Multi-Dimensional Index on Hadoop Distributed File System
In this paper, the authors present an approach to construct a built-in block-based hierarchical index structures, like Rtree, to organize data sets in one, two, or higher dimensional space and improve the query performance towards the common query types (e.g., point query, range query) on Hadoop Distributed File System (HDFS). The query response time for data sets that are stored in HDFS can be significantly reduced by avoiding exhaustive search on the corresponding data sets in the presence of index structures. The basic idea is to adopt the conventional hierarchical structure to HDFS, and several issues, including index organization, index node size, buffer management, and data transfer protocol, are considered to reduce the query response time and data transfer overhead through network.
Provided by: Institute of Electrical & Electronic Engineers Topic: Big Data Date Added: Sep 2010 Format: PDF