This guide provides an overview of the HDFS High Availability (HA) feature and how to configure and manage an HA HDFS cluster, using NFS for the shared storage required by the NameNodes.
This document assumes that the reader has a general understanding of general components and node types in an HDFS cluster. Please refer to the HDFS Architecture guide for details.
This guide discusses how to configure and use HDFS HA using a shared NFS directory to share edit logs between the Active and Standby NameNodes. For information on how to configure HDFS HA using the Quorum Journal Manager instead of NFS, please see this alternative guide.
Prior to Hadoop 2.0.0, the NameNode was a single point of failure (SPOF) in an HDFS cluster. Each cluster had a single NameNode, and if that machine or process became unavailable, the cluster as a whole would be unavailable until the NameNode was either restarted or brought up on a separate machine.
This impacted the total availability of the HDFS cluster in two major ways:
The HDFS High Availability feature addresses the above problems by providing the option of running two redundant NameNodes in the same cluster in an Active/Passive configuration with a hot standby. This allows a fast failover to a new NameNode in the case that a machine crashes, or a graceful administrator-initiated failover for the purpose of planned maintenance.
In a typical HA cluster, two separate machines are configured as NameNodes. At any point in time, exactly one of the NameNodes is in an Active state, and the other is in a Standby state. The Active NameNode is responsible for all client operations in the cluster, while the Standby is simply acting as a slave, maintaining enough state to provide a fast failover if necessary.
In order for the Standby node to keep its state synchronized with the Active node, the current implementation requires that the two nodes both have access to a directory on a shared storage device (eg an NFS mount from a NAS). This restriction will likely be relaxed in future versions.
When any namespace modification is performed by the Active node, it durably logs a record of the modification to an edit log file stored in the shared directory. The Standby node is constantly watching this directory for edits, and as it sees the edits, it applies them to its own namespace. In the event of a failover, the Standby will ensure that it has read all of the edits from the shared storage before promoting itself to the Active state. This ensures that the namespace state is fully synchronized before a failover occurs.
In order to provide a fast failover, it is also necessary that the Standby node have up-to-date information regarding the location of blocks in the cluster. In order to achieve this, the DataNodes are configured with the location of both NameNodes, and send block location information and heartbeats to both.
It is vital for the correct operation of an HA cluster that only one of the NameNodes be Active at a time. Otherwise, the namespace state would quickly diverge between the two, risking data loss or other incorrect results. In order to ensure this property and prevent the so-called "split-brain scenario," the administrator must configure at least one fencing method for the shared storage. During a failover, if it cannot be verified that the previous Active node has relinquished its Active state, the fencing process is responsible for cutting off the previous Active's access to the shared edits storage. This prevents it from making any further edits to the namespace, allowing the new Active to safely proceed with failover.
In order to deploy an HA cluster, you should prepare the following:
Note that, in an HA cluster, the Standby NameNode also performs checkpoints of the namespace state, and thus it is not necessary to run a Secondary NameNode, CheckpointNode, or BackupNode in an HA cluster. In fact, to do so would be an error. This also allows one who is reconfiguring a non-HA-enabled HDFS cluster to be HA-enabled to reuse the hardware which they had previously dedicated to the Secondary NameNode.
Similar to 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 may have the same configuration without the need for deploying different configuration files to different machines based on the type of the node.
Like HDFS Federation, HA clusters reuse the nameservice ID to identify a single HDFS instance that may in fact consist of multiple HA NameNodes. In addition, a new abstraction called NameNode ID is added with HA. Each distinct NameNode in the cluster has a different NameNode ID to distinguish it. To support a single configuration file for all of the NameNodes, the relevant configuration parameters are suffixed with the nameservice ID as well as the NameNode ID.
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. Thus, you should decide on these values before setting the rest of the configuration options.
Choose a logical name for this nameservice, for example "mycluster", and use this logical name for the value of this config 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.
Note: If you are also using HDFS Federation, this configuration setting should also include the list of other nameservices, HA or otherwise, as a comma-separated list.
<property> <name>dfs.nameservices</name> <value>mycluster</value> </property>
Configure with 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 such:
<property> <name>dfs.ha.namenodes.mycluster</name> <value>nn1,nn2</value> </property>
Note: Currently, only a maximum of two NameNodes may be configured per nameservice.
For both of the previously-configured NameNode IDs, set the full address and IPC port of the NameNode processs. Note that this results in two separate configuration options. For example:
<property> <name>dfs.namenode.rpc-address.mycluster.nn1</name> <value>machine1.example.com:8020</value> </property> <property> <name>dfs.namenode.rpc-address.mycluster.nn2</name> <value>machine2.example.com:8020</value> </property>
Note: You may similarly configure the "servicerpc-address" setting if you so desire.
