Comparing Data Lake Job Runs

Yanan Cai shows how to compare stats on different executions of a job:

Troubleshooting issues in recurring job is a time-consuming task. It starts with searching through the Job Browser to find instances of a recurring job and identifying both baseline and anomalous performance. This is followed by multi-way comparisons between job instances to figure out what has been changed in the query, data or environment. This is followed by analysis to discover which changes may have performance impact. While this is happening production workloads continue to under-perform or go down.

Azure Data Lake Tools for Visual Studio now makes it easy to spot anomalies and quickly trace the key characteristics across recurring job instances allowing for an efficient debugging experience. The Pipeline Browser automatically groups recurring jobs to simplify discovery of all runs. The Related Job View collects data about inputs, outputs and execution across multiple runs into a single visualization.

Read on for more.

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