docs/src/site/markdown/install.md - tez - Git at Google

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 <head><title>Install and Deployment Instructions</title></head>

 Install/Deploy Instructions for Tez
 ---------------------------------------------------------------------------
 Replace x.y.z with the tez release number that you are using. E.g. 0.5.0. For Tez
 versions 0.8.3 and higher, Tez needs Apache Hadoop to be of version 2.6.0 or higher.

 1.  Deploy Apache Hadoop using version of 2.6.0 or higher.
     -   You need to change the value of the hadoop.version property in the
         top-level pom.xml to match the version of the hadoop branch being used.

     ```
     $ hadoop version
     ```

 2.  Build tez using `mvn clean package -DskipTests=true -Dmaven.javadoc.skip=true`
     -   This assumes that you have already installed JDK6 or later and Maven 3 or later.
     -   Tez also requires Protocol Buffers 2.5.0, including the protoc-compiler.
         *   This can be downloaded from https://github.com/google/protobuf/tags/.
         *   On Mac OS X with the homebrew package manager `brew install protobuf250`
         *   For rpm-based linux systems, the yum repos may not have the 2.5.0 version.
             `rpm.pbone.net` has the protobuf-2.5.0 and protobuf-compiler-2.5.0 packages.
     -   If you prefer to run the unit tests, remove skipTests from the
         command above.
     -   If you use Eclipse IDE, you can import the projects using
         "Import/Maven/Existing Maven Projects". Eclipse does not
         automatically generate Java sources or include the generated
         sources into the projects. Please build using maven as described
         above and then use Project Properties to include
         "target/generatedsources/java" as a source directory into the
         "Java Build Path" for these projects: tez-api, tez-mapreduce,
         tez-runtime-internals and tez-runtime-library. This needs to be done
         just once after importing the project.
 3.  Copy the relevant tez tarball into HDFS, and configure tez-site.xml
     -   A tez tarball containing tez and hadoop libraries will be found
         at tez-dist/target/tez-x.y.z-SNAPSHOT.tar.gz
     -   Assuming that the tez jars are put in /apps/ on HDFS, the
         command would be

     ```
     hadoop dfs -mkdir /apps/tez-x.y.z-SNAPSHOT
     hadoop dfs -copyFromLocal tez-dist/target/tez-x.y.z-SNAPSHOT-archive.tar.gz /apps/tez-x.y.z-SNAPSHOT/
     ```

     -   tez-site.xml configuration.
         -   Set tez.lib.uris to point to the tar.gz uploaded to HDFS.
             Assuming the steps mentioned so far were followed,
             set tez.lib.uris to `${fs.defaultFS}/apps/tez-x.y.z-SNAPSHOT/tez-x.y.z-SNAPSHOT.tar.gz`
         -   Ensure tez.use.cluster.hadoop-libs is not set in tez-site.xml,
             or if it is set, the value should be false
     -  Please note that the tarball version should match the version of
        the client jars used when submitting Tez jobs to the cluster.
        Please refer to the [Version Compatibility Guide](https://cwiki.apache.org/confluence/display/TEZ/Version+Compatibility)
        for more details on version compatibility and detecting mismatches.
 4.  Optional: If running existing MapReduce jobs on Tez. Modify
     mapred-site.xml to change "mapreduce.framework.name" property from
     its default value of "yarn" to "yarn-tez"
 5.  Configure the client node to include the tez-libraries in the hadoop
     classpath
     -   Extract the tez minimal tarball created in step 2 to a local directory
         (assuming TEZ_JARS is where the files will be decompressed for
         the next steps)

     ```
     tar -xvzf tez-dist/target/tez-x.y.z-minimal.tar.gz -C $TEZ_JARS
     ```

     -   set TEZ_CONF_DIR to the location of tez-site.xml
     -   Add $TEZ_CONF_DIR, ${TEZ_JARS}/* and ${TEZ_JARS}/lib/* to the application classpath.
         For example, doing it via the standard Hadoop tool chain would use the following command
 	to set up the application classpath:

