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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
6862
Venue
SIGMOD
Year
2024
Pagerank
4.5784634e-05
Overall Rank
8,131 | 43.44%
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
158 Automated Selection of Materialized Views and Indexes for SQL Databases 2000 VLDB 0.00040071492
258 DB2 Design Advisor: Integrated Automatic Physical Database Design 2004 VLDB 0.0003022091
333 Neo: A Learned Query Optimizer 2019 VLDB 0.00027206884
359 Self-Driving Database Management Systems 2017 CIDR 0.0002592783
544 Apache Calcite: A Foundational Framework for Optimized Query Processing Over Heterogeneous Data Sources 2018 SIGMOD 0.00020521965
640 Bao: Making Learned Query Optimization Practical 2021 SIGMOD 0.00018759152
716 Query-based Workload Forecasting for Self-Driving Database Management Systems 2018 SIGMOD 0.00017723171
1,009 SnipSuggest: Context-Aware Autocompletion for SQL 2011 VLDB 0.00014653644
1,501 P-Store: An Elastic Database System with Predictive Provisioning 2018 SIGMOD 0.00011664869
1,922 Selecting Subexpressions to Materialize at Datacenter Scale 2018 VLDB 0.00010082599
2,045 Multi-Dimensional Clustering: A New Data Layout Scheme in DB2 2003 SIGMOD 9.6939983e-05
2,083 Towards a Learning Optimizer for Shared Clouds 2019 VLDB 9.5834572e-05
3,625 Cost Models for Big Data Query Processing: Learning, Retrofitting, and Our Findings 2020 SIGMOD 6.9055212e-05
4,174 Computation Reuse in Analytics Job Service at Microsoft 2018 SIGMOD 6.3856219e-05
8,774 Tiresias: Enabling Predictive Autonomous Storage and Indexing 2022 VLDB 4.4559995e-05
9,073 CrocodileDB in Action: Resource-Efficient Query Execution by Exploiting Time Slackness 2020 VLDB 4.4023079e-05
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