Similarly to rpc-address above, set the addresses for both NameNodes' HTTP servers to listen on. For example:
<property> <name>dfs.namenode.http-address.mycluster.nn1</name> <value>machine1.example.com:50070</value> </property> <property> <name>dfs.namenode.http-address.mycluster.nn2</name> <value>machine2.example.com:50070</value> </property>
Note: If you have Hadoop's security features enabled, you should also set the https-address similarly for each NameNode.
This is where one configures the path to the remote shared edits directory which the Standby NameNode uses to stay up-to-date with all the file system changes the Active NameNode makes. You should only configure one of these directories. This directory should be mounted r/w on both NameNode machines. The value of this setting should be the absolute path to this directory on the NameNode machines. For example:
<property> <name>dfs.namenode.shared.edits.dir</name> <value>file:///mnt/filer1/dfs/ha-name-dir-shared</value> </property>
Configure the name of the Java class which will be used by the DFS Client 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:
<property> <name>dfs.client.failover.proxy.provider.mycluster</name> <value>org.apache.hadoop.hdfs.server.namenode.ha.ConfiguredFailoverProxyProvider</value> </property>
It is critical for correctness of the system that only one NameNode be in the Active state at any given time. Thus, during a failover, we first ensure that the Active NameNode is either in the Standby state, or the process has terminated, before transitioning the other NameNode to the Active state. In order to do this, you must configure at least one fencing method. These are configured as a carriage-return-separated list, which will be attempted in order until one indicates that fencing has succeeded. There are two methods which ship with Hadoop: shell and sshfence. For information on implementing your own custom fencing method, see the org.apache.hadoop.ha.NodeFencer class.
The sshfence option SSHes 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, one 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:
<property> <name>dfs.ha.fencing.methods</name> <value>sshfence</value> </property> <property> <name>dfs.ha.fencing.ssh.private-key-files</name> <value>/home/exampleuser/.ssh/id_rsa</value> </property>
Optionally, one may configure a non-standard username or port to perform the SSH. One may also configure a timeout, in milliseconds, for the SSH, after which this fencing method will be considered to have failed. It may be configured like so:
<property> <name>dfs.ha.fencing.methods</name> <value>sshfence([[username][:port]])</value> </property> <property> <name>dfs.ha.fencing.ssh.connect-timeout</name> <value>30000</value> </property>
The shell fencing method runs an arbitrary shell command. It may be configured like so:
<property> <name>dfs.ha.fencing.methods</name> <value>shell(/path/to/my/script.sh arg1 arg2 ...)</value> </property>
The string between '(' and ')' is passed directly to a bash shell and may not include any closing parentheses.
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.
Additionally, the following variables referring to the target node to be fenced are also available:
|$target_host||hostname of the node to be fenced|
|$target_port||IPC port of the node to be fenced|
|$target_address||the above two, combined as host:port|
|$target_nameserviceid||the nameservice ID of the NN to be fenced|
|$target_namenodeid||the namenode ID of the NN to be fenced|
These environment variables may also be used as substitutions in the shell command itself. For example:
<property> <name>dfs.ha.fencing.methods</name> <value>shell(/path/to/my/script.sh --nameservice=$target_nameserviceid $target_host:$target_port)</value> </property>
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.
Note: This fencing method does not implement any timeout. If timeouts are necessary, they should be implemented in the shell script itself (eg by forking a subshell to kill its parent in some number of seconds).
Optionally, you may now configure the default path for Hadoop clients to use the new HA-enabled logical URI. If you used "mycluster" as the nameservice ID earlier, this will be the value of the authority portion of all of your HDFS paths. This may be configured like so, in your core-site.xml file:
<property> <name>fs.defaultFS</name> <value>hdfs://mycluster</value> </property>
After all of the necessary configuration options have been set, one must initially synchronize the two HA NameNodes' on-disk metadata.
At this point you may start both of your HA NameNodes as you normally would start a NameNode.
You can visit each of the NameNodes' web pages separately by browsing to their configured HTTP addresses. You should notice that next to the configured address will be the HA state of the NameNode (either "standby" or "active".) Whenever an HA NameNode starts, it is initially in the Standby state.
Now that your HA NameNodes are configured and started, you will have access to some additional commands to administer your HA HDFS cluster. Specifically, you should familiarize yourself with all of the subcommands of the "hdfs haadmin" command. Running this command without any additional arguments will display the following usage information:
Usage: DFSHAAdmin [-ns <nameserviceId>] [-transitionToActive <serviceId>] [-transitionToStandby <serviceId>] [-failover [--forcefence] [--forceactive] <serviceId> <serviceId>] [-getServiceState <serviceId>] [-checkHealth <serviceId>] [-help <command>]
This guide describes high-level uses of each of these subcommands. For specific usage information of each subcommand, you should run "hdfs haadmin -help <command>".
