7528\u6237\u3002\u4ec5\u8ddf\u8e2a\u6700\u4f73\u7684 500 \u4e2a\u5339\u914d\u9879\u6bd4\u4fdd\u7559\u6240\u6709 2,000,000 \u4e2a\u5339\u914d\u9879\u3001\u6392\u5e8f\u540e\u4e22\u5f03\u9664\u524d 20 \u4e2a\u5916\u7684\u6240\u6709\u5185\u5bb9\uff0c\u5bf9 RAM \u548c CPU \u66f4\u52a0\u9ad8\u6548\u3002`max_matches` \u63a7\u5236\u8be5\u201c\u6700\u4f73 N\u201d\u4e2d\u7684 N \u503c\u3002",
            "russian": "### expand_keywords\n`0` \u0438\u043b\u0438 `1` (\u043f\u043e \u0443\u043c\u043e\u043b\u0447\u0430\u043d\u0438\u044e `0`). \u0420\u0430\u0441\u0448\u0438\u0440\u044f\u0435\u0442 \u043a\u043b\u044e\u0447\u0435\u0432\u044b\u0435 \u0441\u043b\u043e\u0432\u0430 \u0442\u043e\u0447\u043d\u044b\u043c\u0438 \u0444\u043e\u0440\u043c\u0430\u043c\u0438 \u0438/\u0438\u043b\u0438 \u0437\u0432\u0435\u0437\u0434\u043e\u0447\u043a\u0430\u043c\u0438, \u043a\u043e\u0433\u0434\u0430 \u044d\u0442\u043e \u0432\u043e\u0437\u043c\u043e\u0436\u043d\u043e. \u041f\u043e\u0434\u0440\u043e\u0431\u043d\u0435\u0435 \u0441\u043c. [expand_keywords](../Creating_a_table/NLP_and_tokenization/Wildcard_searching_settings.md#expand_keywords).\n\n### expand_blended\n`0`, `off`, `1` \u0438\u043b\u0438 \u043b\u044e\u0431\u0430\u044f \u043a\u043e\u043c\u0431\u0438\u043d\u0430\u0446\u0438\u044f \u043e\u043f\u0446\u0438\u0439 `blend_mode` (\u043f\u043e \u0443\u043c\u043e\u043b\u0447\u0430\u043d\u0438\u044e `0`). \u0420\u0430\u0441\u0448\u0438\u0440\u044f\u0435\u0442 \u0441\u043c\u0435\u0448\u0430\u043d\u043d\u044b\u0435 \u043a\u043b\u044e\u0447\u0435\u0432\u044b\u0435 \u0441\u043b\u043e\u0432\u0430 (\u0442\u043e\u043a\u0435\u043d\u044b, \u0441\u043e\u0434\u0435\u0440\u0436\u0430\u0449\u0438\u0435 \u0441\u0438\u043c\u0432\u043e\u043b\u044b, \u043d\u0430\u0441\u0442\u0440\u043e\u0435\u043d\u043d\u044b\u0435 \u0447\u0435\u0440\u0435\u0437 [blend_chars](../Creating_a_table/NLP_and_tokenization/Low-level_tokenization.md#blend_chars)) \u043d\u0430 \u0438\u0445 \u0441\u043e\u0441\u0442\u0430\u0432\u043d\u044b\u0435 \u0432\u0430\u0440\u0438\u0430\u043d\u0442\u044b \u0432\u043e \u0432\u0440\u0435\u043c\u044f \u0440\u0430\u0437\u0431\u043e\u0440\u0430 \u0437\u0430\u043f\u0440\u043e\u0441\u0430. \u041f\u0440\u0438 \u0432\u043a\u043b\u044e\u0447\u0435\u043d\u0438\u0438 \u043a\u043b\u044e\u0447\u0435\u0432\u044b\u0435 \u0441\u043b\u043e\u0432\u0430, \u0442\u0430\u043a\u0438\u0435 \u043a\u0430\u043a \"well-being\" (\u0435\u0441\u043b\u0438 `-` \u043d\u0430\u0441\u0442\u0440\u043e\u0435\u043d \u0432 `blend_chars`), \u0440\u0430\u0441\u0448\u0438\u0440\u044f\u044e\u0442\u0441\u044f \u0432 \u0432\u0430\u0440\u0438\u0430\u043d\u0442\u044b, \u0442\u0430\u043a\u0438\u0435 \u043a\u0430\u043a \"well-being\", \"wellbeing\", \"well\" \u0438 \"being\", \u043a\u043e\u0442\u043e\u0440\u044b\u0435 \u0437\u0430\u0442\u0435\u043c \u0433\u0440\u0443\u043f\u043f\u0438\u0440\u0443\u044e\u0442\u0441\u044f \u0432 \u043f\u043e\u0434\u0434\u0435\u0440\u0435\u0432\u044c\u044f \u0418\u041b\u0418 \u0432 \u0434\u0435\u0440\u0435\u0432\u0435 \u0437\u0430\u043f\u0440\u043e\u0441\u0430.