     ```
     export HADOOP_CLASSPATH=${TEZ_CONF_DIR}:${TEZ_JARS}/*:${TEZ_JARS}/lib/*
     ```

     -   Please note the "*" which is an important requirement when
         setting up classpaths for directories containing jar files.
 6.  There is a basic example of using an MRR job in the tez-examples.jar.
     Refer to OrderedWordCount.java in the source code. To run this
     example:

     ```
     $HADOOP_PREFIX/bin/hadoop jar tez-examples.jar orderedwordcount <input> <output>
     ```

     This will use the TEZ DAG ApplicationMaster to run the ordered word
     count job. This job is similar to the word count example except that
     it also orders all words based on the frequency of occurrence.

     Tez DAGs could be run separately as different applications or
     serially within a single TEZ session. There is a different variation
     of orderedwordcount in tez-tests that supports the use of Sessions
     and handling multiple input-output pairs. You can use it to run
     multiple DAGs serially on different inputs/outputs.

     ```
     $HADOOP_PREFIX/bin/hadoop jar tez-tests.jar testorderedwordcount <input1> <output1> <input2> <output2> <input3> <output3> ...
     ```

     The above will run multiple DAGs for each input-output pair.

     To use TEZ sessions, set -DUSE_TEZ_SESSION=true

     ```
     $HADOOP_PREFIX/bin/hadoop jar tez-tests.jar testorderedwordcount -DUSE_TEZ_SESSION=true <input1> <output1> <input2> <output2>
     ```
 7.  Submit a MR job as you normally would using something like:

     ```
     $HADOOP_PREFIX/bin/hadoop jar hadoop-mapreduce-client-jobclient-3.0.0-SNAPSHOT-tests.jar sleep -mt 1 -rt 1 -m 1 -r 1
     ```

     This will use the TEZ DAG ApplicationMaster to run the MR job. This
     can be verified by looking at the AM’s logs from the YARN ResourceManager UI.
     This needs mapred-site.xml to have "mapreduce.framework.name" set to "yarn-tez"

 Various ways to configure tez.lib.uris
 ---------------------------------------

 The `tez.lib.uris` configuration property supports a comma-separated list of values. The
 types of values supported are:
   - Path to simple file
   - Path to a directory
   - Path to a compressed archive ( tarball, zip, etc).

 For simple files and directories, Tez will add all these files and first-level entries in the
 directories (recursive traversal of dirs is not supported) into the working directory of the
 Tez runtime and they will automatically be included into the classpath. For archives i.e.
 files whose names end with generally known compressed archive suffixes such as 'tgz',
 'tar.gz', 'zip', etc. will be uncompressed into the container working directory too. However,
 given that the archive structure is not known to the Tez framework, the user is expected to
 configure `tez.lib.uris.classpath` to ensure that the nested directory structure of an
 archive is added to the classpath. This classpath values should be relative i.e. the entries
 should start with "./".

 Hadoop Installation dependent Install/Deploy Instructions
 ---------------------------------------------------------

 The above install instructions use Tez with pre-packaged Hadoop libraries included in the package and is the
 recommended method for installation. A full tarball with all dependencies is a better approach to ensure
 that existing jobs continue to run during a cluster's rolling upgrade.

 Although the `tez.lib.uris` configuration options enable a wide variety of usage patterns, there
 are 2 main alternative modes that are supported by the framework:

 1. Mode A: Using a tez tarball on HDFS along with Hadoop libraries available on the cluster.
 2. Mode B: Using a tez tarball along with the Hadoop tarball.

 Both these modes will require a tez build without Hadoop dependencies and that is available at
 tez-dist/target/tez-x.y.z-minimal.tar.gz.

