Develop a Stream Processing Solution DP-203 Practice Questions (Page 8)

Questions 36–40

1. 36application · medium

   A retail company processes order update events from an Event Hub using Spark structured streaming. Each event contains an order ID, a status, and a timestamp. They maintain a Delta Lake table that stores the latest status for each order. They need to ensure that the table reflects the most recent event for each order, even if events arrive out of order. What should they do?

   • AWrite the events to a temporary table and then use a scheduled job to update the main table.
   • BUse a tumbling window to aggregate the events and write the result to the Delta table.
   • CAppend all events to the Delta table and use a separate batch job to deduplicate.
   • DUse a foreachBatch sink that performs a merge operation on the Delta table using the order ID as the key.
   Reveal Solution Discussion Select an answer first
2. 37application · medium

   A company uses Spark Structured Streaming on Azure Databricks to read from Event Hubs and write to a Delta Lake table. The job needs to handle late-arriving data (up to 10 minutes) and ensure that the output is correct. They have set the watermark to 10 minutes. What is the effect of this watermark on the job's output?

   • AThe job will process events in real-time without any delay, ignoring the watermark.
   • BThe job will drop all events that arrive more than 10 minutes after the event time.
   • CThe job will wait up to 10 minutes after the event time before finalizing a window, allowing late events to be included.
   • DThe job will use the processing time instead of event time for windowing.
   Reveal Solution Discussion Select an answer first
4. 38foundation · easy

   Which Azure service can be used to replay archived stream data into a Stream Analytics job?

   • AAzure Cosmos DB
   • BAzure Event Hubs with Capture
   • CAzure Logic Apps
   • DAzure SQL Database
   Reveal Solution Discussion Select an answer first
5. 39foundation · easy

   In Azure Stream Analytics, what is the purpose of partitioning a stream into multiple partitions?

   • ATo simplify the query logic
   • BTo increase throughput by processing data in parallel
   • CTo reduce the need for checkpointing
   • DTo ensure data is stored in a single location
   Reveal Solution Discussion Select an answer first
6. 40foundation · easy

   What does the term 'upsert' mean in the context of stream data processing?

   • ADeleting a record and then inserting a new one
   • BInserting a new record or updating an existing record if it already exists
   • CAppending a record to the end of a file
   • DReading a record and then writing it to multiple outputs
   Reveal Solution Discussion Select an answer first