\n\n\u041f\u043e\u0434\u0434\u0435\u0440\u0436\u0438\u0432\u0430\u0435\u043c\u044b\u0435 \u0437\u043d\u0430\u0447\u0435\u043d\u0438\u044f:\n* `0` \u0438\u043b\u0438 `off` - \u0420\u0430\u0441\u0448\u0438\u0440\u0435\u043d\u0438\u0435 \u0441\u043c\u0435\u0448\u0430\u043d\u043d\u044b\u0445 \u0441\u043b\u043e\u0432 \u043e\u0442\u043a\u043b\u044e\u0447\u0435\u043d\u043e (\u043f\u043e \u0443\u043c\u043e\u043b\u0447\u0430\u043d\u0438\u044e). \u0421\u043c\u0435\u0448\u0430\u043d\u043d\u044b\u0435 \u043a\u043b\u044e\u0447\u0435\u0432\u044b\u0435 \u0441\u043b\u043e\u0432\u0430 \u043e\u0431\u0440\u0430\u0431\u0430\u0442\u044b\u0432\u0430\u044e\u0442\u0441\u044f \u043e\u0431\u044b\u0447\u043d\u044b\u043c \u043e\u0431\u0440\u0430\u0437\u043e\u043c \u0431\u0435\u0437 \u0440\u0430\u0441\u0448\u0438\u0440\u0435\u043d\u0438\u044f.\n* `1` - \u0420\u0430\u0441\u0448\u0438\u0440\u0435\u043d\u0438\u0435 \u0441\u043c\u0435\u0448\u0430\u043d\u043d\u044b\u0445 \u0441\u043b\u043e\u0432 \u0432\u043a\u043b\u044e\u0447\u0435\u043d\u043e \u0438 \u0438\u0441\u043f\u043e\u043b\u044c\u0437\u0443\u0435\u0442 \u043d\u0430\u0441\u0442\u0440\u043e\u0439\u043a\u0443 [blend_mode](../Creating_a_table/NLP_and_tokenization/Low-level_tokenization.md#blend_mode) \u0442\u0430\u0431\u043b\u0438\u0446\u044b \u0434\u043b\u044f \u043e\u043f\u0440\u0435\u0434\u0435\u043b\u0435\u043d\u0438\u044f, \u043a\u0430\u043a\u0438\u0435 \u0432\u0430\u0440\u0438\u0430\u043d\u0442\u044b \u0433\u0435\u043d\u0435\u0440\u0438\u0440\u043e\u0432\u0430\u0442\u044c.\n* \u041b\u044e\u0431\u0430\u044f \u043e\u043f\u0446\u0438\u044f(\u0438) \u0440\u0435\u0436\u0438\u043c\u0430 \u0441\u043c\u0435\u0448\u0438\u0432\u0430\u043d\u0438\u044f - \u0420\u0430\u0441\u0448\u0438\u0440\u0435\u043d\u0438\u0435 \u0441\u043c\u0435\u0448\u0430\u043d\u043d\u044b\u0445 \u0441\u043b\u043e\u0432 \u0432\u043a\u043b\u044e\u0447\u0435\u043d\u043e \u0441 \u0443\u043a\u0430\u0437\u0430\u043d\u043d\u044b\u043c \u0440\u0435\u0436\u0438\u043c\u043e\u043c(\u0430\u043c\u0438) \u0441\u043c\u0435\u0448\u0438\u0432\u0430\u043d\u0438\u044f, \u043f\u0435\u0440\u0435\u043e\u043f\u0440\u0435\u0434\u0435\u043b\u044f\u044f \u043d\u0430\u0441\u0442\u0440\u043e\u0439\u043a\u0443 `blend_mode` \u0442\u0430\u0431\u043b\u0438\u0446\u044b.\n\n\u041f\u043e\u0434\u0440\u043e\u0431\u043d\u0435\u0435 \u043e\u0431 \u043e\u043f\u0446\u0438\u044f\u0445 \u0441\u043c. [blend_mode](../Creating_a_table/NLP_and_tokenization/Low-level_tokenization.md#blend_mode).\n\n### field_weights\n\u0418\u043c\u0435\u043d\u043e\u0432\u0430\u043d\u043d\u044b\u0439 \u0441\u043f\u0438\u0441\u043e\u043a \u0446\u0435\u043b\u044b\u0445 \u0447\u0438\u0441\u0435\u043b (\u043f\u043e\u043b\u044c\u0437\u043e\u0432\u0430\u0442\u0435\u043b\u044c\u0441\u043a\u0438\u0435 \u0432\u0435\u0441\u0430 \u043f\u043e \u043f\u043e\u043b\u044f\u043c \u0434\u043b\u044f \u0440\u0430\u043d\u0436\u0438\u0440\u043e\u0432\u0430\u043d\u0438\u044f).\n\n\u041f\u0440\u0438\u043c\u0435\u0440:\nCODE_BLOCK_8\n\n### global_idf\n\u0418\u0441\u043f\u043e\u043b\u044c\u0437\u043e\u0432\u0430\u0442\u044c \u0433\u043b\u043e\u0431\u0430\u043b\u044c\u043d\u0443\u044e \u0441\u0442\u0430\u0442\u0438\u0441\u0442\u0438\u043a\u0443 (\u0447\u0430\u0441\u0442\u043e\u0442\u044b) \u0438\u0437 \u0444\u0430\u0439\u043b\u0430 [global_idf](../Creating_a_table/NLP_and_tokenization/Low-level_tokenization.md#global_idf) \u0434\u043b\u044f \u0432\u044b\u0447\u0438\u0441\u043b\u0435\u043d\u0438\u0439 IDF.