From the Dev Team

Follow the latest developments from our technical team

Continuing our series of quick interviews with Apache Hadoop project committers and contributors at Hortonworks.

To follow on from yesterday’s Server Log processing with Apache Flume tutorial we talk with Roshan Naik, Hortonworks engineer and Apache Flume contributor, about what Flume is, how it works and where it’s going.

Learn more about Flume here or at the Apache Hadoop project site.

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. …

This post authored by Zhijie Shen with Vinod Kumar Vavilapalli.

This is the sixth blog in the multi-part series on Apache Hadoop YARN – a general-purpose, distributed, application management framework that supersedes the classic Apache Hadoop MapReduce framework for processing data in Hadoop clusters. Other posts in this series:

Introducing Apache Hadoop YARN
Apache Hadoop YARN – Background and an Overview
Apache Hadoop YARN – Concepts and Applications
Apache Hadoop YARN – ResourceManager
Apache Hadoop YARN – NodeManager

Introduction

The beta release of Apache Hadoop  2.x has finally arrived and we are striving hard to make the release easy to adopt with no or minimal pain to our existing users.…

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.…

The next in our series of quick interviews with Apache Hadoop project committers at Hortonworks.

In this video, we talk with Sanjay Radia, Hortonworks co-founder and Apache Hadoop committer, about the initiation of HDFS, the cost benefits it brings to data storage and future directions for the project.

Learn more about HDFS here or at the Apache Hadoop project site.

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.…

UPDATE: This cheat sheet was so popular, we’ve created a PDF of the content below so you can print it and use it more easily. Download here.

 

If you’re already familiar with SQL then you may well be thinking about how to add Hadoop skills to your toolbelt as an option for data processing.

From a querying perspective, using Apache Hive provides a familiar interface to data held in a Hadoop cluster and is a great way to get started.…

If you want to understand the thinking in the various projects in the Hadoop ecosystem, then who better to talk to than key members of those projects – the committers.

In this video, we talk with Owen O’Malley, Hortonworks co-founder and Apache Hive committer, about the initiation of Hive, why it matters and future directions for the project.

Learn more about Hive here, or at the Apache Hive project site.…

In this blog we’ll set up NFS for HDFS access with the Hortonworks Sandbox 1.3. This allows the reading and writing of files to Hadoop using familiar methods to desktop users. Sandbox is a great way to understand this particular type of access.

If you don’t have it already, then download the sandbox here. Got the download? Then let’s get started.

Start the Sandbox. Get to this screen.

We will now enable Ambari so that we can edit the configuration to enable NFS.…

Today we released the Hortonworks Data Platform 1.3 for Windows for Windows Server 2008 R2 and 2012. This is an exciting major update to the only Enterprise Hadoop distribution on Windows. In this blog post, I will discuss what’s new and how to get started.

 Enabling new data applications

This release brings component parity to the HDP Stack across all operating systems by adding the following components:

  • Apache HBase (0.94.6.1) is a non-relational (NoSQL) database that runs on top of the Hadoop® Distributed File System (HDFS).

Thanks to all who joined us for last week’s webinar on Apache Hadoop YARN: Enabling Next Generation Data Applications. You can listen to the full webinar replay here, and the slides are embedded below.

If you’re already diving into YARN, then we will be hosting the first  ’Office Hours’ sessions at Hortonworks HQ. Join us on August 15th for a Deep Dive on Hoya (HBase on YARN)

Office hours will give you a chance to talk with those Hortonworks developers deeply involved with YARN and Hoya projects as well as your peers just launching their YARN projects.  …

The Hortonworks Sandbox is a great tool for not only learning Hadoop, but also for experimentation and application development.  Deployment in a type 2 hypervisor such as Oracle VirtualBox or VMWare Workstation is straightforward and serves the need for a single user. Sandbox can also be deployed to IaaS environments, and in this case, we walk through the steps of deploying Hortonworks Sandbox on OpenStack. For the purposes of this article, the author has used OpenStack Grizzly release running QEMU-KVM as the underlying hypervisor.…

In the last Hoya article, we talked about the its Application Architecture. Now let’s talk persistence. A key use case for Hoya is:  support long-lived clusters that can be started and stopped on demand. This lets a user start and stop an HBase cluster when they want, only using CPU and memory resources when they actually need it. For example, a specific MR job could use a private HBase instance as part of its join operations, or for an intermediate store of results in a workflow.…

At Hadoop Summit in June, we introduced a little project we’re working on: Hoya: HBase on YARN. Since then the code has been reworked and is now up on Github. It’s still very raw, and requires some local builds of bits of Hadoop and HBase – but it is there for the interested.

In this article we’re going to look at the architecture, and a bit of the implementation.

We’re not going to look at YARN in this article -for that we have a dedicated section of the Hortonworks site -including sample chapters of Arun Murthy’s forthcoming book.…

We continue to make strong headway towards the general availability of Hadoop 2.0.  A release candidate for Hadoop 2.1.0- Beta is currently under consideration by the Apache community. This critical milestone signifies both the outstanding progress being made by the community and equally important, the stabilization of Hadoop 2.0 APIs.

A defining characteristic of Hadoop 2.0 is its next generation resource management framework called YARN.  YARN enables Hadoop to grow beyond its MapReduce origins to embrace multiple workloads spanning interactive queries, batch processing, streaming & more.…

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