We’re pleased to announce the release of Cloudera Enterprise 5.4 (comprising CDH 5.4, Cloudera Manager 5.4, and Cloudera Navigator 2.3).
Cloudera Enterprise 5.4 (Release Notes) reflects critical investments in a production-ready customer experience through governance, security, performance and deployment flexibility in cloud environments. It also includes support for a significant number of updated open standard components–including Apache Spark 1.3, Impala 2.2, and Apache HBase 1.0 (as well as unsupported beta releases of Hive-on-Spark data processing and OpenStack deployments).
Apache Hadoop ecosystem, time to celebrate! The much-anticipated, significantly updated 4th edition of Tom White’s classic O’Reilly Media book, Hadoop: The Definitive Guide, is now available.
The Hadoop ecosystem has changed a lot since the 3rd edition. How are those changes reflected in the new edition?
The core of the book is about the core Apache Hadoop project, and since the 3rd edition,
Thanks to Sam Shuster, Software Engineer at Edmunds.com, for the guest post below about his company’s use case for Spark Streaming, SparkOnHBase, and Morphlines.
Every year, the Super Bowl brings parties, food and hopefully a great game to appease everyone’s football appetites until the fall. With any event that brings in around 114 million viewers with larger numbers each year, Americans have also grown accustomed to commercials with production budgets on par with television shows and with entertainment value that tries to rival even the game itself.
Having a good grasp of HDFS recovery processes is important when running or moving toward production-ready Apache Hadoop. In the conclusion to this two-part post, pipeline recovery is explained.
An important design requirement of HDFS is to ensure continuous and correct operations that support production deployments. For that reason, it’s important for operators to understand how HDFS recovery processes work. In Part 1 of this post, we looked at lease recovery and block recovery.
Cloudera recently announced formal support for Apache Kafka. This simple use case illustrates how to make web log analysis, powered in part by Kafka, one of your first steps in a pervasive analytics journey.
If you are not looking at your company’s operational logs, then you are at a competitive disadvantage in your industry. Web server logs, application logs, and system logs are all valuable sources of operational intelligence,