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Using Spark's "Hadoop Free" Build |
Using Spark's "Hadoop Free" Build |
Licensed to the Apache Software Foundation (ASF) under one or more
contributor license agreements. See the NOTICE file distributed with
this work for additional information regarding copyright ownership.
The ASF licenses this file to You under the Apache License, Version 2.0
(the "License"); you may not use this file except in compliance with
the License. You may obtain a copy of the License at
http://www.apache.org/licenses/LICENSE-2.0
Unless required by applicable law or agreed to in writing, software
distributed under the License is distributed on an "AS IS" BASIS,
WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
See the License for the specific language governing permissions and
limitations under the License.
|
Spark uses Hadoop client libraries for HDFS and YARN. Starting in version Spark 1.4, the project packages "Hadoop free" builds that lets you more easily connect a single Spark binary to any Hadoop version. To use these builds, you need to modify SPARK_DIST_CLASSPATH to include Hadoop's package jars. The most convenient place to do this is by adding an entry in conf/spark-env.sh.
This page describes how to connect Spark to Hadoop for different types of distributions.
For Apache distributions, you can use Hadoop's 'classpath' command. For instance:
{% highlight bash %}
export SPARK_DIST_CLASSPATH=$(hadoop classpath)
export SPARK_DIST_CLASSPATH=$(/path/to/hadoop/bin/hadoop classpath)
export SPARK_DIST_CLASSPATH=$(hadoop --config /path/to/configs classpath)
{% endhighlight %}