Apache Drill: Interactive Ad-Hoc Analysis at Scale

Abstract

Apache Drill is a distributed system for interactive ad-hoc analysis of large-scale datasets. Designed to handle up to petabytes of data spread across thousands of servers, the goal of Drill is to respond to ad-hoc queries in a low-latency manner. In this article, we introduce Drill's architecture, discuss its extensibility points, and put it into the context of the emerging offerings in the interactive analytics realm.

Get full access to this article

View all access options for this article.

References

Sakr

, Liu

, Fayoumi

. The family of MapReduce and large scale data processing systems, arXiv:1302.2966. 2013.

Melnik

, Gubarev

, Long

et al. Dremel: interactive analysis of web-scale datasets. Proceedings of the 36th International Conference on Very Large Data Bases, 2010; 330–339.

Hausenblas

, Villazon-Terrazas

, Cyganiak

. Data shapes and data transformations, arXiv:1211.1565. 2012.

Dean

, Barroso

. The tail at scale. Communications of the ACM, 2013; 56:74–80.

Supplementary Material

Please find the following supplemental material available below.

For Open Access articles published under a Creative Commons License, all supplemental material carries the same license as the article it is associated with.

For non-Open Access articles published, all supplemental material carries a non-exclusive license, and permission requests for re-use of supplemental material or any part of supplemental material shall be sent directly to the copyright owner as specified in the copyright notice associated with the article.

0.00 MB