Title
Bigop: Generating Comprehensive Big Data Workloads As A Benchmarking Framework
Abstract
Big Data is considered proprietary asset of companies, organizations, and even nations. Turning big data into real treasure requires the support of big data systems. A variety of commercial and open source products have been unleashed for big data storage and processing. While big data users are facing the choice of which system best suits their needs, big data system developers are facing the question of how to evaluate their systems with regard to general big data processing needs. System benchmarking is the classic way of meeting the above demands. However, existent big data benchmarks either fail to represent the variety of big data processing requirements, or target only one specific platform, e. g. Hadoop.In this paper, with our industrial partners, we present BigOP, an end-to-end system benchmarking framework, featuring the abstraction of representative Operation sets, workload Patterns, and prescribed tests. BigOP is part of an open-source big data benchmarking project, BigDataBench(1). BigOP's abstraction model not only guides the development of BigDataBench, but also enables automatic generation of tests with comprehensive workloads.We illustrate the feasibility of BigOP by implementing an automatic test generation tool and benchmarking against three widely used big data processing systems, i.e. Hadoop, Spark and MySQL Cluster. Three tests targeting three different application scenarios are prescribed. The tests involve relational data, text data and graph data, as well as all operations and workload patterns. We report results following test specifications.
Year
DOI
Venue
2014
10.1007/978-3-319-05813-9_32
DATABASE SYSTEMS FOR ADVANCED APPLICATIONS, DASFAA 2014, PT II
DocType
Volume
ISSN
Conference
8422
0302-9743
Citations 
PageRank 
References 
6
0.48
13
Authors
7
Name
Order
Citations
PageRank
Zhu Yuqing146737.26
Jianfeng Zhan276762.86
Chuliang Weng344135.39
Raghunath Nambiar411118.92
Jinchao Zhang561.83
Xingzhen Chen660.48
Lei Wang757746.85