Enabling HDFS HA

An HDFS high availability (HA) cluster uses two NameNodes—an active NameNode and a standby NameNode. Only one NameNode can be active at any point in time. HDFS HA depends on maintaining a log of all namespace modifications in a location available to both NameNodes, so that in the event of a failure, the standby NameNode has up-to-date information about the edits and location of blocks in the cluster. For CDH 4 HA features, see the CDH 4 High Availability Guide.

Enabling HDFS HA Using Cloudera Manager

Minimum Required Role: Cluster Administrator (also provided by Full Administrator)

You can use Cloudera Manager to configure your CDH 4 or CDH 5 cluster for HDFS HA and automatic failover. In Cloudera Manager 5, HA is implemented using Quorum-based storage. Quorum-based storage relies upon a set of JournalNodes, each of which maintains a local edits directory that logs the modifications to the namespace metadata. Enabling HA enables automatic failover as part of the same command.

Enabling High Availability and Automatic Failover

The Enable High Availability workflow leads you through adding a second (standby) NameNode and configuring JournalNodes. During the workflow, Cloudera Manager creates a federated namespace.

  1. Perform all the configuration and setup tasks described under Configuring Hardware for HDFS HA.
  2. Ensure that you have a ZooKeeper service.
  3. Go to the HDFS service.
  4. Select Actions > Enable High Availability. A screen showing the hosts that are eligible to run a standby NameNode and the JournalNodes displays.
    1. Specify a name for the nameservice or accept the default name nameservice1 and click Continue.
    2. In the NameNode Hosts field, click Select a host. The host selection dialog box displays.
    3. Check the checkbox next to the hosts where you want the standby NameNode to be set up and click OK. The standby NameNode cannot be on the same host as the active NameNode, and the host that is chosen should have the same hardware configuration (RAM, disk space, number of cores, and so on) as the active NameNode.
    4. In the JournalNode Hosts field, click Select hosts. The host selection dialog box displays.
    5. Check the checkboxes next to an odd number of hosts (a minimum of three) to act as JournalNodes and click OK. JournalNodes should be hosted on hosts with similar hardware specification as the NameNodes. Cloudera recommends that you put a JournalNode each on the same hosts as the active and standby NameNodes, and the third JournalNode on similar hardware, such as the JobTracker.
    6. Click Continue.
    7. In the JournalNode Edits Directory property, enter a directory location for the JournalNode edits directory into the fields for each JournalNode host.
      • You may enter only one directory for each JournalNode. The paths do not need to be the same on every JournalNode.
      • The directories you specify should be empty, and must have the appropriate permissions.
    8. Extra Options: Decide whether Cloudera Manager should clear existing data in ZooKeeper, standby NameNode, and JournalNodes. If the directories are not empty (for example, you are re-enabling a previous HA configuration), Cloudera Manager will not automatically delete the contents—you can select to delete the contents by keeping the default checkbox selection. The recommended default is to clear the directories. If you choose not to do so, the data should be in sync across the edits directories of the JournalNodes and should have the same version data as the NameNodes.
    9. Click Continue.
    Cloudera Manager executes a set of commands that will stop the dependent services, delete, create, and configure roles and directories as appropriate, create a nameservice and failover controller, and restart the dependent services and deploy the new client configuration.
  5. If you want to use other services in a cluster with HA configured, follow the procedures in Configuring Other CDH Components to Use HDFS HA.
  6. If you are running CDH 4.0 or 4.1, the standby NameNode may fail at the bootstrapStandby command with the error Unable to read transaction ids 1-7 from the configured shared edits storage. Use rsync or a similar tool to copy the contents of the dfs.name.dir directory from the active NameNode to the standby NameNode and start the standby NameNode.

Fencing Methods

In order to ensure that only one NameNode is active at a time, a fencing method is required for the shared edits directory. During a failover, the fencing method is responsible for ensuring that the previous active NameNode no longer has access to the shared edits directory, so that the new active NameNode can safely proceed writing to it.

By default, Cloudera Manager configures HDFS to use a shell fencing method (shell(./cloudera_manager_agent_fencer.py)) that takes advantage of the Cloudera Manager Agent. However, you can configure HDFS to use the sshfence method, or you can add your own shell fencing scripts, instead of or in addition to the one Cloudera Manager provides.

The fencing parameters are found in the Service-Wide > High Availability category under the configuration properties for your HDFS service.

For details of the fencing methods supplied with CDH 5, and how fencing is configured, see Fencing Configuration.

