DfAnalyzer: Runtime Dataflow Analysis of Scientific Applications using Provenance
Summary: DfAnalyzer enables runtime dataflow analysis for scientific applications by capturing dataflow, provenance, and execution data to enable runtime queries. Lightweight, pluggable monitoring components integrate with scripts or Spark to enable monitoring, debugging, steering, and analysis. (summarized by gpt-5-nano on Feb 09 2026)
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Authors
- 1. Vítor Silva
- 2. Daniel de Oliveira
- 3. Patrick Valduriez
- 4. Marta Mattoso
Incoming Citations (Sorted by Pagerank)
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Outgoing Citations (Sorted by Pagerank)
Showing 4 of 4 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
| Rank | Cited Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 2,463 | noWorkflow: a Tool for Collecting, Analyzing, and Managing Provenance from Python Scripts | 2017 | VLDB | 8.7561396e-05 |
| 3,535 | Scaling Spark in the Real World: Performance and Usability | 2015 | VLDB | 6.9992495e-05 |
| 3,891 | Slalom: Coasting Through Raw Data via Adaptive Partitioning and Indexing | 2017 | VLDB | 6.659442e-05 |
| 6,836 | An Algebraic Approach for Data-Centric Scientific Workflows | 2011 | VLDB | 4.9114673e-05 |
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