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 ...

Unlock the full InfoQ experience by logging in! Stay updated with your favorite authors and topics, engage with content, and download exclusive resources. This article dives into the happens-before ...

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 ...

Unlock the full InfoQ experience by logging in! Stay updated with your favorite authors and topics, engage with content, and download exclusive resources. Senyo Simpson discusses how Rust's core ...

Reporting and analysis drives businesses in making the best possible decisions. The source of all these decisions is the data. There are two types of data: structured and unstructured. Most recently, ...

The next generation of Apache Hadoop, the software implementation that allows batch processing of petabytes of data, is expected out this year, says a Yahoo executive. Todd Papaioannou, vice president ...

Hadoop training courses and certification programs are available from companies including Cloudera, Hortonworks, IBM and MapR. But if you’re not ready to commit to formal training courses, there are ...

Hadoop is hard. There’s just no way around that. Setting up and running a cluster is hard, and so is developing applications that make sense of, and create value from, big data. What Hadoop really ...

MapR's latest Hadoop distribution includes support for Hadoop 2.2 with YARN, but is also backward compatible with the MapReduce 1.x scheduler, promising organizations a risk-free upgrade path to the ...

Over at The Data Stack, Intel’s Tim Allen writes that the key to optimizing Hadoop on x86 is to tune the underlying Java so that it takes advantage of capabilities in Intel hardware. When you do that, ...