Back to Search Start Over

JetScope

Authors :
Nan Zhang
Xiaoyu Chen
Paul Brett
Jingren Zhou
Jaliya Ekanayake
Zhicheng Yin
Tao Guan
Anna Korsun
Eric Boutin
Source :
Proceedings of the VLDB Endowment. 8:1680-1691
Publication Year :
2015
Publisher :
Association for Computing Machinery (ACM), 2015.

Abstract

Interactive, reliable, and rich data analytics at cloud scale is a key capability to support low latency data exploration and experimentation over terabytes of data for a wide range of business scenarios. Besides the challenges in massive scalability and low latency distributed query processing, it is imperative to achieve all these requirements with effective fault tolerance and efficient recovery, as failures and fluctuations are the norm in such a distributed environment. We present a cloud scale interactive query processing system, called JetScope, developed at Microsoft. The system has a SQL-like declarative scripting language and delivers massive scalability and high performance through advanced optimizations. In order to achieve low latency, the system leverages various access methods, optimizes delivering first rows, and maximizes network and scheduling efficiency. The system also provides a fine-grained fault tolerance mechanism which is able to efficiently detect and mitigate failures without significantly impacting the query latency and user experience. JetScope has been deployed to hundreds of servers in production at Microsoft, serving a few million queries every day.

Details

ISSN :
21508097
Volume :
8
Database :
OpenAIRE
Journal :
Proceedings of the VLDB Endowment
Accession number :
edsair.doi...........09586ac6f1131d133813eb727a675dff
Full Text :
https://doi.org/10.14778/2824032.2824066