文章作者 Adrien Grand

Tech Lead, Elastic

Tech Lead, Elasticsearch

Adrien is a Lucene committer at The Apache Software Foundation and a software engineer at Elastic, where he works on improving Elasticsearch. He has worked with Apache Lucene for a decade. When he’s not tackling search-related problems from his home in Normandy, France, he enjoys horseback riding.


Bringing speedups to top-k queries with many and/or high-frequency terms

Apache Lucene is combining two optimizations for evaluating disjunctive queries, bringing significant speedups to top-k queries, especially with many terms and/or high-frequency terms.


Achieve faster cardinality aggregations via dynamic pruning

Elasticsearch 8.9 introduces optimizations to cardinality aggregations by filtering out documents whose value has already been collected.


Vector search in Elasticsearch: The rationale behind the design

There are different ways to implement a vector database, which have different trade-offs. In this blog, you'll learn more about how vector search has been integrated into Elastisearch and the trade-offs that we made.


How we sped up data ingestion in Elasticsearch 8.6, 8.7, and 8.8

Data ingestion involves a lot of things that usually take a non-negligible amount of time. Fortunately, we've got improvements in 8.6, 8.7, and 8.8, which enabled some good speedups for end-to-end ingestion.


在 Elasticsearch 7.10 中通过提高存储效率节省空间和成本

Elasticsearch 7.10 和 Lucene 8.7 通过增强跨文档重复数据的检测,显著改进了索引压缩。压缩效率提升高达 10%,即刻升级,便可开始节省存储成本。


7.7 版本中的新改进:显著降低 Elasticsearch 堆内存使用量

相比之前的版本,Elasticsearch 7.7 使用的堆内存要少得多,这就使 Elasticsearch 集群的稳定性得以提升,并让存储大量数据的成本实现下降。



Elasticsearch 7.0 弃用了接受类型的 API,引入了新的无类型 API,并移除了对 _default_ 映射的支持。