ODPi, a nonprofit organization accelerating the open ecosystem of big data solutions, announced the first release of the ODPi Runtime Specification and test suite to ensure applications will work across multiple Apache Hadoop® distributions.
Designed to make it easier to create big data solutions and data-driven applications, the ODPi Runtime Specification is the first release from the industry-backed organization. While the Hadoop ecosystem is rapidly innovating, a certain degree of diversity and complexity are actually impeding adoption. Founded last year, more than 25 ODPi members are focused on simplification and standardization within the big data ecosystem and further advancing the work of the Apache Software Foundation.
Descending from Apache Hadoop 2.7, the Runtime Specification features HDFS, YARN, and MapReduce components and is part of the common reference platform ODPi Core.
The turbulent big data market needs more confidence, more maturity, and less friction for both technology vendors and consumers alike,” said Nik Rouda, senior big data analyst at Enterprise Strategy Group (ESG). “ESG research found that 85% of those responsible for current Hadoop deployments believed that ODPi would add value.”
Key ODPi Runtime Specification Technical Features
The ODPi test framework and self-certification also aligns closely with the Apache Software Foundation by leveraging Apache BigTop for comprehensive packaging, testing, and configuration. Additionally, more than half the code in the latest Big Top release originated in ODPi.
All ODPi Runtime-Compliance tests are linked directly to lines in the ODPi Runtime Specification. To assist with compliance, in addition to the test suite, ODPi also provides a reference build.
The published specification also includes rules and guidelines on how to incorporate additional, non-breaking features, which are allowed provided source code is made available through relevant Apache community processes.
What’s Next for ODPi
The ODPi Operations Specification to help enterprises improve installation and management of Hadoop and Hadoop-based applications will be available later this year. The Operations Specification covers Apache Ambari, the ASF project for provisioning, managing, and monitoring Apache Hadoop clusters.
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,” said John Mertic, senior manager of ODPi. “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.”
Comments from Members
With its broader, flexible approach to standardizing the Hadoop stack, ODPi is particularly attractive to smaller companies, such as Ampool. 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 for us.” – Milind Bhandarkar, Ph.D, founder and CEO, Ampool
ODPi will simplify developing and testing applications that work across distros and hence lower the cost of building Hadoop-based big data applications. For example, DataTorrent will be able to certify RTS installation and runtime for ODPi and know it will work with multiple platform providers.” – Thomas Weise, Apache Apex (incubating) PPMC member and architect/co-founder, DataTorrent
At Hortonworks, 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. As a founding member, 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.” – Alan Gates, co-founder, Hortonworks
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.” – Rob Thomas, vice president of product development, IBM Analytics
Linaro recognizes the importance of ODPi’s work to promote and advance the state of Apache Hadoop and Big Data technologies for the enterprise while minimizing fragmentation and redundant effort. Linaro’s own focus is similar to this in developing open source software for the ARM ecosystem and it makes perfect sense that where these two areas intersect that Linaro and ODPi should work together to ensure ARM is fully supported and that fragmentation is minimized across the industry.” – Martin Stadtler, director of the Linaro Enterprise Group (LEG)
It was a little over a year ago that ODPi was formed, and we have already proved beneficial to upstream ASF projects (Hadoop, Bigtop, Ambari). There’s a need for a stable enterprise-grade platform that is managed as an industry asset to benefit all of the companies driving value from Hadoop and big data. This is why the first release of the ODPi Runtime Specification and test suite is so exciting. It is a big step toward realizing our goal of accelerating the delivery of business outcomes through big data solutions by driving interoperability on an enterprise-ready core platform.” – Roman Shaposhnik, director of Open Source at Pivotal, Apache Hadoop and Bigtop committer and ASF member
As a founding member, SAS’s support of the Open Data Platform Initiative demonstrates our ongoing commitment to developing innovative applications and solutions for our customers that are compatible with the Hadoop ecosystem. OPDi enables us to remain committed to ensuring our applications work with and exploit the Hadoop distribution of our customers’ choice, while being able to bank on the stability and quality expected in demanding business environments.” – Craig Rubendall, vice president of platform R&D, SAS
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