These subcommands cause a given NameNode to transition to the Active or Standby state, respectively. These commands do not attempt to perform any fencing, and thus should rarely be used. Instead, one should almost always prefer to use the "hdfs haadmin -failover" subcommand.
This subcommand causes a failover from the first provided NameNode to the second. If the first NameNode is in the Standby state, this command simply transitions the second to the Active state without error. If the first NameNode is in the Active state, an attempt will be made to gracefully transition it to the Standby state. If this fails, the fencing methods (as configured by dfs.ha.fencing.methods) will be attempted in order until one succeeds. Only after this process will the second NameNode be transitioned to the Active state. If no fencing method succeeds, the second NameNode will not be transitioned to the Active state, and an error will be returned.
Connect to the provided NameNode to determine its current state, printing either "standby" or "active" to STDOUT appropriately. This subcommand might be used by cron jobs or monitoring scripts which need to behave differently based on whether the NameNode is currently Active or Standby.
Connect to the provided NameNode to check its health. The NameNode is capable of performing some diagnostics on itself, including checking if internal services are running as expected. This command will return 0 if the NameNode is healthy, non-zero otherwise. One might use this command for monitoring purposes.
Note: This is not yet implemented, and at present will always return success, unless the given NameNode is completely down.
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.
Automatic failover adds two new components to an HDFS deployment: a ZooKeeper quorum, and the ZKFailoverController process (abbreviated as ZKFC).
Apache ZooKeeper is a highly available service for maintaining small amounts of coordination data, notifying clients of changes in that data, and monitoring clients for failures. The implementation of automatic HDFS failover relies on ZooKeeper for the following things:
The ZKFailoverController (ZKFC) is a new component which is a ZooKeeper client which also monitors and manages the state of the NameNode. Each of the machines which runs a NameNode also runs a ZKFC, and that ZKFC is responsible for:
For more details on the design of automatic failover, refer to the design document attached to HDFS-2185 on the Apache HDFS JIRA.
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. Many operators 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.
The setup of ZooKeeper is out of scope for this document. We will 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 ZK CLI.
Before you begin configuring automatic failover, you should shut down your cluster. It is not currently possible to transition from a manual failover setup to an automatic failover setup while the cluster is running.
The configuration of automatic failover requires the addition of two new parameters to your configuration. In your hdfs-site.xml file, add:
<property> <name>dfs.ha.automatic-failover.enabled</name> <value>true</value> </property>
This specifies that the cluster should be set up for automatic failover. In your core-site.xml file, add:
<property> <name>ha.zookeeper.quorum</name> <value>zk1.example.com:2181,zk2.example.com:2181,zk3.example.com:2181</value> </property>
This lists the host-port pairs running the ZooKeeper service.
As with the parameters described earlier in the 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 also several other configuration parameters which may be set to control the behavior of automatic failover; however, they are not necessary for most installations. Please refer to the configuration key specific documentation for details.
After the configuration keys have been added, the next step is to initialize 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 inside of which the automatic failover system stores its data.
Since automatic failover has been enabled in the configuration, the start-dfs.sh script will now automatically start a ZKFC daemon on any machine that runs a NameNode. When the ZKFCs start, they will automatically select one of the NameNodes to become active.
If you manually manage the services on your cluster, you will need to manually start the zkfc daemon on each of the machines that runs a NameNode. You can start the daemon by running:
$ hadoop-daemon.sh start zkfc
If you are running a secure cluster, you will likely 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:
<property> <name>ha.zookeeper.auth</name> <value>@/path/to/zk-auth.txt</value> </property> <property> <name>ha.zookeeper.acl</name> <value>@/path/to/zk-acl.txt</value> </property>
Please 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 ZK CLI. For example, you may specify something like:
...where hdfs-zkfcs is a unique username for ZooKeeper, and mypassword is some unique string used as a password.
Next, generate a ZooKeeper ACL that corresponds to this authentication, using a command like 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:
In order for these ACLs to take effect, you should then rerun the zkfc -formatZK command as described above.
After doing so, you may verify the ACLs from the ZK CLI as follows:
[zk: localhost:2181(CONNECTED) 1] getAcl /hadoop-ha 'digest,'hdfs-zkfcs:vlUvLnd8MlacsE80rDuu6ONESbM= : cdrwa
Once automatic failover has been set up, you should test its operation. To do so, first locate the active NameNode. You can tell which node is active by visiting the NameNode web interfaces -- each node reports its HA state at the top of the page.
