One of the newest (and perhaps most talked about) entrants to the big data landscape is Apache Spark, a tool that many view as a more powerful and accessible alternative to Hadoop. Others recognise ...

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 ...

Cloudera on how the execution engine Apache Spark broadens what companies can do with the big data framework Hadoop.

Apache Spark is one of the most popular open source projects in the world, and has lowered the barrier of entry for processing and analyzing data at scale. We asked some of the leaders in the big data ...

Apache Spark is one of the most widely used tools in the big data space, and will continue to be a critical piece of the technology puzzle for data scientists and data engineers for the foreseeable ...

Apache Spark is hailed as being Hadoop's successor, claiming its throne as the hottest Big Data platform. What the founding fathers of Spark are saying and doing about its future and its ...

Databricks, the primary commercial steward behind the popular open source Apache Spark project, published a new report indicating the technology is still red-hot, driven by more use of SQL, streaming ...

Get the source code for the example applications demonstrated in this article: “Aggregating with Apache Spark.” Created by Ravishankar Nair for JavaWorld.

SPARK 2014 is a programming environment based on the Ada programming language. Apache’s open-source SPARK project is an advanced, Directed Acyclic Graph (DAG) execution engine.

Spark, the open-source cluster computing framework from the Apache Software Foundation, promises to complement Hadoop batch processing, enabling more in-memory for real-time applications.