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

Microsoft Access

Answer

FTP Server

Answer

Apache Subversion

Question 2

What is event-driven processing?

Accepted Answer

Triggering computations in response to individual events as they occur

Answer

Processing all records every 24 hours

Answer

Archiving events after 30 days

Answer

Batch loading events once per week

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

It cannot handle any data

Answer

It only works with structured data

Answer

Output is always less accurate

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

A function that encrypts stream data

Answer

A function that archives old stream data

Answer

A function that converts streams to CSV files

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

Data that is stored in the wrong table

Answer

Data that has not been encrypted

Answer

Records with NULL timestamps

Question 6

Which metric best describes the processing speed of a real-time data pipeline?

Accepted Answer

Latency

Answer

Compression ratio

Answer

Index coverage

Answer

Partition count