The document discusses Hadoop, an open-source software framework for distributed storage and processing of large datasets. It provides an overview of who is using Hadoop, how it is developed under the Apache Software Foundation, how to contribute to the project, and future directions for Hadoop and its core technologies HDFS and MapReduce.

2. The Hadoop Community
Jeff Hammerbacher
Manager, Data
May 28 - 29, 2008

3. Who is Using Hadoop?
▪ Mentioned previously: Yahoo!, Powerset, Quantcast, Last.fm, Autodesk
▪ A9.com
▪ Build Amazon’s product search indices
▪ Session analytics
▪ FIM
▪ Log analysis and machine learning
▪ Wikia Search
▪ 125 nodes
▪ Veoh, NetSeer, Krugle, Rapleaf, Joost, New York Times
▪ For more, check out http://wiki.apache.org/hadoop/PoweredBy

4. Hadoop in the ASF
▪ Began life as subproject of Lucene
▪ Now a top level project: http://hadoop.apache.org
▪ HBase now a subproject of Hadoop
▪ Pig and Mahout are related projects
▪ Zookeeper and virtual cluster management project in Apache soon
▪ Apache Software Foundation provides organizational and legal support
▪ Membership in ASF is by invitation only
▪ ASF Members elect a Board of Directors
▪ Each top level project has a Project Management Committee (PMC)
▪ Each PMC has a VP who is an officer of the ASF appointed by the Board
▪ The VP of the Hadoop PMC is Owen O’Malley of Yahoo

5. The Hadoop PMC
Name Organization
Andrzej Bialecki Getopt
Doug Cutting Yahoo!
Dhruba Borthakur Facebook
Enis Soztutar Agmlab
Jim Kellerman Powerset
Nigel Daley Yahoo!
Owen O’Malley Yahoo!
Michael Stack Powerset
Christophe Taton INRIA
Tom White Independent Consultant

6. Apache Infrastructure for Hadoop
▪ Web site: Apache Forrest
▪ Wiki: MoinMoin
▪ Version Control: Subversion
▪ API Documentation: JavaDoc
▪ Bug Tracking: JIRA
▪ Continuous Build Server: Hudson
▪ IRC Channel: #hadoop on irc.freenode.org
▪ And of course, the mailing lists:
▪ core-user@hadoop.apache.org
▪ core-dev@hadoop.apache.org

7. Contributing to Hadoop
▪ Get comfortable with available documentation on the website
▪ Read through the wiki
▪ Browse the mailing list archives
▪ Dig into the JIRA!
▪ Open source bug tracking software from Atlassian
▪ “Issues”: Bugs, feature requests, documentation requests
▪ Issues categorized by “component” and “version”
▪ “Workflow”: Issue as FSM; each state is a “status”
▪ http://www.atlassian.com/software/jira/docs/latest/introduction.html

8. Contributing to Hadoop
More About JIRA
▪ Every Issue has a unique, numbered Key
▪ Type
▪ Status
▪ Priority
▪ Assignee
▪ Reporter
▪ Votes
▪ Watchers

9. Contributing to Hadoop
More About Ticket Classification
▪ Status: Open, In Progress, Reopened, Resolved, Closed, or Patch Available
▪ Priorities: Blocker, Critical, Major, Minor, Trivial
▪ Type: Bug, Improvement, New Feature, Task
▪ Voting on an issue means you actively want to see it fixed
▪ Watching an issue means you can passively track progress

10. Contributing to Hadoop
More About JIRA
▪ Title, Created Time, Updated Time, Component, Affect/Fix Version, Links/
Sub-Tasks, Description, Comments

11. Contributing to Hadoop
Filters and the Issue Navigator
▪ You can view related Issues via the Issue Navigator
▪ “Filter” determines what is shown in the Navigator
▪ Common Filters on the right-hand side of main login
▪ Outstanding, Assigned to Me, Reported by Me, Resolved Recently, Added
Recently, Updated Recently, Most Important
▪ “Most Important” Filter just sorts by Issue Priority
▪ I’d recommend the “... Recently” and “Most Important” Filters first
▪ Can also click “Find Issues” on top nav to build your own Filters

