pyspark视频

在一个网课上买了一个pyspark视频,贼贵,本来是想把视频解压密码记下来分享出来的,可是其实用的是EVPLAYER,一机一码,一共只有3个激活码

 

这里我分享视频链接,百度网盘: https://pan.baidu.com/s/19o980VYyFAzkMrkQMyCxyA 密码: 51v5

收取15元作为对我的一点点补偿,付款之前可以先留言,我答复之后再付款,付款成功之后将邮箱留在下面,这样的活就省去后面的麻烦了

 

 

转载于:https://www.cnblogs.com/lfqbk/p/9127578.html

About This Book, Learn 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 guide, Who 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 Learn, Learn 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, In Detail, 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., You will get familiar with the modules available in PySpark. You will learn how to abstract data with RDDs and DataFrames and understand the streaming capabilities of PySpark. Also, you will get a thorough overview of machine learning capabilities of PySpark using ML and MLlib, graph processing using GraphFrames, and polyglot persistence using Blaze. Finally, you will learn how to deploy your applications to the cloud using the spark-submit command., By the end of this book, you will have established a firm understanding of the Spark Python API and how it can be used t
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