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From Ross Gardler <>
Subject Re: [PROPOSAL] Oozie for the Apache Incubator
Date Wed, 29 Jun 2011 10:22:39 GMT
You might want to reconsider the name.

In English (British English at least) "ooze" is an unpleasant thing
often related to a body wound or a stagnant river. The formal
definition is not so bad [1], but in common (UK) usage it's



On 29 June 2011 03:07, <> wrote:
> +1 (non-binding).
> Thanks,
> Arvind
> On Fri, Jun 24, 2011 at 12:46 PM, Mohammad Islam <> wrote:
>> Hi,
>> I would like to propose Oozie to be an Apache Incubator project.
>> Oozie is a server-based workflow scheduling and coordination system to manage
>> data processing jobs for Apache Hadoop.
>> Here's a link to the proposal in the Incubator wiki
>> I've also pasted the initial contents below.
>> Regards,
>> Mohammad Islam
>> Start of Oozie Proposal
>> Abstract
>> Oozie is a server-based workflow scheduling and coordination system to manage
>> data processing jobs for Apache HadoopTM.
>> Proposal
>> Oozie is an  extensible, scalable and reliable system to define, manage,
>> schedule,  and execute complex Hadoop workloads via web services. More
>> specifically, this includes:
>>        * XML-based declarative framework to specify a job or a complex workflow
>> dependent jobs.
>>        * Support different types of job such as Hadoop Map-Reduce, Pipe, Streaming,
>> Pig, Hive and custom java applications.
>>        * Workflow scheduling based on frequency and/or data availability.
>>        * Monitoring capability, automatic retry and failure handing of jobs.
>>        * Extensible and pluggable architecture to allow arbitrary grid programming
>> paradigms.
>>        * Authentication, authorization, and capacity-aware load throttling to
>> multi-tenant software as a service.
>> Background
>> Most data  processing applications require multiple jobs to achieve their goals,
>> with inherent dependencies among the jobs. A dependency could be  sequential,
>> where one job can only start after another job has finished.  Or it could be
>> conditional, where the execution of a job depends on the  return value or status
>> of another job. In other cases, parallel  execution of multiple jobs may be
>> permitted – or desired – to exploit  the massive pool of compute nodes provided
>> by Hadoop.
>> These  job dependencies are often expressed as a Directed Acyclic Graph, also
>> called a workflow. A node in the workflow is typically a job (a  computation on
>> the grid) or another type of action such as an eMail  notification. Computations
>> can be expressed in map/reduce, Pig, Hive or  any other programming paradigm
>> available on the grid. Edges of the graph  represent transitions from one node
>> to the next, as the execution of a  workflow proceeds.
>> Describing  a workflow in a declarative way has the advantage of decoupling job
>> dependencies and execution control from application logic. Furthermore,  the
>> workflow is modularized into jobs that can be reused within the same  workflow
>> or across different workflows. Execution of the workflow is  then driven by a
>> runtime system without understanding the application  logic of the jobs. This
>> runtime system specializes in reliable and  predictable execution: It can retry
>> actions that have failed or invoke a  cleanup action after termination of the
>> workflow; it can monitor  progress, success, or failure of a workflow, and send
>> appropriate alerts  to an administrator. The application developer is relieved
>> from  implementing these generic procedures.
>> Furthermore,  some applications or workflows need to run in periodic intervals
>> or  when dependent data is available. For example, a workflow could be  executed
>> every day as soon as output data from the previous 24 instances  of another,
>> hourly workflow is available. The workflow coordinator  provides such scheduling
>> features, along with prioritization, load  balancing and throttling to optimize
>> utilization of resources in the  cluster. This makes it easier to maintain,
>> control, and coordinate  complex data applications.
>> Nearly  three years ago, a team of Yahoo! developers addressed these critical
>> requirements for Hadoop-based data processing systems by developing a  new
>> workflow management and scheduling system called Oozie. While it was  initially
>> developed as a Yahoo!-internal project, it was designed and  implemented with
>> the intention of open-sourcing. Oozie was released as a GitHub project in early
>> 2010. Oozie is used in production within Yahoo and  since it has been
>> open-sourced it has been gaining adoption with  external developers
>> Rationale
>> Commonly,  applications that run on Hadoop require multiple Hadoop jobs in order
>> to  obtain the desired results. Furthermore, these Hadoop jobs are commonly  a
>> combination of Java map-reduce jobs, Streaming map-reduce jobs, Pipes
>> map-reduce jobs, Pig jobs, Hive jobs, HDFS operations, Java programs  and shell
>> scripts.