 For Mode A: Tez tarball with using existing cluster Hadoop libraries by leveraging yarn.application.classpath
 -------------------------------------------------------------------------------------------------------------

 This mode is not recommended for clusters that use rolling upgrades. Additionally, it is the user's responsibility
 to ensure that the tez version being used is compatible with the version of Hadoop running on the cluster.
 Step 3 above changes as follows. Also subsequent steps should use tez-dist/target/tez-x.y.z-minimal.tar.gz
 instead of tez-dist/target/tez-x.y.z.tar.gz

   - A tez build without Hadoop dependencies will be available at tez-dist/target/tez-x.y.z-minimal.tar.gz
     Assuming that the tez jars are put in /apps/ on HDFS, the command would be

     ```
     "hadoop fs -mkdir /apps/tez-x.y.z"
     "hadoop fs -copyFromLocal tez-dist/target/tez-x.y.z-minimal.tar.gz /apps/tez-x.y.z"
     ```

   - tez-site.xml configuration
     - Set tez.lib.uris to point to the paths in HDFS containing the tez jars. Assuming the steps mentioned so far were followed,
 set tez.lib.uris to `${fs.defaultFS}/apps/tez-x.y.z/tez-x.y.z-minimal.tar.gz`
     - Set tez.use.cluster.hadoop-libs to true

 For Mode B: Tez tarball with Hadoop tarball
 --------------------------------------------

 This mode will support rolling upgrades. It is the user's responsibility to ensure that the
 versions of Tez and Hadoop being used are compatible.
 To do this configuration, we need to change Step 3 of the
 default instructions in the following ways.

   - Assuming that the tez archives/jars are put in /apps/ on HDFS, the command to put this
 minimal Tez archive into HDFS would be:

   ```
   "hadoop fs -mkdir /apps/tez-x.y.z"
   "hadoop fs -copyFromLocal tez-dist/target/tez-x.y.z-minimal.tar.gz /apps/tez-x.y.z"
   ```

   - Alternatively, you can put the minimal directory directly into HDFS and
   reference the jars, instead of using an archive. The command to put
   the minimal directory into HDFS would be:

   ```
   "hadoop fs -copyFromLocal tez-dist/target/tez-x.y.z-minimal/* /apps/tez-x.y.z"
   ```

   - After building hadoop, the hadoop tarball will be available at
   hadoop/hadoop-dist/target/hadoop-x.y.z-SNAPSHOT.tar.gz
   - Assuming that the hadoop jars are put in /apps/ on HDFS, the command to put this
     Hadoop archive into HDFS would be:

   ```
   "hadoop fs -mkdir /apps/hadoop-x.y.z"
   "hadoop fs -copyFromLocal hadoop-dist/target/hadoop-x.y.z-SNAPSHOT.tar.gz /apps/hadoop-x.y.z"
   ```

   - tez-site.xml configuration
      - Set tez.lib.uris to point to the the archives and jars that are needed for Tez/Hadoop.

      - Example: When using both Tez and Hadoop archives, set tez.lib.uris to
      `${fs.defaultFS}/apps/tez-x.y.z/tez-x.y.z-minimal.tar.gz#tez,${fs.defaultFS}/apps/hadoop-x.y.z/hadoop-x.y.z-SNAPSHOT.tar.gz#hadoop-mapreduce`

     - Example: When using Tez jars with a Hadoop archive, set tez.lib.uris to:
     `${fs.defaultFS}/apps/tez-x.y.z,${fs.defaultFS}/apps/tez-x.y.z/lib,${fs.defaultFS}/apps/hadoop-x.y.z/hadoop-x.y.z-SNAPSHOT.tar.gz#hadoop-mapreduce`

     - In tez.lib.uris, the text immediately following the '#' symbol is the fragment that
       refers to the symlink that will be created for the archive.  If no fragment is given,
       the symlink will be set to the name of the archive. Fragments should not be given
       to directories or jars.

