The new “Hadoop in Practice. Second Edition” book by Alex Holmes provides a deep insight into Hadoop ecosystem covering a wide spectrum of topics such as data organization, layouts and serialization, data processing, including MapReduce and big data patterns, special structures along with their usage to simplify big data processing, and SQL on Hadoop data.
Datameer, a big data analytics application for Hadoop, introduced Datameer 5.0 with Smart Execution to dynamically select the optimal compute framework at each step in the big data analytics process. InfoQ spoke with Matt Schumpert from Datameer team about the new product and how it works to help with big data analytics needs.
The article describes the general outline of the Stats Anomalies Detector developed at MyHeritage and provides a detailed explanation of how to enhance the code to meet your company’s needs.
"Analytics Across the Enterprise" book is a collection of experiences by analytics practitioners in IBM. InfoQ spoke with authors about lessons learned and IBM technologies in the Big Data area.
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. 6
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.
Spring XD (eXtreme Data) is Pivotal’s Big Data play. It joins Spring Boot and Grails as part of the execution portion of the Spring IO platform. 1
The MLConf conference was going strong in NYC on April 11th and was a full day packed with talks around Machine Learning and Big Data, featuring speakers from many prominent companies.
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
This article provides an overview of tools and libraries available for embedded data analytics & statistics, both stand-alone software packages and programming languages with statistical capabilities.
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.