DP-203 Azure Data Engineer Associate DP-203 Azure Data Engineer Associate Real-Time Analytics and Streaming 2 — Questions and Answers
Question 1: Which windowing function in Azure Stream Analytics produces overlapping windows that slide forward by a defined step interval?
- Tumbling Window
- Hopping Window (Correct answer)
- Session Window
- Snapshot Window
Correct answer: Hopping Window
Hopping Windows have a fixed size but slide forward by a hop interval that is shorter than the window size, resulting in overlapping windows where an event can appear in multiple windows.
Question 2: In Azure Event Hubs, what determines the maximum number of parallel consumers reading from an Event Hub?
- The number of Consumer Groups
- The number of partitions (Correct answer)
- The throughput units provisioned
- The message retention period
Correct answer: The number of partitions
The number of partitions in an Event Hub sets the upper bound on parallelism because each partition can only be read by one consumer at a time within a Consumer Group.
Question 3: Which Azure Databricks feature enables structured streaming of data from Azure Event Hubs?
- Delta Live Tables batch ingestion
- Databricks Auto Loader
- Spark Structured Streaming with Event Hubs connector (Correct answer)
- Databricks SQL Warehouse
Correct answer: Spark Structured Streaming with Event Hubs connector
Spark Structured Streaming in Databricks, combined with the Azure Event Hubs connector library, allows you to consume event streams as a continuous DataFrame.
Question 4: What is Azure IoT Hub's primary advantage over Azure Event Hubs for IoT scenarios?
- Higher throughput capacity
- Bidirectional communication with devices and per-device identity management (Correct answer)
- Lower cost per message
- Native SQL query support for streams
Correct answer: Bidirectional communication with devices and per-device identity management
Azure IoT Hub supports bidirectional communication (device-to-cloud and cloud-to-device), per-device authentication, and device twin state management, which Event Hubs does not offer.
Question 5: In Azure Stream Analytics, which output type allows writing results to a Power BI dataset for real-time dashboards?
- Azure Blob Storage
- Azure SQL Database
- Power BI (Correct answer)
- Azure Data Lake Storage Gen2
Correct answer: Power BI
Stream Analytics supports Power BI as a native output, enabling the query results to be pushed directly to a Power BI streaming dataset for real-time visualization.
Question 6: What does 'checkpointing' accomplish in Spark Structured Streaming?
- It compresses the streaming data before writing to output
- It saves the streaming query progress to fault-tolerant storage to enable recovery after failure (Correct answer)
- It batches micro-intervals for higher throughput
- It validates the schema of each incoming event
Correct answer: It saves the streaming query progress to fault-tolerant storage to enable recovery after failure
Checkpointing in Spark Structured Streaming periodically saves the query's progress metadata and state to a fault-tolerant location (e.g., ADLS) so the stream can resume without data loss after a restart.
DP-203 Azure Data Engineer Associate DP-203 Azure Data Engineer Associate Real-Time Analytics and Streaming 2
Which windowing function in Azure Stream Analytics produces overlapping windows that slide forward by a defined step interval?