Identifying Data Write Duration in Synapse Mapping Data Flows
You have an Azure subscription that contains an Azure Synapse Analytics workspace name workspace1, workspace1 contains an Azure Synapse Analytics dedicated SQL pool named Pool1. You create a mapping data flow in an Azure Synapse pipeline that writes data to Pool1. You execute the data flow and capture the execution information. You need to identify how long it takes to write the data to Pool1. Which metric should you use?
Community Votes
100% of anonymous learners picked answer B. Votes are pick records left by other test-takers — they are not the verified answer.
Community Insight
The question tests knowledge of mapping data flow execution metrics; the trap is confusing total pipeline time or transformation time with the specific sink write latency.
To measure the time taken to write data to a destination like Azure Synapse Dedicated SQL Pool, use the Sink Processing Time metric. Community consensus confirms this is the definitive metric for I/O and write operation duration.
Selecting 'transformation processing time' (C), which measures CPU-intensive transformations before data reaches the final destination, not the actual write operation.
Community Discussion (4 comments)
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Expert Analysis
Why the Answer Is Correct
The Sink Processing Time metric specifically captures the duration required to commit data to the target system. In Azure Synapse mapping data flows, the sink is the final stage where data exits the flow engine into the destination store, such as Pool1.Why the Other Options Are Wrong
Rows written (A) is a count metric, not a temporal one. Transformation processing time (C) measures the time spent on operations like joins or aggregations within the flow, excluding the final write. Post-processing time (D) typically refers to cleanup or metadata operations after the main write, which is negligible compared to the actual I/O write time.Community Comment Notes
Comment [1] clarifies that Sink Processing Time includes both transformation time and I/O time for that specific sink component, making it the comprehensive measure for the write phase. Comments [2] and [3] reinforce that 'sink' equals 'destination', directly linking the metric to the write operation against Pool1.Official Reference
Exam Strategy
When asked about writing to a database or file system in data flows, immediately look for 'Sink' related metrics. Distinguish between data movement (sink) and data manipulation (transformations).