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Customizable and Scalable Fuzzy Join for Big Data

Summary: Customizable, scalable fuzzy join for big data using LSH-based signatures to handle domain-quality issues such as synonyms and abbreviations. On Azure Databricks Spark, it delivers >50x speedup over prior scale-out methods with near-linear scalability in data size and cluster size. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
11931
Venue
VLDB
Year
2019
Pagerank
4.5774794e-05
Overall Rank
8,137 | 43.40%
DOI
10.14778/3352063.3352128

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Incoming Citations (Sorted by Pagerank)

Showing 3 of 3 citing papers.

Rank Citing Paper Year Venue Pagerank
3,942 Ember: No-Code Context Enrichment via Similarity-Based Keyless Joins 2022 VLDB 6.6114622e-05
7,476 Lachesis: Automatic Partitioning for UDF-Centric Analytics 2021 VLDB 4.7188928e-05
10,754 OmniMatch: Joinability Discovery in Data Products 2025 VLDB 4.1945683e-05
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Outgoing Citations (Sorted by Pagerank)

Showing 12 of 12 cited papers.

Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.

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