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Learning PySpark-P2P

Build data-intensive applications locally and deploy at scale using the combined powers of Python and Spark 2.0
About This BookLearn why and how you can efficiently use Python to process data and build machine learning models in Apache Spark 2.0Develop and deploy efficient, scalable real-time Spark solutionsTake your understanding of using Spark with Python to the next level with this jump start guideWho This Book Is For
If you are a Python developer who wants to learn about the Apache Spark 2.0 ecosystem, this book is for you. A firm understanding of Python is expected to get the best out of the book. Familiarity with Spark would be useful, but is not mandatory.
What You Will LearnLearn about Apache Spark and the Spark 2.0 architectureBuild and interact with Spark DataFrames using Spark SQLLearn how to solve graph and deep learning problems using GraphFrames and TensorFrames respectivelyRead, transform, and understand data and use it to train machine learning modelsBuild machine learning models with MLlib and MLLearn how to submit your applications programmatically using spark-submitDeploy locally built applications to a cluster.
Apache Spark is an open source framework for efficient cluster computing with a strong interface for data parallelism and fault tolerance. This book will show you how to leverage the power of Python and put it to use in the Spark ecosystem. You will start by getting a firm understanding of the Spark 2.0 architecture and how to set up a Python environment for Spark.

Learning PySpark-P2P
2017 | ISBN: 1786463709, 9781786463708 | English | 274 pages | PDF | 7.5 MB
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