A comparison of approaches to large-scale data analysis
Brown University · University of Wisconsin–Madison · +3 more institutions
Abstract
There is currently considerable enthusiasm around the MapReduce (MR) paradigm for large-scale data analysis [17]. Although the basic control flow of this framework has existed in parallel SQL database management systems (DBMS) for over 20 years, some have called MR a dramatically new computing model [8, 17]. In this paper, we describe and compare both paradigms. Furthermore, we evaluate both kinds of systems in terms of performance and development complexity. To this end, we define a benchmark consisting of a collection of tasks that we have run on an open source version of MR as well as on two parallel DBMSs. For each task, we measure each system's performance for various degrees of parallelism on a cluster…
Citation impact
- FWCI
- 239.88
- Percentile
- 100%
- References
- 19
Authors
7Topics & keywords
- Computer science
- Benchmark (surveying)
- Task (project management)
- Parallelism (grammar)
- Process (computing)
- Xeon Phi
- Control flow
- Scale (ratio)