\n\n### idf\n\u0417\u0430\u043a\u043b\u044e\u0447\u0435\u043d\u043d\u044b\u0439 \u0432 \u043a\u0430\u0432\u044b\u0447\u043a\u0438 \u0441\u043f\u0438\u0441\u043e\u043a \u0444\u043b\u0430\u0433\u043e\u0432 \u0432\u044b\u0447\u0438\u0441\u043b\u0435\u043d\u0438\u044f IDF, \u0440\u0430\u0437\u0434\u0435\u043b\u0435\u043d\u043d\u044b\u0445 \u0437\u0430\u043f\u044f\u0442\u044b\u043c\u0438. \u0418\u0437\u0432\u0435\u0441\u0442\u043d\u044b\u0435 \u0444\u043b\u0430\u0433\u0438:\n\n* `normalized`: \u0432\u0430\u0440\u0438\u0430\u043d\u0442 BM25, idf = log((N-n+1)/n), \u0441\u043e\u0433\u043b\u0430\u0441\u043d\u043e Robertson et al\n* `plain`: \u043f\u0440\u043e\u0441\u0442\u043e\u0439 \u0432\u0430\u0440\u0438\u0430\u043d\u0442, idf = log(N/n), \u0441\u043e\u0433\u043b\u0430\u0441\u043d\u043e Sparck-Jones\n* `tfidf_normalized`: \u0434\u043e\u043f\u043e\u043b\u043d\u0438\u0442\u0435\u043b\u044c\u043d\u043e \u0434\u0435\u043b\u0438\u0442\u044c IDF \u043d\u0430 \u043a\u043e\u043b\u0438\u0447\u0435\u0441\u0442\u0432\u043e \u0441\u043b\u043e\u0432 \u0432 \u0437\u0430\u043f\u0440\u043e\u0441\u0435, \u0447\u0442\u043e\u0431\u044b `TF*IDF` \u043f\u043e\u043f\u0430\u0434\u0430\u043b \u0432 \u0434\u0438\u0430\u043f\u0430\u0437\u043e\u043d [0, 1]\n* `tfidf_unnormalized`: \u043d\u0435 \u0434\u0435\u043b\u0438\u0442\u044c \u0434\u043e\u043f\u043e\u043b\u043d\u0438\u0442\u0435\u043b\u044c\u043d\u043e IDF \u043d\u0430 \u043a\u043e\u043b\u0438\u0447\u0435\u0441\u0442\u0432\u043e \u0441\u043b\u043e\u0432 \u0432 \u0437\u0430\u043f\u0440\u043e\u0441\u0435, \u0433\u0434\u0435 N - \u0440\u0430\u0437\u043c\u0435\u0440 \u043a\u043e\u043b\u043b\u0435\u043a\u0446\u0438\u0438, \u0430 n - \u043a\u043e\u043b\u0438\u0447\u0435\u0441\u0442\u0432\u043e \u0441\u043e\u0432\u043f\u0430\u0434\u0430\u044e\u0449\u0438\u0445 \u0434\u043e\u043a\u0443\u043c\u0435\u043d\u0442\u043e\u0432\n\n\u0418\u0441\u0442\u043e\u0440\u0438\u0447\u0435\u0441\u043a\u0438 \u0438\u0441\u043f\u043e\u043b\u044c\u0437\u0443\u0435\u043c\u044b\u0439 \u043f\u043e \u0443\u043c\u043e\u043b\u0447\u0430\u043d\u0438\u044e IDF (\u043e\u0431\u0440\u0430\u0442\u043d\u0430\u044f \u0447\u0430\u0441\u0442\u043e\u0442\u0430 \u0434\u043e\u043a\u0443\u043c\u0435\u043d\u0442\u0430) \u0432 Manticore \u044d\u043a\u0432\u0438\u0432\u0430\u043b\u0435\u043d\u0442\u0435\u043d `OPTION idf='normalized,tfidf_normalized'`, \u0438 \u044d\u0442\u0438 \u043d\u043e\u0440\u043c\u0430\u043b\u0438\u0437\u0430\u0446\u0438\u0438 \u043c\u043e\u0433\u0443\u0442 \u0432\u044b\u0437\u044b\u0432\u0430\u0442\u044c \u043d\u0435\u0441\u043a\u043e\u043b\u044c\u043a\u043e \u043d\u0435\u0436\u0435\u043b\u0430\u0442\u0435\u043b\u044c\u043d\u044b\u0445 \u044d\u0444\u0444\u0435\u043a\u0442\u043e\u0432.\n\n\u0412\u043e-\u043f\u0435\u0440\u0432\u044b\u0445, `idf=normalized` \u043f\u0440\u0438\u0432\u043e\u0434\u0438\u0442 \u043a \u0448\u0442\u0440\u0430\u0444\u043e\u0432\u0430\u043d\u0438\u044e \u043a\u043b\u044e\u0447\u0435\u0432\u044b\u0445 \u0441\u043b\u043e\u0432. \u041d\u0430\u043f\u0440\u0438\u043c\u0435\u0440, \u0435\u0441\u043b\u0438 \u0432\u044b \u0438\u0449\u0435\u0442\u0435 `the | something` \u0438 `the` \u0432\u0441\u0442\u0440\u0435\u0447\u0430\u0435\u0442\u0441\u044f \u0431\u043e\u043b\u0435\u0435 \u0447\u0435\u043c \u0432 