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Adaptive and Big Data Scale Parallel Execution in Oracle

Summary: Oracle’s adaptive parallel execution uses multi-stage plans and runtime data/statistics to correct optimizer errors and dynamically choose parallelism and distribution for joins, aggregates, rollups, and windows. It also parallelizes inherently serial operators at big-data scale. (summarized by gpt-5.6-luna on Jul 24 2026)

Paper ID
10736
Venue
VLDB
Year
2013
Pagerank
8.2816537e-05
Overall Rank
2,664 | 81.73%
DOI
10.14778/2536222.2536235

Incoming Non-self Citations Over Time

Authors

BibTeX Citation

@article{bellamkonda_vldb13,
        title = {{Adaptive and Big Data Scale Parallel Execution in Oracle}},
        author = {Bellamkonda, Srikanth and Li, Hua-Gang and Jagtap, Unmesh and Zhu, Yali and Liang, Vince and Cruanes, Thierry},
        journal = {PVLDB},
        series = {{VLDB} '13},
        volume = {6},
        number = {11},
        pages = {1102--1113},
        doi = {10.14778/2536222.2536235},
        url = {https://doi.org/10.14778/2536222.2536235},
        year = {2013}
}

Incoming Citations (Sorted by Pagerank)

Showing 7 of 7 citing papers.

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Outgoing Citations (Sorted by Pagerank)

Showing 7 of 7 cited papers.

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

Rank Cited Paper Year Venue Pagerank
11 Implementing Data Cubes Efficiently 1996 SIGMOD 0.00071822821
207 On the Computation of Multidimensional Aggregates 1996 VLDB 0.00025088003
209 Sort vs. Hash Revisited: Fast Join Implementation on Modern Multi-Core CPUs 2009 VLDB 0.00024932174
1,657 Handling Data Skew in Parallel Joins in Shared-Nothing Systems 2008 SIGMOD 0.00010096933
2,021 WinMagic : Subquery Elimination Using Window Aggregation 2003 SIGMOD 9.297379e-05
2,095 Enhanced Subquery Optimizations in Oracle 2009 VLDB 9.1803718e-05
4,020 Optimization of Analytic Window Functions 2012 VLDB 6.9513881e-05
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