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Memory-Contention Responsive Hash Joins

Summary: Memory-contention responsive hash joins adapt to fluctuating memory via large I/O buffers, dynamic cluster sizing, and destaging/restoration. Outperforms prior adaptive hash-join approaches under medium/high contention and frequent memory changes, especially with mixed workloads. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
8209
Venue
VLDB
Year
1994
Pagerank
6.4043572e-05
Overall Rank
4,149 | 71.17%
DOI
-

Incoming Non-self Citations Over Time

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Incoming Citations (Sorted by Pagerank)

Showing 7 of 7 citing papers.

Rank Citing Paper Year Venue Pagerank
661 Adaptive Self-Tuning Memory in DB2 2006 VLDB 0.00018488168
2,777 Quickstep: A Data Platform Based on the Scaling-Up Approach 2018 VLDB 8.1346418e-05
4,027 Dynamic Resource Brokering for Multi-User Query Execution 1995 SIGMOD 6.51574e-05
4,213 Dynamic Multi-Resource Load Balancing in Parallel Database Systems 1995 VLDB 6.3482542e-05
4,826 Dynamic Memory Adjustment for External Mergesort 1997 VLDB 5.8892345e-05
8,795 Resource-Adaptive Query Execution with Paged Memory Management 2025 CIDR 4.4446768e-05
10,643 Saving Private Hash Join 2025 VLDB 4.1905499e-05
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Outgoing Citations (Sorted by Pagerank)

Showing 8 of 8 cited papers.

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

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