And there’s still more to come, as it also includes some foundational work to take system statistics into account when running queries concurrently, which looks to make the most out of the resources available.Īpart from that, Lucene comes with reworked ConcurrentMergeScheduler settings, which assumes modern I/O to improve indexing performance and prevent systems from running into seemingly random JDK issues. However, the focus of the new major release seems to have been largely placed on performance, as the update’s announcement highlights speed-ups in areas like taxonomy faceting, sorting, and indexing of multi-dimensional points. The resulting implementation uses the Hierarchical Navigable Small World graph algorithm and has been added to answer a growing demand from data scientists working in the field of machine learning to index documents containing vectors. The Lucene team also has been busy exploring the indexing of high-dimensionality numeric vectors to perform nearest-neighbor search in v9.0. It is, for instance, the first release to provide JARs with automatically generated module names, which the team behind the engine hopes will help to enable work with the Java module system somewhere along the line. Lucene 9.0, which serves as the basis for projects such as Elasticsearch and MongoDB Atlas’ full-text search, tries to keep up with the times, by looking into ways of supporting new usage scenarios and Java features. The team behind search engine Apache Lucene has recently made version 9.0 of the open source project available for downloading, sharing performance improvements and first steps towards Java module system support with its user base.
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