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 ...

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 ...

An organization’s Big Data is key to customer insight and product design superiority. The story about the growth of Big Data enabling the crunching of vast amounts of data has been well covered in the ...

After a brief review of how map-reduce works, we shall look at the trade-off that needs to be made when designing map-reduce algorithms for problems that are not embarrassingly parallel. In particular ...

When your data and work grow, and you still want to produce results in a timely manner, you start to think big. Your one beefy server reaches its limits. You need a way to spread your work across many ...

Unlock the full InfoQ experience by logging in! Stay updated with your favorite authors and topics, engage with content, and download exclusive resources. Leann Chen explains how knowledge graphs ...

Big data analytic software vendors who run on Hadoop are increasingly replacing their MapReduce engines with Apache Spark and other in-memory analytic engines as the runtime of choice. Many of these ...