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Posts categorized by : Ambari

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.

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?

Apache Ambari has always provided an operator the ability to provision an Apache Hadoop cluster using an intuitive Cluster Install Wizard web interface, guiding the user through a series of steps:

  • confirming the list of hosts
  • assigning master, slave, and client components to configuring services, and
  • installing, starting and testing the cluster.

With Ambari Blueprints, system administrators and dev-ops engineers can expedite the process of provisioning a cluster. Once defined, Blueprints can be re-used, which facilitates easy configuration and automation for each successive cluster creation.…

We recently hosted the fourth of our seven Discover HDP 2.1 webinars, entitled Apache 2.4.0, HDFS and YARN. It was very well attended and a very informative discourse. The speakers outlined the new features in YARN and HDFS in HDP 2.1 including:

  • HDFS Extended ACLs
  • HTTPs support for WebHDFS and for the Hadoop web UIs
  • HDFS Coordinated DataNode Caching
  • YARN Resource Manager High Availability
  • Application Monitoring through the YARN Timeline Server
  • Capacity Scheduler Preemption

Many thanks to our presenters, Rohit Bakhshi (Hortonworks’ senior product manager), Vinod Kumar Vavilapalli (co-author of the YARN Book, PMC, Hadoop YARN Project Lead at Apache and Hortonworks), and Justin Sears (Hortonworks’ Product Marketing Manager).…

The Apache Ambari community is happy to announce last week’s release of Apache Ambari 1.6.0, which includes exciting new capabilities and resolves 288 JIRA issues.  

Many thanks to all of the contributors in the Apache Ambari community for the collaboration to deliver 1.6.0, especially with Blueprints, a crucial feature that enables rapid instantiation and replication of clusters.

Each release of Ambari makes substantial strides in providing functionality to simplify the lives of system administrators and dev-ops engineers to deploy, manage, and monitor large Hadoop clusters, including those running on Hortonworks Data Platform 2.1 (HDP).…

On Wednesday May 21, Himanshu Bari (Hortonworks’ senior product manager), Venkatesh Seetharam (committer to Apache Falcon), and Justin Sears ( Hortonworks’ Product Marketing Manager), hosted the third of our seven Discover HDP 2.1 webinars. Himanshu and Venkatesh discussed data governance in Hadoop through Apache Falcon that is included in HDP 2.1. As most of you know, ingesting data into Hadoop is one thing; having data governed, by dictating and defining data-pipeline policies, is another thing—a necessity in the enterprise.…

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. …

Yesterday the Apache Ambari community proudly released version 1.5.1. This is the result of constant, concerted collaboration among the Ambari project’s many members. This release represents the work of over 30 individuals over 5 months and, combined with the Ambari 1.5.0 release, resolves more than 1,000 JIRAs.

This version of Ambari makes huge strides in simplifying the deployment, management and monitoring of large Hadoop clusters, including those running Hortonworks Data Platform 2.1.…

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. …

In this post, we will explore how to quickly and easily spin up our own VM with Vagrant and Apache Ambari. Vagrant is very popular with developers as it lets one mirror the production environment in a VM while staying with all the IDEs and tools in the comfort of the host OS.

If you’re just looking to get started with Hadoop in a VM, then you can simply download the Hortonworks Sandbox.…

This guest post from Steve Ratay, Viewpoint Architect, Teradata Corporation

Teradata’s Unified Data Architecture is a powerful combination of the Teradata Enterprise Data Warehouse, the Aster Discovery Platform, Apache Hadoop (via the Hortonworks Data Platform) and Teradata Enterprise Management tools in a single architecture. 

If you are Teradata user managing an Enterprise Data Warehouse or Data Discovery platform, chances are that you are using Teradata Viewpoint, a monitoring and management platform for Teradata Systems. …

I recently sat down with Mahadev Konar and Jeff Sposetti to discuss Apache Ambari v1.4.1. Ambari 1.4.1 is a single framework to provision, manage and monitor clusters based on the Hadoop 2 stack, with YARN and NameNode HA on HDFS.

Mahadev is one of the original architects of Apache Hadoop, a co-founder of Hortonworks, and a committer on Apache Ambari and Apache ZooKeeper. Jeff is the Hortonworks product manager focused on Apache Ambari and Apache Falcon.…

In this post, we’ll walk through the process of deploying an Apache Hadoop 2 cluster on the EC2 cloud service offered by Amazon Web Services (AWS), using Hortonworks Data Platform.

Both EC2 and HDP offer many knobs and buttons to cater to your specific, performance, security, cost, data size, data protection and other requirements. I will not discuss most of these options in this blog as the goal is to walk through one particular path of deployment to get started.…

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.…

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