Project: Alluxio (Runtime / Cloud Native Storage)
File: Hadoop-MapReduce.md

layout: global title: Running Apache Hadoop MapReduce on Alluxio This guide describes how to configure Alluxio with , so that your MapReduce programs can read+write data stored in Alluxio. Alluxio has been set up and is running. Make sure that the Alluxio client jar is available on each machine. This Alluxio client jar file can be found at `{{site.ALLUXIOCLIENTJAR_PATH}}` in the tarball downloaded from the Alluxio . In order to run map-reduce examples, we also recommend downloading the based on your Hadoop version. For example, if you are using Hadoop 2.7 download this . This step is only required for Hadoop 1.x and can be skipped by users of Hadoop 2.x or later. Add the following property to the `core-site.xml` of your Hadoop installation: ```xml <property> <name>fs.alluxio.impl</name> <value>alluxio.hadoop.FileSystem</value> <description>The Alluxio FileSystem</description> </property> ``` This will allow MapReduce jobs to recognize URIs with Alluxio scheme `alluxio://` in their input and output files. In order for the MapReduce applications to read and write files in Alluxio, the Alluxio client jar must be on the JVM classpath of all nodes of the application. The Alluxio client jar should also be added to the `HADOOP_CLASSPATH` environment variable. This makes the Alluxio client available to JVMs which are created when running `hadoop jar` command: ```shell $ export HADOOPCLASSPATH={{site.ALLUXIOCLIENTJARPATH}}:${HADOOP_CLASSPATH} ``` You can use the `-libjars` command line option when using `hadoop jar ...`, specifying `{{site.ALLUXIOCLIENTJAR_PATH}}` as the argument of `-libjars`. Hadoop will place the jar in the Hadoop DistributedCache, making it available to all the nodes. For example, the following command adds the Alluxio client jar to the `-libjars` option: ```shell $ ./bin/hadoop jar share/hadoop/mapreduce/hadoop-mapreduce-examples-2.7.3.jar wordcount \ -libjars {{site.ALLUXIOCLIENTJAR_PATH}} <INPUT FILES> <OUTPUT DIRECTORY> ``` Alternative configurations are described in the section. For this example, we will use a pseudo-distributed Hadoop cluster, started by running: ```shell $ cd $HADOOP_HOME $ ./bin/stop-all.sh $ ./bin/start-all.sh ``` Depending on the Hadoop version, you may need to replace `./bin` with `./sbin`. Start Alluxio locally: ```shell $ ./bin/alluxio process start local ``` You can add a sample file to Alluxio to run MapReduce wordcount on. From your Alluxio directory: ```shell $ ./bin/alluxio fs mkdir /wordcount $ ./bin/alluxio fs cp file://LICENSE /wordcount/input.txt ``` This command will copy the `LICENSE` file into the Alluxio namespace with the path `/wordcount/input.txt`. Now we can run a MapReduce job (using Hadoop 2.7.3 as example) for wordcount. ```shell $ ./bin/hadoop jar share/hadoop/mapreduce/hadoop-mapreduce-examples-2.7.3.jar wordcount \ -libjars {{site.ALLUXIOCLIENTJAR_PATH}} \ alluxio://localhost:19998/wordcount/input.txt \ alluxio://localhost:19998/wordcount/output ``` After this job completes, the result of the wordcount will be in the `/wordcount/output` directory in Alluxio. You can see the resulting files by running: ```shell $ ./bin/alluxio fs ls /wordcount/output $ ./bin/alluxio fs cat /wordcount/output/part-r-00000 ``` TipThe previous wordcount example is also applicable to Alluxio in HA mode. See the instructions on . This guide on describes several ways to distribute the jars to nodes in the

From that guide, the recommended way to distribute the Alluxio client jar is to use the distributed cache, via the `-libjars` command line option. Another way to distribute the client jar is to manually distribute it to all the Hadoop nodes. You could place the client jar `{{site.ALLUXIOCLIENTJARPATH}}` in the `$HADOOPHOME/lib` (it may be `$HADOOP_HOME/share/hadoop/common/lib` for different versions of Hadoop) directory of every MapReduce node, and then restart Hadoop. Alternatively, add this jar to `mapreduce.application.classpath` system property for your Hadoop deployment to the Alluxio client jar is on the classpath. Note that the jars must be installed again for each new release. On the other hand, when the jar is already on every node, then the `-libjars` command line option is not needed. Alluxio configuration parameters can be added to the Hadoop `core-site.xml` file to affect all MapReduce jobs. For example, when Alluxio is running in HA mode, all MapReduce jobs will need to have the Alluxio client configured to communicate to the masters in HA mode. To configure clients to communicate with an Alluxio cluster in HA mode using internal leader election, the following section would need to be added to your Hadoop installation's `core-site.xml` ```xml <configuration> <property> <name>alluxio.master.rpc.addresses</name> <value>masterhostname1:19998,masterhostname2:19998,masterhostname3:19998</value> </property> </configuration> ``` See for more details. Hadoop MapReduce users can add `"-Dproperty=value"` after the `hadoop jar` or `yarn jar` command and the properties will be propagated to all the tasks of this job. For example, the following MapReduce wordcount job sets write type to `CACHE_THROUGH` when writing to Alluxio: ```shell $ ./bin/hadoop jar libexec/share/hadoop/mapreduce/hadoop-mapreduce-examples-2.7.3.jar wordcount \ -Dalluxio.user.file.writetype.default=CACHE_THROUGH \ -libjars {{site.ALLUXIOCLIENTJAR_PATH}} \ <INPUT FILES> <OUTPUT DIRECTORY> ``` Logs with Hadoop can be modified in many different ways. If you wish to directly modify the `log4j.properties` file for Hadoop, then you can add or modify appenders within `${HADOOP_HOME}/conf/log4j.properties` on each of the nodes in your cluster. You may also modify the configuration values in in your installation. If you simply wish to modify log levels then your can change `mapreduce.map.log.level` or `mapreduce.reduce.log.level`. If you are using YARN then you may also wish to modify some of the `yarn.log.*` properties which can be found in A: This error message is seen when your MapReduce application tries to access Alluxio as an HDFS-compatible file system, but the `alluxio://` scheme is not recognized by the application. Please make sure your Hadoop configuration file `core-site.xml` has the following property: ```xml <configuration> <property> <name>fs.alluxio.impl</name> <value>alluxio.hadoop.FileSystem</value> </property> </configuration> ``` A: This error message is seen when your MapReduce application tries to access Alluxio as an HDFS-compatible file system, the `alluxio://` scheme has been configured correctly but the Alluxio client jar is not found on the classpath of your application. You can append the client jar to `$HADOOP_CLASSPATH`: ```shell $ export HADOOPCLASSPATH={{site.ALLUXIOCLIENTJARPATH}}:${HADOOP_CLASSPATH} ``` If the corresponding classpath has been set but exceptions still exist, users can check whether the path is valid by: ```shell $ ls {{site.ALLUXIOCLIENTJAR_PATH}} ```