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2 changes: 2 additions & 0 deletions docs/monitoring.md
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Expand Up @@ -150,6 +150,8 @@ follows:
Note that in all of these UIs, the tables are sortable by clicking their headers,
making it easy to identify slow tasks, data skew, etc.

In YARN, note that the history server only displays completed Spark jobs. One way to signal the completion of a Spark job is to stop the Spark Context explicitly (`sc.stop()`), or in Python using the `with SparkContext() as sc:` to handle the Spark Context setup and tear down, and still show the job history on the UI.
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Actually, this is true not only in YARN. I will fix this myself when I merge


# Metrics

Spark has a configurable metrics system based on the
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