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Hadoop DFS User Guide
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<h1>
Hadoop DFS User Guide
</h1>
<div id="minitoc-area">
<ul class="minitoc">
<li>
<a href="#Purpose">Purpose</a>
</li>
<li>
<a href="#Overview"> Overview </a>
</li>
<li>
<a href="#Pre-requisites"> Pre-requisites </a>
</li>
<li>
<a href="#Web+Interface"> Web Interface </a>
</li>
<li>
<a href="#Shell+Commands">Shell Commands</a>
<ul class="minitoc">
<li>
<a href="#DFSAdmin+Command"> DFSAdmin Command </a>
</li>
</ul>
</li>
<li>
<a href="#Secondary+Namenode"> Secondary Namenode </a>
</li>
<li>
<a href="#Rebalancer"> Rebalancer </a>
</li>
<li>
<a href="#Rack+Awareness"> Rack Awareness </a>
</li>
<li>
<a href="#Safemode"> Safemode </a>
</li>
<li>
<a href="#Fsck"> Fsck </a>
</li>
<li>
<a href="#Upgrade+and+Rollback"> Upgrade and Rollback </a>
</li>
<li>
<a href="#File+Permissions+and+Security"> File Permissions and Security </a>
</li>
<li>
<a href="#Scalability"> Scalability </a>
</li>
<li>
<a href="#Related+Documentation"> Related Documentation </a>
</li>
</ul>
</div>
<a name="N1000D"></a><a name="Purpose"></a>
<h2 class="h3">Purpose</h2>
<div class="section">
<p>
This document aims to be the starting point for users working with
Hadoop Distributed File System (HDFS) either as a part of a
<a href="http://hadoop.apache.org/">Hadoop</a>
cluster or as a stand-alone general purpose distributed file system.
While HDFS is designed to "just-work" in many environments, a working
knowledge of HDFS helps greatly with configuration improvements and
diagnostics on a specific cluster.
</p>
</div>
<a name="N1001B"></a><a name="Overview"></a>
<h2 class="h3"> Overview </h2>
<div class="section">
<p>
HDFS is the primary distributed storage used by Hadoop applications. A
HDFS cluster primarily consists of a <em>NameNode</em> that manages the
filesystem metadata and Datanodes that store the actual data. The
architecture of HDFS is described in detail
<a href="hdfs_design.html">here</a>. This user guide primarily deals with
interaction of users and administrators with HDFS clusters.
The <a href="images/hdfsarchitecture.gif">diagram</a> from
<a href="hdfs_design.html">HDFS architecture</a> depicts
basic interactions among Namenode, Datanodes, and the clients. Eseentially,
clients contact Namenode for file metadata or file modifications and perform
actual file I/O directly with the datanodes.
</p>
<p>
The following are some of the salient features that could be of
interest to many users. The terms in <em>italics</em>
are described in later sections.
</p>
<ul>
<li>
Hadoop, including HDFS, is well suited for distributed storage
and distributed processing using commodity hardware. It is fault
tolerant, scalable, and extremely simple to expand.
<a href="mapred_tutorial.html">Map-Reduce</a>,
well known for its simplicity and applicability for large set of
distributed applications, is an integral part of Hadoop.
</li>
<li>
HDFS is highly configurable with a default configuration well
suited for many installations. Most of the time, configuration
needs to be tuned only for very large clusters.
</li>
<li>
It is written in Java and is supported on all major platforms.
</li>
<li>
Supports <em>shell like commands</em> to interact with HDFS directly.
</li>
<li>
Namenode and Datanodes have built in web servers that makes it
easy to check current status of the cluster.
</li>
<li>
New features and improvements are regularly implemented in HDFS.
The following is a subset of useful features in HDFS:
<ul>
<li>
<em>File permissions and authentication.</em>
</li>
<li>
<em>Rack awareness</em> : to take a node's physical location into
account while scheduling tasks and allocating storage.
</li>
<li>
<em>Safemode</em> : an administrative mode for maintanance.
</li>
<li>
<em>fsck</em> : an utility to diagnose health of the filesystem, to
find missing files or blocks.
</li>
<li>
<em>Rebalancer</em> : tool to balance the cluster when the data is
unevenly distributed among datanodes.
</li>
<li>
<em>Upgrade and Rollback</em> : after a software upgrade,
it is possible to
rollback to HDFS' state before the upgrade in case of unexpected
problems.