Enabling HDFS HA Using the Command Line

This section describes the software configuration required for HDFS HA in CDH 5 and explains how to set configuration properties and use the command line to deploy HDFS HA.

Configuring Software for HDFS HA

Configuration Overview

As with HDFS federation configuration, HA configuration is backward compatible and allows existing single NameNode configurations to work without change. The new configuration is designed such that all the nodes in the cluster can have the same configuration without the need for deploying different configuration files to different machines based on the type of the node.

HA clusters reuse the Nameservice ID to identify a single HDFS instance that may consist of multiple HA NameNodes. In addition, there is a new abstraction called NameNode ID. Each distinct NameNode in the cluster has a different NameNode ID. To support a single configuration file for all of the NameNodes, the relevant configuration parameters include the Nameservice ID as well as the NameNode ID.

Changes to Existing Configuration Parameters

The following configuration parameter has changed for YARN implementations:

fs.defaultFS - formerly fs.default.name, the default path prefix used by the Hadoop FS client when none is given. (fs.default.name is deprecated for YARN implementations, but will still work.)

Optionally, you can configure the default path for Hadoop clients to use the HA-enabled logical URI. For example, if you use mycluster as the Nameservice ID as shown below, this will be the value of the authority portion of all of your HDFS paths. You can configure the default path in your core-site.xml file:
  • For YARN:
  • For MRv1:

New Configuration Parameters

To configure HA NameNodes, you must add several configuration options to your hdfs-site.xml configuration file.

The order in which you set these configurations is unimportant, but the values you choose for dfs.nameservices and dfs.ha.namenodes.[Nameservice ID] will determine the keys of those that follow. This means that you should decide on these values before setting the rest of the configuration options.

Configure dfs.nameservices

dfs.nameservices - the logical name for this new nameservice

Choose a logical name for this nameservice, for example mycluster, and use this logical name for the value of this configuration option. The name you choose is arbitrary. It will be used both for configuration and as the authority component of absolute HDFS paths in the cluster.


Configure dfs.ha.namenodes.[nameservice ID]

dfs.ha.namenodes.[nameservice ID] - unique identifiers for each NameNode in the nameservice

Configure a list of comma-separated NameNode IDs. This will be used by DataNodes to determine all the NameNodes in the cluster. For example, if you used mycluster as the NameService ID previously, and you wanted to use nn1 and nn2 as the individual IDs of the NameNodes, you would configure this as follows:


Configure dfs.namenode.rpc-address.[nameservice ID]

dfs.namenode.rpc-address.[nameservice ID].[name node ID] - the fully-qualified RPC address for each NameNode to listen on

For both of the previously-configured NameNode IDs, set the full address and RPC port of the NameNode process. Note that this results in two separate configuration options. For example:


Configure dfs.namenode.http-address.[nameservice ID]

dfs.namenode.http-address.[nameservice ID].[name node ID] - the fully-qualified HTTP address for each NameNode to listen on

Similarly to rpc-address above, set the addresses for both NameNodes' HTTP servers to listen on. For example:


Configure dfs.namenode.shared.edits.dir

dfs.namenode.shared.edits.dir - the location of the shared storage directory

Configure the addresses of the JournalNodes which provide the shared edits storage, written to by the Active NameNode and read by the Standby NameNode to stay up-to-date with all the file system changes the Active NameNode makes. Though you must specify several JournalNode addresses, you should only configure one of these URIs. The URI should be in the form:


The Journal ID is a unique identifier for this nameservice, which allows a single set of JournalNodes to provide storage for multiple federated namesystems. Though it is not a requirement, it's a good idea to reuse the Nameservice ID for the journal identifier.

For example, if the JournalNodes for this cluster were running on the machines node1.example.com, node2.example.com, and node3.example.com, and the nameservice ID were mycluster, you would use the following as the value for this setting (the default port for the JournalNode is 8485):


Configure dfs.journalnode.edits.dir

dfs.journalnode.edits.dir - the path where the JournalNode daemon will store its local state

On each JournalNode machine, configure the absolute path where the edits and other local state information used by the JournalNodes will be stored; use only a single path per JournalNode. (The other JournalNodes provide redundancy; you can also configure this directory on a locally-attached RAID-1 or RAID-10 array.)

