Apache Spark has become the de facto standard for processing data at scale, whether for querying large datasets, training machine learning models to predict future trends, or processing streaming data ...

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 ...

After an absence of about a year, and a stint as Research Director at the now defunct Gigaom Research, I've returned to ZDNet to cover Big Data. The year went by pretty quickly, but a number of things ...

Editor’s Note: Vaibhav Nivargi is the founder and chief architect of ClearStory Data, a data analytics service provider. This week the fast-growing Apache Spark community is gathering in New York City ...

Yahoo, model Apache Spark citizen and developer of CaffeOnSpark, which made it easier for developers building deep learning models in Caffe to scale with parallel processing, is open sourcing a new ...

Enterprise software development and open source big data analytics technologies have largely existed in separate worlds. This is especially true for developers in the Microsoft .NET ecosystem. The ...

Traditional relational databases have been highly effective at handling large sets of structured data. That’s because structured data conforms nicely to a fixed schema model of neat columns and rows ...

The days of monolithic Apache Spark applications that are difficult to upgrade are numbered, as the popular data processing framework is undergoing an important architectural shift that will utilize ...

It’s been about three years since Apache Spark burst onto the big data scene and became one of the hottest technologies on the planet. Judging by the numbers surrounding Spark’s adoption—including ...