Apache Kafka. Flow processing and data analysis (Kafka: The Definitive Guide)

Everyone is used to me reading books fast enough, but this book didn't work out that way - while I was reading the translation of the first edition, the second edition came out:) The first edition came out in autumn. 2017 year and the second at the end 2021. The first edition consists of 11 heads

1. Meet Kafka In this chapter, we meet with the main character and get acquainted with the basic concepts of messaging, then we learn about the basics of Kafka: messages and packages, messaging schemes, topic and party, producers and consumers, as well as how brokers themselves look and how they are combined into clusters.
2. Installing Kafka - here the authors talk about the installation of Kafka and what to look for when choosing iron (Interestingly, in the second edition, the authors put more emphasis on moving to the cloud.)
3. Kafka Producers: Writing Messages to Kafka - here are discussed the issues of recording in Kafka (The name suggests that this system is geared towards writers:) ). It talks about the configuration of producers, serialization and work with parties.
4. Kafka Consumers: Reading Data from Kafka - here we are talking about how to read from Kafka and manage the offset through different variants of commits: autocommitt, asynchronous and synchronous committ
5. Kafka Internals This part is interesting for those who like to look under the soot. Here we are talking about how the cluster itself works, how membership in the cluster is implemented, what a controller is, what replication looks like, and then processing requests. (write-up)How does the physical level work?
6. Reliable Data Delivery Delivery guarantees are discussed here and how to ensure them through the collaboration of producer, Kafka and consumers. Here you can read about semantics at least once and exactly once in Kafka.
7. Building Data Pipelines - here is a brief description of ETL pipelines and work with Kafka Connect (I recommend reading more on this topic. Data Pipelines Pocket Reference)
8. Cross-Cluster Data Mirroring - about data replication between clusters and that it is better to pull data from a remote cluster than to throw them into a remote cluster (if there is such a possibility)
9. Administering Kafka - Kafka administration issues, there is a lot of complexity buried here, but this part is definitely worth reading if you have Kafka in production:)
10. Monitoring Kafka Monitoring issues are discussed here and mostly relate to monitoring java applications and further using JMX to obtain monitoring data from Kafka processes.
11. Stream Processing This is an interesting section about streaming, which is very concise, but allows you to understand the scope of Kafka Streams API.

That's the end of the book, but it makes sense to go and study the second edition to appreciate the five-year gap:))

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