We are running spark on yarn with combined memory 1TB and when trying to
cache a table partition(which is 100G), seeing a lot of failed collect
stages in the UI and this never succeeds. Because of the failed collect, it
seems like the mapPartitions keep getting resubmitted. We have more than
This is the log output:
2014-11-12 19:07:16,561 INFO thriftserver.SparkExecuteStatementOperation
(Logging.scala:logInfo(59)) - Running query 'CACHE TABLE xyz_cached AS
SELECT * FROM xyz where date_prefix = 20141112'
2014-11-12 19:07:17,455 INFO Configuration.deprecation
On re running the cache statement, from the logs I see that when
collect(stage 1) fails it always leads to mapPartition(stage 0) for one
partition to be re-run. This can be seen from the collect log as well on
the container log:
rg.apache.spark.shuffle.MetadataFetchFailedException: Missing an
