Issues with Elasticsearch 8.5 Query Performance on Large Datasets Using Bool Queries
I'm getting frustrated with Quick question that's been bugging me - I've been experiencing significant performance degradation when running complex bool queries against a large dataset in Elasticsearch 8.5. The index has about 10 million documents, and I'm trying to retrieve results where multiple conditions must be met across various fields. For example, my query looks something like this: ```json { "query": { "bool": { "must": [ { "match": { "title": "Elasticsearch" } }, { "range": { "publish_date": { "gte": "2023-01-01" } } }, { "term": { "status": "published" } } ], "filter": { "term": { "author_id": "12345" } } } } } ``` When I execute this query, it takes several seconds to return results, which is far from acceptable for our application's needs. I’ve also tried optimizing the index by setting the refresh interval to a longer period and ensuring that I have the right number of shards, but the performance still lags. I've checked the cluster health and it seems to be green, but the slow query log shows that it's mostly the boolean query causing the bottleneck. I've tried using a `match_all` query combined with filters instead of a complex bool query, but the results were not what I was expecting. Additionally, I'm using an older version of Elasticsearch's Java client, and I wonder if there are compatibility issues that could affect performance. Here’s how I initialize the client: ```java RestHighLevelClient client = new RestHighLevelClient( RestClient.builder(new HttpHost("localhost", 9200, "http")) ); ``` Is there a recommended way to structure these queries or configurations to improve performance? Should I consider using aggregations or restructuring my index? Any insights would be greatly appreciated! This issue appeared after updating to Java 3.9. Cheers for any assistance!