Apache Kafka - Real-time Stream Processing (Master Class) - Stream Processing in Apache Kafka

The video tutorial introduces Apache Kafka producers and their importance in streaming applications. It covers three main tools for stream processing: Kafka consumer APIs, Kafka Streams Library, and KSQL. The tutorial highlights the limitations of consumer APIs for complex use cases and introduces Kafka Streams API as a more efficient solution. KSQL is discussed as an alternative with its own limitations. The course focuses on Kafka Streams Library for real-time stream processing, leaving KSQL aside.

What is the primary role of Kafka producers in streaming applications?

• To provide a SQL-like interface for stream processing

• To consume data from Kafka brokers

• To originate data streams and bring them into Kafka

• To process data streams in real-time

Which tool is not part of the three main tools offered by Kafka for stream processing?

• Kafka Consumer APIs

• Kafka Streams Library

• Kafka Batch Processor

• KSQL

Which of the following is a limitation of using Kafka Consumer APIs for stream processing?

• They cannot consume data from Kafka brokers

• They are not suitable for simple data ingestion pipelines

• They require custom coding for complex use cases

• They offer a SQL-like interface for stream processing

What is a potential issue when implementing a 5-second window using Kafka Consumer APIs?

• It provides built-in scalability

• It automatically handles fault tolerance

• It requires no custom coding

• It may lead to potential bugs and requires custom coding

What is a key advantage of using Kafka Streams API over Consumer APIs?

• It cannot handle fault tolerance and scalability

• It provides a SQL-like interface

• It simplifies real-time stream processing with less custom coding

• It is only suitable for batch processing

What is KSQL primarily used for in the context of Kafka?

• To develop microservices architecture

• To consume data from Kafka brokers

• To provide a SQL-like interface for stream processing

• To originate data streams

Why might developers prefer Kafka Streams API over KSQL for real-life applications?

• Kafka Streams API cannot handle real-time processing

• Kafka Streams API does not support SQL-like queries

• KSQL is not suitable for microservices architecture

• KSQL is more complex to use