Foreword
Ever since we started the Spark project at Berkeley, I’ve been excited about not just building fast parallel systems, but helping more and more people make use of large-scale computing. This is why I’m very happy to see this book, written by four experts in data science, on advanced analytics with Spark. Sandy, Uri, Sean, and Josh have been working with Spark for a while, and have put together a great collection of content with equal parts explanations and examples.
The thing I like most about this book is its focus on examples, which are all drawn from real applications on real-world data sets. It’s hard to find one, let alone ten examples that cover big data and that you can run on your laptop, but the authors have managed to create such a collection and set everything up so you can run them in Spark. Moreover, the authors cover not just the core algorithms, but the intricacies of data preparation and model tuning that are needed to really get good results. You should be able to take the concepts in these examples and directly apply them to your own problems.
Big data processing is undoubtedly one of the most exciting areas in computing today, and remains an area of fast evolution and introduction of new ideas. I hope that this book helps you get started in this exciting new field.
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