[Due to ASF e-mail outage, I'm not if anyone will actually receive this.] Please vote on releasing the following candidate as Apache Spark version 1.0.0! This has only minor changes on top of rc7.
The tag to be voted on is v1.0.0-rc8 (commit 80eea0f): https://git-wip-us.apache.org/repos/asf?p=spark.git;a=commit;h=80eea0f111c06260ffaa780d2f3f7facd09c17bc The release files, including signatures, digests, etc. can be found at: http://people.apache.org/~pwendell/spark-1.0.0-rc8/ 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-1016/ The documentation corresponding to this release can be found at: http://people.apache.org/~pwendell/spark-1.0.0-rc8-docs/ Please vote on releasing this package as Apache Spark 1.0.0! The vote is open until Monday, May 19, at 10:15 UTC and passes if a majority of at least 3 +1 PMC votes are cast. [ ] +1 Release this package as Apache Spark 1.0.0 [ ] -1 Do not release this package because ... To learn more about Apache Spark, please see http://spark.apache.org/ == API Changes == We welcome users to compile Spark applications against 1.0. There are a few API changes in this release. Here are links to the associated upgrade guides - user facing changes have been kept as small as possible. changes to ML vector specification: http://people.apache.org/~pwendell/spark-1.0.0-rc8-docs/mllib-guide.html#from-09-to-10 changes to the Java API: http://people.apache.org/~pwendell/spark-1.0.0-rc8-docs/java-programming-guide.html#upgrading-from-pre-10-versions-of-spark changes to the streaming API: http://people.apache.org/~pwendell/spark-1.0.0-rc8-docs/streaming-programming-guide.html#migration-guide-from-091-or-below-to-1x changes to the GraphX API: http://people.apache.org/~pwendell/spark-1.0.0-rc8-docs/graphx-programming-guide.html#upgrade-guide-from-spark-091 coGroup and related functions now return Iterable[T] instead of Seq[T] ==> Call toSeq on the result to restore the old behavior SparkContext.jarOfClass returns Option[String] instead of Seq[String] ==> Call toSeq on the result to restore old behavior
