Kafka in Action

Scott, Dylan, Gamov, Viktor, Klein, Dave

  • 出版商: Manning
  • 出版日期: 2022-02-08
  • 售價: $1,740
  • 貴賓價: 9.5$1,653
  • 語言: 英文
  • 頁數: 375
  • 裝訂: Quality Paper - also called trade paper
  • ISBN: 161729523X
  • ISBN-13: 9781617295232
  • 相關分類: Message Queue
  • 相關翻譯: Kafka 實戰 (簡中版)
  • 立即出貨(限量) (庫存=1)

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商品描述

Master the wicked-fast Apache Kafka streaming platform through hands-on examples and real-world projects.

In Kafka in Action you will learn:

    Understanding Apache Kafka concepts
    Setting up and executing basic ETL tasks using Kafka Connect
    Using Kafka as part of a large data project team
    Performing administrative tasks
    Producing and consuming event streams
    Working with Kafka from Java applications
    Implementing Kafka as a message queue

Kafka in Action is a fast-paced introduction to every aspect of working with Apache Kafka. Starting with an overview of Kafka's core concepts, you'll immediately learn how to set up and execute basic data movement tasks and how to produce and consume streams of events. Advancing quickly, you’ll soon be ready to use Kafka in your day-to-day workflow, and start digging into even more advanced Kafka topics.

Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications.

About the technology
Think of Apache Kafka as a high performance software bus that facilitates event streaming, logging, analytics, and other data pipeline tasks. With Kafka, you can easily build features like operational data monitoring and large-scale event processing into both large and small-scale applications.

About the book
Kafka in Action introduces the core features of Kafka, along with relevant examples of how to use it in real applications. In it, you’ll explore the most common use cases such as logging and managing streaming data. When you’re done, you’ll be ready to handle both basic developer- and admin-based tasks in a Kafka-focused team.

What's inside

    Kafka as an event streaming platform
    Kafka producers and consumers from Java applications
    Kafka as part of a large data project

About the reader
For intermediate Java developers or data engineers. No prior knowledge of Kafka required.

商品描述(中文翻譯)

透過實際範例和實際專案,掌握快速的 Apache Kafka 流式平台。

在《Kafka 實戰》中,您將學到:

- 理解 Apache Kafka 的概念
- 設置並執行基本的 ETL 任務使用 Kafka Connect
- 在大型數據專案團隊中使用 Kafka
- 執行管理任務
- 生產和消費事件流
- 從 Java 應用程式中使用 Kafka
- 實現 Kafka 作為訊息佇列

《Kafka 實戰》是一本快節奏的介紹,涵蓋了與 Apache Kafka 相關的各個方面。從 Kafka 的核心概念開始,您將立即學習如何設置和執行基本的數據移動任務,以及如何生成和消費事件流。快速進展,您很快就能在日常工作流程中使用 Kafka,並深入研究更高級的 Kafka 主題。

購買印刷版書籍將包含 Manning Publications 提供的 PDF、Kindle 和 ePub 格式的免費電子書。

關於技術

將 Apache Kafka 視為一個高性能的軟體匯流排,可促進事件流、日誌記錄、分析和其他數據管道任務。使用 Kafka,您可以輕鬆地將操作數據監控和大規模事件處理等功能集成到大型和小型應用程式中。

關於本書

《Kafka 實戰》介紹了 Kafka 的核心功能,並提供了如何在實際應用中使用它的相關示例。您將探索最常見的用例,例如日誌記錄和管理流式數據。完成後,您將能夠在以 Kafka 為重點的團隊中處理基本的開發人員和管理員任務。

內容包括:

- Kafka 作為事件流平台
- 從 Java 應用程式中的 Kafka 生產者和消費者
- Kafka 作為大型數據專案的一部分

讀者對象

適合中級 Java 開發人員或數據工程師。無需事先了解 Kafka。

作者簡介

Dylan Scott is a software developer with over ten years of experience in Java and Perl. His experience includes implementing Kafka as a messaging system for a large data migration, and he uses Kafka in his work in the insurance industry.

Viktor Gamov is a developer advocate at Confluent.

Dave Klein is a developer advocate at Confluent, with over 28 years of experience in the technology industry.

作者簡介(中文翻譯)

Dylan Scott是一位擁有超過十年Java和Perl開發經驗的軟體開發人員。他的經驗包括在大型數據遷移中實施Kafka作為消息系統,並且他在保險行業的工作中使用Kafka。

Viktor Gamov是Confluent的開發者倡導者。

Dave Klein是Confluent的開發者倡導者,擁有超過28年的技術行業經驗。

目錄大綱

Table of Contents
PART 1 GETTING STARTED
1 Introduction to Kafka
2 Getting to know Kafka
PART 2 APPLYING KAFK
3 Designing a Kafka project
4 Producers: Sourcing data
5 Consumers: Unlocking data
6 Brokers
7 Topics and partitions
8 Kafka storage
9 Management: Tools and logging
PART 3 GOING FURTHER
10 Protecting Kafka
11 Schema registry
12 Stream processing with Kafka Streams and ksqlDB

目錄大綱(中文翻譯)

目錄
第一部分 開始使用
1 Kafka 簡介
2 了解 Kafka
第二部分 應用 Kafka
3 設計 Kafka 專案
4 生產者:資料來源
5 消費者:解鎖資料
6 Broker
7 主題和分區
8 Kafka 儲存
9 管理:工具和日誌
第三部分 進一步探索
10 保護 Kafka
11 Schema 註冊表
12 使用 Kafka Streams 和 ksqlDB 進行流處理