Apache Kafka - Real-time Stream Processing (Master Class) - Stream Time and Grace Period

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Information Technology (IT), Architecture
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University
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7 questions
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1.
MULTIPLE CHOICE QUESTION
30 sec • 1 pt
What is the primary characteristic of a tumbling window in Kafka Streams?
Fixed size, non-overlapping, gapless windows
Fixed size, overlapping windows
Overlapping windows with gaps
Variable size, overlapping windows
2.
MULTIPLE CHOICE QUESTION
30 sec • 1 pt
How does Kafka Streams handle late-arriving records?
It ignores them completely
It merges them with the next window
It updates the window count and forwards the results
It stores them separately for later processing
3.
MULTIPLE CHOICE QUESTION
30 sec • 1 pt
What is the purpose of the grace period operator in Kafka Streams?
To ignore all late arrivals
To allow late arrivals within a specified time frame
To merge multiple windows into one
To extend the window duration indefinitely
4.
MULTIPLE CHOICE QUESTION
30 sec • 1 pt
How does stream time differ from wall clock time in Kafka Streams?
Stream time is based on the system clock
Stream time advances with each new record's timestamp
Stream time is always ahead of wall clock time
Stream time is synchronized with wall clock time
5.
MULTIPLE CHOICE QUESTION
30 sec • 1 pt
What happens to a window in Kafka Streams when the grace period expires?
The window count is reset
The window is reopened for new records
The window is considered fully closed and final
The window is merged with the next one
6.
MULTIPLE CHOICE QUESTION
30 sec • 1 pt
What is the default grace period in Kafka Streams?
No default grace period
12 hours
24 hours
48 hours
7.
MULTIPLE CHOICE QUESTION
30 sec • 1 pt
Why might late-arriving records be ignored in certain scenarios?
They are always irrelevant
They may not affect the current calculations
They are too difficult to process
They are automatically deleted
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