Optimizing Analytic Data Flows for Multiple Execution Engines
Summary: Optimizes analytic data flows across DBMS, MapReduce, and orchestration engines for a single objective: performance. Introduces data shipping, function shipping, and operation decomposition, with cross-engine flow graphs and demonstrated performance gains. (summarized by gpt-5-nano on Feb 09 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Alkis Simitsis
- 2. Kevin Wilkinson
- 3. Malu Castellanos
- 4. Umeshwar Dayal
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Showing 11 of 11 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
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Semantically Similar Papers
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|---|---|---|---|---|
| 658 | Towards a Unified Architecture for in-RDBMS Analytics | 2012 | SIGMOD | 0.00018506577 |
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| 538 | The Dataflow Model: A Practical Approach to Balancing Correctness, Latency, and Cost in Massive-Scale, Unbounded, Out-of-Order Data Processing | 2015 | VLDB | 0.00020678804 |
| 9,973 | End-to-End Declarative Data Analytics: Co-designing Engines, Interfaces, and Cloud Infrastructure | 2026 | CIDR | 4.1945683e-05 |
| 2,172 | Spinning Fast Iterative Data Flows | 2012 | VLDB | 9.3706587e-05 |
| 3,674 | An Approach to Optimize Data Processing in Business Processes | 2007 | VLDB | 6.8558403e-05 |
| 2,611 | Opening the Black Boxes in Data Flow Optimization | 2012 | VLDB | 8.4536967e-05 |
| 5,050 | xPAD: A Platform for Analytic Data Flows | 2013 | SIGMOD | 5.7340229e-05 |