For example:


Now create the directory (if it doesn't already exist) and make sure its owner is hdfs, for example:

$ sudo mkdir -p /data/1/dfs/jn
$ sudo chown -R hdfs:hdfs /data/1/dfs/jn

Client Failover Configuration

dfs.client.failover.proxy.provider.[nameservice ID] - the Java class that HDFS clients use to contact the Active NameNode

Configure the name of the Java class which the DFS client will use to determine which NameNode is the current active, and therefore which NameNode is currently serving client requests. The only implementation which currently ships with Hadoop is the ConfiguredFailoverProxyProvider, so use this unless you are using a custom one. For example:


Fencing Configuration

dfs.ha.fencing.methods - a list of scripts or Java classes which will be used to fence the active NameNode during a failover

It is desirable for correctness of the system that only one NameNode be in the active state at any given time.

To improve the availability of the system in the event the fencing mechanisms fail, it is advisable to configure a fencing method which is guaranteed to return success as the last fencing method in the list.

The fencing methods used during a failover are configured as a carriage-return-separated list, and these will be attempted in order until one of them indicates that fencing has succeeded.

There are two fencing methods which ship with Hadoop:

For information on implementing your own custom fencing method, see the org.apache.hadoop.ha.NodeFencer class.

Configuring the sshfence fencing method

sshfence - SSH to the active NameNode and kill the process

The sshfence option uses SSH to connect to the target node and uses fuser to kill the process listening on the service's TCP port. In order for this fencing option to work, it must be able to SSH to the target node without providing a passphrase. Thus, you must also configure the dfs.ha.fencing.ssh.private-key-files option, which is a comma-separated list of SSH private key files.

For example:



Optionally, you can configure a non-standard username or port to perform the SSH as shown below. You can also configure a timeout, in milliseconds, for the SSH, after which this fencing method will be considered to have failed:

    SSH connection timeout, in milliseconds, to use with the builtin
    sshfence fencer.

Configuring the shell fencing method

shell - run an arbitrary shell command to fence the active NameNode

The shell fencing method runs an arbitrary shell command, which you can configure as shown below:

  <value>shell(/path/to/my/script.sh arg1 arg2 ...)</value>

The string between '(' and ')' is passed directly to a bash shell and cannot include any closing parentheses.

When executed, the first argument to the configured script will be the address of the NameNode to be fenced, followed by all arguments specified in the configuration.

The shell command will be run with an environment set up to contain all of the current Hadoop configuration variables, with the '_' character replacing any '.' characters in the configuration keys. The configuration used has already had any NameNode-specific configurations promoted to their generic forms - for example dfs_namenode_rpc-address will contain the RPC address of the target node, even though the configuration may specify that variable as dfs.namenode.rpc-address.ns1.nn1.

The following variables referring to the target node to be fenced are also available:
Variable Description
$target_host Hostname of the node to be fenced
$target_port IPC port of the node to be fenced
$target_address The above two variables, combined as host:port
$target_nameserviceid The nameservice ID of the NameNode to be fenced
$target_namenodeid The NameNode ID of the NameNode to be fenced

You can also use these environment variables as substitutions in the shell command itself. For example:

  <value>shell(/path/to/my/script.sh --nameservice=$target_nameserviceid $target_host:$target_port)</value>

If the shell command returns an exit code of 0, the fencing is determined to be successful. If it returns any other exit code, the fencing was not successful and the next fencing method in the list will be attempted.

Automatic Failover Configuration

The above sections describe how to configure manual failover. In that mode, the system will not automatically trigger a failover from the active to the standby NameNode, even if the active node has failed. This section describes how to configure and deploy automatic failover. For an overview of how automatic failover is implemented, see Automatic Failover Implementation.

Deploying ZooKeeper

In a typical deployment, ZooKeeper daemons are configured to run on three or five nodes. Since ZooKeeper itself has light resource requirements, it is acceptable to collocate the ZooKeeper nodes on the same hardware as the HDFS NameNode and Standby Node. Operators using MapReduce v2 (MRv2) often choose to deploy the third ZooKeeper process on the same node as the YARN ResourceManager. It is advisable to configure the ZooKeeper nodes to store their data on separate disk drives from the HDFS metadata for best performance and isolation.

See the ZooKeeper documentation for instructions on how to set up a ZooKeeper ensemble. In the following sections we assume that you have set up a ZooKeeper cluster running on three or more nodes, and have verified its correct operation by connecting using the ZooKeeper command-line interface (CLI).

Configuring Automatic Failover

Configuring automatic failover requires two additional configuration parameters. In your hdfs-site.xml file, add:


This specifies that the cluster should be set up for automatic failover. In your core-site.xml file, add:


This lists the host-port pairs running the ZooKeeper service.

