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Big Data Consortium Announces Runtime Spec for Hadoop Ecosystem

The Open Data Platform Initiative (ODPi) announced the release of its ODPi runtime specification and test suite in order to ensure that the applications will work across multiple Apache Hadoop distributions.

Tahseen Jamil Mar 30, 2016

The Open Data Platform Initiative (ODPi), a non-profit consortium of big data industry leaders focused on standardization and simplification of the big data ecosystem, announced the release of its ODPi runtime specification and test suite in order to ensure that the applications will work across multiple Apache Hadoop distributions.
Descending from Apache Hadoop 2.7, the runtime specification which includes HDFS, YARN, and MapReduce components and it is part of the common reference platform ODPi Core.
The ODPi test framework and self-certification align closely with the Apache Software Foundation by leveraging Apache Bigtop for comprehensive packaging, testing, and configuration. More than half the code available in the latest Bishop release originates in ODPi.
The runtime specifications and test suits were designed in order to ensure the interoperability across the Hadoop ecosystem. The lack of standards which the ODPi believes that the current ecosystem is slowed by fragmented and duplicated efforts.
Alan Gates, co-founder of Hortonworks, an ODPi member organization, states,
“We aim to speed Hadoop adoption through ecosystem interoperability rooted in open source so enterprise customers can reap the benefits of increased choice with more modern data applications and solutions. We are pleased to see ODPi’s first release become available to the ecosystem and look forward to our continued involvement to accelerate the adoption of modern data applications.”
The published specification also includes rules and guidelines on incorporating additional non-breaking features, which are allowed provided that the source code is made available through the relevant Apache community processes.
Rob Thomas, vice president of product development, IBM Analytics, states,
“Big Data is the key to enterprises welcoming the cognitive era and there’s a need across the board for advancements in the Hadoop ecosystem to ensure companies can get the most out of their deployments in the most efficient ways possible. With the ODPi Runtime Specification, developers can write their application once and run it across a variety of distributions – ensuring more efficient applications that can generate the insights necessary for business change.”
Milind Bhandarkar, founder and CEO of ODPi member organization Ampool, states,
“With its broader, flexible approach to standardizing the Hadoop stack, ODPi is particularly attractive to smaller companies. Instead of spending testing/qualification cycles across different distributions and respective versions, the reference implementation would really help reduce both the effort and risk of Hadoop integration.”
This year, ODPi will be making it operational specification available, which is designed to help enterprises improve installation and management of Hadoop and Hadoop-based application. The operations specifications cover Apache Ambari, the Apache Software Foundation project for provisioning, managing, and monitoring Apache Hadoop clusters.
John Mertic, senior manager of ODPi, states,
“ODPi complements the work done in the Apache projects by filling a gap in the big data community in bringing together all members of the Hadoop ecosystem. Our members - Hadoop distros, app vendors, solution providers, and end-users - are fully committed to leveraging Apache projects and utilizing feedback from real-world use cases to provide industry guidance on how Hadoop should be deployed, configured, and managed. We will continue to expand and contribute to innovation happening inside the Hadoop ecosystem.”

Tahseen Jamil
Tahseen Jamil

I am a freelance writer for the past 3 and half years. I aspire to generate interesting and productive ideas to the readers through my writing. My objective is to share information with the readers and inform them about ... Read more

Hadoop Ecosystem