Cloudera Developer Blog · Guest Posts
The following guest post is re-published here courtesy of Gerd König, a System Engineer with YMC AG. Thanks, Gerd!
Cloudera Manager is a great tool to orchestrate your CDH-based Apache Hadoop cluster. You can use it from cluster installation, deploying configurations, restarting daemons to monitoring each cluster component. Starting with version 4.6, the manager supports the integration of Cloudera Search, which is currently in Beta state. In this post I’ll show you the required steps to set up a Hadoop cluster via Cloudera Manager and how to integrate Cloudera Search.
The following guest post, from Mike Pittaro of Dell’s Cloud Software Solutions team, describes his team’s use of the Dell Crowbar tool in conjunction with the Cloudera Manager API to automate cluster provisioning. Thanks, Mike!
Deploying, managing, and operating Apache Hadoop clusters can be complex at all levels of the stack, from the hardware on up. To hide this complexity and reduce deployment time, since 2011, Dell has been using Dell Crowbar in conjunction with Cloudera Manager to deploy the Dell | Cloudera Solution for Apache Hadoop for joint customers.
We’re very happy to re-publish the following post from Twitter analytics infrastructure engineering manager Dmitriy Ryaboy (@squarecog).
Our thanks to Etsy developer Brad Greenlee (@bgreenlee) for the post below. We think his Mac OS app for JobTracker is great!
JobTracker.app is a Mac menu bar app interface to the Hadoop JobTracker. It provides Growl/Notification Center notices of starting, completed, and failed jobs and gives easy access to the detail pages of those jobs.
Our thanks to Brian Dirking, Director of Product Marketing for Alteryx, for the guest post below:
At Alteryx we are excited about the release of Cloudera Impala. The impact on Big Data Analytics is that the ability to perform real-time queries on Apache Hadoop will provide faster access and results. This is applicable to our customers, the business users who are running analytics to get access to data, perform analytics, and then follow up with new questions. Insight doesn’t happen all at once. The ability to query and refine quickly is ultimately what will lead business users to insight.
Our thanks to Ted Wasserman, product manager for Tableau, for the guest post below:
Many of our customers are turning to Apache Hadoop as they grapple with their big data challenges. Hadoop offers many benefits such as its scalability, economics, and versatility. Even so, adoption-to-date has largely centered around applications with “batch”-oriented workloads because of the latency imposed by the MapReduce framework. To increase Hadoop’s usefulness and adoption in the business intelligence space where users need fast, interactive response times when they ask a question, a new approach was needed.
Our thanks to Yves de Montcheuil, Vice President of Marketing for Talend, for the guest post below:
According to Wikipedia, the impala is a medium-sized African antelope; its name comes from the Zulu language meaning “gazelle”. Like elephants, it is found in savannas, and this may be the link with Hadoop. Impala is also the name of Cloudera’s SQL-on-Apache Hadoop project, launched in beta at Strata last October and just released in version 1.0.
A World-Class EDW Requires a World-Class Hadoop Team
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This guest post comes to us from David Greco, CTO of Eligotech.
Vagrant is a very nice tool for programmatically managing many virtual machines (VMs) on a single physical machine. It natively supports VirtualBox and also provides plugins for VMware Fusion and Amazon EC2, supporting the management of VMs in those environments as well.
As a follow-up to a previous post about the Impala demo he built during Data Hacking Day, Alan Gardner from Pythian has deployed the app for a limited time on Amazon EC2. We republish his original post below.
A little while ago I blogged about (and open sourced) a Cloudera Impala-powered soccer visualization demo, designed to demonstrate just how responsive Impala queries can be. Since not everyone has the time or resources to run the project themselves, we’ve decided to host it ourselves on an EC2 instance. [Note: instance live only for one week!] You can try the visualization; we’ve also opened up the Impala web interface, where you can see query profiles and performance numbers, and Hue (username and password are both ‘test’), where you can run your own queries on the dataset.