Resolving package conflicts with hadoop 0.23.9
Fix UISuite test to handle situations where DEFAULT_PORT is busy on the test machine
Indentation fix
Merge pull request #31 from sundeepn/branch-0.8

Resolving package conflicts with hadoop 0.23.9

Hadoop 0.23.9 is having a package conflict with easymock's dependencies.
Adding Shark 0.7.1 to EC2 scripts
Merge pull request #40 from pwendell/branch-0.8

Adding Shark 0.7.1 to EC2 scripts [branch 0.8 version]

This adds a newer version of Shark to the ec2 scripts. I've tested this for both Hadoop1 and Hadoop2 clusters.
Merge pull request #42 from pwendell/shuffle-read-perf

Fix inconsistent and incorrect log messages in shuffle read path

The user-facing messages generated by the CacheManager are currently wrong and somewhat misleading. This patch makes the messages more accurate. It also uses a consistent representation of the partition being fetched (`rdd_xx_yy`) so that it's easier for users to trace what is going on when reading logs.

(cherry picked from commit ea34c521025d3408d44d45ab5c132fd9791794f6)
Signed-off-by: Reynold Xin <rxin@apache.org>
Merge pull request #43 from mateiz/kryo-fix

Don't allocate Kryo buffers unless needed

I noticed that the Kryo serializer could be slower than the Java one by 2-3x on small shuffles because it spend a lot of time initializing Kryo Input and Output objects. This is because our default buffer size for them is very large. Since the serializer is often used on streams, I made the initialization lazy for that, and used a smaller buffer (auto-managed by Kryo) for input.

(cherry picked from commit e67d5b962a2adddc073cfc9c99be9012fbb69838)
Signed-off-by: Reynold Xin <rxin@apache.org>
add Function3 and WrappedFunction3
fix formating
Add Function4 and WrappedFunction4
Merge pull request #50 from kayousterhout/SPARK-908

Fix race condition in SparkListenerSuite (fixes SPARK-908).

(cherry picked from commit 215238cb399d46c83fafa64b3c98e0ebec21adb9)
Signed-off-by: Reynold Xin <rxin@apache.org>
Merge pull request #49 from mateiz/kryo-fix-2

Fix Chill serialization of Range objects

It used to write out each element one by one, creating very large objects.

(cherry picked from commit 320418f7c8b42d4ce781b32c9ee47a9b54550b89)
Signed-off-by: Reynold Xin <rxin@apache.org>
Merge pull request #47 from xiliu82/branch-0.8

add Function3 and WrappedFunction3

I need these two to add more API to spark streaming
Merge pull request #54 from aoiwelle/remove_unused_imports

Remove unnecessary mutable imports

It appears that the imports aren't necessary here.

(cherry picked from commit dca80094d317363e1e0d7e32bc7dfd99faf943cf)
Signed-off-by: Reynold Xin <rxin@apache.org>
Merge pull request #20 from harveyfeng/hadoop-config-cache

Allow users to pass broadcasted Configurations and cache InputFormats across Hadoop file reads.

Note: originally from https://github.com/mesos/spark/pull/942

Currently motivated by Shark queries on Hive-partitioned tables, where there's a JobConf broadcast for every Hive-partition (i.e., every subdirectory read). The only thing different about those JobConfs is the input path - the Hadoop Configuration that the JobConfs are constructed from remain the same.
This PR only modifies the old Hadoop API RDDs, but similar additions to the new API might reduce computation latencies a little bit for high-frequency FileInputDStreams (which only uses the new API right now).

As a small bonus, added InputFormats caching, to avoid reflection calls for every RDD#compute().

Few other notes:

Added a general soft-reference hashmap in SparkHadoopUtil because I wanted to avoid adding another class to SparkEnv.
SparkContext default hadoopConfiguration isn't cached. There's no equals() method for Configuration, so there isn't a good way to determine when configuration properties have changed.

(cherry picked from commit 4a25b116d4e451afdf10fc4f018c383ed2c7789a)
Signed-off-by: Reynold Xin <rxin@apache.org>
Merge pull request #52 from harveyfeng/hadoop-closure

Add an optional closure parameter to HadoopRDD instantiation to use when creating local JobConfs.

Having HadoopRDD accept this optional closure eliminates the need for the HadoopFileRDD added earlier. It makes the HadoopRDD more general, in that the caller can specify any JobConf initialization flow.

(cherry picked from commit 99796904ae9d00405584ac518b6144973a876e3c)
Signed-off-by: Reynold Xin <rxin@apache.org>
Merge branch 'branch-0.8' of https://git-wip-us.apache.org/repos/asf/incubator-spark into branch-0.8
Merge pull request #38 from AndreSchumacher/pyspark_sorting

SPARK-705: implement sortByKey() in PySpark

This PR contains the implementation of a RangePartitioner in Python and uses its partition ID's to get a global sort in PySpark.

(cherry picked from commit b4fa11f6c96ee37ecd30231c1e22630055f52115)
Signed-off-by: Reynold Xin <rxin@apache.org>
Merge pull request #28 from tgravescs/sparYarnAppName

Allow users to set the application name for Spark on Yarn

(cherry picked from commit 49dbfccf6bab64576d7c594816769c6def01b572)
Signed-off-by: Reynold Xin <rxin@apache.org>