I'm pleased to announce that after some reflection, Yahoo! has decided to discontinue the "The Yahoo Distribution of Hadoop" and focus on Apache Hadoop. We plan to remove all references to a Yahoo distribution from our website (developer.yahoo.com/hadoop), close our github repo (yahoo.github.com/hadoop-common) and focus on working more closely with the Apache community. Our intent is to return to helping Apache produce binary releases of Apache Hadoop that are so bullet proof that Yahoo and other production Hadoop users can run them unpatched on their clusters.
Until Hadoop 0.20, Yahoo committers worked as release masters to produce binary Apache Hadoop releases that the entire community used on their clusters. As the community grew, we experimented with using the "Yahoo! Distribution of Hadoop" as the vehicle to share our work. Unfortunately, Apache is no longer the obvious place to go for Hadoop releases. The Yahoo! team wants to return to a world where anyone can download and directly use releases of Hadoop from Apache. We want to contribute to the stabilization and testing of those releases. We also want to share our regular program of sustaining engineering that backports minor feature enhancements into new dot releases on a regular basis, so that the world sees regular improvements coming from Apache every few months, not years.
Recently the Apache Hadoop community has been very turbulent. Over the last few months we have been developing Hadoop enhancements in our internal git repository while doing a complete review of our options. Our commitment to open sourcing our work was never in doubt, but the future of the "Yahoo Distribution of Hadoop" was far from clear. We've concluded that focusing on Apache Hadoop is the way forward. We believe that more focus on communicating our goals to the Apache Hadoop community, and more willingness to compromise on how we get to those goals, will help us get back to making Hadoop even better.
Unfortunately, we now have to sort out how to contribute several person-years worth of work to Apache to let us unwind the Yahoo! git repositories. We currently run two lines of Hadoop development, our sustaining program (hadoop-0.20-sustaining) and hadoop-future. Hadoop-0.20-sustaining is the stable version of Hadoop we currently run on Yahoo's 40,000 nodes. It contains a series of fixes and enhancements that are all backwards compatible with our "Hadoop 0.20 with security". It is our most stable and high performance release of Hadoop ever. We've expended a lot of energy finding and fixing bugs in it this year. We have initiated the process of contributing this work to Apache in the branch: hadoop/common/branches/branch-0.20-security. We've proposed calling this the 20.100 release. Once folks have had a chance to try this out and we've had a chance to respond to their feedback, we plan to create 20.100 release candidates and ask the community to vote on making them Apache releases.
Hadoop-future is our new feature branch. We are working on a set of new features for Hadoop to improve its availability, scalability and interoperability to make Hadoop more usable in mission critical deployments. You're going to see another burst of email activity from us as we work to get hadoop-future patches socialized, reviewed and checked in. These bulk checkins are exceptional. They are the result of us striving to be more transparent. Once we've merged our hadoop-future and hadoop-0.20-sustaining work back into Apache, folks can expect us to return to our regular development cadence. Looking forward, we plan to socialize our roadmaps regularly, actively synchronize our work with other active Hadoop contributors and develop our code collaboratively, directly in Apache.
In summary, our decision to discontinue the "Yahoo! Distribution of Hadoop" is a commitment to working more effectively with the Apache Hadoop community. Our goal is to make Apache Hadoop THE open source platform for big data.
PS Here is a draft list of key features in hadoop-future:
* HDFS-1052 - Federation, the ability to support much more storage per Hadoop cluster.
* HADOOP-6728 - A the new metrics framework
* MAPREDUCE-1220 - Optimizations for small jobs