글 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.


7.7의 새로운 기능: Elasticsearch 힙 메모리 사용 대폭 감소

Elasticsearch 7.7에서는 이전 버전에서보다 훨씬 더 적은 힙 메모리를 사용하게 되며, 따라서 Elasticsearch 클러스터 안정성이 개선되고 대량의 데이터를 저장하는 비용이 절약됩니다.


형식에서 무형식으로

Elasticsearch 7.0에서는 형식을 허용하는 API의 사용을 중단하고, 새로운 무형식 API를 도입했으며, _default_ 매핑에 대한 지원을 폐지했습니다.