Notes by Arun C. Murthy

• Shared goals
  • Hadoop is HDFS & Map-Reduce in this context of this set of slides
• Priorities
  • Yahoo
    • Correctness
    • Availability: Not the same as high-availability (6 9s. etc.) i.e. SPOFs
    • API Compatibility
    • Scalability
    • Operability
    • Performance
    • Innovation
  • Cloudera
    • Test coverage, api coverage
    • APL Licensed codec (lzo replacement)
    • Security
    • Wire compatibility
    • Cluster-wide resource availability
    • New apis (FileContext, MR Context Objs.), documentation of their advantages
    • HDFS to better support non-MR use-cases
    • Cluster metrics hooks
    • MR modularity (package)
  • Facebook
    • Correctness
    • Availability, High Availability, Failover, Continuous Availability
    • Scalability
• Bar for patches/features keeps going higher as the project matures
  • Build consensus (e.g. Python Enhancement Process, JSR etc.)
  • Run/test on your own to prove the concept/feature or branch and finish
  • Early versions of libraries should be started outside of the project (github etc.) e.g. input-formats, compression-codecs etc.
    • github for all the above
    • Prune contrib
• Maven for packaging
• Tom: Hadoop Common/HDFS/Mapreduce 0.21 release
  • Re‐branch ✔
  • Close blockers
    • Definition? Deadline? Please help!
    • http://bit.ly/common21blockers
    • http://bit.ly/hdfs21blockers
    • http://bit.ly/mapreduce21blockers
  • Create builds
    • Post-split considerations: #artifacts, bin, conf, docs
  • Test
    • Community driven, wiki
  • Vote and release
    • Caveats: not stable
• Owen: Release Manager (see slides)
• Agenda for next meeting
  • Eli: Hadoop Enhancement Process (modelled on PEP?)
  • Branching strategies: Development Models