</li>
<li>
<em>Secondary Namenode</em> : helps keep the size of file
containing log of HDFS modification with in certain limit at
the Namenode.
</li>
</ul>
</li>
</ul>
</div>
<a name="N10083"></a><a name="Pre-requisites"></a>
<h2 class="h3"> Pre-requisites </h2>
<div class="section">
<p>
The following documents describe installation and set up of a
Hadoop cluster :
</p>
<ul>
<li>
<a href="quickstart.html">Hadoop Quickstart</a>
for first-time users.
</li>
<li>
<a href="cluster_setup.html">Hadoop Cluster Setup</a>
for large, distributed clusters.
</li>
</ul>
<p>
The rest of document assumes the user is able to set up and run a
HDFS with at least one Datanode. For the purpose of this document,
both Namenode and Datanode could be running on the same physical
machine.
</p>
</div>
<a name="N100A1"></a><a name="Web+Interface"></a>
<h2 class="h3"> Web Interface </h2>
<div class="section">
<p>
Namenode and Datanode each run an internal web server in order to
display basic information about the current status of the cluster.
With the default configuration, namenode front page is at
<span class="codefrag">http://namenode:50070/</span> .
It lists the datanodes in the cluster and basic stats of the
cluster. The web interface can also be used to browse the file
system (using "Browse the file system" link on the Namenode front
page).
</p>
</div>
<a name="N100AE"></a><a name="Shell+Commands"></a>
<h2 class="h3">Shell Commands</h2>
<div class="section">
<p>
Hadoop includes various "shell-like" commands that directly
interact with HDFS and other file systems that Hadoop supports.
The command
<span class="codefrag">bin/hadoop fs -help</span>
lists the commands supported by Hadoop
shell. Further,
<span class="codefrag">bin/hadoop fs -help command</span>
displays more detailed help on a command. The commands support
most of the normal filesystem operations like copying files,
changing file permissions, etc. It also supports a few HDFS
specific operations like changing replication of files.
</p>
<a name="N100BD"></a><a name="DFSAdmin+Command"></a>
<h3 class="h4"> DFSAdmin Command </h3>
<p>
<span class="codefrag">'bin/hadoop dfsadmin'</span>
command supports a few HDFS administration related operations.
<span class="codefrag">bin/hadoop dfsadmin -help</span>
lists all the commands currently supported. For e.g.:
</p>
<ul>
<li>
<span class="codefrag">-report</span>
: reports basic stats of HDFS. Some of this information is
also available on the Namenode front page.
</li>
<li>
<span class="codefrag">-safemode</span>
: though usually not required, an administrator can manually enter
or leave <em>safemode</em>.
</li>
<li>
<span class="codefrag">-finalizeUpgrade</span>
: removes previous backup of the cluster made during last upgrade.
</li>
</ul>
</div>
<a name="N100E6"></a><a name="Secondary+Namenode"></a>
<h2 class="h3"> Secondary Namenode </h2>
<div class="section">
<p>
Namenode stores modifications to the filesystem as a log
appended to a native filesystem file (<span class="codefrag">edits</span>).
When a Namenode starts up, it reads HDFS state from an image
file (<span class="codefrag">fsimage</span>) and then applies <em>edits</em> from
edits log file. It then writes new HDFS state to (<span class="codefrag">fsimage</span>)
and starts normal
operation with an empty edits file. Since namenode merges
<span class="codefrag">fsimage</span> and <span class="codefrag">edits</span> files only during start up,
edits file could get very large over time on a large cluster.
Another side effect of larger edits file is that next
restart of Namenade takes longer.
</p>
<p>
The secondary namenode merges fsimage and edits log periodically
and keeps edits log size with in a limit. It is usually run on a
different machine than the primary Namenode since its memory requirements
are on the same order as the primary namemode. The secondary
namenode is started by <span class="codefrag">bin/start-dfs.sh</span> on the nodes
specified in <span class="codefrag">conf/masters</span> file.
</p>
</div>
<a name="N1010B"></a><a name="Rebalancer"></a>
<h2 class="h3"> Rebalancer </h2>
<div class="section">
<p>
HDFS data might not always be be placed uniformly across the
datanode. One common reason is addition of new datanodes to an
existing cluster. While placing new <em>blocks</em> (data for a file is
stored as a series of blocks), Namenode considers various
parameters before choosing the datanodes to receive these blocks.
