How to Use Hadoop as a Piece of the Big Data Puzzle

August 30, 2016 by Leave a Comment

Organizations are embracing Hadoop for several notable merits:

• Hadoop is distributed. Bringing a high-tech twist to the adage, “Many hands make light work,” data is stored on local disks of a distributed cluster of servers.
• Hadoop runs on commodity hardware. Based on the average cost per terabyte of compute capacity of a prepackaged system, Hadoop is easily 10 times cheaper for comparable computing capacity compared to higher-cost specialized hardware.
• Hadoop is fault-tolerant. Hardware failure is expected and is mitigated by data replication and speculative processing. If capacity is available, Hadoop runs multiple copies of the same task, accepting the results from the task that finishes first. To learn more read this white paper.

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How YARN Opens Doors to Easier Programming Tools for Hadoop 2.0 Users

August 30, 2016 by Leave a Comment

The emergence of YARN for the Hadoop 2.0 platform has opened the door to new tools and applications that promise to allow more companies to reap the benefits of big data in ways never before possible with outcomes possibly never imagined. By separating the problem of cluster resource management from the data processing function, YARN offers a world beyond MapReduce: less encumbered by complex programming protocols, faster, and at a lower cost. To learn more download this white paper.

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From Yawn to YARN: Why You Should be Excited About Hadoop® 2

August 30, 2016 by Leave a Comment

By now almost everyone has heard the story of the yellow elephant who never forgets data, consumes whatever data you have from any source, and magically produces a big data treasure trove of business insights for you, including tweets, telemetry, customer sentiment, sensor readings, mobile app activity, and more!  In fact, the story has been told and re-told so many […]

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