Apache Hive: From MapReduce to Enterprise-grade Big Data Warehousing

被引：30

作者：

Camacho-Rodriguez, Jesus ^{[1
]}

Chauhan, Ashutosh ^{[1
]}

Gates, Alan ^{[1
]}

Koifman, Eugene ^{[1
]}

O'Malley, Owen ^{[1
]}

Garg, Vineet ^{[1
]}

Haindrich, Zoltan ^{[1
]}

Shelukhin, Sergey ^{[1
]}

Jayachandran, Prasanth ^{[1
]}

Seth, Siddharth ^{[1
]}

Jaiswal, Deepak ^{[1
]}

Bouguerra, Slim ^{[1
]}

Bangarwa, Nishant ^{[1
]}

Hariappan, Sankar ^{[1
]}

Agarwal, Anishek ^{[1
]}

Dere, Jason ^{[1
]}

Dai, Daniel ^{[1
]}

Nair, Thejas ^{[1
]}

Dembla, Nita ^{[1
]}

Vijayaraghavan, Gopal ^{[1
]}

Hagleitner, Guenther ^{[1
]}

机构：

[1] Hortonworks Inc, Santa Clara, CA 95054 USA

来源：

SIGMOD '19: PROCEEDINGS OF THE 2019 INTERNATIONAL CONFERENCE ON MANAGEMENT OF DATA | 2019年

关键词：

Databases; Data Warehouses; Hadoop; Hive;

D O I：

10.1145/3299869.3314045

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

Apache Hive is an open-source relational database system for analytic big-data workloads. In this paperwe 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.

引用

页码：1773 / 1786

页数：14

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