InfoQ Homepage Big Data Content on InfoQ
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High Performance Computing Contributions to the World of Big Data
Sharan Kalwani presents the history of HPC and the technologies and trends which have contributed to creating the world of big data, covering applications of HPC resulting in big data technologies.
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A Distributed Transactional Database on Hadoop
John Leach explains using HBase co-processors to support a full ANSI SQL RDBMS without modifying the core HBase source, showing how Hadoop/HBase can replace traditional RDBMS solutions.
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Hadoop 201 -- Deeper into the Elephant
Roman Shaposhnik discusses more advanced features of HDFS, in addition to how YARN has enabled businesses to massively scale their systems beyond what was previously possible.
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Why Would You Integrate Solr and Hadoop?
Yann Yu discusses how Solr and Hadoop complement each other, and how to use Solr as a real-time, analytical, full-text search front-end to data stored in Hadoop.
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1.5 Million Log Lines Per Second: Building and Maintaining Flume Flows at Conversant
Mike Keane presents how Conversant migrated to Flume, managing 1000 agents across 4 data centers, processing over 50B log lines per day with peak hourly averages of over 1.5 million log lines/sec.
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The Big Data Imperative: Discovering & Protecting Sensitive Data in Hadoop
Jeremy Stieglitz discusses best practices for a data-centric security , compliance and data governance approach, with a particular focus on two customer use cases.
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Why Spark Is the Next Top (Compute) Model
Dean Wampler argues that Spark/Scala is a better data processing engine than MapReduce/Java because tools inspired by mathematics, such as FP, are ideal tools for working with data.
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Unified Big Data Processing with Apache Spark
Matei Zaharia talks about the latest developments in Spark and shows examples of how it can combine processing algorithms to build rich data pipelines in just a few lines of code.
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Customer Analytics on Hadoop
Bob Kelly presents case studies on how Platfora uses Hadoop to do analytics for several of their customers.
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Unleash the Power of HBase Shell
Jayesh Thakrar shows what can be done with irb, how to exploit JRuby-Java integration, and demonstrates how the Shell can be used in Hadoop streaming to perform complex and large volume batch jobs.
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Implementing the Lambda Architecture with Spring XD
Carlos Queiroz introduces the lambda architecture and showcases how it can be implemented with SpringXD, GemFireXD and Hadoop in a CDR(Call Detail Record) mining application.
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Spring XD for Real-time Hadoop Workload Analysis
The authors explain how the Pivotal team leveraged familiar SQL-based queries to analyze fine-grained cluster utilization using Spring XD.
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