Scientists and mathematicians have long loved Python as a vehicle for working with data and automation. Python has not lacked for libraries such as Hadoopy or Pydoop to work with Hadoop, but those ...

The demand for job skills related to data processing — NoSQL, Apache Hadoop, Python, and a smattering of other such skills — has hit all-time highs, according to statistics collected by tech job site ...

When the Big Data moniker is applied to a discussion, it’s often assumed that Hadoop is, or should be, involved. But perhaps that’s just doctrinaire. Hadoop, at its core, consists of HDFS (the Hadoop ...

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 ...

Although not immediately obvious, C++ is used in Big Data along with Java, MapReduce, Python, and Scala. For example, if you’re using a Hadoop framework, it will be implemented in Java, but MapReduce ...

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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.

With the latest update to its Apache Hadoop distribution, Cloudera has provided the possibility of using data processing algorithms beyond the customary MapReduce, the company announced Tuesday.

The market for software related to the Hadoop and MapReduce programming frameworks for large-scale data analysis will jump from $77 million in 2011 to $812.8 million in 2016, a compound annual growth ...