An important part of making sure Apache Hadoop works well for all users is developing and maintaining strong relationships with the folks who run Hadoop day in and day out. Edward Capriolo keeps About.com’s Hadoop cluster happy, and we frequently chew the fat with Ed on issues ranging from administrative best practices to monitoring. Ed’s been an invaluable resource as we beta test our distribution and chase down bugs before our official releases. Today’s article looks at some of Ed’s tricks for monitoring Hadoop with Cacti through JMX.
For the last few months, we’ve been working with the TVA to help them manage hundreds of TB of data from America’s power grids. As the Obama administration investigates ways to improve our energy infrastructure, the TVA is doing everything they can to keep up with the volumes of data generated by the “smart grid.” But as you know, storing that data is only half the battle. In this guest blog post, the TVA’s Josh Patterson goes into detail about how Hadoop enables them to conduct deeper analysis over larger data sets at considerably lower costs than existing solutions. Read More
In addition to providing you with a dependable release of Hadoop that is easy to configure, at Cloudera we also focus on developing tools to extend Hadoop’s usability, and make Hadoop a more central component of your data infrastructure. In this vein, we’re proud to announce the availability of Sqoop, a tool designed to easily import information from SQL databases into your Hadoop cluster.
Sqoop (“SQL-to-Hadoop”) is a straightforward command-line tool with the following capabilities:
- Imports individual tables or entire databases to files in HDFS
- Generates Java classes to allow you to interact with your imported data
- Provides the ability to import from SQL databases straight into your Hive data warehouse
After setting up an import job in Sqoop,