     - If any archives are specified in tez.lib.uris, then tez.lib.uris.classpath must be set
       to define the classpath for these archives as the archive structure is not known.
     - Example: Classpath when using both Tez and Hadoop archives, set tez.lib.uris.classpath to:

     ```
 ./tez/*:./tez/lib/*:./hadoop-mapreduce/hadoop-x.y.z-SNAPSHOT/share/hadoop/common/*:./hadoop-mapreduce/hadoop-x.y.z-SNAPSHOT/share/hadoop/common/lib/*:./hadoop-mapreduce/hadoop-x.y.z-SNAPSHOT/share/hadoop/hdfs/*:./hadoop-mapreduce/hadoop-x.y.z-SNAPSHOT/share/hadoop/hdfs/lib/*:./hadoop-mapreduce/hadoop-x.y.z-SNAPSHOT/share/hadoop/yarn/*:./hadoop-mapreduce/hadoop-x.y.z-SNAPSHOT/share/hadoop/yarn/lib/*:./hadoop-mapreduce/hadoop-x.y.z-SNAPSHOT/share/hadoop/mapreduce/*:./hadoop-mapreduce/hadoop-x.y.z-SNAPSHOT/share/hadoop/mapreduce/lib/*
     ```

     - Example: Classpath when using Tez jars with a Hadoop archive, set tez.lib.uris.classpath to:

     ```
 ./hadoop-mapreduce/hadoop-x.y.z-SNAPSHOT/share/hadoop/common/*:./hadoop-mapreduce/hadoop-x.y.z-SNAPSHOT/share/hadoop/common/lib/*:./hadoop-mapreduce/hadoop-x.y.z-SNAPSHOT/share/hadoop/hdfs/*:./hadoop-mapreduce/hadoop-x.y.z-SNAPSHOT/share/hadoop/hdfs/lib/*:./hadoop-mapreduce/hadoop-x.y.z-SNAPSHOT/share/hadoop/yarn/*:./hadoop-mapreduce/hadoop-x.y.z-SNAPSHOT/share/hadoop/yarn/lib/*:./hadoop-mapreduce/hadoop-x.y.z-SNAPSHOT/share/hadoop/mapreduce/*:./hadoop-mapreduce/hadoop-x.y.z-SNAPSHOT/share/hadoop/mapreduce/lib/*
     ```


 [Install instructions for older versions of Tez (pre 0.5.0)](./install_pre_0_5_0.html)
 -----------------------------------------------------------------------------------
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	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.
	-->

	<head><title>Install and Deployment Instructions</title></head>

	Install/Deploy Instructions for Tez
	---------------------------------------------------------------------------
	Replace x.y.z with the tez release number that you are using. E.g. 0.5.0. For Tez
	versions 0.8.3 and higher, Tez needs Apache Hadoop to be of version 2.6.0 or higher.

	1. Deploy Apache Hadoop using version of 2.6.0 or higher.
	- You need to change the value of the hadoop.version property in the
	top-level pom.xml to match the version of the hadoop branch being used.

	```
	$ hadoop version
	```

	2. Build tez using `mvn clean package -DskipTests=true -Dmaven.javadoc.skip=true`
	- This assumes that you have already installed JDK6 or later and Maven 3 or later.
	- Tez also requires Protocol Buffers 2.5.0, including the protoc-compiler.
	* This can be downloaded from https://github.com/google/protobuf/tags/.
	* On Mac OS X with the homebrew package manager `brew install protobuf250`
	* For rpm-based linux systems, the yum repos may not have the 2.5.0 version.
	`rpm.pbone.net` has the protobuf-2.5.0 and protobuf-compiler-2.5.0 packages.
	- If you prefer to run the unit tests, remove skipTests from the
	command above.
	- If you use Eclipse IDE, you can import the projects using
	"Import/Maven/Existing Maven Projects". Eclipse does not
	automatically generate Java sources or include the generated
	sources into the projects. Please build using maven as described
	above and then use Project Properties to include
	"target/generatedsources/java" as a source directory into the
	"Java Build Path" for these projects: tez-api, tez-mapreduce,
	tez-runtime-internals and tez-runtime-library. This needs to be done
	just once after importing the project.
	3. Copy the relevant tez tarball into HDFS, and configure tez-site.xml
	- A tez tarball containing tez and hadoop libraries will be found
	at tez-dist/target/tez-x.y.z-SNAPSHOT.tar.gz
	- Assuming that the tez jars are put in /apps/ on HDFS, the
	command would be

	```
	hadoop dfs -mkdir /apps/tez-x.y.z-SNAPSHOT
	hadoop dfs -copyFromLocal tez-dist/target/tez-x.y.z-SNAPSHOT-archive.tar.gz /apps/tez-x.y.z-SNAPSHOT/
	```

