# Slow queries (fuzzy) - how to disable score calculation **URL:** \ **Category:** Elasticsearch\ **Created:** [October 16, 2022, 6:52pm UTC](https://discuss.elastic.co/t/slow-queries-fuzzy-how-to-disable-score-calculation/316711 "2022-10-16T18:52:01Z")\ **Posts on this page:** 2\ **Page:** 1
**Author:** ![Giorgos\_Katiforis](https://sea2.discourse-cdn.com/elastic/user_avatar/discuss.elastic.co/giorgos_katiforis/32/100083_2.png) [@Giorgos\_Katiforis](https://discuss.elastic.co/u/Giorgos_Katiforis)\ **Post date:** [October 16, 2022, 6:52pm UTC](https://discuss.elastic.co/t/slow-queries-fuzzy-how-to-disable-score-calculation/316711/1 "2022-10-16T18:52:01Z")
The query has several `match` conditions with `fuzziness 2`, which makes it quite expensive. I don't want to search for document relevance or any kind of scoring, just identify the list of document IDs that match the query criteria. A simplified version of a query is: ```auto { "profile": true, "sort": "_doc", "query": { "constant_score": { "filter": { "bool": { "filter": [ { "bool": { "should": [ { "match": { "namesCombined": { "query": "name1 name2 name3", "operator": "AND", "fuzziness": "2", "fuzzy_rewrite": "constant_score" } } }, { "match": { "namesCombined": { "query": "name1", "operator": "AND", "fuzziness": "2", "fuzzy_rewrite": "constant_score" } } } ], "minimum_should_match": "1" } } ] } }, "boost": 1.0 } }, "_source": { "includes": [ "id" ], "excludes": [] } } ``` The above query takes **5ms** to execute (when the documents are matched) in an index of 2 documents total, which is a long time for such a simple query. After analyzing with profile API seems that the `build_scorer` takes **3.8ms**. Even though I use` bool filter`,` constant_score` queries, and `"fuzzy_rewrite":"constant_score"`, the score calculation slows down the search process. I also noticed that if I use the default rewite method instead of `"fuzzy_rewrite":"constant_score"` the `rewrite_time` increases to **3ms** and the `build_scorer` remains low. Is it possible to disable the scoring or improve the performance? Any advice or suggestion would be appreciated. Profiler results: ```auto { "profile": { "shards": [ { "id": "[v1VNjaOiQrqkDPKg4aTVfA][testindex][0]", "searches": [ { "query": [ { "type": "ConstantScoreQuery", "description": "ConstantScore(((+namesCombined:NICKOLAS~2 +namesCombined:JACK~2 +namesCombined:DOE~2) namesCombined:JACKDOE~2)~1)", "time_in_nanos": 3902030, "breakdown": { "set_min_competitive_score_count": 0, "match_count": 0, "shallow_advance_count": 0, "set_min_competitive_score": 0, "next_doc": 6278, "match": 0, "next_doc_count": 10, "score_count": 0, "compute_max_score_count": 0, "compute_max_score": 0, "advance": 9500, "advance_count": 2, "score": 0, "build_scorer_count": 4, "create_weight": 4852, "shallow_advance": 0, "create_weight_count": 1, "build_scorer": 3881400 }, "children": [ { "type": "BooleanQuery", "description": "((+namesCombined:NICKOLAS~2 +namesCombined:JACK~2 +namesCombined:DOE~2) namesCombined:JACKDOE~2)~1", "time_in_nanos": 3899555, "breakdown": { "set_min_competitive_score_count": 0, "match_count": 0, "shallow_advance_count": 0, "set_min_competitive_score": 0, "next_doc": 5909, "match": 0, "next_doc_count": 10, "score_count": 0, "compute_max_score_count": 0, "compute_max_score": 0, "advance": 9411, "advance_count": 2, "score": 0, "build_scorer_count": 4, "create_weight": 3493, "shallow_advance": 0, "create_weight_count": 1, "build_scorer": 3880742 }, "children": [ { "type": "BooleanQuery", "description": "+namesCombined:NICKOLAS~2 +namesCombined:JACK~2 +namesCombined:DOE~2", "time_in_nanos": 2702444, "breakdown": { "set_min_competitive_score_count": 0, "match_count": 0, "shallow_advance_count": 0, "set_min_competitive_score": 0, "next_doc": 5518, "match": 0, "next_doc_count": 10, "score_count": 0, "compute_max_score_count": 0, "compute_max_score": 0, "advance": 9329, "advance_count": 2, "score": 0, "build_scorer_count": 6, "create_weight": 2024, "shallow_advance": 0, "create_weight_count": 1, "build_scorer": 2685573 }, "children": [ { "type": "MultiTermQueryConstantScoreWrapper", "description": "namesCombined:NICKOLAS~2", "time_in_nanos": 1719693, "breakdown": { "set_min_competitive_score_count": 0, "match_count": 0, "shallow_advance_count": 0, "set_min_competitive_score": 0, "next_doc": 0, "match": 0, "next_doc_count": 0, "score_count": 0, "compute_max_score_count": 0, "compute_max_score": 0, "advance": 4243, "advance_count": 12, "score": 0, "build_scorer_count": 6, "create_weight": 334, "shallow_advance": 0, "create_weight_count": 1, "build_scorer": 1715116 } }, { "type": "MultiTermQueryConstantScoreWrapper", "description": "namesCombined:JACK~2", "time_in_nanos": 543438, "breakdown": { "set_min_competitive_score_count": 0, "match_count": 0, "shallow_advance_count": 0, "set_min_competitive_score": 0, "next_doc": 810, "match": 0, "next_doc_count": 10, "score_count": 0, "compute_max_score_count": 0, "compute_max_score": 0, "advance": 3695, "advance_count": 2, "score": 0, "build_scorer_count": 6, "create_weight": 20, "shallow_advance": 0, "create_weight_count": 1, "build_scorer": 538913 } }, { "type": "MultiTermQueryConstantScoreWrapper", "description": "namesCombined:DOE~2", "time_in_nanos": 416365, "breakdown": { "set_min_competitive_score_count": 0, "match_count": 0, "shallow_advance_count": 0, "set_min_competitive_score": 0, "next_doc": 0, "match": 0, "next_doc_count": 0, "score_count": 0, "compute_max_score_count": 0, "compute_max_score": 0, "advance": 3024, "advance_count": 12, "score": 0, "build_scorer_count": 6, "create_weight": 20, "shallow_advance": 0, "create_weight_count": 1, "build_scorer": 413321 } } ] }, { "type": "MultiTermQueryConstantScoreWrapper", "description": "namesCombined:JACKDOE~2", "time_in_nanos": 1187767, "breakdown": { "set_min_competitive_score_count": 0, "match_count": 0, "shallow_advance_count": 0, "set_min_competitive_score": 0, "next_doc": 0, "match": 0, "next_doc_count": 0, "score_count": 0, "compute_max_score_count": 0, "compute_max_score": 0, "advance": 0, "advance_count": 0, "score": 0, "build_scorer_count": 2, "create_weight": 19, "shallow_advance": 0, "create_weight_count": 1, "build_scorer": 1187748 } } ] } ] } ], "rewrite_time": 28163, "collector": [ { "name": "SimpleFieldCollector", "reason": "search_top_hits", "time_in_nanos": 75426 } ] } ], "aggregations": [] } ] } } ``` A sample document: `{"id":"id","namesCombined":"name1 name2 name3"}` Index settings and mapping: ```auto { "settings": { "index": { "number_of_shards": 1, "number_of_replicas": 0, "store.type": "mmapfs", "refresh_interval": "300s" } }, "mappings": { "namesCombined": { "type": "text", "analyzer": "whitespace", "doc_values": false, "index_options": "docs", "norms": false, "store": false, "term_vector": "no" } } } ``` ---
**Author:** ![system](https://us1.discourse-cdn.com/elastic/original/3X/1/a/1ac57faf039f6b580b3f104ef42a2a89e41014de.png) [@system](https://discuss.elastic.co/u/system)\ **Post date:** [November 13, 2022, 6:52pm UTC](https://discuss.elastic.co/t/slow-queries-fuzzy-how-to-disable-score-calculation/316711/2 "2022-11-13T18:52:19Z")
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