>> Because  of this, developers find themselves writing ad-hoc glue programs to
>> combine these Hadoop jobs. These ad-hoc programs are difficult to  schedule,
>> manage, monitor and recover.
>> Workflow  management and scheduling is an essential feature for large-scale data
>> processing applications. Such applications could write the customized  solution
>> that would require separate development, operational, and  maintenance overhead.
>> Since it is a prevalent use-case for data  processing, the application developer
>> would surely prefer a generalized  solution with little or no such overhead.
>> Oozie addresses the challenge  by providing an execution framework to flexibly
>> specify the job  dependency, data dependency, and time dependency. In addition,
>> Oozie  provides a multi-tenant-based centralized service and the opportunity to
>> optimize load and utilization while respecting SLAs.
>> Oozie  is built on Apache Hadoop to schedule jobs related to various Apache
>> projects such as Hadoop, Pig, and Hive. As an Apache Open source  project, Oozie
>> is expected to attract the larger and more diversified  community that currently
>> uses such Apache sponsored projects.  Additionally, users of the Hadoop
>> ecosystem can influence Oozie’s  roadmap, and contribute to it. Likewise, Oozie,
>> as part of the Apache  Hadoop ecosystem, will be a great benefit to the current
>> Hadoop/Pig/Hive/HBase/HCatalog community.
>> Current Status
>> Meritocracy
>> Oozie  currently is a github-based open sourced project where developers from
>> multiple companies are contributing to the project. Our intent with this
>> incubator proposal is to further extend this diverse developer  community around
>> Oozie following the Apache meritocracy model. We plan  to continue to provide
>> adequate support to new developers and to quickly  recruit those who make solid
>> contributions to committer status. In  addition, Oozie will expect, accept, and
>> work to attract contributions  from amateurs as well.
>> Community
>> While an  efficient workflow management and scheduling system is critical for
>> large companies with huge data processing in multi-tenant clusters, it  is
>> equally necessary for any non-trivial deployment. Different companies  are
>> currently using Oozie as a workflow scheduler for Hadoop-based data  processing.
>> At Yahoo! it is being used extensively in production  clusters to process
>> thousand of jobs. Like the Oozie user community, the  Oozie developer community
>> is also very strong. Developers from Yahoo!  provided the initial code base, and
>> they are still the most active  contributors. In late 2010, developers from
>> Cloudera also started  contributing, and currently other companies (e.g., IBM)
>> are beginning to  participate.
>> We currently use JIRA for issue tracking, github for code hosting and Yahoo!
>> Groups for developer and user communications.
>> Core Developers
>> Oozie is  currently being designed and developed by four engineers from Yahoo! –
>> Mohammad Islam, Angelo Huang, Mayank Bansal, and Andreas Neumann. In  addition,
>> many outside contributors are actively contributing in design  and development.
>> Among them, Alejandro Abdelnur from Cloudera and Chao  Wang from IBM are very
>> important contributors. All of these core  developers have deep expertise in
>> Hadoop and the Hadoop Ecosystem in  general.
>> Alignment
>> The ASF is a  natural host for Oozie given that it is already the home of
>> Hadoop,  Pig, Hive, and other emerging cloud software projects. Oozie was
>> designed to support Hadoop from the beginning in order to solve data  processing
>> challenges in Hadoop clusters. Oozie complements the existing  Apache cloud
>> computing projects by providing a flexible framework for  managing complex data
>> processing tasks.
>> Known Risks
>> Orphaned Products
>> The core  developers plan to work full time on the project. There is very little
>> risk of Oozie getting orphaned since large companies like Yahoo! are
>> extensively using it on their production Hadoop clusters. For example,  there
>> are nearly 400 Yahoo! internal Oozie users and thousands of jobs  are processed
>> hourly through Oozie in production. In addition, there are  nearly 400 active
>> users (including Yahoo! internal and external) in the  email community where
>> nearly 15 emails are exchanged per day.  Furthermore, there were more than 1500
>> downloads of the Oozie binary in  the last eight months from the github site and
>> a large number of  downloads were conducted by other companies such as Cloudera.
