- Create dedup blocks from the complete queue of records matching cluster key instead of truncating the results
- Clean titles once before clustering and similarity comparisons
- Added support for filtered fields in model
- Added support for sorting List fields in model
- Added new JSONListClustering and numAuthorsTitleSuffixPrefixChain clustering functions
- Added new maxLengthMatch comparator function
- Use reduced complexity Levenshtein with threshold in levensteinTitle
- Use reduced complexity AuthorsMatch with threshold early-quit
- Use incremental Connected Component to decrease comparisons in similarity match in BlockProcessor
- Use new clusterings configuration in Dedup tests
SparkWhitelistSimRels: use left semi join for clarity and performance
SparkCreateMergeRels:
- Use new connected component algorithm that converge faster than Spark GraphX provided algorithm
- Refactored to use Windowing sorting rather than groupBy to reduce memory pressure
- Use historical pivot table to generate singleton rels, merged rels and keep continuity with dedupIds used in the past
- Comparator for pivot record selection now uses "tomorrow" as filler for missing or incorrect date instead of "2000-01-01"
- Changed generation of ids of type dedup_wf_001 to avoid collisions
DedupRecordFactory: use reduceGroups instead of mapGroups to decrease memory pressure
Giambattista Bloisi
Sandro La Bruzzo
Claudio Atzori