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Intra-Query Runtime Elasticity for Cloud-Native Data Analysis
Summary: IQRE enables intra-query dynamic DOP adjustment for cloud-native OLAP, lowering compute cost. Accordion, IQRE engine, reconfigures parallelism on-the-fly without halting data, with an auto-tuner and what-if service, built atop Presto.
(summarized by gpt-5-nano on Feb 09 2026)
- Paper ID
- 7238
- Venue
- SIGMOD
- Year
- 2025
- Pagerank
- 4.1905499e-05
- Overall Rank
- 10,501 | 27.02%
- DOI
-
10.1145/3725315
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Incoming Citations (Sorted by Pagerank)
Showing 1 of 1 citing papers.
Outgoing Citations (Sorted by Pagerank)
Showing 28 of 28 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
| Rank |
Cited Paper |
Year |
Venue |
Pagerank |
| 66 |
Spark SQL: Relational Data Processing in Spark |
2015 |
SIGMOD |
0.00061707583 |
| 167 |
The Snowflake Elastic Data Warehouse |
2016 |
SIGMOD |
0.00039408116 |
| 634 |
Bao: Making Learned Query Optimization Practical |
2021 |
SIGMOD |
0.00018844568 |
| 1,229 |
Toward a Progress Indicator for Database Queries |
2004 |
SIGMOD |
0.00013153898 |
| 1,273 |
Amazon Redshift Re-invented |
2022 |
SIGMOD |
0.00012870386 |
| 1,324 |
Starling: A Scalable Query Engine on Cloud Functions |
2020 |
SIGMOD |
0.00012585081 |
| 1,509 |
Estimating Progress of Execution for SQL Queries |
2004 |
SIGMOD |
0.0001158945 |
| 2,222 |
SkinnerDB: Regret-Bounded Query Evaluation via Reinforcement Learning |
2019 |
SIGMOD |
9.2598438e-05 |
| 2,420 |
Lambada: Interactive Data Analytics on Cold Data Using Serverless Cloud Infrastructure |
2020 |
SIGMOD |
8.8474951e-05 |
| 2,553 |
Towards Cost-Optimal Query Processing in the Cloud |
2021 |
VLDB |
8.5522099e-05 |
| 2,777 |
Quickstep: A Data Platform Based on the Scaling-Up Approach |
2018 |
VLDB |
8.1346418e-05 |
| 3,623 |
Cost Models for Big Data Query Processing: Learning, Retrofitting, and Our Findings |
2020 |
SIGMOD |
6.9017341e-05 |
| 4,592 |
Auto-WLM: Machine Learning Enhanced Workload Management in Amazon Redshift |
2023 |
SIGMOD |
6.056004e-05 |
| 4,687 |
Deploying a Steered Query Optimizer in Production at Microsoft |
2022 |
SIGMOD |
5.9915268e-05 |
| 5,210 |
Self-Tuning Query Scheduling for Analytical Workloads |
2021 |
SIGMOD |
5.6244961e-05 |
| 5,234 |
ByteGraph: A High-Performance Distributed Graph Database in ByteDance |
2022 |
VLDB |
5.609287e-05 |
| 5,292 |
StreamOps: Cloud-Native Runtime Management for Streaming Services in ByteDance |
2023 |
VLDB |
5.5784769e-05 |
| 5,537 |
Presto: A Decade of SQL Analytics at Meta |
2023 |
SIGMOD |
5.453017e-05 |
| 5,587 |
Magnet: Push-based Shuffle Service for Large-scale Data Processing |
2020 |
VLDB |
5.4193445e-05 |
| 5,643 |
Intelligent Scaling in Amazon Redshift |
2024 |
SIGMOD |
5.3949759e-05 |
| 5,654 |
AutoSteer: Learned Query Optimization for Any SQL Database |
2023 |
VLDB |
5.3882121e-05 |
| 5,682 |
LSched: A Workload-Aware Learned Query Scheduler for Analytical Database Systems |
2022 |
SIGMOD |
5.3752251e-05 |
| 5,994 |
Steering Query Optimizers: A Practical Take on Big Data Workloads |
2021 |
SIGMOD |
5.2367998e-05 |
| 6,154 |
PolarDB-IMCI: A Cloud-Native HTAP Database System at Alibaba |
2023 |
SIGMOD |
5.1795738e-05 |
| 6,397 |
BigLake: BigQuery’s Evolution toward a Multi-Cloud Lakehouse |
2024 |
SIGMOD |
5.0749432e-05 |
| 7,787 |
Cost-Intelligent Data Analytics in the Cloud |
2024 |
CIDR |
4.6468106e-05 |
| 9,032 |
Making Data Clouds Smarter at Keebo: Automated Warehouse Optimization using Data Learning |
2023 |
SIGMOD |
4.3998185e-05 |
| 9,662 |
Efficient Query Re-optimization with Judicious Subquery Selections |
2023 |
SIGMOD |
4.3056334e-05 |
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