@article{1440538,
      recid = {1440538},
      author = {Luu, Hien,},
      title = {Beginning Apache Spark 3 : with DataFrame, Spark SQL,  structured streaming, and Spark machine learning library /},
      pages = {1 online resource},
      note = {Includes index.},
      abstract = {Take a journey toward discovering, learning, and using  Apache Spark 3.0. In this book, you will gain expertise on  the powerful and efficient distributed data processing  engine inside of Apache Spark; its user-friendly,  comprehensive, and flexible programming model for  processing data in batch and streaming; and the scalable  machine learning algorithms and practical utilities to  build machine learning applications. Beginning Apache Spark  3 begins by explaining different ways of interacting with  Apache Spark, such as Spark Concepts and Architecture, and  Spark Unified Stack. Next, it offers an overview of Spark  SQL before moving on to its advanced features. It covers  tips and techniques for dealing with performance issues,  followed by an overview of the structured streaming  processing engine. It concludes with a demonstration of how  to develop machine learning applications using Spark MLlib  and how to manage the machine learning development  lifecycle. This book is packed with practical examples and  code snippets to help you master concepts and features  immediately after they are covered in each section. After  reading this book, you will have the knowledge required to  build your own big data pipelines, applications, and  machine learning applications. What You Will Learn Master  the Spark unified data analytics engine and its various  components Work in tandem to provide a scalable, fault  tolerant and performant data processing engine Leverage the  user-friendly and flexible programming model to perform  simple to complex data analytics using dataframe and Spark  SQL Develop machine learning applications using Spark MLlib  Manage the machine learning development lifecycle using  MLflow Who This Book Is For Data scientists, data engineers  and software developers.},
      url = {http://library.usi.edu/record/1440538},
      doi = {https://doi.org/10.1007/978-1-4842-7383-8},
}