If I am not mistaken, the binaries for Scala 2.11 were generated against hadoop 1.
What about binaries for Scala 2.11 against hadoop 2.x ? Cheers On Sun, Nov 22, 2015 at 2:21 PM, Michael Armbrust <mich...@databricks.com> wrote: > In order to facilitate community testing of Spark 1.6.0, I'm excited to > announce the availability of an early preview of the release. This is not a > release candidate, so there is no voting involved. However, it'd be awesome > if community members can start testing with this preview package and report > any problems they encounter. > > This preview package contains all the commits to branch-1.6 > <https://github.com/apache/spark/tree/branch-1.6> till commit > 308381420f51b6da1007ea09a02d740613a226e0 > <https://github.com/apache/spark/tree/v1.6.0-preview2>. > > The staging maven repository for this preview build can be found here: > https://repository.apache.org/content/repositories/orgapachespark-1162 > > Binaries for this preview build can be found here: > http://people.apache.org/~pwendell/spark-releases/spark-v1.6.0-preview2-bin/ > > A build of the docs can also be found here: > http://people.apache.org/~pwendell/spark-releases/spark-v1.6.0-preview2-docs/ > > The full change log for this release can be found on JIRA > <https://issues.apache.org/jira/browse/SPARK-11908?jql=project%20%3D%20SPARK%20AND%20fixVersion%20%3D%201.6.0> > . > > *== How can you help? ==* > > If you are a Spark user, you can help us test this release by taking a > Spark workload and running on this preview release, then reporting any > regressions. > > *== Major Features ==* > > When testing, we'd appreciate it if users could focus on areas that have > changed in this release. Some notable new features include: > > SPARK-11787 <https://issues.apache.org/jira/browse/SPARK-11787> *Parquet > Performance* - Improve Parquet scan performance when using flat schemas. > SPARK-10810 <https://issues.apache.org/jira/browse/SPARK-10810> *Session * > *Management* - Multiple users of the thrift (JDBC/ODBC) server now have > isolated sessions including their own default database (i.e USE mydb) > even on shared clusters. > SPARK-9999 <https://issues.apache.org/jira/browse/SPARK-9999> *Dataset > API* - A new, experimental type-safe API (similar to RDDs) that performs > many operations on serialized binary data and code generation (i.e. Project > Tungsten) > SPARK-10000 <https://issues.apache.org/jira/browse/SPARK-10000> *Unified > Memory Management* - Shared memory for execution and caching instead of > exclusive division of the regions. > SPARK-10978 <https://issues.apache.org/jira/browse/SPARK-10978> *Datasource > API Avoid Double Filter* - When implementing a datasource with filter > pushdown, developers can now tell Spark SQL to avoid double evaluating a > pushed-down filter. > SPARK-2629 <https://issues.apache.org/jira/browse/SPARK-2629> *New > improved state management* - trackStateByKey - a DStream transformation > for stateful stream processing, supersedes updateStateByKey in > functionality and performance. > > Happy testing! > > Michael > >
