Recently 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.
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Pascal is a senior IT consultant and has been working in IT since 1997. He is monitoring the latest development in new technologies (Mobile, Cloud, Big Data) closely and particularly interested in Java open source tool stacks, cloud related technologies like AWS and mobile development like building iOS apps with Swift. Specialties: Java/JEE/Spring Amazon AWS API/REST Big Data Continuous Delivery Swift/iOS