Tag Archives: aws

Cloudera Enterprise 5.12 is Now Available

Categories: Altus CDH Cloud Cloudera Manager Cloudera Navigator Data Science Hue Impala Kafka Kudu

Cloudera is pleased to announce that Cloudera Enterprise 5.12 is now generally available (GA). The release includes enhancements for running in cloud environments (with broader ADLS support and improved AWS Spot Instance support), usability and productivity improvements for both data science and analytic workloads, as well as performance gains and self-service performance management across a range of workloads.

As usual, there are also a number of quality enhancements, bug fixes, and other improvements across the stack.

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Announcing Support for Spot Instances in Cloudera Altus

Categories: Cloud

A month ago, we publicly announced Cloudera Altus, our new platform–as–a–service offering, and today, we are expanding the Altus data engineering service to support AWS EC2 Spot instances. Cloud infrastructure is the most costly component of running Altus data engineering workloads in the cloud.  Altus EC2 Spot instance support makes it easy to significantly reduce the cost of cloud infrastructure by allowing users to provision Altus data engineering clusters backed by excess EC2 compute capacity at reduced prices.

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Data Engineering with Cloudera Altus

Categories: Altus Cloud Hive Spark

With modern businesses dealing with an ever-increasing volume of data, and an expanding set of data sources, the data engineering process that enables analysis, visualization, and reporting only becomes more important.

When considering running data engineering workloads in the public cloud, there are capabilities which enable different operational models from on-premises deployments. The key factors here are the presence of a distinct storage layer within the cloud environment, and the ability to provision compute resources on-demand (e.g.: with Amazon’s S3 and EC2 respectively).

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What’s New in Cloudera Director 2.4?

Categories: CDH Cloud

Cloudera Director 2.4 improves support for long-running clusters by syncing with upgrades and topology changes via Cloudera Manager, and adds support for Spark 2 and Kudu. Cloudera Director along with CM and CDH5.11 adds support for Microsoft Azure Data Lake Store (ADLS), and pausing of clusters with Amazon EBS volumes.

Cloudera Director helps you deploy, scale, and manage Apache Hadoop clusters in the cloud of your choice.

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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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