Some of the considerations are :
</p>
<ul>
<li>
Policy to keep one of the replicas of a block on the same node
as the node that is writing the block.
</li>
<li>
Need to spread different replicas of a block across the racks so
that cluster can survive loss of whole rack.
</li>
<li>
One of the replicas is usually placed on the same rack as the
node writing to the file so that cross-rack network I/O is
reduced.
</li>
<li>
Spread HDFS data uniformly across the datanodes in the cluster.
</li>
</ul>
<p>
Due to multiple competing considerations, data might not be
uniformly placed across the datanodes.
HDFS provides a tool for administrators that analyzes block
placement and relanaces data across the datnodes. A brief
adminstrator's guide for rebalancer as a
<a href="http://issues.apache.org/jira/secure/attachment/12368261/RebalanceDesign6.pdf">PDF</a>
is attached to
<a href="http://issues.apache.org/jira/browse/HADOOP-1652">HADOOP-1652</a>.
</p>
</div>
<a name="N10132"></a><a name="Rack+Awareness"></a>
<h2 class="h3"> Rack Awareness </h2>
<div class="section">
<p>
Typically large Hadoop clusters are arranged in <em>racks</em> and
network traffic between different nodes with in the same rack is
much more desirable than network traffic across the racks. In
addition Namenode tries to place replicas of block on
multiple racks for improved fault tolerance. Hadoop lets the
cluster administrators decide which <em>rack</em> a node belongs to
through configuration variable <span class="codefrag">dfs.network.script</span>. When this
script is configured, each node runs the script to determine its
<em>rackid</em>. A default installation assumes all the nodes belong to
the same rack. This feature and configuration is further described
in <a href="http://issues.apache.org/jira/secure/attachment/12345251/Rack_aware_HDFS_proposal.pdf">PDF</a>
attached to
<a href="http://issues.apache.org/jira/browse/HADOOP-692">HADOOP-692</a>.
</p>
</div>
<a name="N10150"></a><a name="Safemode"></a>
<h2 class="h3"> Safemode </h2>
<div class="section">
<p>
During start up Namenode loads the filesystem state from
<em>fsimage</em> and <em>edits</em> log file. It then waits for datanodes
to report their blocks so that it does not prematurely start
replicating the blocks though enough replicas already exist in the
cluster. During this time Namenode stays in <em>safemode</em>. A
<em>Safemode</em>
for Namenode is essentially a read-only mode for the HDFS cluster,
where it does not allow any modifications to filesystem or blocks.
Normally Namenode gets out of safemode automatically at
the beginning. If required, HDFS could be placed in safemode explicitly
using <span class="codefrag">'bin/hadoop dfsadmin -safemode'</span> command. Namenode front
page shows whether safemode is on or off. A more detailed
description and configuration is maintained as JavaDoc for
<a href="http://hadoop.apache.org/core/docs/current/api/org/apache/hadoop/dfs/NameNode.html#setSafeMode(org.apache.hadoop.dfs.FSConstants.SafeModeAction)"><span class="codefrag">setSafeMode()</span></a>.
</p>
</div>
<a name="N1016E"></a><a name="Fsck"></a>
<h2 class="h3"> Fsck </h2>
<div class="section">
<p>
HDFS supports <span class="codefrag">fsck</span> command to check for various
inconsistencies.
It it is designed for reporting problems with various
files, for e.g. missing blocks for a file or under replicated
blocks. Unlike a traditional fsck utility for native filesystems,
this command does not correct the errors it detects. Normally Namenode
automatically corrects most of the recoverable failures.
HDFS' fsck is not a
Hadoop shell command. It can be run as '<span class="codefrag">bin/hadoop fsck</span>'.
Fsck can be run on the whole filesystem or on a subset of files.
</p>
</div>
<a name="N1017E"></a><a name="Upgrade+and+Rollback"></a>
<h2 class="h3"> Upgrade and Rollback </h2>
<div class="section">
<p>
When Hadoop is upgraded on an existing cluster, as with any
software upgrade, it is possible there are new bugs or
incompatible changes that affect existing applications and were
not discovered earlier. In any non-trivial HDFS installation, it
is not an option to loose any data, let alone to restart HDFS from
scratch. HDFS allows administrators to go back to earlier version
of Hadoop and <em>roll back</em> the cluster to the state it was in
before
the upgrade. HDFS upgrade is described in more detail in
<a href="http://wiki.apache.org/hadoop/Hadoop%20Upgrade">upgrade wiki</a>.
