Apache Tez

A Framework for YARN-based, Data Processing Applications In Hadoop

Apache™ Tez is an extensible framework for building high performance batch and interactive data processing applications, coordinated by YARN in Apache Hadoop. Tez improves the MapReduce paradigm by dramatically improving its speed, while maintaining MapReduce’s ability to scale to petabytes of data. Important Hadoop ecosystem projects like Apache Hive and Apache Pig use Apache Tez, as do a growing number of third party data access applications developed for the broader Hadoop ecosystem.

Hive with Tez

As the de facto standard for SQL-In-Hadoop, Apache Hive is optimal for both batch and interactive queries at petabyte scale. Hive embeds Tez so that it can translate complex SQL statements into highly optimized, purpose-built data processing graphs that strike the right balance between performance, throughput, and scalability. Apache Tez innovations drove many of the Hive performance improvements delivered by the Stinger Initiative, a broad community effort that included contributions from 145 engineers across 44 different organizations. Tez helps make Hive interactive.