On Tuesday, Concurrent released Cascading 2.0 under the Apache 2.0 License Agreement. Cascading 2.0 adds a number of new features, including in-memory processing that allows users to run it in memory on a local computer to rapidly test Big Data applications in development. Upstream's Mason says his company made the switch to Cascading 2.0 about two months ago. But even as the CTO of a company that lives and dies on its ability to leverage Big Data, Mason is not as excited by the new features of Cascading as he is in the ability to use it to more easily build a team to meet Upstream's needs.
Leverage Java Developers for Big Data
"It's been easier to hire and build up a team around it," he says. "Cascading makes it look and operate like Java. Management can really go out and build a team around folks that are already very experienced with Java. Switching over to this is really a very short exercise."
He notes that Java developers do need to spend a few weeks learning about Hadoop basics in order to apply their Java knowledge to Cascading, but adds it's nothing compared with learning raw MapReduce.
"There's definitely a learning curve," he says. "But having to learn raw MapReduce is a pretty involved process and takes a lot of time. Cascading just takes that off the table and you don't have to worry about it. You have to understand the concepts of MapReduce, but you don't have to put your feet into the weeds of raw MapReduce."
Thor Olavsrud covers IT Security, Big Data, Open Source, Microsoft Tools and Servers for CIO.com. Follow Thor on Twitter @ThorOlavsrud. Follow everything from CIO.com on Twitter @CIOonline and on Facebook. Email Thor at firstname.lastname@example.org
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