Cloudera Engineering Blog · Cloud Posts

How-to: Get Started with CDH on OpenStack with Sahara

The recent OpenStack Kilo release adds many features to the Sahara project, which provides a simple means of provisioning an Apache Hadoop (or Spark) cluster on top of OpenStack. This how-to, from Intel Software Engineer Wei Ting Chen, explains how to use the Sahara CDH plugin with this new release.

Prerequisites

This how-to assumes that OpenStack is already installed. If not, we recommend using Devstack to build a test OpenStack environment in a short time. (Note: Devstack is not recommended for use in a production environment. For production deployments, refer to the OpenStack Installation Guide.)

Sahara UI

Cloudera Enterprise 5.4 is Released

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).

How-to: Let Users Provision Apache Hadoop Clusters On-Demand

Providing Hadoop-as-a-Service to your internal users can be a major operational advantage.

Cloudera Director (free to download and use) is designed for easy, on-demand provisioning of Apache Hadoop clusters in Amazon Web Services (AWS) environments, with support for other cloud environments in the works. It allows for provisioning clusters in accordance with the Cloudera AWS Reference Architecture.

What’s New in Cloudera Director 1.1?

Cloudera Director 1.1 introduces new features and improvements that provide more options for creating and managing cloud deployments of Apache Hadoop. Here are details about how they work.

Cloudera Director, which was released in October of 2014, delivers production-ready, self-service interaction with Apache Hadoop clusters in cloud environments. You can find background information about Cloudera Director’s purpose and fundamental features in our earlier introductory blog post and technical overview blog post.

New Advanced Analytics and Data Wrangling Tutorials on Cloudera Live

A new Spark tutorial and Trifacta deployment option make Cloudera Live even more useful for getting started with Apache Hadoop.

When it comes to learning Hadoop and CDH (Cloudera’s open source platform including Hadoop), there is no better place to start than Cloudera Live (cloudera.com/live).  With a quick, one-button deployment option, Cloudera Live launches a four-node Cloudera cluster that you can learn and experiment in free for two-weeks. To help plan and extend the capabilities of your cluster, we also offer various partner deployments. Building on the addition of interactive tutorials and Tableau and Zoomdata integration, we have added a new tutorial on Apache Spark and a new Trifacta partner deployment.

Hands-on Hive-on-Spark in the AWS Cloud

Interested in Hive-on-Spark progress? This new AMI gives you a hands-on experience.

Nearly one year ago, the Apache Hadoop community began to embrace Apache Spark as a powerful batch-processing engine. Today, many organizations and projects are augmenting their Hadoop capabilities with Spark. As part of this shift, the Apache Hive community is working to add Spark as an execution engine for Hive. The Hive-on-Spark work is being tracked by HIVE-7292 which is one of the most popular JIRAs in the Hadoop ecosystem. Furthermore, three weeks ago, the Hive-on-Spark team offered the first demo of Hive on Spark.

Inside Cloudera Director

With Cloudera Director, cloud deployments of Apache Hadoop are now as enterprise-ready as on-premise ones. Here’s the technology behind it.

As part of the recent Cloudera Enterprise 5.2 release, we unveiled Cloudera Director, a new product that delivers enterprise-class, self-service interaction with Hadoop clusters in cloud environments. (Cloudera Director is free to download and use, but commercial support requires a Cloudera Enterprise subscription.) It provides a centralized administrative view for cloud deployments and lets end users provision and scale clusters themselves using automated, repeatable, managed processes. To summarize, the same enterprise-grade capabilities that are available with on-premise deployments are now also available for cloud deployments. (For an overview of and motivation for Cloudera Director, please check out this blog post.)

How-to: Write Apache Hadoop Applications on OpenShift with Kite SDK

The combination of OpenShift and Kite SDK turns out to be an effective one for developing and testing Apache Hadoop applications.

At Cloudera, our engineers develop a variety of applications on top of Hadoop to solve our own data needs (here and here). More recently, we’ve started to look at streamlining our development process by using a PaaS (Platform-as-a-Service) for some of these applications. Having single-click deployment and updates to consistent development environments lets us onboard new developers more quickly, and helps ensure that code is written and tested along patterns that will ensure high quality.

Cloudera Enterprise 5.2 is Released

Cloudera Enterprise 5.2 contains new functionality for security, cloud deployments, and real-time architectures, and support for the latest open source component releases and partner technologies.

We’re pleased to announce the release of Cloudera Enterprise 5.2 (comprising CDH 5.2, Cloudera Manager 5.2, Cloudera Director 1.0, and Cloudera Navigator 2.1).

Using Impala, Amazon EMR, and Tableau to Analyze and Visualize Data

Our thanks to AWS Solutions Architect Rahul Bhartia for allowing us to republish his post below.

Apache Hadoop provides a great ecosystem of tools for extracting value from data in various formats and sizes. Originally focused on large-batch processing with tools like MapReduce, Apache Pig, and Apache Hive, Hadoop now provides many tools for running interactive queries on your data, such as Impala, Drill, and Presto. This post shows you how to use Amazon Elastic MapReduce (Amazon EMR) to analyze a data set available on Amazon Simple Storage Service (Amazon S3) and then use Tableau with Impala to visualize the data.

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