/explore
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highscalability.com | ||
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timilearning.com
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| | | | | In the first lecture of this series, I wrote about MapReduce as a distributed computation framework. MapReduce partitions the input data across worker nodes, which process data in two stages: map and reduce. While MapReduce was innovative, it was inefficient for iterative and more complex computations. Researchers at UC Berkeley invented Spark to deal with these limitations. | |
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www.altexsoft.com
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| | | | | The article explains how the main Big Data tools, Hadoop and Spark, work, what benefits and limitations they have, and which one to choose for your project. | |
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github.com
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| | | | | A curated list of software and architecture related design patterns. - DovAmir/awesome-design-patterns | |
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www.kai-waehner.de
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| | | Blog about architectures, best practices and use cases for data streaming, analytics, hybrid cloud infrastructure, internet of things, crypto, and more | ||
