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 ?


On Sun, Nov 22, 2015 at 2:21 PM, Michael Armbrust <mich...@databricks.com>

> 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

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