Tag Archives: Testing

How-to: Write a Cloud Provider Plugin for Cloudera Director

Categories: Cloud How-to

Cloudera Director 1.5 introduces a new plugin architecture to enable support for additional cloud providers. If you want to implement a plugin to add integration with a cloud provider that is not supported out-of-the-box, or to extend one of the existing plugins, these details will get you started.

As discussed in our previous blog post, the Cloudera Director Service Provider Interface (Cloudera Director SPI) defines a Java interface and packaging standards for Cloudera Director plugins.

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How Apache Spark, Scala, and Functional Programming Made Hard Problems Easy at Barclays

Categories: Guest Spark Use Case

Thanks to Barclays employees Sam Savage, VP Data Science, and Harry Powell, Head of Advanced Analytics, for the guest post below about the Barclays use case for Apache Spark and its Scala API.

At Barclays, our team recently built an application called Insights Engine to execute an arbitrary number N of near-arbitrary SQL-like queries and execute them in a way that can scale with increasing N. The queries were non-trivial,

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How-to: Secure YARN Containers with Cloudera Navigator Encrypt

Categories: Cloudera Navigator Platform Security & Cybersecurity YARN

Learn how Cloudera Navigator Encrypt bring data security to YARN containers.

With the introduction of transparent data encryption in HDFS, we are now a big step closer toward a secure platform in the Apache Hadoop world. However, there are still gaps in the platform, including how YARN and its applications manage their cache. In this post, I’ll explain how Cloudera Navigator Encrypt fills that particular gap.

Use Case

When a YARN application runs in a cluster it can sometimes spill data to the hard disk,

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How-to: Install Apache Zeppelin on CDH

Categories: General Guest How-to Spark

Our thanks to Karthik Vadla and Abhi Basu, Big Data Solutions engineers at Intel, for permission to re-publish the following (which was originally available here).

Data science is not a new discipline. However, with the growth of big data and adoption of big data technologies, the request for better quality data has grown exponentially. Today data science is applied to every facet of life—product validation through fault prediction,

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Security, Hive-on-Spark, and Other Improvements in Apache Hive 1.2.0

Categories: Community Hive Spark

Apache Hive 1.2.0, although not a major release, contains significant improvements.

Recently, the Apache Hive community moved to a more frequent, incremental release schedule. So, a little while ago, we covered the Apache Hive 1.0.0 release and explained how it was renamed from 0.14.1 with only minor feature additions since 0.14.0.

Shortly thereafter, Apache Hive 1.1.0 was released (renamed from Apache Hive 0.15.0), which included more significant features—including Hive-on-Spark.

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