>> Oozie has  three major releases and more than 15 patch releases in the last
>> couple  of years which further demonstrates Oozie as a very active project. We
>> plan to extend and diversify this community further through Apache.
>> Inexperience with Open Source
>> The core  developers are all active users and followers of open source. They are
>> already committers and contributors to the Oozie Github project. In  addition,
>> they are very familiar with Apache principals and philosophy  for community
>> driven software development.
>> Homogeneous Developers
>> The core developers are from Yahoo! as well as from several other corporations,
>> including Cloudera and IBM.
>> Reliance on Salaried Developers
>> Currently,  the developers are paid to do work on Oozie. Companies like Yahoo!
>> and  Cloudera are invested in Oozie as the solution to the workflow  management
>> and scheduling problem in Hadoop clusters, and that is not  likely to change. In
>> addition, since workflow management is very  important for most hadoop based
>> data processing, non-salaried developers  and researchers from various
>> institutes are expected to contribute to  the project.
>> Relationships with Other Apache Products
>> Oozie is  based on Apache Hadoop to manage jobs created by different Apache
>> projects such as Hadoop, Pig, and Hive. Users of these products are  extensively
>> using Oozie as their workflow scheduler.
>> An Excessive Fascination with the Apache Brand
>> We deeply  respect the reputation of Apache and have had great success with
>> other  Apache projects such as Pig and HCatalog. We are motivated to expand and
>> increase the adoption and development of Oozie following Apache’s  established
>> open source model. We have also given reasons in the  Rationale and Alignment
>> sections.
>> Documentation
>> Information about Oozie can be found at The
>> following links provide more information about Oozie in open source:
>>        * Codebase at GitHub:
>>        * JIRA :
>>        * Continuous Integration (CI) build:
>>        * Yahoo user community:
>> Initial Source
>> Oozie has been under development since 2009 by a team of engineers at Yahoo!. It
>> is currently hosted on GitHub under an Apache license at
>> External Dependencies
>> The required  external dependencies are all Apache License or compatible
>> licenses.  Following the components with non-Apache licenses are enumerated:
>>        * HSQLDB License: HSQLDB
>>        * JDOM license: JDOM
>>        * BSD: Serp
>>        * CCDL v1: jaxb-api, ejb, JAF
>> NOTE:  With the exception of HSQLDB and JDOM that are directly used by Oozie,
>> the other listed components are transitive dependencies of other Apache
>> components used by Oozie.
>> Cryptography
>> Oozie supports the Kerberos authentication mechanism to access secured Hadoop
>> services.
>> Required Resources
>> Mailing Lists
>>        * oozie-private for private PMC discussions (with moderated subscriptions)
>>        * oozie-dev
>>        * oozie-commits
>>        * oozie-user
>> Subversion Directory
>> Issue Tracking
>> JIRA Oozie (OOZIE)
>> Other Resources
>> The  existing code already has unit tests, so we would like a Hudson instance
>> to run them whenever a new patch is submitted. This can be added after  project
>> creation.
>> Initial Committers
>>        * Mohammad K Islam (mislam77 at yahoo  dot com)
>>        * Angelo K Huang (angelohuang at gmail dot com)
>>        * Mayank Bansal (mabansal at gmail dot com)
>>        * Andreas Neumann (neunand at gmail dot com)
>>        * Alejandro Abdelnur (tucu00 at gmail dot com)
>>        * Chao Wang (brookwc at gmail dot com)
>> Affiliations
>>        * Mohammad K Islam (Yahoo!)
>>        * Angelo Huang (Yahoo!)
>>        * Mayank Bansal (Yahoo!)
>>        * Andreas Neumann (Yahoo!)
>>        * Alejandro Abdelnur (Cloudera)
>>        * Chao Wang (IBM)
>> Sponsors
>> Champion
>> Alan Gates
>> Nominated Mentors
>>        * Owen O'Malley (Incubator PMC member)
>>        * Alan Gates (Incubator PMC member)
>>        * Christopher Douglas(Incubator PMC member)
>>        * Devaraj Das (Hadoop PMC member)
>> Sponsoring EntityWe are requesting the Incubator to sponsor this project.
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Ross Gardler (@rgardler)
Programme Leader (Open Development)

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