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.

Hadoop has been widely embraced for its ability to economically store and analyze large data sets. Using parallel computing techniques like MapReduce, Hadoop can reduce long computation times to hours ...

A monthly overview of things you need to know as an architect or aspiring architect. Unlock the full InfoQ experience by logging in! Stay updated with your favorite authors and topics, engage with ...

A monthly overview of things you need to know as an architect or aspiring architect. Unlock the full InfoQ experience by logging in! Stay updated with your favorite authors and topics, engage with ...

Reporting and analysis tools help businesses make better quality decisions faster. The source of information that enables these decisions is data. There are broadly two types of data: structured and ...

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 is the most significant concrete technology behind the so called “Big Data” revolution. Hadoop combines an economical model for storing massive quantities of data – the Hadoop Distributed File ...

In the race between DNA sequencing throughput and computer speed, sequencing is winning by a mile. Sequencing throughput has recently been improving at a rate of about fivefold per year 1, whereas ...