Advanced Join Strategies for Large-Scale Distributed Computation
Summary: Proposes novel distributed join strategies for cloud-scale clusters, tackling data movement and parallelism in massive clusters. Introduces robust data-skew handling and exploits opportunities unavailable to centralized DBMSs, validated on Scope clusters. (summarized by gpt-5-nano on Feb 09 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Nicolas Bruno
- 2. YongChul Kwon
- 3. Ming-Chuan Wu
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| Overall Rank | Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 11,360 | Scaling Equi-Joins | 2022 | SIGMOD | 4.1905499e-05 |
| 9,705 | Distributed Numerical and Machine Learning Computations via Two-Phase Execution of Aggregated Join Trees | 2021 | VLDB | 4.2951758e-05 |
| 3,899 | Efficient Join Algorithms For Large Database Tables in a Multi-GPU Environment | 2021 | VLDB | 6.6513982e-05 |
| 8,777 | Accelerate Distributed Joins with Predicate Transfer | 2025 | SIGMOD | 4.4492064e-05 |
| 4,068 | Advanced Partitioning Techniques for Massively Distributed Computation | 2012 | SIGMOD | 6.4748133e-05 |
| 3,428 | Distributed Join Algorithms on Thousands of Cores | 2017 | VLDB | 7.1002401e-05 |
| 1,938 | From Theory to Practice: Efficient Join Query Evaluation in a Parallel Database System | 2015 | SIGMOD | 0.00010025547 |
| 11,898 | Let's Rethink Join Optimization in Distributed Systems | 2015 | CIDR | 4.1905499e-05 |
| 4,161 | Scalable Distributed Stream Join Processing | 2015 | SIGMOD | 6.3883784e-05 |
| 5,309 | Continuous Cloud-Scale Query Optimization and Processing | 2013 | VLDB | 5.5714729e-05 |