The Hortonworks Blog

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.…

Nothing happens in a vacuum anymore.  Cities now have the ability to use information collected from a massive variety of sources in order help solve common city problems.  The information can arise from anywhere – tweets, blog posts, and meter readings all can serve to inform public officials (and citizens as a whole) about how to better interact in a data-drenched world.

Most famously, IBM’s Smart Cities initiative looks at how city governments meet the needs of their expanding populations by using available resources more efficiently. …

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.…

Earlier, in the “Big Data in Genomics and Cancer Treatment” blog post, I explored how the extensive amount of information in DNA analysis mostly comes from the vast array of characteristics associated with people’s DNA make up and with different cancer variations. The case with today’s healthcare is very similar. Each patient is unique and has thorough medical history records that allow doctors to make evaluations and recommendations for future treatments.…

Small companies, big data.

Big data is sometimes at odds with the business-savvy entrepreneur who wants to exploit its full potential.   In essence, the business potential of big data is the massive (but promising) elephant in the room that remains invisible because the available talent necessary to take full advantage of the technology is difficult to obtain.

Inventing new technology for the platform is critical, but so too is making it easier to use.…

As organizations continue to ramp the number of MapReduce jobs processed in their Hadoop clusters, we often get questions about how best to share clusters. I wanted to take the opportunity to explain the role of Capacity Scheduler, including covering a few common use cases.

Let me start by stating the underlying challenge that led to the development of Capacity Scheduler and similar approaches.

As organizations become more savvy with Apache Hadoop MapReduce and as their deployments mature, there is a significant pull towards consolidation of Hadoop clusters into a small number of decently sized, shared clusters.…

As Apache Hadoop has risen in visibility and ubiquity we’ve seen a lot of other technologies and vendors put forth as replacements for some or all of the Hadoop stack. Recently, GigaOM listed eight technologies that can be used to replace HDFS (Hadoop Distributed File System) in some use cases. HDFS is not without flaws, but I predict a rosy future for HDFS.  Here is why…

To compare HDFS to other technologies one must first ask the question, what is HDFS good at:

  • Extreme low cost per byte
    HDFS uses commodity direct attached storage and shares the cost of the network & computers it runs on with the MapReduce / compute layers of the Hadoop stack.

Last week was an important milestone for Hortonworks: our one year anniversary. Given all of the activity around Apache Hadoop and Hortonworks, it’s hard to believe it’s only been one year. In honor of our birthday, I thought I would look back to contrast our original intentions with what we delivered over the past year.

Hortonworks was officially announced at Hadoop Summit 2011. At that time, I published a blog on the Hortonworks Manifesto.…

The following is Part 2 of 2 on data in education. The first article introduces the concept and application of data in education. The second article looks at recent movements by the Department of Education in data mining, modeling and learning systems.

Big data analytics are coming to public education. In 2012, the US Department of Education (DOE) was part of a host of agencies to share a $200 million initiative to begin applying big data analytics to their respective functions.…

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