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Astrid: Accurate Selectivity Estimation for String Predicates using Deep Learning

Summary: Astrid blends traditional pruning sketches with deep learning to estimate string selectivity for prefix, substring, and suffix queries. It offers a query-type aware embedding and a revised neural language-model objective with an efficient optimizer, achieving state-of-the-art results on benchmarks. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
h652966c32e439e9f
Venue
VLDB
Year
2021
Pagerank
7.2046519e-05
Overall Rank
3,562 | 76.06%
DOI
10.14778/3436905.3436907

Incoming Non-self Citations Over Time

Authors

BibTeX Citation

@article{shetiya_vldb21,
        title = {{Astrid: Accurate Selectivity Estimation for String Predicates using Deep Learning}},
        author = {Shetiya, Suraj and Thirumuruganathan, Saravanan and Koudas, Nick and Das, Gautam},
        journal = {PVLDB},
        series = {{VLDB} '21},
        volume = {14},
        number = {4},
        pages = {471--484},
        doi = {10.14778/3436905.3436907},
        url = {https://doi.org/10.14778/3436905.3436907},
        year = {2021}
}

Incoming Citations (Sorted by Pagerank)

Showing 16 of 16 citing papers.

Rank Citing Paper Year Venue Pagerank
982 Cardinality Estimation in DBMS: A Comprehensive Benchmark Evaluation 2022 VLDB 0.00012714044
1,199 Balsa: Learning a Query Optimizer Without Expert Demonstrations 2022 SIGMOD 0.00011563985
2,250 QueryFormer: A Tree Transformer Model for Query Plan Representation 2022 VLDB 8.7533306e-05
2,342 Learned Cardinality Estimation: An In-depth Study 2022 SIGMOD 8.6060437e-05
3,327 Robust Query Driven Cardinality Estimation under Changing Workloads 2023 VLDB 7.4207879e-05
4,950 Debunking the Myth of Join Ordering: Toward Robust SQL Analytics 2025 SIGMOD 6.3421691e-05
5,481 A Comparative Study and Component Analysis of Query Plan Representation Techniques in ML4DB Studies 2024 VLDB 6.1125124e-05
6,710 Simple Adaptive Query Processing vs. Learned Query Optimizers: Observations and Analysis 2023 VLDB 5.7019157e-05
6,884 LPLM: A Neural Language Model for Cardinality Estimation of LIKE-Queries 2024 SIGMOD 5.6563432e-05
7,417 Cardinality Estimation of Approximate Substring Queries using Deep Learning 2022 VLDB 5.5327978e-05
10,027 Cardinality Estimation of LIKE Predicate Queries using Deep Learning 2025 SIGMOD 5.0925739e-05
10,057 SPACE: Cardinality Estimation for Path Queries Using Cardinality-Aware Sequence-based Learning 2025 SIGMOD 5.0875952e-05
10,322 SSCard: Substring Cardinality Estimation using Suffix Tree-Guided Learned FM-Index 2026 SIGMOD 5.0346745e-05
10,336 An Elephant Under The Microscope: Analyzing The Interaction Of Optimizer Components In PostgreSQL 2025 SIGMOD 5.0200193e-05
10,691 The Case For Language Model Approximated LIKE Predicate 2026 SIGMOD 4.9793485e-05
10,693 Practical Parameterized Query Optimization via Efficient Plan Reuse and List-wise Ranking 2026 SIGMOD 4.9793485e-05
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Outgoing Citations (Sorted by Pagerank)

Showing 33 of 33 cited papers.

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

Rank Cited Paper Year Venue Pagerank
15 How Good Are Query Optimizers, Really? 2016 VLDB 0.00061066921
37 Improved Histograms for Selectivity Estimation of Range Predicates 1996 SIGMOD 0.00047731453
40 The Case for Learned Index Structures 2018 SIGMOD 0.00046284649
79 Practical Selectivity Estimation through Adaptive Sampling 1990 SIGMOD 0.00036487763
85 Learned Cardinalities: Estimating Correlated Joins with Deep Learning 2019 CIDR 0.00035864347
145 Neo: A Learned Query Optimizer 2019 VLDB 0.0002908188
169 Wavelet-Based Histograms for Selectivity Estimation 1998 SIGMOD 0.00027134723
197 Fast Exact Shortest-Path Distance Queries on Large Networks by Pruned Landmark Labeling 2013 SIGMOD 0.00025584127
255 The History of Histograms (abridged) 2003 VLDB 0.00022981861
275 Optimal Histograms with Quality Guarantees 1998 VLDB 0.00022413521
286 Selectivity Estimation using Probabilistic Models 2001 SIGMOD 0.0002211981
318 DeepDB: Learn from Data, not from Queries! 2020 VLDB 0.00021167555
371 STHoles: A Multidimensional Workload-Aware Histogram 2001 SIGMOD 0.00019829769
406 Deep Unsupervised Cardinality Estimation 2020 VLDB 0.00019045544
457 Distributed Representations of Tuples for Entity Resolution 2018 VLDB 0.00017907103
461 An End-to-End Learning-based Cost Estimator 2020 VLDB 0.00017829982
555 SageDB: A Learned Database System 2019 CIDR 0.00016506678
688 Cardinality Estimation Done Right: Index-Based Join Sampling 2017 CIDR 0.00014753664
692 Selectivity Estimation for Range Predicates using Lightweight Models 2019 VLDB 0.00014741011
742 Dynamic Multidimensional Histograms 2002 SIGMOD 0.0001431602
1,060 Lightweight Graphical Models for Selectivity Estimation Without Independence Assumptions 2011 VLDB 0.00012224575
1,061 VGRAM: Improving Performance of Approximate Queries on String Collections Using Variable-Length Grams 2007 VLDB 0.00012213729
1,163 Estimating Alphanumeric Selectivity in the Presence of Wildcards 1996 SIGMOD 0.00011750813
1,391 Creating Embeddings of Heterogeneous Relational Datasets for Data Integration Tasks 2020 SIGMOD 0.00010816237
1,461 Substring Selectivity Estimation 1999 PODS 0.00010583833
1,542 Improved Selectivity Estimation by Combining Knowledge from Sampling and Synopses 2018 VLDB 0.00010308631
1,580 Deep Learning Models for Selectivity Estimation of Multi-Attribute Queries 2020 SIGMOD 0.00010180835
2,093 Selectivity Estimation For Boolean Queries 2000 PODS 9.0578876e-05
2,144 Cost-Based Variable-Length-Gram Selection for String Collections to Support Approximate Queries Efficiently 2008 SIGMOD 8.9608583e-05
2,216 Estimating Join Selectivities using Bandwidth-Optimized Kernel Density Models 2017 VLDB 8.8177753e-05
2,303 Selectivity Estimation in Extensible Databases - A Neural Network Approach 1998 VLDB 8.6708797e-05
2,967 Extending Q-Grams to Estimate Selectivity of String Matching with Low Edit Distance 2007 VLDB 7.8029216e-05
3,361 Conditional Selectivity for Statistics on Query Expressions 2004 SIGMOD 7.3760492e-05
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5 10,027 Cardinality Estimation of LIKE Predicate Queries using Deep Learning 2025 SIGMOD
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