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Creating efficient queries using data Query Profile Insights
Creating efficient queries using data Query Profile Insights

Stop wasting time on inefficient queries using Astrato's data Query Profile Insights Snowflake's GET_QUERY_OPERATOR_STATS

Piers Batchelor avatar
Written by Piers Batchelor
Updated over a year ago

Astrato's Data Query Profile Insights detects and identifies query inefficiencies - no coding required. This feature works with Snowflake's new table function - GET_QUERY_OPERATOR_STATS - that returns statistics about individual operators within a query.

Right-click on any chart, scroll down to select Data Query Insights.

Figure 1: Right-click on any chart, scroll down to select Data Query Insights

Viewing your Data Query Insights

  1. Right-click on any chart.

  2. Scroll down to select Data Query Insights.

  3. The Query Profile Insights details display beneath the formatted SQL query.

  4. The results display a red circle when a common query inefficiency - Cartesian, Union, Memory, or Pruning - appears.

  5. Click Copy result to send the results to your Snowflake administrator. The results include the number of rows scanned and the estimated credits the query uses.

Figure 2: View and copy the results of the data Query Profile.

Example of a query result

{"querylink":"https://app.snowflake.com/west-europe.azure/fd29442/#/compute/history/queries/01abdcff-0101-f3ec-0000-43c1049318da/detail","cacheUsed":false,"metaDataQuery":false,"creditsBestCase":0.000031,"creditsWorstCase":0.000276,"creditsFairValue":0.000276,"rowsScanned":2788,"joinIssue":false,"unionIssue":false,"memoryIssue":false,"pruningIssue":false}

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