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Apache Kafka Quick Start Guide电子书

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1人正在读 | 0人评论 9.8

作       者:Raúl Estrada

出  版  社:Packt Publishing

出版时间:2018-12-27

字       数:22.4万

所属分类: 进口书 > 外文原版书 > 电脑/网络

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Process large volumes of data in real-time while building high performance and robust data stream processing pipeline using the latest Apache Kafka 2.0 Key Features *Solve practical large data and processing challenges with Kafka *Tackle data processing challenges like late events, windowing, and watermarking *Understand real-time streaming applications processing using Schema registry, Kafka connect, Kafka streams, and KSQL Book Description Apache Kafka is a great open source platform for handling your real-time data pipeline to ensure high-speed filtering and pattern matching on the ?y. In this book, you will learn how to use Apache Kafka for efficient processing of distributed applications and will get familiar with solving everyday problems in fast data and processing pipelines. This book focuses on programming rather than the configuration management of Kafka clusters or DevOps. It starts off with the installation and setting up the development environment, before quickly moving on to performing fundamental messaging operations such as validation and enrichment. Here you will learn about message composition with pure Kafka API and Kafka Streams. You will look into the transformation of messages in different formats, such asext, binary, XML, JSON, and AVRO. Next, you will learn how to expose the schemas contained in Kafka with the Schema Registry. You will then learn how to work with all relevant connectors with Kafka Connect. While working with Kafka Streams, you will perform various interesting operations on streams, such as windowing, joins, and aggregations. Finally, through KSQL, you will learn how to retrieve, insert, modify, and delete data streams, and how to manipulate watermarks and windows. What you will learn *How to validate data with Kafka *Add information to existing data ?ows *Generate new information through message composition *Perform data validation and versioning with the Schema Registry *How to perform message Serialization and Deserialization *How to perform message Serialization and Deserialization *Process data streams with Kafka Streams *Understand the duality between tables and streams with KSQL Who this book is for This book is for developers who want to quickly master the practical concepts behind Apache Kafka. The audience need not have come across Apache Kafka previously; however, a familiarity of Java or any JVM language will be helpful in understanding the code in this book.
目录展开

Title page

Copyright and Credits

Apache Kafka Quick Start Guide

Dedication

About Packt

Why subscribe?

Packt.com

Contributors

About the author

About the reviewer

Packt is searching for authors like you

Preface

Who this book is for

What this book covers

To get the most out of this book

Download the example code files

Conventions used

Get in touch

Reviews

Configuring Kafka

Kafka in a nutshell

Kafka installation

Kafka installation on Linux

Kafka installation on macOS

Confluent Platform installation

Running Kafka

Running Confluent Platform

Running Kafka brokers

Running Kafka topics

A command-line message producer

A command-line message consumer

Using kafkacat

Summary

Message Validation

Enterprise service bus in a nutshell

Event modeling

Setting up the project

Reading from Kafka

Writing to Kafka

Running the processing engine

Coding a validator in Java

Running the validation

Summary

Message Enrichment

Extracting the geographic location

Enriching the messages

Extracting the currency price

Enriching with currency price

Running the engine

Extracting the weather data

Summary

Serialization

Kioto, a Kafka IoT company

Project setup

The constants

HealthCheck message

Java PlainProducer

Running the PlainProducer

Java plain consumer

Java PlainProcessor

Running the PlainProcessor

Custom serializer

Java CustomProducer

Running the CustomProducer

Custom deserializer

Java custom consumer

Java custom processor

Running the custom processor

Summary

Schema Registry

Avro in a nutshell

Defining the schema

Starting the Schema Registry

Using the Schema Registry

Registering a new version of a schema under a – value subject

Registering a new version of a schema under a – key subject

Registering an existing schema into a new subject

Listing all subjects

Fetching a schema by its global unique ID

Listing all schema versions registered under the healthchecks–value subject

Fetching version 1 of the schema registered under the healthchecks-value subject

Deleting version 1 of the schema registered under the healthchecks-value subject

Deleting the most recently registered schema under the healthchecks-value subject

Deleting all the schema versions registered under the healthchecks–value subject

Checking whether a schema is already registered under the healthchecks–key subject

Testing schema compatibility against the latest schema under the healthchecks–value subject

Getting the top-level compatibility configuration

Globally updating the compatibility requirements

Updating the compatibility requirements under the healthchecks–value subject

Java AvroProducer

Running the AvroProducer

Java AvroConsumer

Java AvroProcessor

Running the AvroProcessor

Summary

Kafka Streams

Kafka Streams in a nutshell

Project setup

Java PlainStreamsProcessor

Running the PlainStreamsProcessor

Scaling out with Kafka Streams

Java CustomStreamsProcessor

Running the CustomStreamsProcessor

Java AvroStreamsProcessor

Running the AvroStreamsProcessor

Late event processing

Basic scenario

Late event generation

Running the EventProducer

Kafka Streams processor

Running the Streams processor

Stream processor analysis

Summary

KSQL

KSQL in a nutshell

Running KSQL

Using the KSQL CLI

Processing data with KSQL

Writing to a topic

Summary

Kafka Connect

Kafka Connect in a nutshell

Project setup

Spark Streaming processor

Reading Kafka from Spark

Data conversion

Data processing

Writing to Kafka from Spark

Running the SparkProcessor

Summary

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