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Sibyl: Forecasting Time-Evolving Query Workloads

Summary: Sibyl forecasts time-evolving query workloads, with full statements, across multiple future windows. Template-based featurization plus a stacked-LSTM encoder-decoder handles drift and large windows, delivering 87.3% median F1 and 1.7x/1.3x gains for MV/index selection. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
6863
Venue
SIGMOD
Year
2024
Pagerank
4.6415559e-05
Overall Rank
7,809 | 45.73%
DOI
10.1145/3639308

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Showing 16 of 16 cited papers.

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

Rank Cited Paper Year Venue Pagerank
160 Automated Selection of Materialized Views and Indexes for SQL Databases 2000 VLDB 0.00040053897
258 DB2 Design Advisor: Integrated Automatic Physical Database Design 2004 VLDB 0.00030196528
329 Neo: A Learned Query Optimizer 2019 VLDB 0.00027301488
371 Self-Driving Database Management Systems 2017 CIDR 0.00025382677
542 Apache Calcite: A Foundational Framework for Optimized Query Processing Over Heterogeneous Data Sources 2018 SIGMOD 0.00020522627
634 Bao: Making Learned Query Optimization Practical 2021 SIGMOD 0.00018844568
704 Query-based Workload Forecasting for Self-Driving Database Management Systems 2018 SIGMOD 0.00017785557
1,010 SnipSuggest: Context-Aware Autocompletion for SQL 2011 VLDB 0.00014644808
1,498 P-Store: An Elastic Database System with Predictive Provisioning 2018 SIGMOD 0.00011660631
1,921 Selecting Subexpressions to Materialize at Datacenter Scale 2018 VLDB 0.00010085899
2,080 Towards a Learning Optimizer for Shared Clouds 2019 VLDB 9.5954034e-05
2,092 Multi-Dimensional Clustering: A New Data Layout Scheme in DB2 2003 SIGMOD 9.5635999e-05
3,623 Cost Models for Big Data Query Processing: Learning, Retrofitting, and Our Findings 2020 SIGMOD 6.9017341e-05
4,171 Computation Reuse in Analytics Job Service at Microsoft 2018 SIGMOD 6.3800823e-05
8,714 Tiresias: Enabling Predictive Autonomous Storage and Indexing 2022 VLDB 4.457682e-05
9,027 CrocodileDB in Action: Resource-Efficient Query Execution by Exploiting Time Slackness 2020 VLDB 4.4011428e-05
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