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DP-700 · Question #34

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…

The correct answer is B. No. 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.

Monitor and optimize an analytics solution

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?

Exhibit

DP-700 question #34 exhibit

Options

  • AYes
  • BNo

How the community answered

(46 responses)
  • A
    28% (13)
  • B
    72% (33)

Why each option

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.

AYes

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.

BNoCorrect

The make_list() function is an aggregation function that creates a dynamic array of values, typically used within a summarize operator to group and aggregate data. Introducing an aggregation like make_list() into this query, which is designed to plot individual points on a scatter chart, would fundamentally alter the data structure. This change would likely either break the render scatterchart operation or introduce additional processing complexity for aggregation, thus not reducing and possibly increasing runtime.

Concept tested: KQL aggregation functions and query optimization for visualization

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

Topics

#KQL Performance Optimization#KQL Aggregation Functions#Azure Data Explorer#Query Optimization

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