New in Cloudera Enterprise 5.10: Hue SQL Editor and Security Improvements

Categories: Hadoop Hue Oozie

Cloudera Enterprise 5.10 includes the latest updates of Hue, the intelligent editor for SQL Developers and Analysts.

As part of Cloudera’s continuing investments in user experience and productivity, Cloudera Enterprise 5.10 includes an updated version of Hue. We provide a summary of the main enhancements in the following part of this blog post. (Hue from C5.10 is also available for a quick try in one click on demo.gethue.com.)

SQL Improvements

The Hue editor keeps getting better with these major improvements:

Row Count

The number of rows returned is displayed so you can quickly see the size of the dataset.

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Accelerating Apache Spark MLlib with Intel® Math Kernel Library (Intel® MKL)

Categories: Data Science Spark

There are two clear trends in the big-data ecosystem: the growth of machine learning use cases that leverage large distributed data sets, and the growth of Spark’s Machine Learning libraries (often referred to as MLlib) for these use cases. In fact, Spark’s MLlib library is arguably the leading solution for machine learning on large distributed data sets.

Intel and Cloudera have collaborated to speed up Spark’s ML algorithms, via integration with Intel’s Math Kernel Library (Intel® MKL).

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Analyzing US flight data on Amazon S3 with sparklyr and Apache Spark 2.0

Categories: CDH Data Science Hadoop Spark Use Case

We posted several blog posts about sparklyr (introduction, automation), which enables you to analyze big data leveraging Apache Spark seamlessly with R. sparklyr, developed by RStudio, is an R interface to Spark that allows users to use Spark as the backend for dplyr, which is the popular data manipulation package for R.

If you are interested in sparklyr, you can learn how to use it with the official document,

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Working with UDFs in Apache Spark

Categories: Hadoop Spark

User-defined functions (UDFs) are a key feature of most SQL environments to extend the system’s built-in functionality.  UDFs allow developers to enable new functions in higher level languages such as SQL by abstracting their lower level language implementations.  Apache Spark is no exception, and offers a wide range of options for integrating UDFs with Spark SQL workflows.

In this blog post, we’ll review simple examples of Apache Spark UDF and UDAF (user-defined aggregate function) implementations in Python,

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Up and running with Apache Spark on Apache Kudu

Categories: CDH Data Ingestion Data Science General Hadoop How-to Impala Kudu Spark Training Use Case

After the GA of Apache Kudu in Cloudera CDH 5.10, we take a look at the Apache Spark on Kudu integration, share code snippets, and explain how to get up and running quickly, as Kudu is already a first-class citizen in Spark’s ecosystem.

 

As the Apache Kudu development team celebrates the initial 1.0 release launched on September 19, and the most recent 1.2.0 version now GA as part of Cloudera’s CDH 5.10 release,

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