+1. Ran spark on yarn on hadoop 0.23 and 2.x. Tom
On Wednesday, September 3, 2014 2:25 AM, Patrick Wendell <pwend...@gmail.com> wrote: Please vote on releasing the following candidate as Apache Spark version 1.1.0! The tag to be voted on is v1.1.0-rc4 (commit 2f9b2bd): https://git-wip-us.apache.org/repos/asf?p=spark.git;a=commit;h=2f9b2bd7844ee8393dc9c319f4fefedf95f5e460 The release files, including signatures, digests, etc. can be found at: http://people.apache.org/~pwendell/spark-1.1.0-rc4/ Release artifacts are signed with the following key: https://people.apache.org/keys/committer/pwendell.asc The staging repository for this release can be found at: https://repository.apache.org/content/repositories/orgapachespark-1031/ The documentation corresponding to this release can be found at: http://people.apache.org/~pwendell/spark-1.1.0-rc4-docs/ Please vote on releasing this package as Apache Spark 1.1.0! The vote is open until Saturday, September 06, at 08:30 UTC and passes if a majority of at least 3 +1 PMC votes are cast. [ ] +1 Release this package as Apache Spark 1.1.0 [ ] -1 Do not release this package because ... To learn more about Apache Spark, please see http://spark.apache.org/ == Regressions fixed since RC3 == SPARK-3332 - Issue with tagging in EC2 scripts SPARK-3358 - Issue with regression for m3.XX instances == What justifies a -1 vote for this release? == This vote is happening very late into the QA period compared with previous votes, so -1 votes should only occur for significant regressions from 1.0.2. Bugs already present in 1.0.X will not block this release. == What default changes should I be aware of? == 1. The default value of "spark.io.compression.codec" is now "snappy" --> Old behavior can be restored by switching to "lzf" 2. PySpark now performs external spilling during aggregations. --> Old behavior can be restored by setting "spark.shuffle.spill" to "false". 3. PySpark uses a new heuristic for determining the parallelism of shuffle operations. --> Old behavior can be restored by setting "spark.default.parallelism" to the number of cores in the cluster. --------------------------------------------------------------------- To unsubscribe, e-mail: dev-unsubscr...@spark.apache.org For additional commands, e-mail: dev-h...@spark.apache.org
