With the advent of Hadoop’s 2.x version, there finally is a working High-Availability solution. Even two of those. Now it really is easy to configure and use those solutions. It no longer require external components, like DRBD. It all is just neatly packed into Cloudera Hadoop distribution - the precursor of this solution.
Read on to find out how to use it.
The most important weakness of previous Hadoop releases was the single-point-of-failure, which happend to be NameNode. NameNode as a key component of every Hadoop cluster, is responsible for managing filesystem namespace information and block location. Loosing its data results in loosing all the data stored on DataNodes. HDFS is no longer able to reach for specific files, or its blocks. This renders your cluster inoperable.
So it is crucial to be able to detect and counter problems with NameNode. The most desirable behavior is to have a hot backup, that would ensure a no-downtime cluster operation. To achieve this, the second NameNode need to have up-to-date information on filesystem metadata and it needs to be also up and running. Starting NameNode with existing set of data may easily take many minutes to parse the actual filesystem state.
Previously used solution - depoying SecondaryNameNode - was somewhat flawed. It took long time to recover after failure. It was not a hot-backup solution, which also added to the problem. Some other solution was required.
So, what needed to be made redundant is the edits dir contents and sending block location maps from each of the DataNodes to NameNodes - in case of HA deployment - to both NameNodes. This was accomplished in two steps. The first one with the release of CDH 4 beta - solution based on sharing edits directory. Than, with CDH 4.1 came quorum based solution.
Find out how to configure those on your cluster.
Shared edits directory solution
For this kind of setup, there is an assumption, that in a cluster exists a shared storage directory. It should be deployed using some kind of network-based filesystem. You could try with NFS or GlusterFS.
This setup is quite OK, as long as you’re comfortable with maintaining a separate service (network storage) for handling the HA state. It seems error prone to me, because it adds another service which high availability should be ensured. NFS seems to be a bad choice here, because AFAIK it does not offer HA out of the box.
On the other hand, we have GlusterFS, which is a distributed filesystem, you can deploy on multiple bricks and increase the replication level.
Nevertheless, it still brings additional burden of another service to maintain.
Quorum based solution
With the release of CDH 4.1.0 we are now able to use a much better integrated solution called JournalNode. Now all the updates are synchronized through a JournalNode. Each JournalNode have the same data and all the NameNodes are able to recive filesystem state updates from that daemons.
This solution is much more consistent with Hadoop ecosystem.
Please note, that the config is almost identical to the one needed for shared edits directory solution. The only difference is the value for dfs.namenode.shared.edits.dir. This now points to all the journal nodes deployed in our cluster.
Infrastructure
In both cases you need to run Zookeeper-based Failover Controller (hadoop-hdfs-zkfc). This daemon negotiates which NameNode should become active and which standby.
But that’s not all. Depending on the way you’ve choosen to deploy HA you need to do some other things:
Shared edits dir
With shared edits dir you need to deploy networked filesystem, and mount it on your NameNodes. After that you can run your cluster and be happy with your new HA.
Quroum based
For QJournal to operate you need to install one new package called hadoop-hdfs-journalnode. This provides startup scripts for Journal Node daemons. Choose at least three nodes that will be responsible for handling edits state and deploy journal nodes on them.
Conclusion
Thanks to guys from Cloudera we now can use an enterprise grade High Availability features for Hadoop. Eliminating the single point of failure in your cluster is essential for easy maintainability of your infrastructure.
Given the above choices, I’d suggest using QJournal setup, becasue of its relatively small impact on the overal cluster architecture. It’s good performance and fairly simple setup enable the users to easily start using Hadoop in HA setup.
Are you using Hadoop with HA? What are your impressions?