QPPT: Query Processing on Prefix Trees

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Provided by: Creative Commons
Topic: Big Data
Format: PDF
Modern database systems have to process huge amounts of data and should provide results with low latency at the same time. To achieve this, data is nowadays typically hold completely in main memory, to benefit of its high bandwidth and low access latency that could never be reached with disks. Current in-memory databases are usually column stores that exchange columns or vectors between operators and suffer from a high tuple reconstruction overhead. In this paper, the authors present the indexed table-at-a-time processing model that makes indexes the first-class citizen of the database system.
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