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NoDB in action: adaptive query processing on raw data by Ioannis Alagiannis; Renata Borovica; Miguel Branco; Stratos Idreos; Anastasia Ailamaki is a scholarly article available to read on EtoBox.

What is NoDB in action: adaptive query processing on raw data about?

As data collections become larger and larger, users are faced with increasing bottlenecks in their data analysis. More data means more time to prepare the data, to load the data into the database and to execute the desired queries. Many applications already avoid using traditional database systems, e.g., scientific data analysis and social networks, due to their complexity and the increased__data-to-query__time, i.e. the time between getting the data and retrieving its first useful results. For many applications data collections keep growing fast, even on a daily basis, and this__data deluge__will only increase in the future, where it is expected to have much more data than what we can move or store, let alone analyze. In this demonstration, we will showcase a new philosophy for designing database systems called NoDB. NoDB aims at minimizing the data-to-query time, most prominently by removing the need to load data before launching queries. We will present our prototype implementation, PostgresRaw, built on top of PostgreSQL, which allows for efficient query execution over raw data files with zero initialization overhead. We will visually demonstrate how PostgresRaw incrementally a

Author

Ioannis Alagiannis; Renata Borovica; Miguel Branco; Stratos Idreos; Anastasia Ailamaki

Publisher

ACM

Published

2012

Language

EN