Demo: Managing Spark

By Lionel Gibbons | December 21, 2016

There's more to big data than Hadoop. If your plans call for high performance data crunching, you may be thinking of deploying Apache Spark, but setting up and running a Spark cluster can be challenging. Bright Cluster Manager makes it easy by giving you a comprehensive solution for deploying, monitoring, and managing Spark. 

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Bright Cluster on Demand – Spin Up a Cluster for Testing, Training and More

By Teun Docter | September 27, 2016

Version 7.3 of Bright OpenStack has a lot of great features. One I am most excited about is Cluster on Demand (COD), which lets end users provision entire cluster environments in a Bright OpenStack cloud. Any kind of cluster can be implemented, including HPC, Hadoop, Spark, or even a Bright OpenStack cloud.

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Spark Enhancements in Bright Cluster Manager Version 7.2

By Michele Lamarca | April 13, 2016

As you’ve probably heard by now, Apache Spark™ is a fast general processing engine which can be used for large-scale data processing. Bright Cluster Manager has supported Spark since version 7.1, but a number of recent enhancements were made to the Bright support for Spark in Version 7.2 which improve functionality and ease of use for our users.

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Want to spark your interest in Spark? Check out our 3-part vodcast series

By Lionel Gibbons | October 28, 2015

If you are curious to know more about Apache Spark™ and how it can be used for large-scale data processing, check out our latest vodcast series. As a fast and general processing engine compatible with Hadoop data, Spark can run in Hadoop clusters through YARN or in a standalone mode. For both batch processing and new workloads like streaming, interactive queries, and machine learning, Spark has a lot going for it.

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The Rise in Popularity of Apache Spark - Vodcast

By Ian Lumb | May 06, 2015

Apache Spark™ lives up to its tagline of ‘Lightning Fast Cluster Computing,’ according to Bright Computing’s Ian Lumb, who discussed this ‘hot’ cluster computing framework in our newly released vodcast. The vodcast, titled ‘The Rise in Popularity of Apache Spark,’ includes Ian’s take on the meteoric rise in popularity of Spark, comparisons between Spark and Hadoop, the importance of Spark’s excellent handling of converged analytics, and the exciting potential intersection of Spark and HPC. Take a listen to learn more about the unique solution that has ignited so much interest in the world of Big Data and beyond.

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My 2-Minute Drill at the Rice Oil and Gas HPC Workshop: Spark’ing Possibilities for Energy Exploration and Other Industries

By Ian Lumb | April 01, 2015

Spark'ing Scope Creep

I had the fortunate opportunity to present in the disruptive-technology track at the 2015 Rice Oil and Gas HPC Workshop during the first week of March. What I presented during my two-minute drill in this session ended up being much more disruptive than I anticipated.

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4 Bright Topics for the Euro Hadoop Summit: Only 3 Days Left to Cast Your Vote!

By Ian Lumb | January 13, 2015

Shape the program of the Hadoop Summit Europe 2015 with your votes. Is there a better way to demonstrate community? We think not!

The Summit features 6 tracks. By tapping the expertise of our Hadoop braintrust, we’ve submitted 4 ideas to 3 different tracks. Because we’d like to earn your votes, please allow us elaborate.

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How to Upgrade Your Hadoop Stack in 1 Step—With Zero Downtime

By Ian Lumb | October 30, 2014

Pop quiz: How many steps does it take to upgrade your Hadoop distribution?

Choose one answer:

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Bright Cluster Manager for Apache Hadoop: The First 6 Months of a Radiant Relationship

By Ian Lumb | September 26, 2014

Last week we released support for Apache Hadoop 2.5.0. I thought it would be a good time to revisit all the updates we’ve made over the last 6 months - in case you missed them.

Latest Updates

Our latest updates include:

  • Apache Hadoop 2.5.1  Typo? Not exactly. We introduced support for Apache Hadoop 2.5.0 last week. Since Version 2.5.1 (released on September 13, 2014) is a minor release that builds upon the stable 2.4.1 release, you can now expect support via YUM updates to Bright. Note that vanilla Apache Hadoop includes HDFS (the Hadoop Distributed File System), ZooKeeper (the coordination service) as well as YARN (the workload manager).
  • Cloudera CDH 5.1.0  We introduced support for CDH 5.1.0 in mid-July.
  • Hortonworks HDP 2.1  We introduced support for Hortonworks Data Platform (HDP) 2.1 in mid-May.

Bottom line: Bright Cluster Manager maintains support for all major distributions of Apache Hadoop. Because we’re obsessed with keeping you current, you don’t have to be. We free you up to focus on the analysis of Big Data - and wasn’t that why you got interested in Hadoop in the first place?

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