Data analytics with spark using python
- Boston : Addison-Wesley, 2018
- x, 306 p. ; ill. 24 cm
Includes bibliographical references and index.
Spark for Data Professionals introduces and solidifies the concepts behind Spark 2.x, teaching working developers, architects, and data professionals exactly how to build practical Spark solutions. Jeffrey Aven covers all aspects of Spark development, including basic programming to SparkSQL, SparkR, Spark Streaming, Messaging, NoSQL and Hadoop integration. Each chapter presents practical exercises deploying Spark to your local or cloud environment, plus programming exercises for building real applications. Unlike other Spark guides, Spark for Data Professionals explains crucial concepts step-by-step, assuming no extensive background as an open source developer. It provides a complete foundation for quickly progressing to more advanced data science and machine learning topics. This guide will help you: Understand Spark basics that will make you a better programmer and cluster “citizen” Master Spark programming techniques that maximize your productivity Choose the right approach for each problem Make the most of built-in platform constructs, including broadcast variables, accumulators, effective partitioning, caching, and checkpointing Leverage powerful tools for managing streaming, structured, semi-structured, and unstructured data.
9780134846019
Python Anonymous function Apache Big data Broadcast method Checkpointing Create Direct Stream method Data frames Dsteams Environment variables FlatMap Hadoop Higher-order function JSON JDBC Lamda syntax MapReduce NOSQL systems PySpark Spark cluster architecture Tuple function Unpersist method YARN