Apache Lucene for Mac OS X 10.3.1 freeware
... Lucene is a powerful, high-performance search library designed for full-text indexing and searching. Developed by the Apache Software Foundation, it offers a robust framework for implementing search capabilities in applications, supporting complex queries, ... to customize and extend functionalities, making it ideal for a variety of use cases, from simple search engines to advanced data re ... ...
| Author | Apache Software Foundation |
| Released | 2025-10-06 |
| Filesize | 71.40 MB |
| Downloads | 331 |
| OS | Windows 11, Windows 10 64 bit |
| Installation | Instal And Uninstall |
| Keywords | search engine library, text search, library, search engine, component |
| Users' rating (23 rating) |
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| 10.3.1 | Oct 6, 2025 | New Release | Bug Fixes: Fix the Impact returned from Lucene103PostingsReader when frequencies are not indexed. |
| 10.2.2 | Jun 21, 2025 | New Release | Bug fixes: Reduce NeighborArray on-heap memory during HNSW graph building Fix IndexSortSortedNumericDocValuesRangeQuery for int sort ValueSource.fromDoubleValuesSource(dvs).getSortField() would throw errors when used if the DoubleValuesSource needed scores |
| 9.12.0 | Sep 29, 2024 | New Release | Security Fixes: Deserialization of Untrusted Data vulnerability in Apache Lucene Replicator - CVE-2024-45772 New Features: Improve intra-merge parallelism for many value types. (Ben Trent) Add support JDK 23 to the Panama Vectorization Provider. (Chris Hegarty) Improvements: Add Intervals.regexp and Intervals.range methods to produce IntervalsSource for regexp and range queries. (Mayya Sharipova) Remove support for writing 8 bit scalar vector quantization. 4 and 7 bit quantization are still supported (Michael McCandless ) Optimizations: Inline postings skip data to improve performance of queries that need skipping such as conjunctions. (Adrien Grand) Optimizations to the decoding logic of blocks of postings. (Adrien Grand, Uwe Schindler, Greg Miller) Avoid performance degradation with closing shared mapped segment data (Chris Hegarty, Michael Gibney, Uwe Schindler) |
