학술논문
Apache Hive: From MapReduce to Enterprise-grade Big Data Warehousing
Document Type
Working Paper
Author
Camacho-Rodríguez, Jesús; Chauhan, Ashutosh; Gates, Alan; Koifman, Eugene; O'Malley, Owen; Garg, Vineet; Haindrich, Zoltan; Shelukhin, Sergey; Jayachandran, Prasanth; Seth, Siddharth; Jaiswal, Deepak; Bouguerra, Slim; Bangarwa, Nishant; Hariappan, Sankar; Agarwal, Anishek; Dere, Jason; Dai, Daniel; Nair, Thejas; Dembla, Nita; Vijayaraghavan, Gopal; Hagleitner, Günther
Source
Subject
Language
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.
Comment: SIGMOD'19, 14 pages
Comment: SIGMOD'19, 14 pages