The Hortonworks Blog

Posts categorized by : Apache Hadoop

StackIQ, a Hortonworks technology partner, offers a comprehensive software suite that automates the deployment, provisioning, and management of Big Infrastructure. In this guest blog, Anoop Rajendra (@anoop_r), a Senior Software Developer at StackIQ, gives instructions for using StackIQ Cluster Manager to deploy Apache Ambari on a cluster running Hortonworks Data Platform (HDP).

Provisioning, managing and monitoring an Apache™ Hadoop cluster can be challenging. With this in mind, the engineers at Hortonworks introduced the Apache Ambari project into the Apache Software Foundation.…

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.…

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.…

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.…

Although the Hadoop Summit San Jose 2014 has come and gone, the invaluable content—keynotes, sessions, and tracks—is available here. We ’ve selected a few sessions for Hadoop developers, practitioners, and architects, curating them under Apache Hadoop YARN, the architectural center and the data operating system.

In most of the keynotes and tracks three themes resonated:

  • Enterprises are transitioning from traditional Hadoop to modern Hadoop 2.
  • YARN is an enabler, the central orchestrator that facilitates multiple workloads, runs multiple data engines, and supports multiple access patterns—batch, interactive, streaming, and real-time—in Apache Hadoop 2.
  • 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.

    Merv Adrian couldn’t have said it better. In his blog post from the weekend, he continued in his quest to define Hadoop. And it is no easy quest as the components of, and evolution of, Hadoop is happening at a pace that is, frankly, astounding.

    The continuous evolution of Hadoop has even given rise to sentiments such as ‘Is Hadoop dead? ‘ The answer to that question is YES. And NO.  …

    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.…

    IBM InfoSphere Guardium has certified with HDP 2.1. The  Hortonworks Certified Technology Program simplifies big data planning by providing pre-built and validated integrations between leading enterprise technologies and HDP. 

    Kathryn Zeidenstein, InfoSphere Guardium Evangelist, is our guest blogger and describes security, Hadoop, and the Guardium solution.

    Those of us in the data security and privacy space tend to worry a lot. With each new breaking story on the latest data breach, and with the subsequent fallout, people higher and higher up the food chain are also worrying a lot.…

    Today, we announce certification of Apache Spark as YARN Ready. This certification ensures memory and CPU intensive Spark-based applications can co-exist within a single Hadoop cluster with all the other workloads you have deployed. Together, they allow you to use a single cluster with a single set of data for multiple purposes rather than silo your Spark workloads into a separate cluster.
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