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authorAnkur Dave <ankurdave@gmail.com>2014-01-08 21:19:08 -0800
committerAnkur Dave <ankurdave@gmail.com>2014-01-08 21:19:08 -0800
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Merge remote-tracking branch 'spark-upstream/master' into HEAD
Conflicts: README.md core/src/main/scala/org/apache/spark/util/collection/OpenHashMap.scala core/src/main/scala/org/apache/spark/util/collection/OpenHashSet.scala core/src/main/scala/org/apache/spark/util/collection/PrimitiveKeyOpenHashMap.scala pom.xml project/SparkBuild.scala repl/src/main/scala/org/apache/spark/repl/SparkILoop.scala
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@@ -24,9 +24,9 @@ For its Scala API, Spark {{site.SPARK_VERSION}} depends on Scala {{site.SCALA_VE
# Running the Examples and Shell
Spark comes with several sample programs in the `examples` directory.
-To run one of the samples, use `./run-example <class> <params>` in the top-level Spark directory
-(the `run-example` script sets up the appropriate paths and launches that program).
-For example, try `./run-example org.apache.spark.examples.SparkPi local`.
+To run one of the samples, use `./bin/run-example <class> <params>` in the top-level Spark directory
+(the `bin/run-example` script sets up the appropriate paths and launches that program).
+For example, try `./bin/run-example org.apache.spark.examples.SparkPi local`.
Each example prints usage help when run with no parameters.
Note that all of the sample programs take a `<master>` parameter specifying the cluster URL
@@ -34,8 +34,8 @@ to connect to. This can be a [URL for a distributed cluster](scala-programming-g
or `local` to run locally with one thread, or `local[N]` to run locally with N threads. You should start by using
`local` for testing.
-Finally, you can run Spark interactively through modified versions of the Scala shell (`./spark-shell`) or
-Python interpreter (`./pyspark`). These are a great way to learn the framework.
+Finally, you can run Spark interactively through modified versions of the Scala shell (`./bin/spark-shell`) or
+Python interpreter (`./bin/pyspark`). These are a great way to learn the framework.
# Launching on a Cluster
@@ -56,14 +56,16 @@ Hadoop, you must build Spark against the same version that your cluster uses.
By default, Spark links to Hadoop 1.0.4. You can change this by setting the
`SPARK_HADOOP_VERSION` variable when compiling:
- SPARK_HADOOP_VERSION=1.2.1 sbt/sbt assembly
+ SPARK_HADOOP_VERSION=2.2.0 sbt/sbt assembly
-In addition, if you wish to run Spark on [YARN](running-on-yarn.md), set
+In addition, if you wish to run Spark on [YARN](running-on-yarn.html), set
`SPARK_YARN` to `true`:
SPARK_HADOOP_VERSION=2.0.5-alpha SPARK_YARN=true sbt/sbt assembly
-(Note that on Windows, you need to set the environment variables on separate lines, e.g., `set SPARK_HADOOP_VERSION=1.2.1`.)
+Note that on Windows, you need to set the environment variables on separate lines, e.g., `set SPARK_HADOOP_VERSION=1.2.1`.
+
+For this version of Spark (0.8.1) Hadoop 2.2.x (or newer) users will have to build Spark and publish it locally. See [Launching Spark on YARN](running-on-yarn.html). This is needed because Hadoop 2.2 has non backwards compatible API changes.
# Where to Go from Here