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 ...

What are some of the cool things in the 2.0 release of Hadoop? To start, how about a revamped MapReduce? And what would you think of a high availability (HA) implementation of the Hadoop Distributed ...

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 ...

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 ...

Once, Hadoop and MapReduce were nearly synonymous, but today, Spark is the framework of choice for a new wave of big data practitioners Hadoop has never been in more desperate need of a lift than now.

Hadoop and MapReduce have long been mainstays of the big data movement, but some companies now need new and faster ways to extract business value from massive — and constantly growing — datasets.

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.

‘Big data’ is a term that is appearing with increasing frequency. It is often used to mean large volumes of structured data (such as your customer list) but also to describe semi-structured data ...

One question I get asked a lot by my clients is: Should we go for Hadoop or Spark as our big data framework? Spark has overtaken Hadoop as the most active open source Big Data project. While they are ...

The year 2015 started out with people recognizing that the Hadoop ecosystem is here to stay. As was stated by Gartner, Hadoop was in the “trough of disillusionment,” meaning that the hype was at an ...