HDFS can have one such backup at a time. Before upgrading,
administrators need to remove existing backup using <span class="codefrag">bin/hadoop
dfsadmin -finalizeUpgrade</span> command. The following
briefly describes typical upgrade procedure :
</p>
<ul>
<li>
Before upgrading Hadoop software,
<em>finalize</em> if there an existing backup.
<span class="codefrag">dfsadmin -upgradeProgress status</span>
can tell if the cluster needs to be <em>finalized</em>.
</li>
<li>Stop the cluster and distribute new version of Hadoop.</li>
<li>
Run the new version with <span class="codefrag">-upgrade</span> option
(<span class="codefrag">bin/start-dfs.sh -upgrade</span>).
</li>
<li>
Most of the time, cluster works just fine. Once the new HDFS is
considered working well (may be after a few days of operation),
finalize the upgrade. Note that until the cluster is finalized,
deleting the files that existed before the upgrade does not free
up real disk space on the datanodes.
</li>
<li>
If there is a need to move back to the old version,
<ul>
<li> stop the cluster and distribute earlier version of Hadoop. </li>
<li> start the cluster with rollback option.
(<span class="codefrag">bin/start-dfs.h -rollback</span>).
</li>
</ul>
</li>
</ul>
</div>
<a name="N101BF"></a><a name="File+Permissions+and+Security"></a>
<h2 class="h3"> File Permissions and Security </h2>
<div class="section">
<p>
The file permissions are designed to be similar to file permissions on
other familiar platforms like Linux. Currently, security is limited
to simple file permissions. The user that starts Namenode is
treated as the <em>super user</em> for HDFS. Future versions of HDFS will
support network authentication protocols like Kerberos for user
authentication and encryption of data transfers. The details are discussed in the
<a href="hdfs_permissions_guide.html"><em>Permissions User and Administrator Guide</em></a>.
</p>
</div>
<a name="N101D1"></a><a name="Scalability"></a>
<h2 class="h3"> Scalability </h2>
<div class="section">
<p>
Hadoop currently runs on clusters with thousands of nodes.
<a href="http://wiki.apache.org/hadoop/PoweredBy">PoweredBy Hadoop</a>
lists some of the organizations that deploy Hadoop on large
clusters. HDFS has one Namenode for each cluster. Currently
the total memory available on Namenode is the primary scalability
limitation. On very large clusters, increasing average size of
files stored in HDFS helps with increasing cluster size without
increasing memory requirements on Namenode.
The default configuration may not suite very large clustes.
<a href="http://wiki.apache.org/hadoop/FAQ">Hadoop FAQ</a> page lists
suggested configuration improvements for large Hadoop clusters.
</p>
</div>
<a name="N101E3"></a><a name="Related+Documentation"></a>
<h2 class="h3"> Related Documentation </h2>
<div class="section">
<p>
This user guide is intended to be a good starting point for
working with HDFS. While it continues to improve,
there is a large wealth of documentation about Hadoop and HDFS.
The following lists starting points for further exploration :
</p>
<ul>
<li>
<a href="http://hadoop.apache.org/">Hadoop Home Page</a>
: the start page for everything Hadoop.
</li>
<li>
<a href="http://wiki.apache.org/hadoop/FrontPage">Hadoop Wiki</a>
: Front page for Hadoop Wiki documentation. Unlike this
guide which is part of Hadoop source tree, Hadoop Wiki is
regularly edited by Hadoop Community.
</li>
<li>
<a href="http://wiki.apache.org/hadoop/FAQ">FAQ</a> from Hadoop Wiki.
</li>
<li>
Hadoop <a href="http://hadoop.apache.org/core/docs/current/api/">
JavaDoc API</a>.
</li>
<li>
Hadoop User Mailing List :
<a href="mailto:core-user@hadoop.apache.org">core-user[at]hadoop.apache.org</a>.
</li>
<li>
Explore <span class="codefrag">conf/hadoop-default.xml</span>.
It includes brief
description of most of the configuration variables available.
</li>
</ul>
</div>
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