Title: Apache Lucene™ 6.5.0 available category: core/news URL: save_as:

The Lucene PMC is pleased to announce the release of Apache Lucene 6.5.0

Apache Lucene is a high-performance, full-featured text search engine library written entirely in Java. It is a technology suitable for nearly any application that requires full-text search, especially cross-platform.

This release contains numerous bug fixes, optimizations, and improvements, some of which are highlighted below. The release is available for immediate download at:

https://www.apache.org/dyn/closer.lua/lucene/java/6.5.0

See the CHANGES.txt file included with the release for a full list of changes and further details.

Highlights of this Lucene release include:

  • It is now possible filter out duplicates in the NRT suggester

  • SimpleQueryString now supports default fuziness

  • IndexWriter can return the list of visible field names

  • DisjunctionScorer now supports returning the matching children clauses

  • A new FunctionScoreQuery that modifies the internal query's score using the per-document values

  • A new FunctionMatchQuery that returns any documents with a value that matches a predicate

  • A new WordDelimiterGraphFilter that outputs a correct graph structure for multi-token expansion at query time

  • A new PatternTokenizer that uses Lucene's RegExp implementation

  • RangeFieldQuery now supports CROSSES relation

  • A new IndexOrDocValuesQuery that uses either an index (points or terms) or doc values in order to run a (range, geo box and distance) query, depending which one is more efficient

  • index-time boosts are deprecated

  • Term filters are no longer cached

  • Compound filters are cached earlier than regular queries

  • BKDReader now calls grow on larger increments

  • LatLonPointInPolygonQuery are faster

  • LatLonPointDistanceQuery now skips distance computations more often

  • To-parent block joins now implements two-phase iteration

  • Point ranges that match most documents are faster

  • PointValues#estimatePointCount is faster with Relation.CELL_INSIDE_QUERY

  • Segments are now also sorted during flush, and merging on a sorted index is substantially faster by using some of the same bulk merge optimizations that non-sorted merging uses