Apache Kafka - Real-time Stream Processing (Master Class) - Kafka Consumer - Practical Introduction

The video tutorial provides a practical introduction to Kafka consumer APIs, focusing on building a real-time data validation service for invoices. It covers the configuration and creation of Kafka consumers, processing records, and validating invoices. The tutorial concludes with testing the application and discussing the importance of Kafka Streams API for scalability and fault tolerance.

What is the primary focus of the lecture regarding Kafka APIs?

• Kafka Consumer APIs

• Kafka Broker APIs

• Kafka Producer APIs

• Kafka Streams Library

What defines an invalid invoice in the given business rule?

• Duplicate invoice entry

• Incorrect invoice amount

• Marked for home delivery without a contact number

• Missing invoice number

What is the first step in creating a Kafka consumer?

• Subscribing to a topic

• Creating a Java properties object

• Reading messages in a loop

• Setting up a producer

Which configuration is NOT required for a Kafka consumer?

• Client ID

• Bootstrap server

• Key and value deserializer

• Producer ID

What method is used to read messages from a Kafka topic?

• consume

• retrieve

• poll

• fetch

What is the purpose of the infinite loop in the Kafka consumer?

• To handle errors in message processing

• To stop the application after a certain time

• To process records in real-time continuously

• To subscribe to multiple topics

What is the key used for in the producer record?

• To identify the message type

• To determine the partition

• To set the store ID

• To specify the topic name

What is the main function of the example application discussed?

• To simulate a POS system

• To consume messages from multiple topics

• To produce invoices to a Kafka topic

• To validate invoices and segregate them into topics

What additional considerations are mentioned for real-time stream processing applications?

• Security and encryption

• Scalability and fault tolerance

• Data storage solutions

• User interface design

Why is Kafka Streams API recommended over consumer APIs for stream processing?

• It supports more data formats

• It is easier to configure

• It offers better scalability and fault tolerance

• It requires less coding