Oracle in-database hadoop: when mapreduce meets RDBMS

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Oracle in-database hadoop: when mapreduce meets RDBMS
Big data is the tar sands of the data world: vast reserves of raw gritty data whose valuable information content can only be extracted at great cost. MapReduce is a popular parallel programming paradigm well suited to the programmatic extraction and analysis of information from these unstructured Big Data reserves. The Apache Hadoop implementation of MapReduce has become an important player in this market due to its ability to exploit large networks of inexpensive servers. The increasing importance of unstructured data has led to the interest in MapReduce and its Apache Hadoop implementation, which has led to the interest of data processing vendors in supporting this programming style. Oracle RDBMS has had support for the MapReduce paradigm for many years through the mechanism of user defined pipelined table functions and aggregation objects. However, such support has not been Hadoop source compatible. Native Hadoop programs needed to be rewritten before becoming usable in this frame...
Xueyuan Su, Garret Swart
Added 27 Sep 2012
Updated 27 Sep 2012
Type Journal
Year 2012
Authors Xueyuan Su, Garret Swart
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