Category: Amazon EMR

Our customers use Amazon EMR (including Apache Hadoop and the full range of tools that make up the Apache Spark ecosystem) to handle many types of mission-critical big data use cases. For example: Yelp processes over a terabyte of log files and photos every day. Expedia processes streams of clickstream, user interaction, and supply data. […]

The Amazon EMR team has been cranking out new releases at a fast and furious pace! Here’s a quick recap of this year’s launches: EMR 4.7.0 – Updates to Apache Tez, Apache Phoenix, Presto, HBase, and Mahout (June). EMR 4.6.0 – HBase for realtime access to massive datasets (April). EMR 4.5.0 – Updates to Hadoop, […]

Amazon EMR allows you to quickly and cost-effectively process vast amounts of data. Since the 2009 launch, we have added many new features and support for an ever-increasing roster of applications from the Hadoop ecosystem. Here are a few of the additions that we have made this year: April – Support for Apache HBase 1.2 […]

Apache HBase is a distributed, scalable big data store designed to support tables with billions of rows and millions of columns. HBase runs on top of Hadoop and HDFS and can also be queried using MapReduce, Hive, and Pig jobs. AWS customers use HBase for their ad tech, web analytics, and financial services workloads. They […]

Rob Leidle, Development Manager for Amazon EMR, wrote the guest post below to introduce you to the latest and greatest version! — Jeff; Today we are announcing Amazon EMR release 4.4.0, which adds support for Apache Sqoop (1.4.6) and Apache HCatalog 1.0.0, an upgraded release of Apache Mahout (0.11.1), and upgraded sandbox releases for Presto […]

My colleague Abhishek Sinha wrote the guest post below to tell you about the latest additions to Amazon EMR. — Jeff; Amazon EMR is a service that allows you to use distributed data processing frameworks such as Apache Hadoop, Apache Spark and Presto to process data on a managed cluster of EC2 instances. Newer versions […]

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 […]