LICENSE and NOTICE files are good Hash files are good Signature files are good No 3rd parties executables Source compiled Run local and standalone tests Test persist off heap with Tachyon looks good
+1 - Henry On Wed, Sep 3, 2014 at 12:24 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 > --------------------------------------------------------------------- To unsubscribe, e-mail: dev-unsubscr...@spark.apache.org For additional commands, e-mail: dev-h...@spark.apache.org
