Apache Hive: From MapReduce to Enterprise-grade Big Data Warehousing
Databases
2019-03-27 v1
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.
Keywords
Cite
@article{arxiv.1903.10970,
title = {Apache Hive: From MapReduce to Enterprise-grade Big Data Warehousing},
author = {Jesús Camacho-Rodríguez and Ashutosh Chauhan and Alan Gates and Eugene Koifman and Owen O'Malley and Vineet Garg and Zoltan Haindrich and Sergey Shelukhin and Prasanth Jayachandran and Siddharth Seth and Deepak Jaiswal and Slim Bouguerra and Nishant Bangarwa and Sankar Hariappan and Anishek Agarwal and Jason Dere and Daniel Dai and Thejas Nair and Nita Dembla and Gopal Vijayaraghavan and Günther Hagleitner},
journal= {arXiv preprint arXiv:1903.10970},
year = {2019}
}
Comments
SIGMOD'19, 14 pages