Parallel Tree Reduction on MapReduce
| Autor: | Kento Emoto, Hiroto Imachi |
|---|---|
| Jazyk: | angličtina |
| Předmět: |
Speedup
Theoretical computer science computer.internet_protocol Computer science business.industry Tree Homomorphism Cloud computing Parallel computing Reduction (complexity) Tree (data structure) Hadoop Parallel programming model General Earth and Planetary Sciences MapReduce business computer General Environmental Science XPath |
| Zdroj: | ICCS |
| ISSN: | 1877-0509 |
| DOI: | 10.1016/j.procs.2012.04.201 |
| Popis: | MapReduce, the de facto standard for large scale data-intensive applications, is a remarkable parallel programming model, allowing for easy parallelization of data intensive computations over many machines in a cloud. As huge tree data such as XML has achieved the status of the de facto standard for representing structured information, the situation calls for effcient MapReduce programs treating such a tree data structure in parallel. However, development of such MapReduce programs has remained a challenge. In this paper, restructuring our previous BSP algorithm for tree reduction computations, we propose a new MapReduce algorithm that can be used to implement various tree computations such as XPath queries. Our algorithm is designed to achieve linear speedup even for extreme inputs, and our experimental result shows that our prototype implementation actually achieves linear speedup even for monadic trees. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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