50% \u0434\u043e\u043a\u0443\u043c\u0435\u043d\u0442\u043e\u0432, \u0442\u043e \u0434\u043e\u043a\u0443\u043c\u0435\u043d\u0442\u044b \u0441 \u043e\u0431\u043e\u0438\u043c\u0438 \u043a\u043b\u044e\u0447\u0435\u0432\u044b\u043c\u0438 \u0441\u043b\u043e\u0432\u0430\u043c\u0438 `the` \u0438 `something` \u043f\u043e\u043b\u0443\u0447\u0430\u0442 \u043c\u0435\u043d\u044c\u0448\u0438\u0439 \u0432\u0435\u0441, \u0447\u0435\u043c \u0434\u043e\u043a\u0443\u043c\u0435\u043d\u0442\u044b \u0442\u043e\u043b\u044c\u043a\u043e \u0441 \u043e\u0434\u043d\u0438\u043c \u043a\u043b\u044e\u0447\u0435\u0432\u044b\u043c \u0441\u043b\u043e\u0432\u043e\u043c `something`. \u0418\u0441\u043f\u043e\u043b\u044c\u0437\u043e\u0432\u0430\u043d\u0438\u0435 `OPTION idf=plain` \u043f\u043e\u0437\u0432\u043e\u043b\u044f\u0435\u0442 \u0438\u0437\u0431\u0435\u0436\u0430\u0442\u044c \u044d\u0442\u043e\u0433\u043e. \u041f\u0440\u043e\u0441\u0442\u043e\u0439 IDF \u0432\u0430\u0440\u044c\u0438\u0440\u0443\u0435\u0442\u0441\u044f \u0432 \u0434\u0438\u0430\u043f\u0430\u0437\u043e\u043d\u0435 `[0, log(N)]`, \u0438 \u043a\u043b\u044e\u0447\u0435\u0432\u044b\u0435 \u0441\u043b\u043e\u0432\u0430 \u043d\u0438\u043a\u043e\u0433\u0434\u0430 \u043d\u0435 \u0448\u0442\u0440\u0430\u0444\u0443\u044e\u0442\u0441\u044f; \u0432 \u0442\u043e \u0432\u0440\u0435\u043c\u044f \u043a\u0430\u043a \u043d\u043e\u0440\u043c\u0430\u043b\u0438\u0437\u043e\u0432\u0430\u043d\u043d\u044b\u0439 IDF \u0432\u0430\u0440\u044c\u0438\u0440\u0443\u0435\u0442\u0441\u044f \u0432 \u0434\u0438\u0430\u043f\u0430\u0437\u043e\u043d\u0435 `[-log(N), log(N)]`, \u0438 \u0441\u043b\u0438\u0448\u043a\u043e\u043c \u0447\u0430\u0441\u0442\u044b\u0435 \u043a\u043b\u044e\u0447\u0435\u0432\u044b\u0435 \u0441\u043b\u043e\u0432\u0430 \u0448\u0442\u0440\u0430\u0444\u0443\u044e\u0442\u0441\u044f.\n\n\u0412\u043e-\u0432\u0442\u043e\u0440\u044b\u0445, `idf=tfidf_normalized` \u043f\u0440\u0438\u0432\u043e\u0434\u0438\u0442 \u043a \u0441\u043c\u0435\u0449\u0435\u043d\u0438\u044e IDF \u043c\u0435\u0436\u0434\u0443 \u0437\u0430\u043f\u0440\u043e\u0441\u0430\u043c\u0438. \u0418\u0441\u0442\u043e\u0440\u0438\u0447\u0435\u0441\u043a\u0438 IDF \u0442\u0430\u043a\u0436\u0435 \u0434\u0435\u043b\u0438\u043b\u0441\u044f \u043d\u0430 \u043a\u043e\u043b\u0438\u0447\u0435\u0441\u0442\u0432\u043e \u043a\u043b\u044e\u0447\u0435\u0432\u044b\u0445 \u0441\u043b\u043e\u0432 \u0432 \u0437\u0430\u043f\u0440\u043e\u0441\u0435, \u0433\u0430\u0440\u0430\u043d\u0442\u0438\u0440\u0443\u044f, \u0447\u0442\u043e \u0432\u0441\u044f `sum(tf*idf)` \u043f\u043e \u0432\u0441\u0435\u043c \u043a\u043b\u044e\u0447\u0435\u0432\u044b\u043c \u0441\u043b\u043e\u0432\u0430\u043c \u043e\u0441\u0442\u0430\u0435\u0442\u0441\u044f \u0432 \u043f\u0440\u0435\u0434\u0435\u043b\u0430\u0445 \u0434\u0438\u0430\u043f\u0430\u0437\u043e\u043d\u0430 [0,1]. \u041e\u0434\u043d\u0430\u043a\u043e \u044d\u0442\u043e \u043e\u0437\u043d\u0430\u0447\u0430\u043b\u043e, \u0447\u0442\u043e \u0437\u0430\u043f\u0440\u043e\u0441\u044b \u0442\u0438\u043f\u0430 `word1` \u0438 `word1 | nonmatchingword2` \u043f\u0440\u0438\u0441\u0432\u0430\u0438\u0432\u0430\u043b\u0438 \u0440\u0430\u0437\u043d\u044b\u0435 \u0432\u0435\u0441\u0430 \u043e\u0434\u043d\u043e\u043c\u0443 \u0438 \u0442\u043e\u043c\u0443 \u0436\u0435 \u043d\u0430\u0431\u043e\u0440\u0443 \u0440\u0435\u0437\u0443\u043b\u044c\u0442\u0430\u0442\u043e\u0432, \u043f\u043e\u0441\u043a\u043e\u043b\u044c\u043a\u0443 IDF \u043a\u0430\u043a \u0434\u043b\u044f `word1`, \u0442\u0430\u043a \u0438 \u0434\u043b\u044f `nonmatchingword2` \u0434\u0435\u043b\u0438\u043b\u0438\u0441\u044c \u043d\u0430 2. \u0418\u0441\u043f\u043e\u043b\u044c\u0437\u043e\u0432\u0430\u043d\u0438\u0435 `OPTION idf='tfidf_unnormalized'` \u0440\u0435\u0448\u0430\u0435\u0442 \u044d\u0442\u0443 \u043f\u0440\u043e\u0431\u043b\u0435\u043c\u0443. \u0418\u043c\u0435\u0439\u0442\u0435 \u0432 \u0432\u0438\u0434\u0443, \u0447\u0442\u043e \u0444\u0430\u043a\u0442\u043e\u0440\u044b \u0440\u0430\u043d\u0436\u0438\u0440\u043e\u0432\u0430\u043d\u0438\u044f BM25, BM25A, BM25F() \u0431\u0443\u0434\u0443\u0442 \u0441\u043e\u043e\u0442\u0432\u0435\u0442\u0441\u0442\u0432\u0443\u044e\u0449\u0438\u043c \u043e\u0431\u0440\u0430\u0437\u043e\u043c \u0441\u043a\u043e\u0440\u0440\u0435\u043a\u0442\u0438\u0440\u043e\u0432\u0430\u043d\u044b \u043f\u0440\u0438 \u043e\u0442\u043a\u043b\u044e\u0447\u0435\u043d\u0438\u0438 \u044d\u0442\u043e\u0439 \u043d\u043e\u0440\u043c\u0430\u043b\u0438\u0437\u0430\u0446\u0438\u0438.\n\n\u0424\u043b\u0430\u0433\u0438 IDF \u043c\u043e\u0436\u043d\u043e \u043a\u043e\u043c\u0431\u0438\u043d\u0438\u0440\u043e\u0432\u0430\u0442\u044c; `plain` \u0438 `normalized` \u044f\u0432\u043b\u044f\u044e\u0442\u0441\u044f \u0432\u0437\u0430\u0438\u043c\u043e\u0438\u0441\u043a\u043b\u044e\u0447\u0430\u044e\u0449\u0438\u043c\u0438; `tfidf_unnormalized` \u0438 `tfidf_normalized` \u0442\u0430\u043a\u0436\u0435 \u044f\u0432\u043b\u044f\u044e\u0442\u0441\u044f \u0432\u0437\u0430\u0438\u043c\u043e\u0438\u0441\u043a\u043b\u044e\u0447\u0430\u044e\u0449\u0438\u043c\u0438; \u0438 \u043d\u0435\u0443\u043a\u0430\u0437\u0430\u043d\u043d\u044b\u0435 \u0444\u043b\u0430\u0433\u0438 \u0432 \u0442\u0430\u043a\u0438\u0445 \u0432\u0437\u0430\u0438\u043c\u043e\u0438\u0441\u043a\u043b\u044e\u0447\u0430\u044e\u0449\u0438\u0445 \u0433\u0440\u0443\u043f\u043f\u0430\u0445 \u043f\u043e \u0443\u043c\u043e\u043b\u0447\u0430\u043d\u0438\u044e \u0441\u043e\u0445\u0440\u0430\u043d\u044f\u044e\u0442 \u0441\u0432\u043e\u0438 \u0438\u0441\u0445\u043e\u0434\u043d\u044b\u0435 \u043d\u0430\u0441\u0442\u0440\u043e\u0439\u043a\u0438. \u042d\u0442\u043e \u043e\u0437\u043d\u0430\u0447\u0430\u0435\u0442, \u0447\u0442\u043e `OPTION idf=plain` \u044d\u043a\u0432\u0438\u0432\u0430\u043b\u0435\u043d\u0442\u043d\u043e \u043f\u043e\u043b\u043d\u043e\u043c\u0443 \u0443\u043a\u0430\u0437\u0430\u043d\u0438\u044e `OPTION idf='plain,tfidf_normalized'`.\n\n### jieba_mode\n\u041e\u043f\u0440\u0435\u0434\u0435\u043b\u044f\u0435\u0442 \u0440\u0435\u0436\u0438\u043c \u0441\u0435\u0433\u043c\u0435\u043d\u0442\u0430\u0446\u0438\u0438 Jieba \u0434\u043b\u044f \u0437\u0430\u043f\u0440\u043e\u0441\u0430.