As with the parameters described earlier in this document, these settings may be configured on a per-nameservice basis by suffixing the configuration key with the nameservice ID. For example, in a cluster with federation enabled, you can explicitly enable automatic failover for only one of the nameservices by setting dfs.ha.automatic-failover.enabled.my-nameservice-id.

There are several other configuration parameters which you can set to control the behavior of automatic failover, but they are not necessary for most installations. See the configuration section of the Hadoop documentation for details.

Initializing the HA state in ZooKeeper

After you have added the configuration keys, the next step is to initialize the required state in ZooKeeper. You can do so by running the following command from one of the NameNode hosts.

$ hdfs zkfc -formatZK

This will create a znode in ZooKeeper in which the automatic failover system stores its data.

Securing access to ZooKeeper

If you are running a secure cluster, you will probably want to ensure that the information stored in ZooKeeper is also secured. This prevents malicious clients from modifying the metadata in ZooKeeper or potentially triggering a false failover.

In order to secure the information in ZooKeeper, first add the following to your core-site.xml file:


Note the '@' character in these values – this specifies that the configurations are not inline, but rather point to a file on disk.

The first configured file specifies a list of ZooKeeper authentications, in the same format as used by the ZooKeeper CLI. For example, you may specify something like digest:hdfs-zkfcs:mypassword where hdfs-zkfcs is a unique username for ZooKeeper, and mypassword is some unique string used as a password.

Next, generate a ZooKeeper Access Control List (ACL) that corresponds to this authentication, using a command such as the following:

$ java -cp $ZK_HOME/lib/*:$ZK_HOME/zookeeper-3.4.2.jar org.apache.zookeeper.server.auth.DigestAuthenticationProvider hdfs-zkfcs:mypassword
output: hdfs-zkfcs:mypassword->hdfs-zkfcs:P/OQvnYyU/nF/mGYvB/xurX8dYs=

Copy and paste the section of this output after the '->' string into the file zk-acls.txt, prefixed by the string "digest:". For example:


To put these ACLs into effect, rerun the zkfc -formatZK command as described above.

After doing so, you can verify the ACLs from the ZooKeeper CLI as follows:

[zk: localhost:2181(CONNECTED) 1] getAcl /hadoop-ha
: cdrwa
Automatic Failover FAQ
Is it important that I start the ZKFC and NameNode daemons in any particular order?
No. On any given node you may start the ZKFC before or after its corresponding NameNode.
What additional monitoring should I put in place?
You should add monitoring on each host that runs a NameNode to ensure that the ZKFC remains running. In some types of ZooKeeper failures, for example, the ZKFC may unexpectedly exit, and should be restarted to ensure that the system is ready for automatic failover. Additionally, you should monitor each of the servers in the ZooKeeper quorum. If ZooKeeper crashes, automatic failover will not function.
What happens if ZooKeeper goes down?

If the ZooKeeper cluster crashes, no automatic failovers will be triggered. However, HDFS will continue to run without any impact. When ZooKeeper is restarted, HDFS will reconnect with no issues.

Can I designate one of my NameNodes as primary/preferred?

No. Currently, this is not supported. Whichever NameNode is started first will become active. You may choose to start the cluster in a specific order such that your preferred node starts first.

How can I initiate a manual failover when automatic failover is configured?
Even if automatic failover is configured, you can initiate a manual failover. It will perform a coordinated failover.

Deploying HDFS High Availability

After you have set all of the necessary configuration options, you are ready to start the JournalNodes and the two HA NameNodes.

Install and Start the JournalNodes

  1. Install the JournalNode daemons on each of the machines where they will run.

    To install JournalNode on Red Hat-compatible systems:

    $ sudo yum install hadoop-hdfs-journalnode

    To install JournalNode on Ubuntu and Debian systems:

    $ sudo apt-get install hadoop-hdfs-journalnode 

    To install JournalNode on SLES systems:

    $ sudo zypper install hadoop-hdfs-journalnode
  2. Start the JournalNode daemons on each of the machines where they will run:
    sudo service hadoop-hdfs-journalnode start 

Wait for the daemons to start before formatting the primary NameNode (in a new cluster) and before starting the NameNodes (in all cases).

Format the NameNode (if new cluster)

If you are setting up a new HDFS cluster, format the NameNode you will use as your primary NameNode; see Formatting the NameNode.

