# Multi process search performance **URL:** \ **Category:** Elasticsearch\ **Created:** [April 8, 2020, 10:52am UTC](https://discuss.elastic.co/t/multi-process-search-performance/227103 "2020-04-08T10:52:46Z")\ **Posts on this page:** 2\ **Page:** 1
**Author:** ![Sunho\_Lee](https://sea2.discourse-cdn.com/elastic/user_avatar/discuss.elastic.co/sunho_lee/32/65911_2.png) [@Sunho\_Lee](https://discuss.elastic.co/u/Sunho_Lee)\ **Post date:** [April 8, 2020, 10:52am UTC](https://discuss.elastic.co/t/multi-process-search-performance/227103/1 "2020-04-08T10:52:46Z")
Hi everybody. I have strange results that multi-process search too slow. I have tested that 35 billion documents in 1 index vs 3.5 billion documents in 10 index. I used 7.6 version elasticsearch. and 2 data nodes (52 core, 62GB memory). 1. search query to 35 billion document index(50 shards) 2. search query to 3.5 billion documents in 10 index(5 shards per index) by a comma-separated like ["index\_A", "index\_B", ...] 3. search query to 3.5 billion documents in 10 index(5 shards per index) by python client with pool.starmap() using 10 processes. each process query to each index I expected the 3rd result to be ten times better than the 1st result. because of the smaller is faster. but the three results almost the same. I can't understand that result. 1. Can you explain why this happens? 2. I profiled the API. 'build\_scorer' used almost elapsed time. as the number of processes increased, the 'build\_scorer' also increased at 3rd experiment. why? ---
**Author:** ![system](https://us1.discourse-cdn.com/elastic/original/3X/1/a/1ac57faf039f6b580b3f104ef42a2a89e41014de.png) [@system](https://discuss.elastic.co/u/system)\ **Post date:** [May 6, 2020, 10:52am UTC](https://discuss.elastic.co/t/multi-process-search-performance/227103/2 "2020-05-06T10:52:48Z")
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