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Workload-driven, Lazy Discovery of Data Dependencies for Query Optimization

Summary: Workload-driven, lazy discovery that extracts dependency candidates from executed plans, validates them dynamically, and maintains lightweight metadata to enable practical dependency-based query optimizations. Hyrise prototype shows feasibility and up to 27% JOB speedup, demonstrating practicality in columnar DBMSs. (summarized by gpt-5-mini on Feb 09 2026)

Paper ID
465
Venue
CIDR
Year
2022
Pagerank
4.4647237e-05
Overall Rank
8,703 | 39.46%
DOI
-

Incoming Non-self Citations Over Time

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Incoming Citations (Sorted by Pagerank)

Showing 2 of 2 citing papers.

Rank Citing Paper Year Venue Pagerank
9,204 Themis: A GPU-accelerated Relational Query Execution Engine 2025 VLDB 4.3737475e-05
9,760 Adaptive data transformations for QaaS 2025 CIDR 4.2856106e-05
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Outgoing Citations (Sorted by Pagerank)

Showing 6 of 6 cited papers.

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

Rank Cited Paper Year Venue Pagerank
71 How Good Are Query Optimizers, Really? 2016 VLDB 0.00059038975
185 DuckDB: an Embeddable Analytical Database 2019 SIGMOD 0.00036538405
659 The Making of TPC-DS 2006 VLDB 0.00018500853
894 A Hybrid Approach to Functional Dependency Discovery 2016 SIGMOD 0.00015556428
1,263 Data Blocks: Hybrid OLTP and OLAP on Compressed Storage using both Vectorization and Compilation 2016 SIGMOD 0.00012982857
6,756 Fast Incremental Discovery of Pointwise Order Dependencies 2020 VLDB 4.9379361e-05
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