SH2O: Efficient Data Access for Work-Sharing Databases

Summary: SH2O replaces shared filters with multidimensional range access patterns to reduce bottlenecks in highly concurrent work-sharing databases. Three-tier design: spatial indices, a range-optimizer, and partitioned, independent access with tuning—yields 1.8–22.2× speedups on hundreds of queries. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID: h0d7673ae0ff302b9
Venue: SIGMOD
Year: 2023
Pagerank: 4.9769913e-05
Overall Rank: 11,733 | 21.15%
DOI: 10.1145/3617340

Incoming Non-self Citations Over Time

No non-self incoming citations found for this paper in this database.

Authors

1. Panagiotis Sioulas (Oracle)
2. Ioannis Mytilinis (Oracle)
3. Anastasia Ailamaki (EPFL)

BibTeX Citation

@inproceedings{sioulas_sigmod23,
        title = {{SH2O: Efficient Data Access for Work-Sharing Databases}},
        author = {Sioulas, Panagiotis and Mytilinis, Ioannis and Ailamaki, Anastasia},
        series = {{SIGMOD} '23},
        booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
        publisher = {Association for Computing Machinery},
        doi = {10.1145/3617340},
        url = {https://dl.acm.org/doi/10.1145/3617340},
        year = {2023}
}

Incoming Citations (Sorted by Pagerank)

Showing 0 of 0 citing papers.

Rank	Citing Paper	Year	Venue	Pagerank

Outgoing Citations (Sorted by Pagerank)

Showing 25 of 25 cited papers.

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

Rank	Cited Paper	Year	Venue	Pagerank
2	R-Trees: A Dynamic Index Structure For Spatial Searching	1984	SIGMOD	0.0019923528
15	How Good Are Query Optimizers, Really?	2016	VLDB	0.00061067652
71	DuckDB: an Embeddable Analytical Database	2019	SIGMOD	0.00037724477
200	Continuously Adaptive Continuous Queries over Streams	2002	SIGMOD	0.00025444144
216	Small Materialized Aggregates: A Light Weight Index Structure for Data Warehousing	1998	VLDB	0.00024485637
331	Column-Stores vs. Row-Stores: How Different Are They Really?	2008	SIGMOD	0.0002076806
390	QPipe: A Simultaneously Pipelined Relational Query Engine	2005	SIGMOD	0.00019265472
406	Deep Unsupervised Cardinality Estimation	2020	VLDB	0.00019050182
669	SharedDB: Killing One Thousand Queries With One Stone	2012	VLDB	0.00014975391
691	Selectivity Estimation for Range Predicates using Lightweight Models	2019	VLDB	0.00014737455
704	Main-Memory Scan Sharing For Multi-Core CPUs	2008	VLDB	0.00014653079
762	Cooperative Scans: Dynamic Bandwidth Sharing in a DBMS	2007	VLDB	0.00014134432
1,034	A Scalable, Predictable Join Operator for Highly Concurrent Data Warehouses	2009	VLDB	0.00012389548
1,036	Fine-grained Partitioning for Aggressive Data Skipping	2014	SIGMOD	0.00012372946
1,040	The DataPath System: A Data-Centric Analytic Processing Engine for Large Data Warehouses	2010	SIGMOD	0.00012358804
1,128	Qd-tree: Learning Data Layouts for Big Data Analytics	2020	SIGMOD	0.00011901941
1,423	Procella: Unifying serving and analytical data at YouTube	2019	VLDB	0.00010715412
1,918	Predictable Performance for Unpredictable Workloads	2009	VLDB	9.375192e-05
3,075	Pushing Data-Induced Predicates Through Joins in Big-Data Clusters	2020	VLDB	7.6742518e-05
3,083	Skipping-oriented Partitioning for Columnar Layouts	2017	VLDB	7.6620866e-05
3,597	Access Path Selection in Main-Memory Optimized Data Systems: Should I Scan or Should I Probe?	2017	SIGMOD	7.1759026e-05
4,732	MQJoin: Efficient Shared Execution of Main-Memory Joins	2016	VLDB	6.4439712e-05
5,793	OLTPShare: The Case for Sharing in OLTP Workloads	2018	VLDB	5.9906809e-05
6,971	Jigsaw: A Data Storage and Query Processing Engine for Irregular Table Partitioning	2021	SIGMOD	5.628441e-05
7,344	Scalable Multi-Query Execution using Reinforcement Learning	2021	SIGMOD	5.5455974e-05

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