Hadoop and MapReduce, the parallel programming paradigm and API originally behind Hadoop, used to be synonymous. Nowadays when we talk about Hadoop, we mostly talk about an ecosystem of tools built ...

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 ...

Getting insights out of big data is typically neither quick nor easy, but Google is aiming to change all that with a new, managed service for Hadoop and Spark. Cloud Dataproc, which the search giant ...

Snowflake is launching a client connector to run Apache Spark code directly in its cloud warehouse - no cluster setup required.… This is designed to avoid provisioning and maintaining a cluster ...

Apache Spark is a hugely popular execution framework for running data engineering and machine learning workloads. It powers the Databricks platform and is available in both on-premises and cloud-based ...

When it comes to leveraging existing Hadoop infrastructure to extend what is possible with large volumes of data and various applications, Yahoo is in a unique position–it has the data and just as ...

Today Intel Corporation and BlueData announced a broad strategic technology and business collaboration, as well as an additional equity investment in BlueData from Intel Capital. BlueData is a Silicon ...

The need for CIOs to support fast-growing data volumes with budgets that aren’t growing nearly as fast has spurred a renewed focus on efficiency among analytics vendors, some of which are going as low ...

eWEEK content and product recommendations are editorially independent. We may make money when you click on links to our partners. Learn More. Big data analytics technologies such as Hadoop and Spark ...

Apache Spark brings high-speed, in-memory analytics to Hadoop clusters, crunching large-scale data sets in minutes instead of hours Apache Spark got its start in 2009 at UC Berkeley’s AMPLab as a way ...