	- tez-site.xml configuration.
	- Set tez.lib.uris to point to the tar.gz uploaded to HDFS.
	Assuming the steps mentioned so far were followed,
	set tez.lib.uris to `${fs.defaultFS}/apps/tez-x.y.z-SNAPSHOT/tez-x.y.z-SNAPSHOT.tar.gz`
	- Ensure tez.use.cluster.hadoop-libs is not set in tez-site.xml,
	or if it is set, the value should be false
	- Please note that the tarball version should match the version of
	the client jars used when submitting Tez jobs to the cluster.
	Please refer to the [Version Compatibility Guide](https://cwiki.apache.org/confluence/display/TEZ/Version+Compatibility)
	for more details on version compatibility and detecting mismatches.
	4. Optional: If running existing MapReduce jobs on Tez. Modify
	mapred-site.xml to change "mapreduce.framework.name" property from
	its default value of "yarn" to "yarn-tez"
	5. Configure the client node to include the tez-libraries in the hadoop
	classpath
	- Extract the tez minimal tarball created in step 2 to a local directory
	(assuming TEZ_JARS is where the files will be decompressed for
	the next steps)

	```
	tar -xvzf tez-dist/target/tez-x.y.z-minimal.tar.gz -C $TEZ_JARS
	```

	- set TEZ_CONF_DIR to the location of tez-site.xml
	- Add $TEZ_CONF_DIR, ${TEZ_JARS}/* and ${TEZ_JARS}/lib/* to the application classpath.
	For example, doing it via the standard Hadoop tool chain would use the following command
	to set up the application classpath:

	```
	export HADOOP_CLASSPATH=${TEZ_CONF_DIR}:${TEZ_JARS}/:${TEZ_JARS}/lib/
	```

	- Please note the "*" which is an important requirement when
	setting up classpaths for directories containing jar files.
	6. There is a basic example of using an MRR job in the tez-examples.jar.
	Refer to OrderedWordCount.java in the source code. To run this
	example:

	```
	$HADOOP_PREFIX/bin/hadoop jar tez-examples.jar orderedwordcount <input> <output>
	```

	This will use the TEZ DAG ApplicationMaster to run the ordered word
	count job. This job is similar to the word count example except that
	it also orders all words based on the frequency of occurrence.

	Tez DAGs could be run separately as different applications or
	serially within a single TEZ session. There is a different variation
	of orderedwordcount in tez-tests that supports the use of Sessions
	and handling multiple input-output pairs. You can use it to run
	multiple DAGs serially on different inputs/outputs.

	```
	$HADOOP_PREFIX/bin/hadoop jar tez-tests.jar testorderedwordcount <input1> <output1> <input2> <output2> <input3> <output3> ...
	```

	The above will run multiple DAGs for each input-output pair.

	To use TEZ sessions, set -DUSE_TEZ_SESSION=true

	```
	$HADOOP_PREFIX/bin/hadoop jar tez-tests.jar testorderedwordcount -DUSE_TEZ_SESSION=true <input1> <output1> <input2> <output2>
	```
	7. Submit a MR job as you normally would using something like:

	```
	$HADOOP_PREFIX/bin/hadoop jar hadoop-mapreduce-client-jobclient-3.0.0-SNAPSHOT-tests.jar sleep -mt 1 -rt 1 -m 1 -r 1
	```

	This will use the TEZ DAG ApplicationMaster to run the MR job. This
	can be verified by looking at the AM’s logs from the YARN ResourceManager UI.
	This needs mapred-site.xml to have "mapreduce.framework.name" set to "yarn-tez"

	Various ways to configure tez.lib.uris
	---------------------------------------

	The `tez.lib.uris` configuration property supports a comma-separated list of values. The
	types of values supported are:
	- Path to simple file
	- Path to a directory
	- Path to a compressed archive ( tarball, zip, etc).

