The Hortonworks Blog

Posts categorized by : HDP

As part of HDP 2.0 Beta, YARN takes the resource management capabilities that were in MapReduce and packages them so they can be used by new engines.  This also streamlines MapReduce to do what it does best, process data.  With YARN, you can now run multiple applications in Hadoop, all sharing a common resource management.

In this blog post we’ll walk through how to plan for and configure processing capacity in your enterprise HDP 2.0 cluster deployment.…

The upcoming Hive 0.12 is set to bring some great new advancements in the storage layer in the forms of higher compression and better query performance.

Higher Compression

ORCFile was introduced in Hive 0.11 and offered excellent compression, delivered through a number of techniques including run-length encoding, dictionary encoding for strings and bitmap encoding.

This focus on efficiency leads to some impressive compression ratios. This picture shows the sizes of the TPC-DS dataset at Scale 500 in various encodings.…

The Stinger Initiative is Hortonworks’ community-facing roadmap laying out the investments Hortonworks is making to improve Hive performance 100x and evolve Hive to SQL compliance to simplify migrating SQL workloads to Hive.

We launched the Stinger Initiative along with Apache Tez to evolve Hadoop beyond its MapReduce roots into a data processing platform that satisfies the need for both interactive query AND petabyte scale processing. We believe it’s more feasible to evolve Hadoop to cover interactive needs rather than move traditional architectures into the era of big data.…

We hosted a webinar on YARN a couple of weeks ago (see the slides and playback here). As you might expect, there was a lot of great questions and here is a set of answers to those questions.

Our next YARN-oriented Office Hours online on Sept 11th at 2pm PST. Join us on Meetup!

Who is using YARN and what benefits have they received from it?

On great public example of in production use of YARN, is at Yahoo!.…

This guest post from John Haddad, Director of Product Marketing at Informatica Corporation. He has over 25 years’ experience designing, building, integrating and marketing enterprise applications. His current focus is helping organizations get the most business value from Big Data by delivering timely, trusted, and relevant data across the extended enterprise.

Why is it so important for companies today to adopt a modern data architecture and why is next generation data integration on Apache Hadoop such a critical component?…

Another week, another release…  Following the release of Apache Hadoop 2.0 beta last week, we are excited to release the beta of Hortonworks Data Platform 2.0, the first commercial release of the stable YARN API and protocols on which new applications can now be built.

For our customers this is a great opportunity to ensure the release meets expectations and provides a vehicle to voice feedback that will work to improve Hadoop and shape its roadmap. …

In the last 60 seconds there were 1,300 new mobile users and there were 100,000 new tweets. As you contemplate what happens in an internet minute Amazon brought in $83,000 worth of sales. What would be the impact of you being able to identify:

  • What is the most efficient path for a site visitor to research a product, and then buy it?
  • What products do visitors tend to buy together, and what are they most likely to buy in the future?

Historical data is now an essential tool for businesses as they struggle to meet increasingly stringent regulatory requirements, manage risk and perform predictive analytics that help improve business decisions. And while recent data may be available from an enterprise data warehouse, the traditional practice of archiving old data offsite on tape makes business analytics challenging, if not impossible, because the historical information needed is simply unavailable.

Fortunately, the modern approach to data storage business analytics utilizes technologies like virtualization and big data Hadoop clusters to enable partitioned access to historical data.…

When they’re not planning to overthrow their human overlords, most servers can be found spewing out vast amounts of data in the form of server logs. As we showed in our video - Deliver responsive IT from events in Server Logs - these logs contain a lot of value.

So if you fire up the Hortonworks Sandbox today, you’ll be delighted to find Tutorial 12: Refining and Visualizing Server Log Data as a step-by-step guide to the video. …

Chances are you’ve already used Tableau Software if you’ve been involved with data analysis and visualization solutions for any length of time. Tableau 6.1.4 introduced the ability to visualize large, complex data stored in Hadoop with Hortonworks Data Platform via Hive and the Hortonworks Hive ODBC driver.

If you want to get hands on with Tableau as quickly as possible, we recommend using the Hortonworks Sandbox and the ‘Visualize Data with Tableau’ tutorial.…

It’s my great pleasure to announce that the Apache Hadoop community has declared Hadoop 2.x as Beta with the vote closing over the weekend for the hadoop-2.1.0-beta release.

As noted in the announcement to the mailing lists, this is a significant milestone across multiple dimensions: not only is the release chock-full of significant features (see below), it also represents a very stable set of APIs and protocols on which we can continue to build for the future.…

Before I was a developer of Hadoop, I was a user of Hadoop.  I was responsible for operation and maintenance of multiple Hadoop clusters, so it’s very satisfying when I get the opportunity to implement features that make life easier for operations staff.

Have you ever wondered what’s happening during a namenode restart?  A new feature coming in HDP 2.0 will give operators greater visibility into this critical process.  This is a feature that would have been very useful to me in my prior role.…

A busy week at Hortonworks Towers means a quick recap on what’s been happening.

Hadoop on Windows. On Tuesday we announced the GA of HDP 1.3 for Windows. Apart from being the only native Windows distribution for Hadoop, the updates and innovation in this release bring it to parity with our Linux distribution which means Hadoop Everywhere! Later on, we talked about getting started with HDP 1.3 for Windows, and also pointed at some great resources and tutorials.…

This week, we announced the launch of Hortonworks Data Platform (HDP) 1.3 for Windows which brings our native Windows Hadoop distribution to parity with our Linux distribution. HDP for Windows is also the Hadoop foundation for Microsoft’s HDInsight Service which delivers Hadoop and BI capabilities in in the Azure cloud.

Impetus, a Hortonworks System Integrator partner, is an early adopter of the Hortonworks Data Platform (HDP) and has leveraged the combined power of Hadoop & Microsoft Azure platform for a number of successful big data implementations using Microsoft’s HDInsight Service.…

This guest post from Sofia Parfenovich, Data Scientist at Altoros Systems, a big data specialist and a Hortonworks System Integrator partner. Sofia explains she optimized a customer’s trading solution by using Hadoop (Hortonworks Data Platform) and by clustering stock data.

Automated trading solutions are widely used by investors, banks, funds, and other stock market players. These systems are based on complex mathematical algorithms and can take into account hundreds of factors.…

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