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Apache Big Data Seville 2016 – Hive 2.0 SQL, Speed, Scale – Alan Gates

January 5, 2017

Hive 2.0 SQL, Speed, Scale – Alan Gates

Apache Hive is the most commonly used SQL interface for Hadoop. To meet users data warehousing needs it must scale to petabytes of data, provide the necessary SQL, and perform in interactive time. The Hive community ihas produced a 2.0 release of Hive that includes significant improvements. These include:

* LLAP, a daemon layer that enables sub-second response time.
* HBase to store Hiveäó»s metadata, resulting in significantly reduced planning time.
* Using Apache Calcite to build a cost based optimizer
* Adding procedural SQL
* Improvements in using Spark as an engine for Hive execution

This talk will cover the use cases these changes enable, the architectural changes being made in Hive as part of building these features, and share performance test results on how these improvements are speeding up Hive.

More information about this talk

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