	For simple files and directories, Tez will add all these files and first-level entries in the
	directories (recursive traversal of dirs is not supported) into the working directory of the
	Tez runtime and they will automatically be included into the classpath. For archives i.e.
	files whose names end with generally known compressed archive suffixes such as 'tgz',
	'tar.gz', 'zip', etc. will be uncompressed into the container working directory too. However,
	given that the archive structure is not known to the Tez framework, the user is expected to
	configure `tez.lib.uris.classpath` to ensure that the nested directory structure of an
	archive is added to the classpath. This classpath values should be relative i.e. the entries
	should start with "./".

	Hadoop Installation dependent Install/Deploy Instructions
	---------------------------------------------------------

	The above install instructions use Tez with pre-packaged Hadoop libraries included in the package and is the
	recommended method for installation. A full tarball with all dependencies is a better approach to ensure
	that existing jobs continue to run during a cluster's rolling upgrade.

	Although the `tez.lib.uris` configuration options enable a wide variety of usage patterns, there
	are 2 main alternative modes that are supported by the framework:

	1. Mode A: Using a tez tarball on HDFS along with Hadoop libraries available on the cluster.
	2. Mode B: Using a tez tarball along with the Hadoop tarball.

	Both these modes will require a tez build without Hadoop dependencies and that is available at
	tez-dist/target/tez-x.y.z-minimal.tar.gz.

	For Mode A: Tez tarball with using existing cluster Hadoop libraries by leveraging yarn.application.classpath
	-------------------------------------------------------------------------------------------------------------

	This mode is not recommended for clusters that use rolling upgrades. Additionally, it is the user's responsibility
	to ensure that the tez version being used is compatible with the version of Hadoop running on the cluster.
	Step 3 above changes as follows. Also subsequent steps should use tez-dist/target/tez-x.y.z-minimal.tar.gz
	instead of tez-dist/target/tez-x.y.z.tar.gz

	- A tez build without Hadoop dependencies will be available at tez-dist/target/tez-x.y.z-minimal.tar.gz
	Assuming that the tez jars are put in /apps/ on HDFS, the command would be

	```
	"hadoop fs -mkdir /apps/tez-x.y.z"
	"hadoop fs -copyFromLocal tez-dist/target/tez-x.y.z-minimal.tar.gz /apps/tez-x.y.z"
	```

	- tez-site.xml configuration
	- Set tez.lib.uris to point to the paths in HDFS containing the tez jars. Assuming the steps mentioned so far were followed,
	set tez.lib.uris to `${fs.defaultFS}/apps/tez-x.y.z/tez-x.y.z-minimal.tar.gz`
	- Set tez.use.cluster.hadoop-libs to true

	For Mode B: Tez tarball with Hadoop tarball
	--------------------------------------------

	This mode will support rolling upgrades. It is the user's responsibility to ensure that the
	versions of Tez and Hadoop being used are compatible.
	To do this configuration, we need to change Step 3 of the
	default instructions in the following ways.

	- Assuming that the tez archives/jars are put in /apps/ on HDFS, the command to put this
	minimal Tez archive into HDFS would be:

	```
	"hadoop fs -mkdir /apps/tez-x.y.z"
	"hadoop fs -copyFromLocal tez-dist/target/tez-x.y.z-minimal.tar.gz /apps/tez-x.y.z"
	```

	- Alternatively, you can put the minimal directory directly into HDFS and
	reference the jars, instead of using an archive. The command to put
	the minimal directory into HDFS would be:

	```
	"hadoop fs -copyFromLocal tez-dist/target/tez-x.y.z-minimal/* /apps/tez-x.y.z"
	```

