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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> : performs periodic checkpoints of the 
    		namespace and helps keep the size of file containing log of HDFS 
    		modifications within certain limits 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 file system as a log
     appended to a native file system 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>
<p>
     The start of the checkpoint process on the secondary name-node is 
     controlled by two configuration parameters.
   </p>
<ul>
      
<li>
        
<span class="codefrag">fs.checkpoint.period</span>, set to 1 hour by default, specifies
        the maximal delay between two consecutive checkpoints, and 
      </li>
      
<li>
        
<span class="codefrag">fs.checkpoint.size</span>, set to 64MB by default, defines the
        size of the edits log file that forces an urgent checkpoint even if 
        the maximal checkpoint delay is not reached.
      </li>
   
</ul>
<p>
     The secondary name-node stores the latest checkpoint in a storage 
     directory, which is structured the same way as the primary name-node's
     storage directory. So that the checkpointed image is always ready to be
     read by the primary name-node if necessary.
   </p>
<p>
     The latest checkpoint can be imported to the primary name-node if
     all other copies of the image and the edits files are lost.
     In order to do that one should:
   </p>
<ul>
      
<li>
        create an empty storage directory specified in the 
        <span class="codefrag">dfs.name.dir</span> configuration variable;
      </li>
      
<li>
        specify the location of the checkpoint storage directory in the 
        configuration variable <span class="codefrag">fs.checkpoint.dir</span>;
      </li>
      
<li>
        and start the name-node with <span class="codefrag">-importCheckpoint</span> option.
      </li>
   
</ul>
<p>
     The name-node will upload the checkpoint from the 
     <span class="codefrag">fs.checkpoint.dir</span> directory and then save it to the name-node
     storage directory(s) set in <span class="codefrag">dfs.name.dir</span>.
     The name-node will fail if a legal image is contained in 
     <span class="codefrag">dfs.name.dir</span>.
     The name-node verifies that the image in <span class="codefrag">fs.checkpoint.dir</span> is
     consistent, but does not modify it in any way.
   </p>
</div> 
<a name="N10147"></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="N1016E"></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="N1018C"></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="N101AA"></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. By default
      fsck ignores open files but provides an option to select during reporting.
      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="N101BA"></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="N101FB"></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="N1020D"></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="N1021F"></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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