Category: Amazon EMR

My colleague Jon Fritz wrote the blog post below to introduce you to some new features of Amazon EMR. — Jeff; Today we are announcing Amazon EMR release 4.3.0, which adds support for Apache Hadoop 2.7.1, Apache Spark 1.6.0, Ganglia 3.7.2, and a new sandbox release for Presto (0.130). We have also enhanced our maximizeResourceAllocation […]

My colleague Jon Fritz wrote the guest post below to introduce you to an important new feature for Amazon EMR. — Jeff; Today we are announcing that Amazon EMR now supports launching clusters in Amazon Virtual Private Cloud (VPC) private subnets, allowing you to quickly, cost-effectively, and securely create fully configured clusters with Hadoop ecosystem […]

My colleagues Jon Fritz and Abhishek Sinha are both Senior Product Managers on the EMR team. They wrote the guest post below to introduce you to the newest release of EMR and to tell you about new EMR cluster resizing functionality. — Jeff; Amazon EMR is a managed service that simplifies running and managing distributed […]

My colleague Jon Fritz wrote the guest post below to introduce a powerful new feature for Amazon EMR. We updated it on May 16, 2017 in order to describe some new console features and to account for the availability of Spark 2.0. — Jeff; I’m happy to announce that Amazon EMR now supports Apache Spark. […]

Amazon Elastic MapReduce (EMR) accelerates big data analytics. It provides instant scalability and elasticity, letting you focus on analytics instead of infrastructure for your data-intensive projects. Whether you are indexing large data sets or analyzing massive amounts of scientific data or processing clickstream logs, EMR simplifies running Hadoop and related big data applications on AWS. When […]