Bhaskar Himatsingka

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I/O subsystem is widely accepted as one of the principal bottlenecks for high performance parallel databases systems. The emergence of parallel I/O architectures has made the problem of data declustering, i.e. fragmenting a le of records and allocating the pieces to diierent disks, one of prime importance. This is evident from the growing activity in this(More)
In this paper we present an approach for transforming a relational join tree into a detailed execution plan with resource allocation information, for execution on a parallel machine. Our approach starts by transforming a query tree, such as might be generated by a sequential optimizer, into an operator tree which is then partitioned into a forest of linear(More)
The I/O subsystem is widely accepted as one of the principal bottlenecks for high performance parallel databases systems. The emergence of parallel I/O architectures has made the problem of data declustering, i.e. fragmenting a le of records and allocating the pieces to different disks, one of prime importance. This is evident from the growing activity in(More)
Selecting the best plan for executing a given query is the problem of query optimization. The focus of query optimization for sequential machines has been on nding query plans which involve the least amount of work, since response time is equivalent to work done in a uniprocessor environment. With the advent of parallel computers and their application to(More)
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