The Hortonworks Blog

Posts categorized by : HDP

Security is a top agenda item and represents critical requirements for Hadoop projects. Over the years, Hadoop has evolved to address key concerns regarding authentication, authorization, accounting, and data protection natively within a cluster and there are many secure Hadoop clusters in production. Hadoop is being used securely and successfully today in sensitive financial services applications, private healthcare initiatives and in a range of other security-sensitive environments. As enterprise adoption of Hadoop grows, so do the security concerns and a roadmap to embrace and incorporate these enterprise security features has emerged.…

This is a guest post from our partner, Revelytix who recently created a step-by-step tutorial on using Loom with the Hortonworks Sandbox. 

Enterprises are excited about the Hortonworks Data Platform (HDP) for many reasons, such as low cost, scalability, and flexibility. The latter in particular holds out new possibilities for data science. The Hadoop Distributed File System (HDFS) accepts files of any type and format, unlike traditional data warehouses which require a schema up front.…

The Apache Tez team is proud to announce the first release of Apache Tez – version 0.2.0-incubating.

Apache Tez is an application framework which allows for a complex directed-acyclic-graph of tasks for processing data and is built atop Apache Hadoop YARN. You can learn much more from our Tez blog series tracked here.

Since entering the Apache Incubator project in late February of 2013, there have been over 400 tickets resolved, culminating in this significant release.…

We are very excited to announce that Apache Ambari has graduated out of Incubator and is now an Apache Top Level Project! Hortonworks introduced Ambari as an Apache Incubator project back in August 2011 with the vision of making Hadoop cluster management dead simple.  In little over two years, the development community grew significantly, from a small team in Hortonworks, to a large number of contributors from various organizations beyond Hortonworks; upon graduation, there were more than 60 contributors, 37 of whom had become committers.…

We believe the fastest path to innovation is the open community and we work hard to help deliver this innovation from the community to the enterprise.  However, this is a two way street. We are also hearing very distinct requirements being voiced by the broad enterprise as they integrate Hadoop into their data architecture.

Take a look at the Falcon Technical Preview and the Data Management Labs.

Open Source, Open Community & An Open Roadmap for Dataset Management

Over the past year, a set of enterprise requirements has emerged for dataset management.  …

In just a few years, interest in Hadoop has enjoyed a meteoric rise. It is everywhere… and it should be available everywhere.

Here at Hortonworks we have worked to provide the widest range of deployment options for Hadoop… from on-premises to the cloud, Linux and Windows, and from commodity server clusters to high-end appliances. Deployment options are critical to the adoption of Hadoop and a key factor to adoption.

Today, we add Ubuntu to the list of options we support for HDP 2.0.…

Hortonworks customers can now enhance their Hadoop applications with Elasticsearch real-time data exploration, analytics, logging and search features, all designed to help businesses ask better questions, get clearer answers and better analyze their business metrics in real-time.

Hortonworks Data Platform and Elasticsearch make for a powerful combination of technologies that are extremely useful to anyone handling large volumes of data on a day-to-day basis. With the ability of YARN to support multiple workloads, customers with current investments in flexible batch processing can also add real-time search applications from Elasticsearch.…

We have heard plenty in the news lately about healthcare challenges and the difficult choices faced by hospital administrators, technology and pharmaceutical providers, researchers, and clinicians. At the same time, consumers are experiencing increased costs without a corresponding increase in health security or in the reliability of clinical outcomes.

One key obstacle in the healthcare market is data liquidity (for patients, practitioners and payers) and some are using Apache Hadoop to overcome this challenge, as part of a modern data architecture.…

User logs of Hadoop jobs serve multiple purposes. First and foremost, they can be used to debug issues while running a MapReduce application – correctness problems with the application itself, race conditions when running on a cluster, and debugging task/job failures due to hardware or platform bugs. Secondly, one can do historical analyses of the logs to see how individual tasks in job/workflow perform over time. One can even analyze the Hadoop MapReduce user-logs using Hadoop MapReduce(!) to determine any performance issues.…

This is the second of two posts examining the use of Hive for interaction with HBase tables. This is a hands-on exploration so the first post isn’t required reading for consuming this one. Still, it might be good context.

“Nick!” you exclaim, “that first post had too many words and I don’t care about JIRA tickets. Show me how I use this thing!”

This is post is exactly that: a concrete, end-to-end example of consuming HBase over Hive.…

Join Hortonworks and Pactera for a Webinar on Unlocking Big Data’s Potential in Financial Services Thursday, November 21st at 12:00 EST.

Have you ever had your debit or credit card declined for seemingly no reason? Turns out, the rejections are not so random. Banks are increasingly turning to analytics to predict and prevent fraud in real-time. That can sometimes be an inconvenience for customers who are traveling or making large purchases, but it’s necessary inconvenience today in order for banks to reduce billions in losses due to fraud.…

This is the first of two posts examining the use of Hive for interaction with HBase tables. The second post is here.

One of the things I’m frequently asked about is how to use HBase from Apache Hive. Not just how to do it, but what works, how well it works, and how to make good use of it. I’ve done a bit of research in this area, so hopefully this will be useful to someone besides myself.…

I teach for Hortonworks and in class just this week I was asked to provide an example of using the R statistics language with Hadoop and Hive. The good news was that it can easily be done. The even better news is that it is actually possible to use a variety of tools: Python, Ruby, shell scripts and R to perform distributed fault tolerant processing of your data on a Hadoop cluster.…

This post is authored by Omkar Vinit Joshi with Vinod Kumar Vavilapalli and is the ninth post in the multi-part blog 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:

Introduction

In the previous post, we explained the basic concepts of LocalResources and resource localization in YARN.…

Using Hadoop as an enterprise data platform means great integration with other technologies in the data center.

To that end, the Hortonworks Sandbox Partner Gallery showcases how our partners’ solutions integrate with Hadoop and provide you with easy access to learn how to use those solutions with the Hortonworks Data Platform via the Sandbox.

Don’t have the Sandbox? Get your free download of this single node Hadoop environment that’s delivered as a Virtual Machine that you can run on your laptop.…

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