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HOTFIX: Minor doc update for sbt change
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README.md

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Spark uses the Hadoop core library to talk to HDFS and other Hadoop-supported
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storage systems. Because the protocols have changed in different versions of
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Hadoop, you must build Spark against the same version that your cluster runs.
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You can change the version by setting the `SPARK_HADOOP_VERSION` environment
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when building Spark.
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You can change the version by setting `-Dhadoop.version` when building Spark.
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For Apache Hadoop versions 1.x, Cloudera CDH MRv1, and other Hadoop
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versions without YARN, use:
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# Apache Hadoop 1.2.1
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$ SPARK_HADOOP_VERSION=1.2.1 sbt/sbt assembly
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$ sbt/sbt -Dhadoop.version=1.2.1 assembly
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# Cloudera CDH 4.2.0 with MapReduce v1
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$ SPARK_HADOOP_VERSION=2.0.0-mr1-cdh4.2.0 sbt/sbt assembly
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$ sbt/sbt -Dhadoop.version=2.0.0-mr1-cdh4.2.0 assembly
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For Apache Hadoop 2.2.X, 2.1.X, 2.0.X, 0.23.x, Cloudera CDH MRv2, and other Hadoop versions
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with YARN, also set `SPARK_YARN=true`:
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# Apache Hadoop 2.0.5-alpha
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$ SPARK_HADOOP_VERSION=2.0.5-alpha SPARK_YARN=true sbt/sbt assembly
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$ sbt/sbt -Dhadoop.version=2.0.5-alpha -Pyarn assembly
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# Cloudera CDH 4.2.0 with MapReduce v2
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$ SPARK_HADOOP_VERSION=2.0.0-cdh4.2.0 SPARK_YARN=true sbt/sbt assembly
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$ sbt/sbt -Dhadoop.version=2.0.0-cdh4.2.0 -Pyarn assembly
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# Apache Hadoop 2.2.X and newer
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$ SPARK_HADOOP_VERSION=2.2.0 SPARK_YARN=true sbt/sbt assembly
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$ sbt/sbt -Dhadoop.version=2.2.0 -Pyarn assembly
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When developing a Spark application, specify the Hadoop version by adding the
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"hadoop-client" artifact to your project's dependencies. For example, if you're

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