You might have heard of Apache Tez, a new distributed execution framework that is targeted towards data-processing applications on Hadoop. But what exactly is it? How does it work? Who should use it and why? In their presentation, Apache Tez: Accelerating Hadoop Query Processing, Bikas Saha and Arun Murthy discuss Tez’s design, highlight some of its features and share some of the initial results obtained by making Hive use Tez instead of MapReduce. Presentation transcript edited by Roopesh Shenoy Tez generalizes the MapReduce paradigm to a more powerful framework based on expressing computations as a dataflow graph. Tez is not meant directly for end-users – in fact it enables developers to build end-user applications with much better performance and flexibility. Hadoop has …
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