Andrew and developers, thank you for excellent release!
It fixed almost all of our issues. Now we are migrating to Spark from Zoo of
Python, Java, Hive, Pig jobs.
Our Scala/Spark jobs often failed on 1.1. Spark 1.1.1 works like a Swiss
watch.
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About version compatibility and upgrade path - can the Java application
dependencies and the Spark server be upgraded separately (i.e. will 1.1.0
library work with 1.1.1 server, and vice versa), or do they need to be
upgraded together?
Thanks!
*Romi Kuntsman*, *Big Data Engineer*
By the Spark server do you mean the standalone Master? It is best if they
are upgraded together because there have been changes to the Master in
1.1.1. Although it might just work, it's highly recommended to restart
your cluster manager too.
2014-12-03 13:19 GMT-08:00 Romi Kuntsman
Because this was a maintenance release, we should not have introduced any
binary backwards or forwards incompatibilities. Therefore, applications
that were written and compiled against 1.1.0 should still work against a
1.1.1 cluster, and vice versa.
On Wed, Dec 3, 2014 at 1:30 PM, Andrew Or
I am happy to announce the availability of Spark 1.1.1! This is a
maintenance release with many bug fixes, most of which are concentrated in
the core. This list includes various fixes to sort-based shuffle, memory
leak, and spilling issues. Contributions from this release came from 55
developers.
