Charles Reiss created SPARK-4351:
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Summary: Record cacheable RDD reads and display RDD miss rates
Key: SPARK-4351
URL: https://issues.apache.org/jira/browse/SPARK-4351
Project: Spark
Issue Type: Improvement
Reporter: Charles Reiss
Priority: Minor
Currently, when Spark fails to keep an RDD cached, there is little visibility
to the user (beyond performance effects), especially if the user is not reading
executor logs. We could expose this information to the Web UI and the event log
like we do for RDD storage information by reporting RDD reads and their results
with task metrics.
>From this, live computation of RDD miss rates is straightforward, and
>information in the event log would enable more complicated post-hoc analyses.
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