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Key benefits

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

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

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Frequently bought together

Building Big Data Pipelines with Apache Beam

$48.99

$54.99

The Machine Learning Solutions Architect Handbook

$89.99

Total $ 193.97

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Amazon verified reviews

rafael Jan 21, 2022

This book impressed me a lot, I don't know if it is the first book that talks about this framework (Apache Beam), but it has helped me with some tips in my work.but I must also recognize that it is a very technical book and some experience is required to be able to understand it easily. It is not a book for someone who is starting in this world of Data Engineering, much less someone with little knowledge of Apache Beam. Although it explains very well and has good examples and graphics that help to understand, I think it is necessary to have at least an intermediate level on the subject.Therefore, I would like to highlight a few things about this experience:- Documented examples and with a repository on github, this is appreciated.- the book not only focuses on giving concepts, but also has many practical examples using other solutions such as kafka, apache flink or minikube, etc.- It is mentioned how to do unit tests on the constructed pipeline, but perhaps this is a point to improve by giving more depth to this topic.- Excellent explanation of the Use of Ptransform object GroupByKey, the graphics are also appreciated to understand this topic.- I liked how the book is sectioned- It is appreciated that there is information in both java programming language and python

Amazon Verified review

Antonio Cachuan Feb 22, 2022

A great opportunity to increase your skill in doing Apache Beam pipelines. I think this book is a good pocket reference if you are consolidating your Beam knowledge. Let me share the pros and cons after reading it:Pros-The book starts by giving you an overview of all the requirements for setting up an environment, and all the examples (mainly using Java) are located in a repository. I was new to using Minikube but I was able to run the examples without major difficulties. -Continuous giving details about Beam concepts like PCollections, PTransform, and others. Here I have to admit that the explanation of the concept of Window helped me to finally clarify some personal doubts in this field.-I agree with how was presented the batch to the streaming world "batch is a special case of streaming" and the examples that followed support the author's idea.-All the chapters include examples and Jan explains line-by-line the main parts of his code.-In chapters 8 and 4, the author made a great work explaining all about Runners and PTransform respectively.Cons-I would like to get more advice for deploying a pipeline in production. For example, including tips and more troubleshooting or including a deployment sample in any cloud provider.-Not exactly a con, but you need some experience in Java, and some background developing pipelines.ConclusionsMy final thought is that if you want to go serious in Apache Beam purchasing this book is a no doubt decision.

Joseph Jan 22, 2022

As someone who has implemented an Apache Beam pipeline and actively works to maintain it weekly, I really wish I had this resource a year ago.Jan does a fantastic job explicating the reasons why Apache Beam exists in the first place, the foundational concepts underlying how it functions and provides comprehensive examples of how to use it effectively. Depending on your needs and technical acumen, some sections may not be as enticing or useful to you; however, that is where this book shines. By gradually building upon previous sections and increasing the level of granularity, two people with very disparate use cases can read until they have the information they need and no further.Due to the fact that I found the beam documentation lacking in explaining some of the foundational concepts, this book has been a great clarifier. I also appreciate the use of multiple languages since my pipelines are primarily built for purposes of data science and machine learning, where python dominates the landscape.Overall, I would absolutely recommend this to someone trying to start or further their career in data engineering. Thank you Jan for this fantastic resource!

Amazon Customer Jan 24, 2022

This book goes over every topic intended for engineer who’s ready to get their hands dirty with Apache beam !I’ve used this book to review many of my base concepts and build code.This is a useful guide for Apache beam users!!

Rachel Jun 15, 2022

The book explains Apache Beam distributed data processing system for batch and streaming processing, from introducing learning examples to diving deep into advanced topics.I liked that book provides Github repo with all you need to focus on learning Apache Beam.The first two chapters introduce foundational concepts for pipelines, data transforms, batch, streaming, how to think of event and processing times, and windowed processing. Next, book covers stateful processing that can be used for processing data with external RPC services, using side inputs to enrich data. While the initial introduction is using Java, then the book expands to using Apache Beam with SQL, Python, and a concept of cross-language pipelines.Advanced topics include exploring building your custom I/O using splittable DoFn, understanding how Beam runners execute pipelines at scale, observability etc. - this all helps to deeper understand Apache Beam and apply that to help optimize data pipelines.

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

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