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Earlier this month, the Apache Ambari community released Apache Ambari 1.6.1, which includes multiple improvements for performance and usability. The momentum in and around the Ambari community is unstoppable. Today we saw the Pivotal team lean in to Ambari, and this is the sixth release of this critical component in 2014, proving again that open source is the fastest path to innovation.

Many thanks to the wealth of contribution from the broad Ambari community that resulted in 585 JIRA issues being resolved in this release.…

Apache Hadoop clusters grow and change with use. Maybe you used Apache Ambari to build your initial cluster with a base set of Hadoop services targeting known use cases and now you want to add other services for new use cases. Or you may just need to expand the storage and processing capacity of the cluster.

Ambari can help in both scenarios. In this blog, we’ll cover a few different ways that Ambari can help you expand your cluster.…

There are many projects that have been contributed to the Apache Software Foundation (ASF) by both vendors and users alike that greatly expand Apache Hadoop’s capabilities as an enterprise data platform.

While Hadoop – with YARN at its architectural center – provides the foundational capabilities for managing and accessing data at scale, a broader blueprint for Enterprise Hadoop has emerged that specifies how this array of Apache projects fit across five distinct pillars to form a complete enterprise data platform: data access, data management, security, operations and governance.…

Last week, Apache Tez graduated to become a top level project within the Apache Software Foundation (ASF). This represents a major step forward for the project and is representative of its momentum that has been built by a broad community of developers from not only Hortonworks but Cloudera, Facebook, LinkedIn, Microsoft, NASA JPL, Twitter, and Yahoo as well.

What is Apache Tez and why is it useful?

Apache™ Tez is an extensible framework for building YARN based, high performance batch and interactive data processing applications in Hadoop that need to handle TB to PB scale datasets.…

The Apache Pig community released Pig 0.13. earlier this month. Pig uses a simple scripting language to perform complex transformations on data stored in Apache Hadoop. The Pig community has been working diligently to prepare Pig to take advantage of the DAG processing capabilities in Apache Tez. We also improved usability and performance.

This blog post summarizes the progress we’ve made.

Support for Backends Other Than MapReduce

We made the Pig 0.13 architecture more general to support multiple backends beyond just MapReduce, while maintaining backward compatibility.…

As part of our YARN Ready program, we are hosting a series of technical webinars highlighting the technologies and resources available to developers for creating YARN applications. In our first webinar, “Introduction to YARN Ready,” we presented an overview of the YARN Ready program.

To extend your technical knowledge, please join us for our first in-depth YARN Ready technology webinar, “Integrating Applications Natively to YARN” on Thursday July 24 at 9am Pacific Time.…

Incremental Updates

Hadoop and Hive are quickly evolving to outgrow previous limitations for integration and data access.
On the near-term development roadmap, we expect to see Hive supporting full CRUD operations (Insert, Select, Update, Delete). As we wait for these advancements, there is still a need to work with the current options—OVERWRITE or APPEND— for Hive table integration.

The OVERWRITE option requires moving the complete record set from source to Hadoop.…

Hadoop Summit Content Curation

Although the Hadoop Summit San Jose 2014 has come and gone, the invaluable content—keynotes, sessions, and tracks—is available here. I’ve selected a few sessions below for Hadoop system administrators and dev-ops, curating them under a general Hadoop operations theme.

Dev-ops engineers and system administrators know best that ease of operations and deployments can make or break a large Hadoop production cluster, which is why they care about all of the following:

  • how rapidly they can create or replicate a cluster;
  • how efficiently they can manage or monitor at scale;
  • how easily and programmatically they can extend or customize their operational scripts; and
  • how accurately they can foresee, forestall, or forecast resource starvation or capacity stipulation.

The Apache Storm community recently announced the release of Apache Storm 0.9.2, which includes improvements to Storm’s user interface and an overhaul of its netty-based transport.

We thank all who have contributed to Storm – whether through direct code contributions, documentation, bug reports, or helping other users on the mailing lists. Together, we resolved 112 JIRA issues.

Here are summaries of this version’s important fixes and improvements.

New Feature Highlights
Netty Transport Overhaul

Storm’s Netty-based transport has been overhauled to significantly improve performance through better utilization of thread, CPU, and network resources, particularly in cases where message sizes are small.…

Last Thursday we hosted the last of our seven Discover HDP 2.1 webinars, Using Apache Ambari to Manage Hadoop Clusters. Over 140 people attended and joined in the conversation.

The speakers gave an overview of Apache Ambari, discussed new features, and showed an end-to-end demo.

Thanks to our presenters Justin Sears (Hortonworks’ Product Marketing Manager), Jeff Sposetti (Hortonworks’ Senior Director of Product Management), and Mahadev Konar (Hortonworks’ Co-founder, Committer, and PMC Member for Apache Hadoop, Apache Ambari, and Apache Zookeeper) who presented the webinar.…

We recently hosted the sixth of our seven Discover HDP 2.1 webinars, entitled Apache Storm for Stream Data Processing in Hadoop. Over 200 people attended the webinar and joined in the conversation.

Thanks to our presenters Justin Sears (Hortonworks’ Product Marketing Manager), Himanshu Bari (Hortonworks’ Senior Product Manager for Storm), and Taylor Goetz (Hortonworks’ Software Engineer and Apache Storm Committer) who presented the webinar. The speakers covered:

  • Why use Apache Storm?

Data Analytics Virtual Event

Hortonworks and Teradata have partnered to provide a clear path to Big Data Analytics via stable and reliable Hadoop for the enterprise. We are excited to support their upcoming Big Data Analytics virtual event, “Data Discovery in Action.” We will have experts standing by to help answer questions to help ensure you have the right strategy in place for all of your big data.

At this event on July 2 nd, you will learn more about how Teradata’s Unified Big Data Architecture™ provides a quick path to data discovery.…

We’re finally catching our breath after a phenomenal Hadoop Summit event last week in San Jose.  Thank you to everyone that came to participate in the celebration of Hadoop advances and adoption—from many of the organizations that shared their Hadoop journey with us that fundamentally transformed their businesses, to those just getting started, to the huge ecosystem of vendors. It is amazing to be part of such a broad and deep community that is contributing to making the market for everyone.…

Apache YARN, Apache Slider, and Docker

Join us June 19 at 6 pm at the Hilton Fort Worth, Texas for an educational workshop hosted by Hortonworks and Sendero Business Services. The topic is “The Key To Success is Consistently Making Good Decisions & The Key To Good Decisions is Good Information.” The speaker is Don Hilborn, Solutions Engineer at Hortonworks.

Don will introduce the paradigm of

  • Efficiency – double processing in Hadoop on the same hardware while providing predictable performance and quality of service; and
  • Resource sharing – providing a stable common set of shared resources across multiple, coordinated workloads in Hadoop.

This is the second in the series of blogs exploring how to write data-driven applications in Java using the Cascading SDK. The series are:

  • WordCount
  • Log Parsing
  • Historically, programming languages and software frameworks have evolved in a singular direction, with a singular purpose: to achieve simplicity, hide complexity, improve developer productivity, and make coding easier. And in the process, foster innovation to the degree we have seen today—and benefited from.

    Anyone among you is “young” enough to admit writing code in microcode and assembly language?…

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