Hadoop and MapReduce Design Patterns

hadoopRecently I finished my last project in which I was implementing Mule ESB. This gives me some room in my schedule to dive into the world of Big Data again (more specifically the Hadoop ecosystem). I have looked into this subject before which resulted into several blog posts. This time I started with a refresh by taking the online training of AWS: Big Data Technology Fundamentals. It is about MapReduce, Hadoop, Pig and Hive. After this nice online training I started with the Hadoop training of core-servlets. I had to get used to the form and layout of the training but now I have been working with it for a while I realise it contains a lot of information about the way Hadoop works. It comes with a (working!) virtual machine (based on Cloudera’s CDH4) on which Hadoop and the necessary tooling is installed including all training and exercise materials (and solutions).
Paralel to this (low level) training I am going through the book MapReduce Design Patterns. With this book you get a good idea which problems you can manage/solve with MapReduce framework and in what way. Especially the recommendation when not to use a certain pattern can be very handy while working with MapReduce.

About Pascal Alma

Pascal is a senior software developer and architect. Pascal has been designing and building applications since 2001. He is particularly interested in Open Source toolstack (Mule, Spring Framework, JBoss) and technologies like Web Services, SOA and Cloud technologies. Lately he is having great fun by building iOS apps with Swift. Specialties: JEE AWS XML/XSD/XSLT Web Services/SOA Mule ESB/ WSO2 ESB Maven Cloud Technology Swift/ iOS
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2 Responses to Hadoop and MapReduce Design Patterns

  1. Pingback: Running MapReduce Design Patterns on Cloudera’s CDH5 | The Pragmatic Integrator

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