MapReduce was invented by Google in 2004, made into the Hadoop open source project by Yahoo! in 2007, and now is being used increasingly as a massively parallel data processing engine for Big Data.

The USPTO awarded search giant Google a software method patent that covers the principle of distributed MapReduce, a strategy for parallel processing that is used by the search giant. If Google ...

Google introduced the MapReduce algorithm to perform massively parallel processing of very large data sets using clusters of commodity hardware. MapReduce is a core Google technology and key to ...

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Novel architectures are born out of necessity and for some applications, including molecular dynamics, there have been endless attempts to push parallel performance. According to the leads behind a ...

Unlock the full InfoQ experience by logging in! Stay updated with your favorite authors and topics, engage with content, and download exclusive resources. Vivek Yadav, an engineering manager from ...

The MapReduce paradigm has emerged as a transformative framework for processing vast datasets by decomposing complex tasks into simpler map and reduce functions. This approach has been instrumental in ...

In the vast universe of IT, data is categorized as being either structured or unstructured, from a macro perspective. Generation of unstructured data is orders of magnitude higher than that generated ...

Hadoop has been known as MapReduce running on HDFS, but with YARN, Hadoop 2.0 broadens pool of potential applications Hadoop has always been a catch-all for disparate open source initiatives that ...

Google on Wednesday launched Cloud Dataflow, a big data analytics service to crunch information in either streaming or batch mode. The announcement, made at Google's I/O keynote in San Francisco, ...