Artikel von 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.


Neu in 7.7: Deutliche Reduzierung der Nutzung des Elasticsearch-Heap-Speichers

Elasticsearch 7.7 wird deutlich weniger Heap-Speicher als vorherige Versionen verbrauchen, was das Elasticsearch-Cluster stabiler macht und die Kosten für das Speichern großer Datenmengen senkt.


Von typisierten zu typenlosen APIs

Mit Elasticsearch 7.0 gelten typisierte APIs als veraltet. Stattdessen wurden neue typenlose APIs eingeführt und das Mapping „_default_“ wird nicht mehr