aderm opened a new issue #4291: Improve ES query performance
URL: https://github.com/apache/skywalking/issues/4291
 
 
   Please answer these questions before submitting your issue.
   
   - Why do you submit this issue?
   - [ ] Question or discussion
   - [ ] Bug
   - [ ] Requirement
   - [x] Feature or performance improvement
   
   ___
   ### Question
   - What do you want to know?
   
   ___
   ### Bug
   - Which version of SkyWalking, OS and JRE?
   
   - Which company or project?
   
   - What happen?
   If possible, provide a way for reproducing the error. e.g. demo application, 
component version.
   
   ___
   ### Requirement or improvement
   - Please describe about your requirements or improvement suggestions.
   We can use the 'qool bool filter' statement to replace the normal query of 
'qool bool'.
   There are two benefits:
   1.No scoring calculation is needed to speed up the calculation;
   2. Filter query can make full use of the cache and improve the time of 
repeated sub-query
   
   Take the query interface `MetadataQueryEsDAO#getAllServices` as an example:
   
   - ES query dsl:
   
   
`{"size":5000,"query":{"bool":{"must":[{"bool":{"should":[{"bool":{"must":[{"range":{"heartbeat_time":{"from":1580292720000,"to":null,"include_lower":true,"include_upper":true,"boost":1.0}}},{"range":{"register_time":{"from":null,"to":1580292720000,"include_lower":true,"include_upper":true,"boost":1.0}}}],"adjust_pure_negative":true,"boost":1.0}},{"bool":{"must":[{"range":{"register_time":{"from":null,"to":1580292720000,"include_lower":true,"include_upper":true,"boost":1.0}}},{"range":{"heartbeat_time":{"from":1580291760000,"to":null,"include_lower":true,"include_upper":true,"boost":1.0}}}],"adjust_pure_negative":true,"boost":1.0}}],"adjust_pure_negative":true,"boost":1.0}},{"term":{"is_address":{"value":0,"boost":1.0}}},{"term":{"node_type":{"value":0,"boost":1.0}}}],"adjust_pure_negative":true,"boost":1.0}}}`
   
   - and result:
   
`{"took":0,"timed_out":false,"_shards":{"total":2,"successful":2,"skipped":0,"failed":0},"hits":{"total":{"value":1,"relation":"eq"},**"max_score":6.0**,"hits":[{"_index":"service_inventory","_type":"_doc","_id":"Your_ApplicationName_0_0",**"_score":6.0**,"_source":{"sequence":2,"last_update_time":1580287478790,"heartbeat_time":1580292752350,"node_type":0,"name":"Your_ApplicationName","address_id":0,"is_address":0,"mapping_service_id":0,"register_time":1580287478790,"properties":"{}"}}]}}`
   In the results, we see that the search engine scored:`max_score:6.0`.
   
   When improvements are made:
   
   - ES query dsl:
   
   
`{"size":5000,"query":{"bool":{"**filter**":[{"bool":{"must":[{"bool":{"should":[{"bool":{"must":[{"range":{"heartbeat_time":{"from":1580293080000,"to":null,"include_lower":true,"include_upper":true,"boost":1.0}}},{"range":{"register_time":{"from":null,"to":1580293080000,"include_lower":true,"include_upper":true,"boost":1.0}}}],"adjust_pure_negative":true,"boost":1.0}},{"bool":{"must":[{"range":{"register_time":{"from":null,"to":1580293080000,"include_lower":true,"include_upper":true,"boost":1.0}}},{"range":{"heartbeat_time":{"from":1580292120000,"to":null,"include_lower":true,"include_upper":true,"boost":1.0}}}],"adjust_pure_negative":true,"boost":1.0}}],"adjust_pure_negative":true,"boost":1.0}},{"term":{"is_address":{"value":0,"boost":1.0}}},{"term":{"node_type":{"value":0,"boost":1.0}}}],"adjust_pure_negative":true,"boost":1.0}}],"adjust_pure_negative":true,"boost":1.0}}}`
   
   - and result:
   
   
`{"took":0,"timed_out":false,"_shards":{"total":2,"successful":2,"skipped":0,"failed":0},"hits":{"total":{"value":1,"relation":"eq"},**"max_score":0.0**,"hits":[{"_index":"service_inventory","_type":"_doc","_id":"Your_ApplicationName_0_0",**"_score":0.0**,"_source":{"sequence":2,"last_update_time":1580287478790,"heartbeat_time":1580293072125,"node_type":0,"name":"Your_ApplicationName","address_id":0,"is_address":0,"mapping_service_id":0,"register_time":1580287478790,"properties":"{}"}}]}}`
   
   As you can see from the results, no score is calculated, this is what we 
need. **max_score":0.0**

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