A manufacturing company uses Azure Stream Analytics to process machine sensor data. Occasionally, the JSON payloads contain malformed fields (e.g., a string in a numeric field). The company wants to ensure that these malformed events do not cause the job to fail and that they are logged for later analysis. What should they configure?

Use a custom deserializer with error handling that routes malformed events to a separate output (e.g., a dead-letter queue).

Use a JavaScript UDF to validate and clean each field before processing.

Enable the 'Drop events' option in the input settings to discard malformed events.

Set the job's 'Event ordering' policy to 'Adjust' to automatically fix malformed fields.

What is the purpose of replaying archived stream data?

To reprocess historical data for analysis or to recover from processing errors

To delete old data from the archive

In Spark Structured Streaming, what is the default mechanism for reading from multiple partitions of a Kafka topic?

Partitions are merged into one before reading

Only the first partition is read

All partitions are read sequentially by a single task

Each partition is read by a separate task in parallel

What is schema drift in the context of streaming data?

The gradual change in the structure or types of fields in incoming data

The process of partitioning data across multiple nodes

The movement of data between different storage tiers

The loss of data due to network interruptions

Microsoft Certified:Azure Data Engineer Associate

Domain 2Objective 3

Develop a Stream Processing Solution DP-203 Practice Questions (Page 6)

Part of the Develop data processing domain, which accounts for 40–45% of the DP-203 exam. Microsoft does not publish an official question count, but from its 100-minute exam (~40–65 total, ~16–29 in this domain), expect 4–7 from this objective — we provide 47 practice questions to prepare you well beyond it. (estimate)

47questions here

10free pages

16concepts

40–45%of the exam

Questions 26–30

26application · medium
A manufacturing company uses Azure Stream Analytics to process machine sensor data. Occasionally, the JSON payloads contain malformed fields (e.g., a string in a numeric field). The company wants to ensure that these malformed events do not cause the job to fail and that they are logged for later analysis. What should they configure?
Select an answer first
27foundation · easy
What is the purpose of replaying archived stream data?
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28foundation · easy
In Spark Structured Streaming, what is the default mechanism for reading from multiple partitions of a Kafka topic?
Select an answer first
29foundation · easy
What is schema drift in the context of streaming data?
Select an answer first
30foundation · easy
Which Azure service is specifically designed for storing and analyzing time series data from IoT devices?
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Develop a Stream Processing Solution DP-203 Practice Questions (Page 6)

Questions 26–30

What is the purpose of replaying archived stream data?

In Spark Structured Streaming, what is the default mechanism for reading from multiple partitions of a Kafka topic?

What is schema drift in the context of streaming data?

Which Azure service is specifically designed for storing and analyzing time series data from IoT devices?

Keep studying — Develop data processing