Apache Kafka - Real-time Stream Processing (Master Class) - Creating Hopping Windows

This lecture explains hopping windows, which are overlapping windows defined by window size and advance interval. It uses a visual diagram to illustrate how hopping windows work with invoices, showing how message counts change as windows slide. The lecture also discusses the applications of hopping windows, their terminology differences in Kafka streams, and how to modify examples to implement hopping windows.

What are the two main properties that define a hopping window?

• Window size and advance interval

• Window size and overlap duration

• Window size and start time

• Advance interval and overlap duration

How does a hopping window differ from a tumbling window?

• Hopping windows are non-overlapping

• Hopping windows have a fixed start time

• Hopping windows are larger in size

• Hopping windows overlap with each other

In the given example, how many messages does the second window cover?

• Four messages

• Three messages

• Two messages

• One message

What is a common use case for hopping windows?

• Computing moving averages for a fixed size window

• Identifying the earliest message timestamp

• Calculating the total number of messages

• Determining the maximum message size

How can you modify a tumbling window to become a hopping window?

• By changing the start time

• By decreasing the window size

• By increasing the window size

• By adding an advance interval