+1

Tested Scala/MLlib apps on Fedora 20 (OpenJDK 7) and OS X 10.9 (Oracle JDK 8).


best,
wb


----- Original Message -----
> From: "Patrick Wendell" <pwend...@gmail.com>
> To: dev@spark.apache.org
> Sent: Saturday, August 30, 2014 5:07:52 PM
> Subject: [VOTE] Release Apache Spark 1.1.0 (RC3)
> 
> Please vote on releasing the following candidate as Apache Spark version
> 1.1.0!
> 
> The tag to be voted on is v1.1.0-rc3 (commit b2d0493b):
> https://git-wip-us.apache.org/repos/asf?p=spark.git;a=commit;h=b2d0493b223c5f98a593bb6d7372706cc02bebad
> 
> The release files, including signatures, digests, etc. can be found at:
> http://people.apache.org/~pwendell/spark-1.1.0-rc3/
> 
> 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-1030/
> 
> The documentation corresponding to this release can be found at:
> http://people.apache.org/~pwendell/spark-1.1.0-rc3-docs/
> 
> Please vote on releasing this package as Apache Spark 1.1.0!
> 
> The vote is open until Tuesday, September 02, at 23:07 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 RC1 ==
> - Build issue for SQL support:
> https://issues.apache.org/jira/browse/SPARK-3234
> - EC2 script version bump to 1.1.0.
> 
> == 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".
> 
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> 
> 

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