A study of object declustering strategies in parallel temporal object database systems

13 years 4 months ago

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In a transaction-time temporal object database management system (TODBMS), updating an object creates a new version of the object, but the old version is still accessible. A TODBMS will store large amounts of data, and in order to provide the necessary computing power and data bandwidth, a parallel system based on a shared-nothing architecture is necessary. In order to benefit from a parallel architecture, a suitable declustering of the objects over the nodes in the system is important. In this paper, we study three low-cost declustering algorithms: 1) declustering based on the hash value of the OID of the objects, 2) range partitioning, based on the timestamp of the objects, and 3) a new hybrid algorithm, where current object versions are declustered according to the hash value of the OID, and the historical versions are range partitioned based on timestamp. In contrast to many similar studies, we study the performance with a workload including both read and update operations. We sho...

Kjetil Nørvåg

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