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Just-In-Time Data Distribution for Analytical Query Processing
[chapter]
<span title="">2012</span>
<i title="Springer Berlin Heidelberg">
<a target="_blank" rel="noopener" href="https://fatcat.wiki/container/2w3awgokqne6te4nvlofavy5a4" style="color: black;">Lecture Notes in Computer Science</a>
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Distributed processing commonly requires data spread across machines using a priori static or hash-based data allocation. In this paper, we explore an alternative approach that starts from a master node in control of the complete database, and a variable number of worker nodes for delegated query processing. Data is shipped just-in-time to the worker nodes using a need to know policy, and is being reused, if possible, in subsequent queries. A bidding mechanism among the workers yields a
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... ng with the most efficient reuse of previously shipped data, minimizing the data transfer costs. Just-in-time data shipment allows our system to benefit from locally available idle resources to boost overall performance. The system is maintenance-free and allocation is fully transparent to users. Our experiments show that the proposed adaptive distributed architecture is a viable and flexible alternative for small scale MapReduce-type of settings.
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