	- After building hadoop, the hadoop tarball will be available at
	hadoop/hadoop-dist/target/hadoop-x.y.z-SNAPSHOT.tar.gz
	- Assuming that the hadoop jars are put in /apps/ on HDFS, the command to put this
	Hadoop archive into HDFS would be:

	```
	"hadoop fs -mkdir /apps/hadoop-x.y.z"
	"hadoop fs -copyFromLocal hadoop-dist/target/hadoop-x.y.z-SNAPSHOT.tar.gz /apps/hadoop-x.y.z"
	```

	- tez-site.xml configuration
	- Set tez.lib.uris to point to the the archives and jars that are needed for Tez/Hadoop.

	- Example: When using both Tez and Hadoop archives, set tez.lib.uris to
	`${fs.defaultFS}/apps/tez-x.y.z/tez-x.y.z-minimal.tar.gz#tez,${fs.defaultFS}/apps/hadoop-x.y.z/hadoop-x.y.z-SNAPSHOT.tar.gz#hadoop-mapreduce`

	- Example: When using Tez jars with a Hadoop archive, set tez.lib.uris to:
	`${fs.defaultFS}/apps/tez-x.y.z,${fs.defaultFS}/apps/tez-x.y.z/lib,${fs.defaultFS}/apps/hadoop-x.y.z/hadoop-x.y.z-SNAPSHOT.tar.gz#hadoop-mapreduce`

	- In tez.lib.uris, the text immediately following the '#' symbol is the fragment that
	refers to the symlink that will be created for the archive. If no fragment is given,
	the symlink will be set to the name of the archive. Fragments should not be given
	to directories or jars.

	- If any archives are specified in tez.lib.uris, then tez.lib.uris.classpath must be set
	to define the classpath for these archives as the archive structure is not known.
	- Example: Classpath when using both Tez and Hadoop archives, set tez.lib.uris.classpath to:

	```
	./tez/:./tez/lib/:./hadoop-mapreduce/hadoop-x.y.z-SNAPSHOT/share/hadoop/common/:./hadoop-mapreduce/hadoop-x.y.z-SNAPSHOT/share/hadoop/common/lib/:./hadoop-mapreduce/hadoop-x.y.z-SNAPSHOT/share/hadoop/hdfs/:./hadoop-mapreduce/hadoop-x.y.z-SNAPSHOT/share/hadoop/hdfs/lib/:./hadoop-mapreduce/hadoop-x.y.z-SNAPSHOT/share/hadoop/yarn/:./hadoop-mapreduce/hadoop-x.y.z-SNAPSHOT/share/hadoop/yarn/lib/:./hadoop-mapreduce/hadoop-x.y.z-SNAPSHOT/share/hadoop/mapreduce/:./hadoop-mapreduce/hadoop-x.y.z-SNAPSHOT/share/hadoop/mapreduce/lib/
	```

	- Example: Classpath when using Tez jars with a Hadoop archive, set tez.lib.uris.classpath to:

	```
	./hadoop-mapreduce/hadoop-x.y.z-SNAPSHOT/share/hadoop/common/:./hadoop-mapreduce/hadoop-x.y.z-SNAPSHOT/share/hadoop/common/lib/:./hadoop-mapreduce/hadoop-x.y.z-SNAPSHOT/share/hadoop/hdfs/:./hadoop-mapreduce/hadoop-x.y.z-SNAPSHOT/share/hadoop/hdfs/lib/:./hadoop-mapreduce/hadoop-x.y.z-SNAPSHOT/share/hadoop/yarn/:./hadoop-mapreduce/hadoop-x.y.z-SNAPSHOT/share/hadoop/yarn/lib/:./hadoop-mapreduce/hadoop-x.y.z-SNAPSHOT/share/hadoop/mapreduce/:./hadoop-mapreduce/hadoop-x.y.z-SNAPSHOT/share/hadoop/mapreduce/lib/
	```


	[Install instructions for older versions of Tez (pre 0.5.0)](./install_pre_0_5_0.html)
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