Abstract
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.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.