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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
7299
Venue
SIGMOD
Year
2025
Pagerank
5.093636e-05
Overall Rank
10,768 | 26.13%
DOI
10.1145/3725315

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Authors

BibTeX Citation

@inproceedings{zhang_sigmod25,
        title = {{Intra-Query Runtime Elasticity for Cloud-Native Data Analysis}},
        author = {Zhang, Xukang and Zhang, Huanchen and Meng, Xiaofeng},
        series = {{SIGMOD} '25},
        booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
        publisher = {Association for Computing Machinery},
        doi = {10.1145/3725315},
        url = {https://dl.acm.org/doi/10.1145/3725315},
        year = {2025}
}

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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
24 Spark SQL: Relational Data Processing in Spark 2015 SIGMOD 0.00054865648
66 The Snowflake Elastic Data Warehouse 2016 SIGMOD 0.00038561587
378 Bao: Making Learned Query Optimization Practical 2021 SIGMOD 0.00019638121
818 Amazon Redshift Re-invented 2022 SIGMOD 0.00013822916
939 Starling: A Scalable Query Engine on Cloud Functions 2020 SIGMOD 0.00013083524
1,143 Toward a Progress Indicator for Database Queries 2004 SIGMOD 0.00011999403
1,562 Estimating Progress of Execution for SQL Queries 2004 SIGMOD 0.00010354429
1,712 SkinnerDB: Regret-Bounded Query Evaluation via Reinforcement Learning 2019 SIGMOD 9.9492299e-05
1,784 Lambada: Interactive Data Analytics on Cold Data Using Serverless Cloud Infrastructure 2020 SIGMOD 9.7726335e-05
2,156 Quickstep: A Data Platform Based on the Scaling-Up Approach 2018 VLDB 9.0635624e-05
2,344 Towards Cost-Optimal Query Processing in the Cloud 2021 VLDB 8.7199754e-05
2,822 Cost Models for Big Data Query Processing: Learning, Retrofitting, and Our Findings 2020 SIGMOD 8.0898536e-05
3,809 Auto-WLM: Machine Learning Enhanced Workload Management in Amazon Redshift 2023 SIGMOD 7.1074195e-05
3,998 Deploying a Steered Query Optimizer in Production at Microsoft 2022 SIGMOD 6.9676473e-05
4,493 Self-Tuning Query Scheduling for Analytical Workloads 2021 SIGMOD 6.6647555e-05
4,544 ByteGraph: A High-Performance Distributed Graph Database in ByteDance 2022 VLDB 6.6382612e-05
4,649 BigLake: BigQuery’s Evolution toward a Multi-Cloud Lakehouse 2024 SIGMOD 6.586622e-05
4,705 Presto: A Decade of SQL Analytics at Meta 2023 SIGMOD 6.5529421e-05
4,929 AutoSteer: Learned Query Optimization for Any SQL Database 2023 VLDB 6.4423294e-05
5,059 Steering Query Optimizers: A Practical Take on Big Data Workloads 2021 SIGMOD 6.3807509e-05
5,148 LSched: A Workload-Aware Learned Query Scheduler for Analytical Database Systems 2022 SIGMOD 6.3465986e-05
5,369 Intelligent Scaling in Amazon Redshift 2024 SIGMOD 6.2437078e-05
5,390 Magnet: Push-based Shuffle Service for Large-scale Data Processing 2020 VLDB 6.2346971e-05
5,477 PolarDB-IMCI: A Cloud-Native HTAP Database System at Alibaba 2023 SIGMOD 6.2051869e-05
5,821 StreamOps: Cloud-Native Runtime Management for Streaming Services in ByteDance 2023 VLDB 6.07598e-05
7,589 Cost-Intelligent Data Analytics in the Cloud 2024 CIDR 5.5907048e-05
9,008 Making Data Clouds Smarter at Keebo: Automated Warehouse Optimization using Data Learning 2023 SIGMOD 5.3335632e-05
9,756 Efficient Query Re-optimization with Judicious Subquery Selections 2023 SIGMOD 5.2258278e-05
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