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.
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.
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.
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 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. 7
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.
How to use various tools such as Apache Avro, Apache Crunch, Cloudera ML and the Cloudera Development Kit to build applications that use Hadoop.
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.
Elasticsearch is an open source, distributed real-time search and analytics engine for the cloud. InfoQ spoke with Costin Leau about Elasticsearch and how it integrates with Hadoop and Big Data.
Although Hadoop is a set of an open source Apache (and now GitHub) projects, there are currently a large number of alternatives for installing a version of Hadoop and realizing big data processes. 4