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Whenever data is moved across nodes in the parallel database system, the indexes need to be modified too. Index modification overhead can be quite severe because there can be a large number of indexes on a relation. In this paper, we study two alternatives to index modification, namely OAT (One-At-a-Time page movement) and BULK (bulk page movement). OAT and BULK are two extremes on the spectrum of the granularity of data movement. OAT and BULK differ in two respects: first, OAT uses very little additional disk space (at most one extra page), whereas BULK uses a large amount of disk space. Second, BULK uses sequential prefetch I/O to optimize on the number of I/Os during index modification, while OAT does not. Using an experimental testbed, we show that BULK is an order of magnitude faster than OAT. In terms of the impact on transaction performance during reorganization, BULK and OAT perform differently: when the number of indexes to be modified is either one or two, OAT has a lesser impact on the transaction performance degradation. However, when the number of indexes is greater than two, both techniques have the same impact on transaction performance.

Two techniques for on-line index modification in shared nothing parallel databases