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From Mohammad Islam <>
Subject [VOTE] Oozie to join the Incubator
Date Wed, 29 Jun 2011 19:10:26 GMT
Hi All,

The discussion about Oozie proposal is settling down. Therefore I would like to 
initiate a vote to accept Oozie as an Apache Incubator project.

The latest proposal is pasted at the end and it could be found in the wiki as 

The related discussion thread is at:

Please cast your votes:

[  ] +1 Accept Oozie for incubation
[  ] +0 Indifferent to Oozie incubation
[  ] -1 Reject Oozie for incubation

This vote will close 72 hours  from now.


Oozie is a server-based workflow scheduling and coordination system to manage 
data processing jobs for Apache HadoopTM. 

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 of 
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 

	* Authentication, authorization, and capacity-aware load throttling to allow 
multi-tenant software as a service. 

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 

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 

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 HadoopTM 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 TMecosystem, will be a great benefit to the current 
Hadoop/Pig/Hive/HBase/HCatalog community. 

Current Status
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. 

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. 

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 

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. 

Oozie supports the Kerberos authentication mechanism to access secured Hadoop 

Required Resources
Mailing Lists
	* oozie-private for private PMC discussions (with moderated subscriptions) 
	* oozie-dev 
	* oozie-commits 
	* oozie-user 
Subversion Directory 
Issue Tracking
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 

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) 
	* Mohammad K Islam (Yahoo!) 
	* Angelo Huang (Yahoo!) 
	* Mayank Bansal (Yahoo!) 
	* Andreas Neumann (Yahoo!) 
	* Alejandro Abdelnur (Cloudera) 
	* Chao Wang (IBM) 
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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