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Accelerating Big Data with Hadoop (HDFS, MapReduce, and HBase)

DZone's Guide to

Accelerating Big Data with Hadoop (HDFS, MapReduce, and HBase)

· Database Zone
Free Resource

Read why times series is the fastest growing database category.

In this video, D.K. Panda from Ohio State University presents: Accelerating Big Data with Hadoop (HDFS, MapReduce and HBase) and Memcached.

"The SuperMUC has 147,456 cores and a peak performance of about 3 petaflop/s. The main memory will be 288 terabytes together with 12 petabytes hard disk space based on the GPFS file system. The system will use 18,432 Intel Xeon Sandy Bridge-EP processors running in IBM System x iDataPlex servers. It will also use a new form of cooling that IBM developed, called Aquasar, that uses hot water to cool the processors, a design that should cut cooling electricity usage by 40 percent, IBM claims."

Recorded at the 2013 HPC Advisory Council Switzerland Conference.

Learn more at: http://www.hpcadvisorycouncil.com/eve...


Learn how to get 20x more performance than Elastic by moving to a Time Series database.

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