Data Processing Batch Processing and Real-Time Processing 2

Question 1

Which framework is widely used for real-time stream processing in the US?

Accepted Answer

Apache Kafka Streams

Answer

Apache Kafka Streams is a widely adopted library for building real-time stream processing applications on top of Apache Kafka.

Question 2

What is event-driven processing?

Accepted Answer

Triggering computations in response to individual events as they occur

Answer

Event-driven processing executes logic immediately in response to each discrete event, enabling highly responsive and decoupled systems.

Question 3

What is the primary disadvantage of real-time stream processing compared to batch?

Accepted Answer

Higher system complexity and infrastructure cost to achieve low-latency guarantees

Answer

Real-time stream processing requires more sophisticated infrastructure, fault tolerance mechanisms, and operational expertise than simple batch pipelines.

Question 4

What is a windowing function in stream processing?

Accepted Answer

A function that groups stream events into time-based segments for aggregation

Answer

Windowing groups stream events into fixed or sliding time segments so aggregations like counts or averages can be computed over those intervals.

Question 5

What is late data in stream processing?

Accepted Answer

Events that arrive after the processing window they belong to has already closed

Answer

Late data refers to events that arrive out of order after their expected processing window has closed, requiring special handling to maintain accuracy.

Data Processing Practice Test

Data Processing Practice Test

Data Processing Batch Processing and Real-Time Processing 2