12. The JIRA Issue Navigator

13. The JIRA Issue Navigator
Creating a New Filter

14. Contributing to Hadoop
JIRA Reports and Release Notes
▪ Reports add a visualization component to Filters
▪ Most can be applied to any saved filter
▪ Some Reports have a chart configured
▪ Common Reports:
▪ Road Map
▪ Open Issues
▪ Popular Issues (based on number of Votes)
▪ To keep up with what’s new, the Release Notes are quite useful

15. Future Directions for Hadoop
HDFS
▪ For 0.18
▪ HADOOP-1700: Append to Files in HDFS
▪ Numerous blocking issues; hope to have code freeze by early June
▪ 8 Voters, 21 Watchers
▪ HADOOP-3022: Fast Cluster Restart
▪ HADOOP-1702: Reduce buffer copies when data is written to DFS
▪ HADOOP-3164: Use FileChannel.transferTo() when data is read from DN
▪ HADOOP-3058: Hadoop DFS to report more replication metrics
▪ HADOOP-3246: FTP client over HDFS

16. Future Directions for Hadoop
HDFS
▪ Scalability
▪ Separate DFS into multiple volumes and have a NN per volume
▪ Manage volume metadata in Zookeeper
▪ Availability
▪ Mirroring
▪ Have Zookeeper manage metadata
▪ Backup and Recovery
▪ Synchronized global snapshot via ZFS or LVM
▪ http://wiki.apache.org/hadoop/HdfsFutures

17. Future Directions for Hadoop
MapReduce
▪ For 0.18
▪ HADOOP-544: Replace the job, tip and task ids with objects
▪ HADOOP-3245: Provide ability to persist running jobs
▪ HADOOP-3130: Shuffling takes too long to get the last map output
▪ HADOOP-3221: Need a quot;LineBasedTextInputFormatquot;
▪ HADOOP-3149: Supporting multiple outputs for M/R jobs
▪ HADOOP-2182: Input Split details for maps should be logged
▪ HADOOP-3226: Run combiner when merging spills from map output
▪ HADOOP-3227: Implement a binary input/output format for Streaming

18. Future Directions for Hadoop
MapReduce
▪ Scheduling
▪ Factor job and task scheduling out of code to allow for testing
different policies (HADOOP-3412)
▪ Augment JobTracker to be a resource manager and job scheduler
▪ Speculative Execution Policies
▪ Separate logic for Mapper and Reducer
▪ Break Reducer into more granular tasks
▪ Allow for execution across many different data sources
▪ for example, MySQL

19. Future Directions for Hadoop
Other Interesting Tickets
▪ HADOOP-4: Tool to mount dfs on linux
▪ HADOOP-249: Improving Map -> Reduce performance and Task JVM reuse
▪ HADOOP-2510: Map-Reduce 2.0
▪ HADOOP-2864: Improve the Scalability and Robustness of IPC
▪ HADOOP-2884: Refactor Hadoop package structure and source tree
▪ HADOOP-3366: Shuffle/Merge improvements
▪ HADOOP-3421: Requirements for a Resource Manager for Hadoop
▪ HADOOP-3444: Implementing a Resource Manager (V1) for Hadoop

20. Contributing to Hadoop
Patch Submission
▪ http://wiki.apache.org/hadoop/HowToContribute
▪ Basically run “svn diff” on your checkout of trunk and write output to a
“.patch” file, then attach it to the issue
▪ Hudson will pick up patch and apply to trunk
▪ Make sure to have tests and JavaDoc comments
▪ Performance regressions tested via DFSIO and GridMix benchmarks

21. Contributing to Hadoop
Project Ideas
▪ http://wiki.apache.org/hadoop/ProjectSuggestions
▪ Testing, Tools, and Research
▪ Security
▪ Tools
▪ Performance monitoring and benchmarking
▪ Anomaly detection
▪ General system management

22. Contributing to Hadoop
Project Ideas continued
▪ Performance
▪ Speculative execution policies
▪ Resource-aware task scheduling (instead of slot-based)
▪ Better failure detection algorithms
▪ Linear Algebra, Statistics, and Machine Learning
▪ SAS/R for massive data sets
▪ Vector and Matrix algebra libraries
▪ Common statistical functions: point estimation, hypothesis testing
▪ Model training and validation libraries

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