DfAnalyzer: Runtime Dataflow Analysis of Scientific Applications using Provenance - LIRMM - Laboratoire d’Informatique, de Robotique et de Microélectronique de Montpellier
Article Dans Une Revue Proceedings of the VLDB Endowment (PVLDB) Année : 2018

DfAnalyzer: Runtime Dataflow Analysis of Scientific Applications using Provenance

Résumé

We present DfAnalyzer, a tool that enables monitoring, debugging, steering, and analysis of dataflows while being generated by scientific applications. It works by capturing strategic domain data, registering provenance and execution data to enable queries at runtime. DfAnalyzer provides lightweight dataflow monitoring components to be invoked by high performance applications. It can be plugged in scripts, or Spark applications, in the same way users already plug visualization library components. During this demo, we will show how DfAnalyzer captures the dataflow, provenance, as well as how it provides runtime data analyses of applications. We will also encourage attendees to use DfAnalyzer for their own applications. PVLDB Reference Format: Vítor Silva, Daniel de Oliveira, Patrick Valduriez, Marta Mattoso. Word Template for VLDB Conferences. PVLDB, 11(5): xxxx-2018, 2018. DOI: https://doi.org/TBD
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Dates et versions

lirmm-01867887 , version 1 (04-09-2018)

Identifiants

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Vítor Silva, Daniel de Oliveira, Patrick Valduriez, Marta Mattoso. DfAnalyzer: Runtime Dataflow Analysis of Scientific Applications using Provenance. Proceedings of the VLDB Endowment (PVLDB), 2018, 11 (12), pp.2082-2085. ⟨10.14778/3229863.3236265⟩. ⟨lirmm-01867887⟩
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