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Cache Conscious Algorithms for Relational Query Processing

Summary: Cache-conscious redesign of relational query processing leverages CPU cache hierarchies to narrow the DRAM–CPU gap. Demonstrates 8–200% speedups over traditional algorithms by reordering and structuring operators to maximize cache reuse. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
8219
Venue
VLDB
Year
1994
Pagerank
0.00055548574
Overall Rank
81 | 99.44%
DOI
-

Incoming Non-self Citations Over Time

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Incoming Citations (Sorted by Pagerank)

Showing 3 of 53 citing papers.

Rank Citing Paper Year Venue Pagerank
9,980 Declarative Memory Services 2026 CIDR 4.1945683e-05
10,372 Data Chunk Compaction in Vectorized Execution 2025 SIGMOD 4.1945683e-05
10,671 Chimera: Mitigating Ownership Transfers in Multi-Primary Shared-Storage Cloud-Native Databases 2025 VLDB 4.1945683e-05
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Outgoing Citations (Sorted by Pagerank)

Showing 2 of 2 cited papers.

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

Rank Cited Paper Year Venue Pagerank
9 Implementation Techniques For Main Memory Database Systems 1984 SIGMOD 0.0014279444
84 AlphaSort: A RISC Machine Sort 1994 SIGMOD 0.00053866006
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