Spark on YARN
We have a fair-sharing cluster set up, including the external shuffle service. When a new job arrives, existing jobs are successfully preempted down to fit.
A spate of these messages arrives:
ExecutorLostFailure (executor 48 exited unrelated to the running tasks) Reason: Container container_1458935819920_0019_01_000143 on host: ip-10-12-46-235.us-west-2.compute.internal was preempted.
This seems fine - the problem is that soon thereafter, our whole application fails because it is unable to fetch blocks from the pre-empted containers:
org.apache.spark.storage.BlockFetchException: Failed to fetch block from 1 locations. Most recent failure cause:
Caused by: java.io.IOException: Failed to connect to ip-10-12-46-235.us-west-2.compute.internal/10.12.46.235:55681
Caused by: java.net.ConnectException: Connection refused: ip-10-12-46-235.us-west-2.compute.internal/10.12.46.235:55681
Full stack: https://gist.github.com/milescrawford/33a1c1e61d88cc8c6daf
Spark does not attempt to recreate these blocks - the tasks simply fail over and over until the maxTaskAttempts value is reached.
It appears to me that there is some fault in the way preempted containers are being handled - shouldn't these blocks be recreated on demand?
- is related to
SPARK-17485 Failed remote cached block reads can lead to whole job failure