\n\n\u041f\u0440\u0438 \u0438\u0441\u043f\u043e\u043b\u044c\u0437\u043e\u0432\u0430\u043d\u0438\u0438 \u043a\u0438\u0442\u0430\u0439\u0441\u043a\u043e\u0439 \u0441\u0435\u0433\u043c\u0435\u043d\u0442\u0430\u0446\u0438\u0438 Jieba \u0438\u043d\u043e\u0433\u0434\u0430 \u043c\u043e\u0436\u0435\u0442 \u0431\u044b\u0442\u044c \u043f\u043e\u043b\u0435\u0437\u043d\u043e \u0438\u0441\u043f\u043e\u043b\u044c\u0437\u043e\u0432\u0430\u0442\u044c \u0440\u0430\u0437\u043d\u044b\u0435 \u0440\u0435\u0436\u0438\u043c\u044b \u0441\u0435\u0433\u043c\u0435\u043d\u0442\u0430\u0446\u0438\u0438 \u0434\u043b\u044f \u0442\u043e\u043a\u0435\u043d\u0438\u0437\u0430\u0446\u0438\u0438 \u0434\u043e\u043a\u0443\u043c\u0435\u043d\u0442\u043e\u0432 \u0438 \u0437\u0430\u043f\u0440\u043e\u0441\u0430. \u041f\u043e\u043b\u043d\u044b\u0439 \u0441\u043f\u0438\u0441\u043e\u043a \u0440\u0435\u0436\u0438\u043c\u043e\u0432 \u0441\u043c. \u0432 [jieba_mode](../Creating_a_table/NLP_and_tokenization/Morphology.md#jieba_mode).\n\n### index_weights\n\u0418\u043c\u0435\u043d\u043e\u0432\u0430\u043d\u043d\u044b\u0439 \u0441\u043f\u0438\u0441\u043e\u043a \u0446\u0435\u043b\u044b\u0445 \u0447\u0438\u0441\u0435\u043b. \u041f\u043e\u043b\u044c\u0437\u043e\u0432\u0430\u0442\u0435\u043b\u044c\u0441\u043a\u0438\u0435 \u0432\u0435\u0441\u0430 \u043f\u043e \u0442\u0430\u0431\u043b\u0438\u0446\u0430\u043c \u0434\u043b\u044f \u0440\u0430\u043d\u0436\u0438\u0440\u043e\u0432\u0430\u043d\u0438\u044f.\n\n### local_df\n`0` \u0438\u043b\u0438 `1`, \u0430\u0432\u0442\u043e\u043c\u0430\u0442\u0438\u0447\u0435\u0441\u043a\u0438 \u0441\u0443\u043c\u043c\u0438\u0440\u043e\u0432\u0430\u0442\u044c DF \u043f\u043e \u0432\u0441\u0435\u043c \u043b\u043e\u043a\u0430\u043b\u044c\u043d\u044b\u043c \u0447\u0430\u0441\u0442\u044f\u043c \u0440\u0430\u0441\u043f\u0440\u0435\u0434\u0435\u043b\u0435\u043d\u043d\u043e\u0439 \u0442\u0430\u0431\u043b\u0438\u0446\u044b, \u043e\u0431\u0435\u0441\u043f\u0435\u0447\u0438\u0432\u0430\u044f \u0441\u043e\u0433\u043b\u0430\u0441\u043e\u0432\u0430\u043d\u043d\u044b\u0435 (\u0438 \u0442\u043e\u0447\u043d\u044b\u0435) IDF \u0434\u043b\u044f \u043b\u043e\u043a\u0430\u043b\u044c\u043d\u043e \u0448\u0430\u0440\u0434\u0438\u0440\u043e\u0432\u0430\u043d\u043d\u043e\u0439 \u0442\u0430\u0431\u043b\u0438\u0446\u044b. \u041f\u043e \u0443\u043c\u043e\u043b\u0447\u0430\u043d\u0438\u044e \u0432\u043a\u043b\u044e\u0447\u0435\u043d\u043e \u0434\u043b\u044f \u0434\u0438\u0441\u043a\u043e\u0432\u044b\u0445 \u0447\u0430\u043d\u043a\u043e\u0432 RT-\u0442\u0430\u0431\u043b\u0438\u0446\u044b. \u0422\u0435\u0440\u043c\u0438\u043d\u044b \u0437\u0430\u043f\u0440\u043e\u0441\u0430 \u0441 \u043f\u043e\u0434\u0441\u0442\u0430\u043d\u043e\u0432\u043e\u0447\u043d\u044b\u043c\u0438 \u0437\u043d\u0430\u043a\u0430\u043c\u0438 \u0438\u0433\u043d\u043e\u0440\u0438\u0440\u0443\u044e\u0442\u0441\u044f.\n\n### low_priority\n`0` \u0438\u043b\u0438 `1` (\u043f\u043e \u0443\u043c\u043e\u043b\u0447\u0430\u043d\u0438\u044e `0`). \u0423\u0441\u0442\u0430\u043d\u043e\u0432\u043a\u0430 `low_priority=1` \u0432\u044b\u043f\u043e\u043b\u043d\u044f\u0435\u0442 \u0437\u0430\u043f\u0440\u043e\u0441 \u0441 \u0431\u043e\u043b\u0435\u0435 \u043d\u0438\u0437\u043a\u0438\u043c \u043f\u0440\u0438\u043e\u0440\u0438\u0442\u0435\u0442\u043e\u043c, \u043f\u0435\u0440\u0435\u043f\u043b\u0430\u043d\u0438\u0440\u0443\u044f \u0435\u0433\u043e \u0437\u0430\u0434\u0430\u0447\u0438 \u0432 10 \u0440\u0430\u0437 \u0440\u0435\u0436\u0435, \u0447\u0435\u043c \u0434\u0440\u0443\u0433\u0438\u0435 \u0437\u0430\u043f\u0440\u043e\u0441\u044b \u0441 \u043e\u0431\u044b\u0447\u043d\u044b\u043c \u043f\u0440\u0438\u043e\u0440\u0438\u0442\u0435\u0442\u043e\u043c.