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    3. Building Big Data Pipelines with Apache Beam: Use a single programming model for both batch and stream data processing

    Building Big Data Pipelines with Apache Beam: Use a single programming model for both batch and stream data processing

    Posted By: yoyoloit
    Date: 21 Jan 2022 10:12:43
    Building Big Data Pipelines with Apache Beam: Use a single programming model for both batch and stream data processing

    Building Big Data Pipelines with Apache Beam
    by Jan Lukavský
    English | 2022 | ISBN: ‎ 1800564937 | 342 pages | True PDF EPUB | 7.78 MB

    Implement, run, operate, and test data processing pipelines using Apache Beam
    Key Features

    Understand how to improve usability and productivity when implementing Beam pipelines
    Learn how to use stateful processing to implement complex use cases using Apache Beam
    Implement, test, and run Apache Beam pipelines with the help of expert tips and techniques

    Book Description

    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.
    What you will learn

    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

    Who this book is for

    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.
    UPWARDS