Our Newest Vodcast Reviews the Latest Enhancements to Bright Cluster Manager for Big Data in Version 7.2

page_header_divider_line

By Lionel Gibbons | May 25, 2016 |

   

 

In our latest vodcast, we review the key improvements in Bright Cluster Manager for Big Data in Version 7.2 that will help end users monitor and manage their big data clusters even more easily. The top two changes highlighted are improved support for Apache Spark and tighter integration with Hadoop.

The 4-minute video takes viewers through the updated support for Apache Spark, which makes it easier for Big Data users to get the most from a Spark deployment. Highlights include a new configuration wizard and a Hadoop adapter for Lustre (HAL) that lets HPC users immediately apply the analytic power of Spark to their data.

We also review how tighter integration with Hadoop Version 7.2 gives users more control over their Hadoop stack. The video shows the many dedicated roles we’ve provided for popular Hadoop components, as well as dedicated scripts for managing Apache Tachyon and Ignite. 

Reviewing other important updates in Version 7.2, we touch upon the enhanced Slurm workload manager. Now those who use the Slurm workload manager can also use it to run Hadoop jobs, so they can fit Hadoop into a unified workflow.

Learn about the enhancements by watching the vodcast below or by sending an email to info@brightcomputing.com

resource_asset_divider_image

COMMENTS