AWS Big Data Blog

Tag: Amazon EMR

Getting HBase Running on Amazon EMR and Connecting it to Amazon Kinesis

Wangechi Doble is an AWS Solutions Architect Introduction Apache HBase is an open-source, column-oriented, distributed NoSQL database that runs on the Apache Hadoop framework. In the AWS Cloud, you can choose to deploy Apache HBase on Amazon Elastic Compute Cloud (Amazon EC2) and manage it yourself or leverage Apache HBase as a managed service on […]

Installing Apache Spark on an Amazon EMR Cluster

Jonathan Fritz is a Senior Product Manager for Amazon EMR ———————– Please note – Amazon EMR now officially supports Spark. For more information about Spark on EMR, visit the Spark on Amazon EMR page or read Intent Media’s guest post on the AWS Big Data Blog about Spark on EMR. ——–————— Over the last five […]

Deploying Cloudera’s Enterprise Data Hub on AWS

Karthik Krishnan is an AWS Solutions Architect UPDATE April 6, 2015: The newest quickstart reference guide supports Cloudera Director 1.1.0. To manage your cluster with Cloudera Director 1.1.0, refer to the updated reference guide.  Apache Hadoop is an open-source software framework to store and process large scale data-sets.  In this post, we discuss the deployment of […]

Statistical Analysis with Open-Source R and RStudio on Amazon EMR

Markus Schmidberger is a Senior Big Data Consultant for AWS Professional Services Big Data is on every CIO’s mind. It is synonymous with technologies like Hadoop and the ‘NoSQL’ class of databases. Another technology shaking things up in Big Data is R. This blog post describes how to set up R, RHadoop packages and RStudio […]

Using Amazon EMR and Tableau to Analyze and Visualize Data

Rahul Bhartia is an AWS Solutions Architect Introduction Hadoop provides a great ecosystem of tools for extracting value from data in various formats and sizes. Originally focused on large-batch processing with tools like MapReduce, Pig and Hive, Hadoop now provides many tools for running interactive queries on your data, such as Impala, Drill, and Presto. […]