CDH3 Update 1 Released
Continuing with our practice from Cloudera’s Distribution Including Apache Hadoop v2 (CDH2), our goal is to provide regular (quarterly), predictable updates to the generally available release of our open source distribution. For CDH3 the first such update is available today, approximately 3 months from when CDH3 went GA.
For those of you who are recent Cloudera users, here is a refresh on our update policy:
- We will only include patches in updates that are non-compatibility breaking.
- We will only include patches in updates that are non-disruptive.
- You can skip updates without penalty – i.e., if you don’t find the contents of an update compelling, you can skip it and wait for a future update without having to do a delta upgrade.
There is one new addition to our update policy going forward: when it’s possible to pull features from our CDH4 roadmap into CDH3 updates in a non-disruptive way, we’ll take advantage of that opportunity.
With all that said, there are a number of improvements coming to CDH3 with update 1. Among them are:
- New features – integrated Apache-compatible licensed fast compression throughout CDH, web shell for Hue, Flume / HBase integration, Fair Scheduler ACL’s, improved datanode handling of hard drive failures, and email actions and date formatting for Oozie.
- Improvements (stability and performance) – HBase bulk loading, Namenode stability, Fuse-DFS (mountable HDFS).
- New component versions – Hive 0.7.1, Pig 0.8.1, Hbase 0.90.3, Flume 0.9.4 and Sqoop 1.3.
- Bug fixes – 80+ bug fixes. Per our standard practice, the enumerated fixes and their corresponding Apache project jiras are provided in the release notes.
Update 1 is available in all the usual formats (RHEL, SLES, Ubuntu, Debian packages, tarballs, and SCM Express). Check out the installation docs for instructions. If you’re running components from the Cloudera Management Suite they will not be impacted by moving to update 1. The next update (update 2) for CDH3 is planned for mid-October.
Thank you for supporting Apache Hadoop and thank you for supporting Cloudera.