Kafka_The Definitive Guide_Real-Time Data and Stream Processing at Scale-2017
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资源说明:The greatest compliment you can give an author of a technical book is “This is the book I wish I had when I got started with this subject.” This is the goal we set for our‐ selves when we started writing this book. We looked back at our experience writing Kafka, running Kafka in production, and helping many companies use Kafka to build software architectures and manage their data pipelines and we asked ourselves, “What are the most useful things we can share with new users to take them from beginner to experts?” This book is a reflection of the work we do every day: run Apache Kafka and help others use it in the best ways. We included what we believe you need to know in order to successfully run Apache Kafka in production and build robust and performant applications on top of it. We highlighted the popular use cases: message bus for event-driven microservices, stream-processing applications, and large-scale data pipelines. We also focused on making the book general and comprehensive enough so it will be useful to anyone using Kafka, no matter the use case or architecture. We cover practical matters such as how to install and configure Kafka and how to use the Kafka APIs, and we also dedicated space to Kafka’s design principles and reliability guarantees, and explore several of Kafka’s delightful architecture details: the replication protocol, controller, and storage layer. We believe that knowledge of Kafka’s design and internals is not only a fun read for those interested in distributed systems, but it is also incredibly useful for those who are seeking to make informed decisions when they deploy Kafka in production and design applications that use Kafka. The better you understand how Kafka works, the more you can make informed decisions regarding the many trade- offs that are involved in engineering. One of the problems in software engineering is that there is always more than one way to do anything. Platforms such as Apache Kafka provide plenty of flexibility, which is great for experts but makes for a steep learning curve for beginners. Very often, Apache Kafka tells you how to use a feature but not why you should or shouldn’t use it. Whenever possible, we try to clarify the existing choices, the trade‐ offs involved, and when you should and shouldn’t use the different options presented by Apache Kafka.
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