The Business Value Of Upgrading To Hadoop 3

Kevin Feasel

2018-02-12

Hadoop

Roni Fontaine, Vinod Vavilapalli, and Saumitra Buragohain explain some of the business case for upgrading to Hadoop 3 from Hadoop 2:

Hadoop 2 doesn’t support GPUs. Hadoop 3 enables scheduling of additional resources, such as disks and GPUs for better integration with containers, deep learning & machine learning.  This feature provides the basis for supporting GPUs in Hadoop clusters, which enhances the performance of computations required for Data Science and AI use cases.

Hadoop 2 cannot accommodate intra-node disk balancing. Hadoop 3 has intra-node disk balancing. If you are repurposing or adding new storage to an existing server with older capacity drives, this leads to unevenly disks space in each server.   With intra-node disk balancing, the space in each disk is evenly distributed.

Hadoop 2 has only inter-queue preemption across queues. Hadoop 3 introduces intra-queue preemption which goes to the next level time by allowing preemption between application within a single queue. This means that you can prioritize jobs within the queue based on user limits and/or application priority

Read on for more examples.

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