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From Sean McNamara <Sean.McNam...@Webtrends.com>
Subject RE: [VOTE] Release Apache Spark 1.1.0 (RC3)
Date Wed, 03 Sep 2014 00:30:52 GMT
+1
________________________________________
From: Patrick Wendell [pwendell@gmail.com]
Sent: Saturday, August 30, 2014 4:08 PM
To: dev@spark.apache.org
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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