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. Jinsong Yu shares deep architectural insights ...

Apache Spark™’s ability to speed analytic applications by orders of magnitude, its versatility, and ease of use are quickly winning the market. With Spark’s appeal to developers, end users, and ...

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 ...

Apache Spark has become the defacto standard computational engine in the big data world. But as an in-memory technology, Spark has limitations. One of the ways people are getting around those ...

A Spark application contains several components, all of which exist whether you’re running Spark on a single machine or across a cluster of hundreds or thousands of nodes. Each component has a ...

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 ...

Apache Ignite is an open source in-memory data fabric which provides a wide variety of computing solutions including an in-memory data grid, compute grid, streaming, as well as acceleration solutions ...

Apache Spark is an execution engine that broadens the type of computing workloads Hadoop can handle, while also tuning the performance of the big data framework. Hadoop specialist Cloudera recently ...

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 ...