InfoQ Homepage Distributed Systems Content on InfoQ
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Book Review and Interview: The Practice of Cloud System Administration
The new book, The Practice of Cloud System Administration: Designing and Operating Large Distributed Systems, looks at a wide range of considerations for cloud-scale systems. In this book review and interview with the authors, we look at how teams can apply proven best practices.
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Designing a Highly Available, Fault Tolerant, Hadoop Cluster with Data Isolation
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.
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Interview with Alex Holmes, author of “Hadoop in Practice. Second Edition”
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.
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Matt Schumpert on Datameer Smart Execution
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.
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Real-Time Stream Processing as Game Changer in a Big Data World with Hadoop and Data Warehouse
This article discusses what stream processing is, how it fits into a big data architecture with Hadoop and a data warehouse (DWH), when stream processing makes sense, and what technologies and products you can choose from.
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Nikita Ivanov on GridGain’s In-Memory Accelerator for Hadoop
GridGain recently announced the In-Memory Accelerator for Hadoop, offering the benefits of in-memory computing to Hadoop based applications. It includes two components: an in-memory file system and a MapReduce implementation. InfoQ spoke with Nikita Ivanov, CTO of GridGain about the architecture of the product.
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Rich Reimer on SQL-on-Hadoop Databases and Splice Machine
SQL-on-Hadoop technologies include a SQL layer or a SQL database over Hadoop. These solutions are becoming popular recently as they solve the data management issues of Hadoop and provide a scale-out alternative for traditional RDBMSs. InfoQ spoke with Rich Reimer, VP of Marketing and Product Management at Splice Machine about the architecture and data patterns for SQL in Hadoop databases.
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Lambda Architecture: Design Simpler, Resilient, Maintainable and Scalable Big Data Solutions
Lambda Architecture proposes a simpler, elegant paradigm designed to store and process large amounts of data. In this article, author Daniel Jebaraj presents the motivation behind the Lambda Architecture, reviews its structure with the help of a sample Java application.
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Big Data Analytics for Security
In this article, authors discuss the role of big data and Hadoop in security analytics space and how to use MapReduce to efficiently process data for security analysis for use cases like Security Information and Event Management (SIEM) and Fraud Detection.
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Building Applications With Hadoop
When building applications using Hadoop, it is common to have input data from various sources coming in various formats. In his presentation, “New Tools for Building Applications on Apache Hadoop”, Eli Collins overviews how to build better products with Hadoop and various tools that can help, such as Apache Avro, Apache Crunch, Cloudera ML and the Cloudera Development Kit.
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Building a Real-time, Personalized Recommendation System with Kiji
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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Costin Leau on Elasticsearch, BigData and Hadoop
Elasticsearch is an open source, distributed real-time search and analytics engine for the cloud. The first milestone of elasticsearch-hadoop 1.3.M1 was released last month. InfoQ spoke with Costin Leau about Elasticsearch and how it integrates with Hadoop and other Big Data technologies.