Thanks to Jonathan Natkins, a field engineer from StreamSets, for the guest post below about using StreamSets Data Collector—open source, GUI-driven ingest technology for developing and operating data pipelines with a minimum of code—and Cloudera Search and HUE to build a real-time search environment.
As pressure mounts on data engineers to deliver more data from more sources in less time, StreamSets Data Collector can serve as a linchpin in the data management process,
Cloudera Enterprise 5.5 improves the life of the admin through a deeper integration between HUE and Cloudera Manager, as well as a rebase on HUE 3.9.
Cloudera Enterprise 5.5 contains a number of improvements related to HUE (the open source GUI that makes Apache Hadoop easier to use), including easier setup for HUE HA, built-in activity monitoring for improved stability, and better security and reporting via Cloudera Navigator and Apache Sentry (incubating).
Cloudera Enterprise 5.5 (comprising CDH 5.5, Cloudera Manager 5.5, and Cloudera Navigator 2.4) has been released.
Cloudera is excited to bring you news of Cloudera Enterprise 5.5. Our persistent emphasis on quality is especially pronounced in this release, with more than 500 issues identified and triaged during its development.
A highlight of this release is the inclusion of Cloudera Navigator Optimizer (available in limited beta for select Cloudera Enterprise customers;
Big Industries, Cloudera systems integration and reseller partner for Belgium and Luxembourg, has developed an integration of Apache Mesos and CDH that can be deployed and managed through Cloudera Manager. In this post, Big Industries’ Rob Gibbon explains the benefits of deploying Mesos on your cluster and walks you through the process of setting it up.
[Editor’s Note: Mesos integration is not currently supported by Cloudera, thus the setup described below is not recommended for production use.]
Apache Mesos is a distributed,
The best data protection strategy is to remove sensitive information from everyplace it’s not needed.
Have you ever wondered what sort of “sensitive” information might wind up in Apache Hadoop log files? For example, if you’re storing credit card numbers inside HDFS, might they ever “leak” into a log file outside of HDFS? What about SQL queries? If you have a query like select * from table where creditcard = ‘1234-5678-9012-3456’,