Providing Hadoop-as-a-Service to your internal users can be a major operational advantage.
Cloudera Director (free to download and use) is designed for easy, on-demand provisioning of Apache Hadoop clusters in Amazon Web Services (AWS) environments, with support for other cloud environments in the works. It allows for provisioning clusters in accordance with the Cloudera AWS Reference Architecture.
At Cloudera, Cloudera Director is used internally to enable our technical field to provision clusters on-demand for demos,
Installing CDH on newer unsupported operating systems (such as Ubuntu 13.04 and later) can lead to conflicts. These guidelines will help you avoid them.
Some of the more recently released operating systems that bundle portions of the Apache Hadoop stack in their respective distro repositories can conflict with software from Cloudera repositories. Consequently, when you set up CDH for installation on such an OS, you may end up picking up packages with the same name from the OS’s distribution instead of Cloudera’s distribution.
Thanks to Guy Harrison of Dell Inc. for the guest post below about time-tested performance optimizations for connecting Oracle Database with Apache Hadoop that are now available in Apache Sqoop 1.4.5 and later.
Back in 2009, I attended a presentation by a Cloudera employee named Aaron Kimball at the MySQL User Conference in which he unveiled a new tool for moving data from relational databases into Hadoop. This tool was to become,
With Cloudera Director, cloud deployments of Apache Hadoop are now as enterprise-ready as on-premise ones. Here’s the technology behind it.
As part of the recent Cloudera Enterprise 5.2 release, we unveiled Cloudera Director, a new product that delivers enterprise-class, self-service interaction with Hadoop clusters in cloud environments. (Cloudera Director is free to download and use, but commercial support requires a Cloudera Enterprise subscription.) It provides a centralized administrative view for cloud deployments and lets end users provision and scale clusters themselves using automated,
Our thanks to AWS Solutions Architect Rahul Bhartia for allowing us to republish his post below.
Apache 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, Apache Pig, and Apache Hive, Hadoop now provides many tools for running interactive queries on your data, such as Impala, Drill, and Presto. This post shows you how to use Amazon Elastic MapReduce (Amazon EMR) to analyze a data set available on Amazon Simple Storage Service (Amazon S3) and then use Tableau with Impala to visualize the data.