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If you been following #hadoopsummit on twitter you might have noticed some excitement around the community choice, a public voting system that enables the entire Apache Hadoop community to have a say in the sessions chosen for #hadoopsummit EU. Anyone can vote and the top vote getters in each track will automatically be included in the #hadoopsummit EU agenda, March 20-21, 2013.

If you’re still deciding which sessions, in which tracks, should be so lucky to get your vote, I have one for your consideration.…

Thankful…

Happy Thanksgiving!

Today, like the rest of the U.S., we take a pause from our regular blog schedule to give thanks…

We are thankful for mappers and reducers. We are thankful for namenodes and jobtrackers. We give thanks to speculative execution battling the march of the last reducer. Give thanks to every petabyte, terabyte, gigabyte, file and block of data. We are thankful for the capacity scheduler.

We are very thankful for many things here at Hortonworks and I know many of us are thankful for an extra long weekend.…

As we speed towards wide spread enterprise adoption of Apache Hadoop, it has become readily apparent that this new data platform must not only capture, process and distribute data, but it also must be able to be deployed in a variety of ways, be it on premise, in a VM, as an appliance or better yet in the cloud…

Today we announced a new relationship with Rackspace in which we will develop an OpenStack based Hadoop solution for the public and private cloud.…

Visit Hortonworks at Strata New York!

We are so excited to attend O’Reilly Strata Conference in New York next week! If you are going to be there,  please come by booth 16 meet the members of the Hortonworks team who will be happy to discuss any questions you have about Hortonworks Data Platform, business benefits, see a nice demo and walk away with cool swags!

Hortonworks will also be participating in an array of sessions and meet-ups at this conference.…

Hortonworks Summer Internship 2012

As a first time intern, I can undoubtedly say that Hortonworks was the perfect place for me to gain real world work experience and have the chance to team up with many incredibly talented, driven people. Of course, I didn’t get to fully interact with everyone in the company in the three months that I was here but even after such a short time it is clear to me that it is the welcoming atmosphere and the determined team here that have allowed Hortonworks to achieve so many goals in just over a year.…

Hortonworks Data Platform 1.1 Brings Expanded High Availability and Streaming Data Capture, Easier Integration with Existing Tools to Improve Enterprise Reliability and Performance of Apache Hadoop

It is exactly three months to the day that Hortonworks Data Platform version 1.0 was announced. A lot has happened since that day…

  • Our distribution has been downloaded by thousands and is delivering big value to organizations throughout the world,
  • Hadoop Summit gathered over 2200 Hadoop enthusiasts into the San Jose Convention Center,
  • And, our Hortonworks team grew by leaps and bounds!

Series Introduction

Apache Pig is a dataflow oriented, scripting interface to Hadoop. Pig enables you to manipulate data as tuples in simple pipelines without thinking about the complexities of MapReduce.

But Pig is more than that. Pig has emerged as the ‘duct tape’ of Big Data, enabling you to send data between distributed systems in a few lines of code. In this series, we’re going to show you how to use Hadoop and Pig to connect different distributed systems to enable you to process data from wherever and to wherever you like.…

Pre-crime? Pretty close…

If you have seen the futuristic movie Minority Report, you most likely have an idea of how many factors and decisions go into crime prevention. Yes, Pre-crime is an aspect of the future but even today it is clear that many social, economic, psychological, racial, and geographical circumstances must be thoroughly considered in order to make crime prediction even partially possible and accurate. The predictive analytics made possible with Apache Hadoop can significantly benefit this area of government security.…

This is the first part of a series written by Charles Boicey from the UC Irvine Medical Center.  The series will demonstrate a real case study for Apache Hadoop in healthcare and also journal the architecture and technical considerations presented during implementation.

With a single observation in early 2011, the Hadoop strategy at UC Irvine Medical Center started. While using Twitter, Facebook, LinkedIn and Yahoo we came to the conclusion that healthcare data although domain specific is structurally not much different than a tweet, Facebook posting or LinkedIn profile and that the environment powering these applications should be able to do the same with healthcare data.…

This week, I spent some time and enjoyed speaking at the Softgrid 2012 conference in San Francisco. It was a great collection of speakers and attendees and opened my eyes to some Hadoop driven possibilities that not only differentiate utilities companies but will also transform our day-to-day lives.

The conference focused on software (in this case intelligent analytics) as a competitive advantage to enable value and growth for utilities.  These often large and historically conservative organizations have moved beyond the notion that their sole business is to distribute electric power efficiently, reliably, and cost-effectively to consumers.…

Do you want to understand how Apache Hadoop can benefit your business? Do you understand the relationship between Hadoop and your Big Data initiatives? Are you struggling to explain the benefits of Hadoop to your management team?

At Hortonworks, we are constantly being asked by business and executive audiences to explain use cases, benefits and components of Hadoop. While the interest in Big Data and Hadoop grows, this urgent and often pressing demand for a map to create value and differentiation amplifies.…

Series Introduction

Apache Pig is a dataflow oriented, scripting interface to Hadoop. Pig enables you to manipulate data as tuples in simple pipelines without thinking about the complexities of MapReduce.

But Pig is more than that. Pig has emerged as the ‘duct tape’ of Big Data, enabling you to send data between distributed systems in a few lines of code. In this series, we’re going to show you how to use Hadoop and Pig to connect different distributed systems, to enable you to process data from wherever and to wherever you like.…

Other posts in this series:
Introducing Apache Hadoop YARN
Apache Hadoop YARN – Background and an Overview
Apache Hadoop YARN – Concepts and Applications
Apache Hadoop YARN – ResourceManager
Apache Hadoop YARN – NodeManager

Apache Hadoop YARN – Concepts & Applications

As previously described, YARN is essentially a system for managing distributed applications. It consists of a central ResourceManager, which arbitrates all available cluster resources, and a per-node NodeManager, which takes direction from the ResourceManager and is responsible for managing resources available on a single node.…

Other posts in this series:
Introducing Apache Hadoop YARN
Philosophy behind YARN Resource Management
Apache Hadoop YARN – Background and an Overview
Apache Hadoop YARN – Concepts and Applications
Apache Hadoop YARN – ResourceManager
Apache Hadoop YARN – NodeManager

Apache Hadoop YARN – Background & Overview

Celebrating the significant milestone that was Apache Hadoop YARN being promoted to a full-fledged sub-project of Apache Hadoop in the ASF we present the first blog in a multi-part series on Apache Hadoop YARN – a general-purpose, distributed, application management framework that supersedes the classic Apache Hadoop MapReduce framework for processing data in Hadoop clusters.…

Other posts in this series:
Introducing Apache Hadoop YARN
Apache Hadoop YARN – Background and an Overview
Apache Hadoop YARN – Concepts and Applications
Apache Hadoop YARN – ResourceManager
Apache Hadoop YARN – NodeManager

Introducing Apache Hadoop YARN

I’m thrilled to announce that the Apache Hadoop community has decided to promote the next-generation Hadoop data-processing framework, i.e. YARN, to be a sub-project of Apache Hadoop in the ASF!

Apache Hadoop YARN joins Hadoop Common (core libraries), Hadoop HDFS (storage) and Hadoop MapReduce (the MapReduce implementation) as the sub-projects of the Apache Hadoop which, itself, is a Top Level Project in the Apache Software Foundation.…

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