Cloudera Engineering Blog · CDH Posts
I recently gave a talk at the LA Hadoop User Group about Apache HBase Do’s and Don’ts. The audience was excellent and had very informed and well articulated questions. Jody from Shopzilla was an excellent host and I owe him a big thanks for giving the opportunity to speak with over 60 LA Hadoopers. Since not everyone lives in LA or could make it to the meetup, I’ve summarized some of the salient points here. For those of you with a busy day, here’s the tl;dr:
I am very pleased to announce the general availability of Cloudera’s Distribution including Apache Hadoop, version 3. We’ve been working on this release for more than a year — our initial beta release was on March 24 of 2010, and we’ve made a number of enhancements to the software in the intervening months. This release is the culmination of that long process. It includes the hard work of the broad Apache Hadoop community and the entire team here at Cloudera.
We’ve done three things in this release that I’m particularly proud of.
On Monday, we held our second Flume Office Hours at Cloudera HQ in Palo Alto. The intent was to meet informally, to talk about what’s new, to answer questions, and to get feedback from the community to help prioritize features for future releases.
Below is the slide deck from Flume Office Hours:
Cloudera is happy to announce the fourth beta release of Cloudera’s Distribution for Apache Hadoop version 3 — CDH3b4. As usual, we’d like to share a few highlights from this release.
Since this will be the last beta before we designate CDH3 stable, our focuses for this release have been on stability, security, and scalability.
A common question on the Apache Hadoop mailing lists is what’s going on with availability? This post takes a look at availability in the context of Hadoop, gives an overview of the work in progress and where things are headed.
When discussing Hadoop availability people often start with the NameNode since it is a single point of failure (SPOF) in HDFS, and most components in the Hadoop ecosystem (MapReduce, Apache HBase, Apache Pig, Apache Hive etc) rely on HDFS directly, and are therefore limited by its availability. However, Hadoop availability is a larger, more general issue, so it’s helpful to establish some context before diving in.