Building Big Data Pipelines with Apache Beam: Use a single programming model for both batch and stream data processing
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Author
Publication
Packt Publishing
Apache Beam is an open source unified programming model for implementing and executing data processing pipelines, including Extract, Transform, and Load (ETL), batch, and stream processing.
This book will help you to confidently build data processing pipelines with Apache Beam. You'll start with an overview of Apache Beam and understand how to use it to implement basic pipelines. You'll also learn how to test and run the pipelines efficiently. As you progress, you'll explore how to structure your code for reusability and also use various Domain Specific Languages (DSLs). Later chapters will show you how to use schemas and query your data using (streaming) SQL. Finally, you'll understand advanced Apache Beam concepts, such as implementing your own I/O connectors.
By the end of this book, you'll have gained a deep understanding of the Apache Beam model and be able to apply it to solve problems.
Review
"Apache Beam can be daunting even for experienced big data engineers. As a contributor to the open source technology, Jan shares his years of experience in a logical, beginner-friendly way. He breaks down each practical scenario, describing the implementation, testing, and deployment and makes following along effortless with the books complimentary GitHub repo, which uses Kafka and Flink. Moreover, Jan explains difficult streaming topics such as triggers, windowing and even Splittable DoFns. I highly recommend it to anyone looking to advance in the data processing domain." -- Konrad Janica, Dataflow Engineer at Google
About the Author
- Understand the core concepts and architecture of Apache Beam
- Implement stateless and stateful data processing pipelines
- Use state and timers for processing real-time event processing
- Structure your code for reusability
- Use streaming SQL to process real-time data for increasing productivity and data accessibility
- Run a pipeline using a portable runner and implement data processing using the Apache Beam Python SDK
- Implement Apache Beam I/O connectors using the Splittable DoFn API
This book is for data engineers, data scientists, and data analysts who want to learn how Apache Beam works. Intermediate-level knowledge of the Java programming language is assumed.
- Introduction to Data Processing with Apache Beam
- Implementing, Testing, and Deploying Basic Pipelines
- Implementing Pipelines Using Stateful Processing
- Structuring Code for Reusability
- Using SQL for Pipeline Implementation
- Using Your Preferred Language with Portability
- Extending Apache Beam's I/O Connectors
- Understanding How Runners Execute Pipelines
