Abstract
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 scientific code 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.
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