\n\n### max_matches\n\u0426\u0435\u043b\u043e\u0435 \u0447\u0438\u0441\u043b\u043e. \u0417\u043d\u0430\u0447\u0435\u043d\u0438\u0435 \u043c\u0430\u043a\u0441\u0438\u043c\u0430\u043b\u044c\u043d\u043e\u0433\u043e \u043a\u043e\u043b\u0438\u0447\u0435\u0441\u0442\u0432\u0430 \u0441\u043e\u0432\u043f\u0430\u0434\u0435\u043d\u0438\u0439 \u043d\u0430 \u0437\u0430\u043f\u0440\u043e\u0441.\n\n\u041c\u0430\u043a\u0441\u0438\u043c\u0430\u043b\u044c\u043d\u043e\u0435 \u043a\u043e\u043b\u0438\u0447\u0435\u0441\u0442\u0432\u043e \u0441\u043e\u0432\u043f\u0430\u0434\u0435\u043d\u0438\u0439, \u043a\u043e\u0442\u043e\u0440\u043e\u0435 \u0441\u0435\u0440\u0432\u0435\u0440 \u0445\u0440\u0430\u043d\u0438\u0442 \u0432 \u043e\u043f\u0435\u0440\u0430\u0442\u0438\u0432\u043d\u043e\u0439 \u043f\u0430\u043c\u044f\u0442\u0438 \u0434\u043b\u044f \u043a\u0430\u0436\u0434\u043e\u0439 \u0442\u0430\u0431\u043b\u0438\u0446\u044b \u0438 \u043c\u043e\u0436\u0435\u0442 \u0432\u0435\u0440\u043d\u0443\u0442\u044c \u043a\u043b\u0438\u0435\u043d\u0442\u0443. \u041f\u043e \u0443\u043c\u043e\u043b\u0447\u0430\u043d\u0438\u044e \u0440\u0430\u0432\u043d\u043e 1000.\n\n\u0412\u0432\u0435\u0434\u0435\u043d\u043d\u0430\u044f \u0434\u043b\u044f \u043a\u043e\u043d\u0442\u0440\u043e\u043b\u044f \u0438 \u043e\u0433\u0440\u0430\u043d\u0438\u0447\u0435\u043d\u0438\u044f \u0438\u0441\u043f\u043e\u043b\u044c\u0437\u043e\u0432\u0430\u043d\u0438\u044f \u043e\u043f\u0435\u0440\u0430\u0442\u0438\u0432\u043d\u043e\u0439 \u043f\u0430\u043c\u044f\u0442\u0438, \u043d\u0430\u0441\u0442\u0440\u043e\u0439\u043a\u0430 `max_matches` \u043e\u043f\u0440\u0435\u0434\u0435\u043b\u044f\u0435\u0442, \u0441\u043a\u043e\u043b\u044c\u043a\u043e \u0441\u043e\u0432\u043f\u0430\u0434\u0435\u043d\u0438\u0439 \u0431\u0443\u0434\u0435\u0442 \u0445\u0440\u0430\u043d\u0438\u0442\u044c\u0441\u044f \u0432 \u043e\u043f\u0435\u0440\u0430\u0442\u0438\u0432\u043d\u043e\u0439 \u043f\u0430\u043c\u044f\u0442\u0438 \u043f\u0440\u0438 \u043f\u043e\u0438\u0441\u043a\u0435 \u043f\u043e \u043a\u0430\u0436\u0434\u043e\u0439 \u0442\u0430\u0431\u043b\u0438\u0446\u0435. \u041a\u0430\u0436\u0434\u043e\u0435 \u043d\u0430\u0439\u0434\u0435\u043d\u043d\u043e\u0435 \u0441\u043e\u0432\u043f\u0430\u0434\u0435\u043d\u0438\u0435 \u0432\u0441\u0435 \u0440\u0430\u0432\u043d\u043e \u043e\u0431\u0440\u0430\u0431\u0430\u0442\u044b\u0432\u0430\u0435\u0442\u0441\u044f, \u043d\u043e \u0442\u043e\u043b\u044c\u043a\u043e \u043b\u0443\u0447\u0448\u0438\u0435 N \u0438\u0437 \u043d\u0438\u0445 \u0431\u0443\u0434\u0443\u0442 \u0441\u043e\u0445\u0440\u0430\u043d\u0435\u043d\u044b \u0432 \u043f\u0430\u043c\u044f\u0442\u0438 \u0438 \u0432 \u043a\u043e\u043d\u0435\u0447\u043d\u043e\u043c \u0438\u0442\u043e\u0433\u0435 \u0432\u043e\u0437\u0432\u0440\u0430\u0449\u0435\u043d\u044b \u043a\u043b\u0438\u0435\u043d\u0442\u0443. \u041d\u0430\u043f\u0440\u0438\u043c\u0435\u0440, \u043f\u0440\u0435\u0434\u043f\u043e\u043b\u043e\u0436\u0438\u043c, \u0447\u0442\u043e \u0442\u0430\u0431\u043b\u0438\u0446\u0430 \u0441\u043e\u0434\u0435\u0440\u0436\u0438\u0442 2 000 000 \u0441\u043e\u0432\u043f\u0430\u0434\u0435\u043d\u0438\u0439 \u0434\u043b\u044f \u0437\u0430\u043f\u0440\u043e\u0441\u0430. \u0420\u0435\u0434\u043a\u043e \u0432\u043e\u0437\u043d\u0438\u043a\u0430\u0435\u0442 \u043d\u0435\u043e\u0431\u0445\u043e\u0434\u0438\u043c\u043e\u0441\u0442\u044c \u043f\u043e\u043b\u0443\u0447\u0438\u0442\u044c \u0438\u0445 \u0432\u0441\u0435. \u0412\u043c\u0435\u0441\u0442\u043e \u044d\u0442\u043e\u0433\u043e \u0432\u0430\u043c \u043d\u0443\u0436\u043d\u043e \u043f\u0440\u043e\u0441\u043a\u0430\u043d\u0438\u0440\u043e\u0432\u0430\u0442\u044c \u0438\u0445 \u0432\u0441\u0435, \u043d\u043e \u0432\u044b\u0431\u0440\u0430\u0442\u044c \u0442\u043e\u043b\u044c\u043a\u043e \"\u043b\u0443\u0447\u0448\u0438\u0435\" 500, \u043d\u0430\u043f\u0440\u0438\u043c\u0435\u0440, \u043d\u0430 \u043e\u0441\u043d\u043e\u0432\u0435 \u043d\u0435\u043a\u043e\u0442\u043e\u0440\u044b\u0445 \u043a\u0440\u0438\u0442\u0435\u0440\u0438\u0435\u0432 (\u043d\u0430\u043f\u0440\u0438\u043c\u0435\u0440, \u043e\u0442\u0441\u043e\u0440\u0442\u0438\u0440\u043e\u0432\u0430\u043d\u043d\u044b\u0445 \u043f\u043e \u0440\u0435\u043b\u0435\u0432\u0430\u043d\u0442\u043d\u043e\u0441\u0442\u0438, \u0446\u0435\u043d\u0435 \u0438\u043b\u0438 \u0434\u0440\u0443\u0433\u0438\u043c \u0444\u0430\u043a\u0442\u043e\u0440\u0430\u043c) \u0438 \u043e\u0442\u043e\u0431\u0440\u0430\u0437\u0438\u0442\u044c \u044d\u0442\u0438 500 \u0441\u043e\u0432\u043f\u0430\u0434\u0435\u043d\u0438\u0439 \u043a\u043e\u043d\u0435\u0447\u043d\u043e\u043c\u0443 \u043f\u043e\u043b\u044c\u0437\u043e\u0432\u0430\u0442\u0435\u043b\u044e \u0441\u0442\u0440\u0430\u043d\u0438\u0446\u0430\u043c\u0438 \u043f\u043e 20-100 \u0441\u043e\u0432\u043f\u0430\u0434\u0435\u043d\u0438\u0439. \u041e\u0442\u0441\u043b\u0435\u0436\u0438\u0432\u0430\u043d\u0438\u0435 \u0442\u043e\u043b\u044c\u043a\u043e \u043b\u0443\u0447\u0448\u0438\u0445 500 \u0441\u043e\u0432\u043f\u0430\u0434\u0435\u043d\u0438\u0439 \u0433\u043e\u0440\u0430\u0437\u0434\u043e \u044d\u0444\u0444\u0435\u043a\u0442\u0438\u0432\u043d\u0435\u0435 \u043f\u043e \u0438\u0441\u043f\u043e\u043b\u044c\u0437\u043e\u0432\u0430\u043d\u0438\u044e \u043e\u043f\u0435\u0440\u0430\u0442\u0438\u0432\u043d\u043e\u0439 \u043f\u0430\u043c\u044f\u0442\u0438 \u0438 \u043f\u0440\u043e\u0446\u0435\u0441\u0441\u043e\u0440\u0430, \u0447\u0435\u043c \u0445\u0440\u0430\u043d\u0435\u043d\u0438\u0435 \u0432\u0441\u0435\u0445 2 000 000 \u0441\u043e\u0432\u043f\u0430\u0434\u0435\u043d\u0438\u0439, \u0438\u0445 \u0441\u043e\u0440\u0442\u0438\u0440\u043e\u0432\u043a\u0430, \u0430 \u0437\u0430\u0442\u0435\u043c \u043e\u0442\u0431\u0440\u0430\u0441\u044b\u0432\u0430\u043d\u0438\u0435 \u0432\u0441\u0435\u0433\u043e, \u043a\u0440\u043e\u043c\u0435 \u043f\u0435\u0440\u0432\u044b\u0445 20, \u043d\u0435\u043e\u0431\u0445\u043e\u0434\u0438\u043c\u044b\u0445 \u0434\u043b\u044f \u0441\u0442\u0440\u0430\u043d\u0438\u0446\u044b \u0440\u0435\u0437\u0443\u043b\u044c\u0442\u0430\u0442\u043e\u0432 \u043f\u043e\u0438\u0441\u043a\u0430. `max_matches` \u043a\u043e\u043d\u0442\u0440\u043e\u043b\u0438\u0440\u0443\u0435\u0442 N \u0432 \u044d\u0442\u043e\u043c \u043a\u043e\u043b\u0438\u0447\u0435\u0441\u0442\u0432\u0435 \"\u043b\u0443\u0447\u0448\u0438\u0445 N\"."
        },
        "is_code_or_comment": false,
        "model": "deepseek/deepseek-v3.2",
        "updated_at": 1768542001
    }
}