The Hortonworks Blog

Posts categorized by : YARN

On May 15, Owen O’Malley and Carter Shanklin hosted the second of our seven Discover HDP 2.1 webinars. Owen and Carter discussed the Stinger Initiative and the improvements to Apache Hive that are included in HDP 2.1:

  • Faster queries with Hive on Tez, vectorized query execution and a cost-based optimizer
  • New SQL semantics and datatypes
  • SQL-standard authorization
  • The Hive job visualizer in Apache Ambari
  • And many more

Here is the complete recording of the webinar.…

Syncsort is a Hortonworks Certified Technology Partner and has over 40 years of experience helping organizations integrate big data…smarter. Keith Kohl, Director of Product Management, Syncsort, is our guest blogger. Below he talks about the importance of certification and how it benefits Syncsort’s customers and prospects interested in Hadoop.

Back in January, Syncsort announced our partnership with Hortonworks and the certification of DMX-h on HDP 2.0. I was also given the opportunity to write a guest BLOG on the Hortonworks site about HDP 2 and the GA of YARN (thanks Hortonworks!).…

The first use of the term BoF session was used at the Digital Equipment Users’ Society (DECUS) conference in the 1960s. Its essence was to bring together like minds and thought leaders—just as birds of the feather flock together— to share and exchange computing ideas, in an informal yet spirited way. Since then, the organizers and sponsors of most computing conferences have been loyal to its essence and spirit.

For ideas and innovation happen in collaboration—not in isolation. …

This is the second in our series on the motivations and architecture for improvements to the Apache Hadoop YARN’s Resource Manager Restart resiliency. Other in the series are:

Introduction: Phase I – Preserve Application-queues

In the introductory blog, we previewed what RM Restart Phase I entails. In essence, we preserve the application-queue state into a persistent store and reread it upon RM restart, eliminating the need for users to resubmit their applications.…

This is the first post in our series on the motivations and architecture for improvements to the Apache Hadoop YARN’s Resource Manager Restart resiliency. Other in the series are:

Resource Manager (RM) is the central authority of Apache Hadoop YARN for resource management and scheduling. It is responsible for allocation of resources to applications like Hadoop MapReduce jobs, Apache TEZ DAGs, and other applications running atop YARN.…

The power of a well-crafted speech is indisputable, for words matter—they inspire to act. And so is the power of a well-designed Software Development Kit (SDK), for high-level abstractions and logical constructs in a programming language matter—they simplify to write code.

In 2007, when Chris Wensel, the author of Cascading Java API, was evaluating Hadoop, he had a couple of prescient insights. First, he observed that finding Java developers to write Enterprise Big Data applications in MapReduce will be difficult and convincing developers to write directly to the MapReduce API was a potential blocker.…

The pace of innovation within the Apache Hadoop community is truly remarkable, enabling us to announce the availability of Hortonworks Data Platform 2.1, incorporating the very latest innovations from the Hadoop community in an integrated, tested, and completely open enterprise data platform.

Download HDP 2.1 Technical Preview Now

What’s In Hortonworks Data Platform 2.1?

The advancements in HDP 2.1 span every aspect of Enterprise Hadoop: from data management, data access, integration & governance, security and operations. …

It gives me great pleasure to announce that the Apache Hadoop community has voted to release Apache Hadoop 2.3.0!

hadoop-2.3.0 is the first release for the year 2014, and brings a number of enhancements to the core platform, in particular to HDFS.

With this release, there are two significant enhancements to HDFS:

  • Support for Heterogeneous Storage Hierarchy in HDFS (HDFS-2832)
  • In-memory Cache for data resident in HDFS via Datanodes (HDFS-4949)

With support for heterogeneous storage classes in HDFS, we now can take advantage of different storage types on the same Hadoop clusters.…

Earlier this week Microsoft announced via their blog that a new version of Windows Azure HDInsight is available in public preview.

Microsoft recognizes the importance of the technical innovation in and around YARN as well as Hortonworks leadership in this area and we have worked collaboratively to bring Hadoop 2.2 to Azure via our Hortonworks Data Platform 2.0 for Windows release.

Apache Hadoop YARN is the data operating system for Hadoop and greatly expands the applications possible of this emerging technology by allowing multiple processing frameworks such as streaming or graph processing to plug in natively.…

I recently sat down with Himanshu Bari to discuss how Apache Ambari will serve as the single point of management for Hadoop 2 clusters integrated with Apache Storm and its real-time, streaming event processing.

Himanshu discusses Apache Storm’s five key benefits and how those will add to the power and stability of a Hadoop 2 stack, providing analysis of huge data flows from the second data is created and then for decades of historical analysis of that data stored in HDFS.…

This guest blog post is from Syncsort, a Hortonworks Technology Partner and certified on HDP 2.0, by Keith Kohl, Director, Product Management, Syncsort (@keithkohl)

Several years ago, Syncsort set on a journey to contribute to the Apache Hadoop projects to open and extend Hadoop, and specifically the MapReduce processing framework.  One of the contributions was to open the sort – both map side sort and reduce side – and to make it pluggable. …

Last week was a busy week for shipping code, so here’s a quick recap on the new stuff to keep you busy over the holiday season.

There is a lot of information available on the benefits of Apache YARN but how do you get started building applications? On December 18 at 9am Pacific Time, Hortonworks will host a webinar and go over just that:  what independent software vendors (ISVs) and developers need to do to take the first steps towards developing applications or integrating existing applications on YARN.

Register for the webinar here.

Why YARN?

As Hadoop gains momentum it’s important to recognize the benefits to customers and the competitive advantage software vendors will have if their application is integrated with YARN like elasticity, reliability and efficiency.…

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.…

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.…

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