Initialize the Shared Edits directory (if converting existing non-HA cluster)

If you are converting a non-HA NameNode to HA, initialize the shared edits directory with the edits data from the local NameNode edits directories:
hdfs namenode -initializeSharedEdits

Start the NameNodes

  1. Start the primary (formatted) NameNode:
    $ sudo service hadoop-hdfs-namenode start
  2. Start the standby NameNode:
    $ sudo -u hdfs hdfs namenode -bootstrapStandby
    $ sudo service hadoop-hdfs-namenode start 

Starting the standby NameNode with the -bootstrapStandby option copies over the contents of the primary NameNode's metadata directories (including the namespace information and most recent checkpoint) to the standby NameNode. (The location of the directories containing the NameNode metadata is configured using the configuration options dfs.namenode.name.dir and dfs.namenode.edits.dir.)

You can visit each NameNode's web page by browsing to its configured HTTP address. Notice that next to the configured address is the HA state of the NameNode (either "Standby" or "Active".) Whenever an HA NameNode starts and automatic failover is not enabled, it is initially in the Standby state. If automatic failover is enabled the first NameNode that is started will become active.

Restart Services (if converting existing non-HA cluster)

If you are converting from a non-HA to an HA configuration, you need to restart the JobTracker and TaskTracker (for MRv1, if used), or ResourceManager, NodeManager, and JobHistory Server (for YARN), and the DataNodes:

On each DataNode:

$ sudo service hadoop-hdfs-datanode start

On each TaskTracker system (MRv1):

$ sudo service hadoop-0.20-mapreduce-tasktracker start

On the JobTracker system (MRv1):

$ sudo service hadoop-0.20-mapreduce-jobtracker start

Verify that the JobTracker and TaskTracker started properly:

sudo jps | grep Tracker

On the ResourceManager system (YARN):

$ sudo service hadoop-yarn-resourcemanager start

On each NodeManager system (YARN; typically the same ones where DataNode service runs):

$ sudo service hadoop-yarn-nodemanager start

On the MapReduce JobHistory Server system (YARN):

$ sudo service hadoop-mapreduce-historyserver start

Deploy Automatic Failover (if it is configured)

If you have configured automatic failover using the ZooKeeper FailoverController (ZKFC), you must install and start the zkfc daemon on each of the machines that runs a NameNode. Proceed as follows.

To install ZKFC on Red Hat-compatible systems:

$ sudo yum install hadoop-hdfs-zkfc

To install ZKFC on Ubuntu and Debian systems:

$ sudo apt-get install hadoop-hdfs-zkfc

To install ZKFC on SLES systems:

$ sudo zypper install hadoop-hdfs-zkfc

To start the zkfc daemon:

$ sudo service hadoop-hdfs-zkfc start

It is not important that you start the ZKFC and NameNode daemons in a particular order. On any given node you can start the ZKFC before or after its corresponding NameNode.

You should add monitoring on each host that runs a NameNode to ensure that the ZKFC remains running. In some types of ZooKeeper failures, for example, the ZKFC may unexpectedly exit, and should be restarted to ensure that the system is ready for automatic failover.

Additionally, you should monitor each of the servers in the ZooKeeper quorum. If ZooKeeper crashes, then automatic failover will not function. If the ZooKeeper cluster crashes, no automatic failovers will be triggered. However, HDFS will continue to run without any impact. When ZooKeeper is restarted, HDFS will reconnect with no issues.

Verifying Automatic Failover

After the initial deployment of a cluster with automatic failover enabled, you should test its operation. To do so, first locate the active NameNode. As mentioned above, you can tell which node is active by visiting the NameNode web interfaces.

Once you have located your active NameNode, you can cause a failure on that node. For example, you can use kill -9 <pid of NN> to simulate a JVM crash. Or you can power-cycle the machine or its network interface to simulate different kinds of outages. After you trigger the outage you want to test, the other NameNode should automatically become active within several seconds. The amount of time required to detect a failure and trigger a failover depends on the configuration of ha.zookeeper.session-timeout.ms, but defaults to 5 seconds.

If the test does not succeed, you may have a misconfiguration. Check the logs for the zkfc daemons as well as the NameNode daemons in order to further diagnose the issue.

Upgrading an HDFS HA Configuration to the Latest Release

Upgrading to CDH 5

To upgrade an HDFS HA configuration using Quorum-base storage from CDH 4 to the latest release, follow the directions for upgrading a cluster under Upgrading from CDH 4 to CDH 5.