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S4: Top-k Spreadsheet-Style Search for Query Discovery

Summary: S4 proposes top-k project-join query discovery with approximate containment of user-provided example tuples. It enables spreadsheet-style, incremental search that returns results as users type or edit a cell, delivering substantial efficiency gains over prior state-of-the-art. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
5069
Venue
SIGMOD
Year
2015
Pagerank
8.5112408e-05
Overall Rank
2,576 | 82.09%
DOI
10.1145/2723372.2749452

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Showing 15 of 15 citing papers.

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Showing 13 of 13 cited papers.

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

Rank Cited Paper Year Venue Pagerank
7 Optimal Aggregation Algorithms for Middleware [Extended Abstract] 2001 PODS 0.0015496097
54 DISCOVER: Keyword Search in Relational Databases 2002 VLDB 0.00066047203
179 Efficient and Extensible Algorithms for Multi Query Optimization 2000 SIGMOD 0.00037672155
276 Efficient IR-Style Keyword Search over Relational Databases 2003 VLDB 0.00029336949
492 Query by Output 2009 SIGMOD 0.00021974699
802 Optimal Multi-Step k-Nearest Neighbor Search 1998 SIGMOD 0.00016502317
1,201 SPARK: Top-k Keyword Query in Relational Databases 2007 SIGMOD 0.0001334371
1,509 Discovering Queries based on Example Tuples 2014 SIGMOD 0.00011612727
1,572 Reverse Engineering Complex Join Queries 2013 SIGMOD 0.00011298251
2,078 Sample-Driven Schema Mapping 2012 SIGMOD 9.599707e-05
2,205 ReStore: Reusing Results of MapReduce Jobs 2012 VLDB 9.2920002e-05
3,703 Multi-Query Optimization in MapReduce Framework 2014 VLDB 6.8289978e-05
4,414 Efficient Type-Ahead Search on Relational Data: a TASTIER Approach 2009 SIGMOD 6.2056993e-05
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