Chapter 1, Introducing Kafka, discusses how organizations are realizing the real value of data and evolving the mechanism of collecting and processing it.

Chapter 2, Installing Kafka, describes how to install and build Kafka 0.7.x and 0.8.

Chapter 3, Setting up the Kafka Cluster, describes the steps required to set up a single/multibroker Kafka cluster.

Chapter 4, Kafka Design, discusses the design concepts used for building a solid foundation for Kafka.

Chapter 5, Writing Producers, provides detailed information about how to write basic producers and some advanced-level Java producers that use message partitioning.

Chapter 6, Writing Consumers, provides detailed information about how to write basic consumers and some advanced-level Java consumers that consume messages from the partitions.

Chapter 7, Kafka Integrations, discusses how Kafka integration works for both Storm and Hadoop to address real-time and batch processing needs.

Chapter 8, Kafka Tools, describes information about Kafka tools, such as its administrator tools, and Kafka integration with Camus, Apache Camel, Amazon cloud, and so on.

In the simplest case, a single Linux-based (CentOS 6.x) machine with JDK 1.6 installed will give you a platform to explore almost all the exercises in this book. We assume you have some familiarity with command-line Linux; any modern distribution will suffice.

Some of the examples in this book need multiple machines to see things working, so you will require access to at least three such hosts. Virtual machines are fine for learning and exploration.

You will generally need the big data technologies, such as Hadoop and Storm, to run your Hadoop and Storm clusters.

This book is for readers who want to know about Apache Kafka at a hands-on level; the key audience is those with software development experience but no prior exposure to Apache Kafka or similar technologies.

This book is also for enterprise application developers and big data enthusiasts who have worked with other publisher-subscriber-based systems and now want to explore Apache Kafka as a futuristic scalable solution.

In this book, you will find a number of styles of text that distinguish between different kinds of information. Here are some examples of these styles, and an explanation of their meaning.

Code words in text are shown as follows: "We can include other contexts through the use of the include directive."

A block of code is set as follows:

String messageStr = new String("Hello from Java Producer");
KeyedMessage<Integer, String> data = new KeyedMessage<Integer, String>(topic, messageStr);
producer.send(data);

When we wish to draw your attention to a particular part of a code block, the relevant lines or items are set in bold:

Properties props = new Properties();
props.put("metadata.broker.list","localhost:9092");
props.put("serializer.class","kafka.serializer.StringEncoder");
props.put("request.required.acks", "1");
ProducerConfig config = new ProducerConfig(props); 
Producer<Integer, String> producer = new Producer<Integer, String>(config);

Any command-line input or output is written as follows:

[root@localhost kafka-0.8]# java SimpleProducer kafkatopic Hello_There

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