Once you have located your active NameNode, you may cause a failure on that node. For example, you can use kill -9 <pid of NN> to simulate a JVM crash. Or, you could power cycle the machine or unplug its network interface to simulate a different kind of outage. After triggering the outage you wish to test, the other NameNode should automatically become active within several seconds. The amount of time required to detect a failure and trigger a fail-over 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.
No. On any given node you may 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.
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.
Even if automatic failover is configured, you may initiate a manual failover using the same hdfs haadmin command. It will perform a coordinated failover.
One option for shared storage for the NameNode is BookKeeper. BookKeeper achieves high availability and strong durability guarantees by replicating edit log entries across multiple storage nodes. The edit log can be striped across the storage nodes for high performance. Fencing is supported in the protocol, i.e, BookKeeper will not allow two writers to write the single edit log.
The meta data for BookKeeper is stored in ZooKeeper. In current HA architecture, a Zookeeper cluster is required for ZKFC. The same cluster can be for BookKeeper metadata.
For more details on building a BookKeeper cluster, please refer to the BookKeeper documentation
The BookKeeperJournalManager is an implementation of the HDFS JournalManager interface, which allows custom write ahead logging implementations to be plugged into the HDFS NameNode.
To use BookKeeperJournalManager, add the following to hdfs-site.xml.
<property> <name>dfs.namenode.shared.edits.dir</name> <value>bookkeeper://zk1:2181;zk2:2181;zk3:2181/hdfsjournal</value> </property> <property> <name>dfs.namenode.edits.journal-plugin.bookkeeper</name> <value>org.apache.hadoop.contrib.bkjournal.BookKeeperJournalManager</value> </property>
The URI format for bookkeeper is bookkeeper://[zkEnsemble]/[rootZnode] [zookkeeper ensemble] is a list of semi-colon separated, zookeeper host:port pairs. In the example above there are 3 servers, in the ensemble, zk1, zk2 & zk3, each one listening on port 2181.
[root znode] is the path of the zookeeper znode, under which the edit log information will be stored.
The class specified for the journal-plugin must be available in the NameNode's classpath. We explain how to generate a jar file with the journal manager and its dependencies, and how to put it into the classpath below.
<property> <name>dfs.namenode.bookkeeperjournal.output-buffer-size</name> <value>1024</value> </property>
<property> <name>dfs.namenode.bookkeeperjournal.ensemble-size</name> <value>3</value> </property>
<property> <name>dfs.namenode.bookkeeperjournal.quorum-size</name> <value>2</value> </property>
<property> <name>dfs.namenode.bookkeeperjournal.digestPw</name> <value>myPassword</value> </property>
<property> <name>dfs.namenode.bookkeeperjournal.zk.session.timeout</name> <value>3000</value> </property>
To generate the distribution packages for BK journal, do the following.
$ mvn clean package -Pdist
This will generate a jar with the BookKeeperJournalManager, all the dependencies needed by the journal manager, hadoop-hdfs/src/contrib/bkjournal/target/hadoop-hdfs-bkjournal-VERSION.jar
Note that the -Pdist part of the build command is important, as otherwise the dependencies would not be packaged in the jar. The dependencies included in the jar are shaded to avoid conflicts with other dependencies of the NameNode.
To run a HDFS namenode using BookKeeper as a backend, copy the bkjournal jar, generated above, into the lib directory of hdfs. In the standard distribution of HDFS, this is at $HADOOP_HDFS_HOME/share/hadoop/hdfs/lib/
cp hadoop-hdfs/src/contrib/bkjournal/target/hadoop-hdfs-bkjournal-VERSION.jar $HADOOP_HDFS_HOME/share/hadoop/hdfs/lib/
1) NameNode format command will not format the BookKeeper data automatically. We have to clean the data manually from BookKeeper cluster and create the /ledgers/available path in Zookeeper. ---- $ zkCli.sh create /ledgers 0 $ zkCli.sh create /ledgers/available 0 ---- Note: bookkeeper://zk1:2181;zk2:2181;zk3:2181/hdfsjournal The final part /hdfsjournal specifies the znode in zookeeper where ledger metadata will be stored. Administrators may set this to anything they wish.
2) Security in BookKeeper. BookKeeper does not support SASL nor SSL for connections between the NameNode and BookKeeper storage nodes.
3) Auto-Recovery of storage node failures. Work inprogress BOOKKEEPER-237. Currently we have the tools to manually recover the data from failed storage nodes.