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  • Oozie Plugin for Eclipse

    by Ahmed Mahran on  Oct 30, 2015

    Oozie Eclipse plugin is a new tool for editing Apache Oozie workflows graphically inside Eclipse. Usage of this plugin allows to skip hard to develop and maintain process definition in HPDL. Instead a process graph is defined graphically by placing process actions on pallet and connecting them. An article introduces Eclipse Oozie plugin and provides an example of its usage.

  • Big Data as a Service, an Interview with Google's William Vambenepe

    by Chris Swan on  Jul 06, 2015

    Many of the Big Data technologies in common use originated from Google and have become popular open source platforms, but now Google is bringing an increasing range of big data services to market as part of its Google Cloud Platform. InfoQ caught up with Google's William Vambenepe, who's lead product manager for Big Data services to ask him about the shift towards service based consumption.

  • Designing a Highly Available, Fault Tolerant, Hadoop Cluster with Data Isolation

    by Monica Beckwith on  Dec 16, 2014

    As data grows exponentially, the modern Hadoop ecosystem provides not only a reliable distributed aggregation system that delivers data parallelism, but also analytics for great data insights. In this article Monica Beckwith, starting from core Hadoop components, investigates the design of a highly available, fault tolerant Hadoop cluster, adding security and data-level isolation.

Interview with Alex Holmes, author of “Hadoop in Practice. Second Edition”

Posted by Boris Lublinsky on  Nov 20, 2014

The new “Hadoop in Practice. 2 Edition" book by Alex Holmes covers a lot of topics building Hadoop code and organizing data to support code simplicity and execution speed.

Matt Schumpert on Datameer Smart Execution

Posted by Srini Penchikala on  Nov 13, 2014

Datameer, a big data analytics application for Hadoop, introduced Datameer 5.0 with Smart Execution to enhance the data analytics. InfoQ spoke with Matt Schumpert from Datameer about the new product.

Real-Time Stream Processing as Game Changer in a Big Data World with Hadoop and Data Warehouse

Posted by Kai Wähner on  Sep 10, 2014

This article discusses what stream processing is, how it fits into a big data architecture with Hadoop and a data warehouse (DWH), and what technologies and products you can choose from. 8

Nikita Ivanov on GridGain’s In-Memory Accelerator for Hadoop

Posted by Srini Penchikala on  Sep 08, 2014

GridGain announced In-Memory Accelerator for Hadoop, offering benefits of in-memory computing to Hadoop applications. InfoQ spoke with Nikita Ivanov from GridGain about the product's architecture.

Rich Reimer on SQL-on-Hadoop Databases and Splice Machine

Posted by Srini Penchikala on  Jun 19, 2014

InfoQ spoke with Rich Reimer, VP of Marketing and Product Management at Splice Machine about the architecture and data patterns for SQL-on-Hadoop technologies.

Lambda Architecture: Design Simpler, Resilient, Maintainable and Scalable Big Data Solutions

Posted by Daniel Jebaraj on  Mar 12, 2014

Lambda Architecture proposes a simpler, elegant paradigm designed to process large amounts of data. In this article, author discusses Lambda Architecture with the help of a sample Java application. 20

Big Data Analytics for Security

Posted by Alvaro A. Cárdenas, Pratyusa K. Manadhata, Sreeranga P. Rajan on  Feb 11, 2014

In this article, authors discuss the role of big data and Hadoop in security analytics space and how to use MapReduce to process data for security analysis.

Building Applications With Hadoop

Posted by Roopesh Shenoy on  Jan 30, 2014

How to use various tools such as Apache Avro, Apache Crunch, Cloudera ML and the Cloudera Development Kit to build applications that use Hadoop.

Building a Real-time, Personalized Recommendation System with Kiji

Posted by Jon Natkins on  Dec 26, 2013

Jon Natkins explains in this article how to create a personalized recommendation system fed with large amounts of real-time data using Kiji, which leverages HBase, Avro, Map-Reduce and Scalding.

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