Apache Spark is a ?exible framework that allows processing of batch and real-time data. Its unified engine has made it quite popular for big data use cases. This book will help you to get started with Apache Spark 2.0 and write big data applications for a variety of use cases.
It will also introduce you to Apache Spark – one of the most popular Big Data processing frameworks. Although this book is intended to help you get started with Apache Spark, but it also focuses on explaining the core concepts.
This practical guide provides a quick start to the Spark 2.0 architecture and its components. It teaches you how to set up Spark on your local machine. As we move ahead, you will be introduced to resilient distributed datasets (RDDs) and DataFrame APIs, and their corresponding transformations and actions. Then, we move on to the life cycle of a Spark application and learn about the techniques used to debug slow-running applications. You will also go through Spark’s built-in modules for SQL, streaming, machine learning, and graph analysis.
Finally, the book will lay out the best practices and optimization techniques that are key for writing efficient Spark applications. By the end of this book, you will have a sound fundamental understanding of the Apache Spark framework and you will be able to write and optimize Spark applications.
publication date
2019-01-31
what you will learn
Learn core concepts such as RDDs, DataFrames, transformations, and more
Set up a Spark development environment
Choose the right APIs for your applications
Understand Spark’s architecture and the execution ?ow of a Spark application
Explore built-in modules for SQL, streaming, ML, and graph analysis
Optimize your Spark job for better performance
key features
Learn about the core concepts and the latest developments in Apache Spark * Master writing efficient big data applications with Spark’s built-in modules for SQL, Streaming, Machine Learning and Graph analysis * Get introduced to a variety of optimizations based on the actual experience
approach
Readers will be taken through core concepts and modules of Apache spark and learn in detail, how to apply them in a variety of big data use cases. At each step along the way, the reader will be able to learn about both advantages and disadvantages of each feature.
audience
If you are a big data enthusiast and love processing huge amount of data, this book is for you. If you are data engineer and looking for the best optimization techniques for your Spark applications, then you will find this book helpful. This book also helps data scientists who want to implement their machine learning algorithms in Spark. You need to have a basic understanding of any one of the programming languages such as Scala, Python or Java.
short description
Apache Spark is a ?exible in-memory framework that allows processing of both batch and real-time data. Its unified engine has made it quite popular for big data use cases. This book will help you to quickly get started with Apache Spark 2.0 and write efficient big data applications for a variety of use cases.
subtitle
Quickly learn the art of writing efficient big data applications with Apache Spark
keywords
Apache Spark, data science, Spark, big data, Spark Cluster, RDD, Dataframes, Spark SQL, MLib, Stream Processing, SparkR, GraphX, Spark Core, structured data processing, Datasets API, DataFrames, structured streaming, interactive querying, SparkSQL,
Product ISBN
9781789349108
