Apache Kafka - Real-time Stream Processing (Master Class) - Supressing Intermediate Results

Apache Kafka - Real-time Stream Processing (Master Class) - Supressing Intermediate Results

Assessment

Interactive Video

Information Technology (IT), Architecture

University

Hard

Created by

Quizizz Content

FREE Resource

The lecture discusses suppressing intermediate results in stream processing, focusing on a use case involving application monitoring with Kafka streams. It explains how to count heartbeats, send alerts, and handle continuous updates. The lecture highlights the importance of suppressing intermediate results to avoid false alerts and ensure accurate monitoring. A practical example demonstrates the implementation, emphasizing the need for a grace period and suppression to manage intermediate results effectively.

Read more

7 questions

Show all answers

1.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

What is the primary purpose of suppressing intermediate results in Kafka Streams?

To improve processing speed

To enhance data security

To reduce memory usage

To prevent false alerts in threshold monitoring

2.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

In the context of heartbeat monitoring, what is the significance of a grace period?

It reduces the number of heartbeats required

It decreases the alert threshold

It allows for late-arriving heartbeats to be considered

It increases the processing time

3.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

What is the main issue with continuous updates in Kafka Streams for threshold monitoring?

They cause delays in processing

They lead to premature alerts

They increase memory usage

They complicate the code

4.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

How does the suppress method help in handling continuous updates?

By discarding old data

By buffering intermediate results until the window closes

By increasing the processing speed

By reducing the number of events processed

5.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

What happens when the window is fully closed in Kafka Streams?

The system resets the count to zero

The final count is computed and alerts are sent if necessary

All intermediate results are discarded

The grace period is extended

6.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

Why is it important to have an unbounded buffer when using the suppress method?

To ensure all intermediate results are buffered until the window closes

To store all incoming data indefinitely

To reduce the memory usage

To increase the speed of processing

7.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

What is the outcome when a late-arriving heartbeat is within the grace period?

It triggers an immediate alert

It is ignored

It is processed and included in the count

It resets the window