Apache Hive: From MapReduce to Enterprise-grade Big Data Warehousing
March 26, 2019 Β· Declared Dead Β· π SIGMOD Conference
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Authors
JesΓΊs Camacho-RodrΓguez, Ashutosh Chauhan, Alan Gates, Eugene Koifman, Owen O'Malley, Vineet Garg, Zoltan Haindrich, Sergey Shelukhin, Prasanth Jayachandran, Siddharth Seth, Deepak Jaiswal, Slim Bouguerra, Nishant Bangarwa, Sankar Hariappan, Anishek Agarwal, Jason Dere, Daniel Dai, Thejas Nair, Nita Dembla, Gopal Vijayaraghavan, GΓΌnther Hagleitner
arXiv ID
1903.10970
Category
cs.DB: Databases
Citations
71
Venue
SIGMOD Conference
Last Checked
3 months ago
Abstract
Apache Hive is an open-source relational database system for analytic big-data workloads. In this paper we describe the key innovations on the journey from batch tool to fully fledged enterprise data warehousing system. We present a hybrid architecture that combines traditional MPP techniques with more recent big data and cloud concepts to achieve the scale and performance required by today's analytic applications. We explore the system by detailing enhancements along four main axis: Transactions, optimizer, runtime, and federation. We then provide experimental results to demonstrate the performance of the system for typical workloads and conclude with a look at the community roadmap.
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