Please vote on releasing the following candidate as Apache Spark version 1.0.0!
This patch has minor documentation changes and fixes on top of rc6. The tag to be voted on is v1.0.0-rc7 (commit 9212b3e): https://git-wip-us.apache.org/repos/asf?p=spark.git;a=commit;h=9212b3e5bb5545ccfce242da8d89108e6fb1c464 The release files, including signatures, digests, etc. can be found at: http://people.apache.org/~pwendell/spark-1.0.0-rc7/ 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-1015 The documentation corresponding to this release can be found at: http://people.apache.org/~pwendell/spark-1.0.0-rc7-docs/ Please vote on releasing this package as Apache Spark 1.0.0! The vote is open until Sunday, May 18, at 09:12 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-rc5-docs/mllib-guide.html#from-09-to-10 changes to the Java API: http://people.apache.org/~pwendell/spark-1.0.0-rc5-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-rc5-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-rc5-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
