DP-700 Question #34: Real Exam Question with Answer & Explanation

Question

You have a KQL database that contains two tables named Stream and Reference. Stream contains streaming data in the following format: Column name Data type Timestamp Datetime Geolocation Dynamic Temperature Decimal DeviceId Int Reference contains reference data in the following format. Column name Data type DeviceId Int DeviceName String Both tables contain millions of rows. You have the following KQL queryset. 01 stream 02 | extend lat = todecimal(geolocation.Latitude), long = todecimal(geolocation.Longitude) 03 | join kind=inner Reference on DeviceId 04 | project Timestamp, lat, long, Temperature, DeviceName 05 | filter Temperature >= 10 06 | render scatterchart with (kind = map) You need to reduce how long it takes to run the KQL queryset. Solution: You add the make_list() function to the output columns. Does this meet the goal?

Options

• AYes
• BNo

Explanation

Adding the make_list() function to the KQL queryset, especially before a render scatterchart operation, is unlikely to reduce runtime as it implies an aggregation that would alter the data structure required for a point-based chart and potentially add processing overhead.

Common mistakes.

• A. Adding an aggregation function like make_list() before a scatterchart render usually changes the granularity of the data or adds processing overhead for grouping, which is not conducive to reducing runtime for a point-based visualization.

Concept tested. KQL aggregation functions and query optimization for visualization

Reference. https://learn.microsoft.com/en-us/azure/data-explorer/kusto/query/makelist-aggfunction

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