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The Case for Learned In-Memory Joins

Summary: Explores CDF-based learned indexes (RMI, RadixSpline) for in-memory indexed nested-loop, sort, and hash joins. Optimized learned variants outperform state-of-the-art joins across diverse datasets and workloads. (summarized by gpt-5.6-luna on Jul 24 2026)

Paper ID
13221
Venue
VLDB
Year
2023
Pagerank
5.460955e-05
Overall Rank
8,234 | 43.51%
DOI
10.14778/3587136.3587148

Incoming Non-self Citations Over Time

Authors

BibTeX Citation

@article{sabek_vldb23,
        title = {{The Case for Learned In-Memory Joins}},
        author = {Sabek, Ibrahim and Kraska, Tim},
        journal = {PVLDB},
        series = {{VLDB} '23},
        volume = {16},
        number = {7},
        pages = {1749--1762},
        doi = {10.14778/3587136.3587148},
        url = {https://doi.org/10.14778/3587136.3587148},
        year = {2023}
}

Incoming Citations (Sorted by Pagerank)

Showing 5 of 5 citing papers.

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Outgoing Citations (Sorted by Pagerank)

Showing 35 of 35 cited papers.

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

Rank Cited Paper Year Venue Pagerank
18 How Good Are Query Optimizers, Really? 2016 VLDB 0.00059284255
29 Database Architecture Optimized for the New Bottleneck: Memory Access 1999 VLDB 0.00052093615
43 The Case for Learned Index Structures 2018 SIGMOD 0.00046060254
84 Learned Cardinalities: Estimating Correlated Joins with Deep Learning 2019 CIDR 0.00035838391
154 Neo: A Learned Query Optimizer 2019 VLDB 0.00028726181
209 Sort vs. Hash Revisited: Fast Join Implementation on Modern Multi-Core CPUs 2009 VLDB 0.00024932174
252 Multi-Core, Main-Memory Joins: Sort vs. Hash Revisited 2014 VLDB 0.00023242719
360 Design and Evaluation of Main Memory Hash Join Algorithms for Multi-core CPUs 2011 SIGMOD 0.00020182846
378 Bao: Making Learned Query Optimization Practical 2021 SIGMOD 0.00019638121
422 Umbra: A Disk-Based System with In-Memory Performance 2020 CIDR 0.00018732744
423 Massively Parallel Sort-Merge Joins in Main Memory Multi-Core Database Systems 2012 VLDB 0.00018725853
447 ALEX: An Updatable Adaptive Learned Index 2020 SIGMOD 0.00018322593
477 The PGM-index: a fully-dynamic compressed learned index with provable worst-case bounds 2020 VLDB 0.00017851226
631 Relational Joins on Graphics Processors 2008 SIGMOD 0.00015591241
847 Benchmarking Learned Indexes 2021 VLDB 0.0001365768
873 Learning Multi-dimensional Indexes 2020 SIGMOD 0.00013481915
987 What happens during a Join? Dissecting CPU and Memory Optimization Effects 2000 VLDB 0.00012814017
1,110 Buffering Accesses to Memory-Resident Index Structures 2003 VLDB 0.00012140661
1,135 Qd-tree: Learning Data Layouts for Big Data Analytics 2020 SIGMOD 0.00012032847
1,203 NUMA-aware algorithms: the case of data shuffling 2013 CIDR 0.00011671169
1,265 An Experimental Comparison of Thirteen Relational Equi-Joins in Main Memory 2016 SIGMOD 0.00011415709
1,551 Updatable Learned Index with Precise Positions 2021 VLDB 0.00010381398
2,156 Quickstep: A Data Platform Based on the Scaling-Up Approach 2018 VLDB 9.0635624e-05
2,649 Asynchronous Memory Access Chaining 2016 VLDB 8.2926258e-05
2,767 Exploiting Coroutines to Attack the "Killer Nanoseconds" 2018 VLDB 8.1507611e-05
2,806 Are Updatable Learned Indexes Ready? 2022 VLDB 8.1013097e-05
2,926 Distributed Join Algorithms on Thousands of Cores 2017 VLDB 7.9549783e-05
2,962 To Partition, or Not to Partition, That is the Join Question in a Real System 2021 SIGMOD 7.9170451e-05
3,865 The Case for a Learned Sorting Algorithm 2020 SIGMOD 7.0621718e-05
4,780 Can Learned Models Replace Hash Functions? 2023 VLDB 6.5118885e-05
5,148 LSched: A Workload-Aware Learned Query Scheduler for Analytical Database Systems 2022 SIGMOD 6.3465986e-05
5,974 Towards instance-optimized data systems 2021 VLDB 6.0230488e-05
6,163 A Critical Analysis of Recursive Model Indexes 2022 VLDB 5.9532723e-05
7,792 Cache-Oblivious Query Processing 2007 CIDR 5.5431413e-05
9,939 Is FPGA Useful for Hash Joins? Exploring Hash Joins on Coupled CPU-FPGA Architecture 2020 CIDR 5.1947648e-05
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