In this thesis we proposed and implemented the MMR, a new and open-source MapRe- duce model with MPI for parallel and distributed programing. MMR combines Pthreads, MPI and the Google's MapReduce processing model to support multi-threaded as well as dis- tributed parallelism. Experiments show that our model signi cantly outperforms the leading open-source solution, Hadoop. It demonstrates linear scaling for CPU-intensive processing and even super-linear scaling for indexing-related workloads. In addition, we designed a MMR live DVD which facilitates the automatic installation and con guration of a Linux cluster with integrated MMR library which enables the development and execution of MMR applications.
| Identifer | oai:union.ndltd.org:uno.edu/oai:scholarworks.uno.edu:td-1944 |
| Date | 15 May 2009 |
| Creators | Wang, Liqiang |
| Publisher | ScholarWorks@UNO |
| Source Sets | University of New Orleans |
| Detected Language | English |
| Type | text |
| Format | application/pdf |
| Source | University of New Orleans Theses and Dissertations |
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