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)

Stream processor analysis

If you have a lot of questions here, it is normal.

The first thought to consider is that in streaming aggregation, and in streaming in general, the Streams are unbounded. It is never clear when we will take the final results, that is, we as programmers have to decide when to consider a partial value of an aggregation as a final result.

Recall that the print of the Stream is an instant photo of the KTable at a certain time. Therefore, the results of a KTable are only valid at the time of the output. It is important to remember that in the future, the values of the KTable may be different. Now, to see results more frequently, change the value of the commit interval to zero, shown as follows:

props.put("", 0);

This line says that the results of the KTable will be printed when they are modified, that is, it will print new values...