Sharing Data and Work Across Concurrent Analytical Queries
Summary: Two runtime sharing methods for concurrent analytics: SP and GQP. SP and GQP are orthogonal; push SP helps high concurrency (20-48%) but hurts low concurrency; pull SP removes bottlenecks and scales up to 82-86%, yielding a low-vs-high concurrency trade-off. (summarized by gpt-5-nano on Feb 09 2026)
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|---|---|---|---|---|
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| 7,622 | Workload Optimization using SharedDB | 2013 | SIGMOD | 4.6935227e-05 |
| 4,680 | To Share or Not to Share? | 2007 | VLDB | 6.0039406e-05 |
| 2,330 | Concurrent Analytical Query Processing with GPUs | 2014 | VLDB | 9.0192228e-05 |
| 1,429 | A Scalable, Predictable Join Operator for Highly Concurrent Data Warehouses | 2009 | VLDB | 0.00012033518 |
| 9,583 | Reactive and Proactive Sharing Across Concurrent Analytical Queries | 2014 | SIGMOD | 4.3219514e-05 |