Cluster based parallel database management system for data intensive computing

This paper describes a computer-cluster based parallel database management system (DBMS), InfiniteDB, developed by the authors. InfiniteDB aims at efficiently support data intensive computing in response to the rapid growing in database size and the need of high performance analyzing of massive databases. It can be efficiently executed in the computing system composed by thousands of computers such as cloud computing system. It supports the parallelisms of intra-query, inter-query, intra-operation, inter-operation and pipelining. It provides effective strategies for managing massive databases including the multiple data declustering methods, the declustering-aware algorithms for relational operations and other database operations, and the adaptive query optimization method. It also provides the functions of parallel data warehousing and data mining, the coordinator-wrapper mechanism to support the integration of heterogeneous information resources on the Internet, and the fault tolerant and resilient infrastructures. It has been used in many applications and has proved quite effective for data intensive computing.