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Native Libraries Guide
======================

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Overview
--------

This guide describes the native hadoop library and includes a small discussion about native shared libraries.

Note: Depending on your environment, the term "native libraries" could refer to all \*.so's you need to compile; and, the term "native compression" could refer to all \*.so's you need to compile that are specifically related to compression. Currently, however, this document only addresses the native hadoop library (`libhadoop.so`). The document for libhdfs library (`libhdfs.so`) is [here](../hadoop-hdfs/LibHdfs.html).

Native Hadoop Library
---------------------

Hadoop has native implementations of certain components for performance reasons and for non-availability of Java implementations. These components are available in a single, dynamically-linked native library called the native hadoop library. On the \*nix platforms the library is named `libhadoop.so`.

Usage
-----

It is fairly easy to use the native hadoop library:

1.  Review the components.
2.  Review the supported platforms.
3.  Either download a hadoop release, which will include a pre-built version of the native hadoop library, or build your own version of the native hadoop library. Whether you download or build, the name for the library is the same: libhadoop.so
4.  Install the compression codec development packages (\>zlib-1.2, \>gzip-1.2):
    * If you download the library, install one or more development packages - whichever compression codecs you want to use with your deployment.
    * If you build the library, it is mandatory to install both development packages.
5.  Check the runtime log files.

Components
----------

The native hadoop library includes various components:

* Compression Codecs (bzip2, lz4, snappy, zlib)
* Native IO utilities for [HDFS Short-Circuit Local Reads](../hadoop-hdfs/ShortCircuitLocalReads.html) and [Centralized Cache Management in HDFS](../hadoop-hdfs/CentralizedCacheManagement.html)
* CRC32 checksum implementation

Supported Platforms
-------------------

The native hadoop library is supported on \*nix platforms only. The library does not to work with Cygwin or the Mac OS X platform.

The native hadoop library is mainly used on the GNU/Linus platform and has been tested on these distributions:

* RHEL4/Fedora
* Ubuntu
* Gentoo

On all the above distributions a 32/64 bit native hadoop library will work with a respective 32/64 bit jvm.

Download
--------

The pre-built 32-bit i386-Linux native hadoop library is available as part of the hadoop distribution and is located in the `lib/native` directory. You can download the hadoop distribution from Hadoop Common Releases.

Be sure to install the zlib and/or gzip development packages - whichever compression codecs you want to use with your deployment.

Build
-----

The native hadoop library is written in ANSI C and is built using the GNU autotools-chain (autoconf, autoheader, automake, autoscan, libtool). This means it should be straight-forward to build the library on any platform with a standards-compliant C compiler and the GNU autotools-chain (see the supported platforms).

The packages you need to install on the target platform are:

* C compiler (e.g. GNU C Compiler)
* GNU Autools Chain: autoconf, automake, libtool
* zlib-development package (stable version \>= 1.2.0)
* openssl-development package(e.g. libssl-dev)

Once you installed the prerequisite packages use the standard hadoop pom.xml file and pass along the native flag to build the native hadoop library:

       $ mvn package -Pdist,native -DskipTests -Dtar

You should see the newly-built library in:

       $ hadoop-dist/target/hadoop-${project.version}/lib/native

Please note the following:

* It is mandatory to install both the zlib and gzip development packages on the target platform in order to build the native hadoop library; however, for deployment it is sufficient to install just one package if you wish to use only one codec.
* It is necessary to have the correct 32/64 libraries for zlib, depending on the 32/64 bit jvm for the target platform, in order to build and deploy the native hadoop library.

Runtime
-------

The bin/hadoop script ensures that the native hadoop library is on the library path via the system property: `-Djava.library.path=<path> `

During runtime, check the hadoop log files for your MapReduce tasks.

* If everything is all right, then: `DEBUG util.NativeCodeLoader - Trying to load the custom-built native-hadoop library...` `INFO util.NativeCodeLoader - Loaded the native-hadoop library`
* If something goes wrong, then: `INFO util.NativeCodeLoader - Unable to load native-hadoop library for your platform... using builtin-java classes where applicable`

Check
-----

NativeLibraryChecker is a tool to check whether native libraries are loaded correctly. You can launch NativeLibraryChecker as follows:

       $ hadoop checknative -a
       14/12/06 01:30:45 WARN bzip2.Bzip2Factory: Failed to load/initialize native-bzip2 library system-native, will use pure-Java version
       14/12/06 01:30:45 INFO zlib.ZlibFactory: Successfully loaded & initialized native-zlib library
       Native library checking:
       hadoop: true /home/ozawa/hadoop/lib/native/libhadoop.so.1.0.0
       zlib:   true /lib/x86_64-linux-gnu/libz.so.1
       snappy: true /usr/lib/libsnappy.so.1
       zstd: true /usr/lib/libzstd.so.1
       lz4:    true revision:99
       bzip2:  false

Native Shared Libraries
-----------------------

You can load any native shared library using DistributedCache for distributing and symlinking the library files.

This example shows you how to distribute a shared library, mylib.so, and load it from a MapReduce task.

1.  First copy the library to the HDFS: `bin/hadoop fs -copyFromLocal mylib.so.1 /libraries/mylib.so.1`
2.  The job launching program should contain the following: `DistributedCache.createSymlink(conf);` `DistributedCache.addCacheFile("hdfs://host:port/libraries/mylib.so. 1#mylib.so", conf);`
3.  The MapReduce task can contain: `System.loadLibrary("mylib.so");`

Note: If you downloaded or built the native hadoop library, you don’t need to use DistibutedCache to make the library available to your MapReduce tasks.