Book Image

Apache Kafka Quick Start Guide

By : Raúl Estrada
Book Image

Apache Kafka Quick Start Guide

By: Raúl Estrada

Overview of this book

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.
Table of Contents (10 chapters)

Running the Streams processor

To run the EventProcessor, follow these steps:

  1. Create the aggregates topic as follows:
$. /bin/kafka-topics --zookeeper localhost:2181 --create --topic 
aggregates --replication-factor 1 --partitions 4
  1. Run a console consumer for the aggregates topic, as follows:
$ ./bin/kafka-console-consumer --bootstrap-server localhost:9092 
--topic aggregates --property print.key=true
  1. From the IDE, run the main method of the EventProducer.
  2. From the IDE, run the main method of the EventProcessor.
  3. Remember that it writes to the topic every 30 seconds. The output on the console consumer for the aggregates topic should be similar to the following:
1532529050000 10
1532529060000 10
1532529070000 9
1532529080000 3

After the second window, we can see that the values in the KTable are updated with fresh (and correct) data, shown as follows:

1532529050000 10
1532529060000...