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Dynamic_table_refresh_history

As explained in Snowflake Data Engineering

dynamic_table_refresh_history is a Snowflake built-in function that returns execution and refresh records for dynamic tables.

dynamic_table_refresh_history is a Snowflake built-in function for monitoring dynamic table executions. Its output records scheduled refresh attempts according to the table’s target lag, including attempts where no source data changed. section 5.4

Query refresh history

select * from table(information_schema.dynamic_table_refresh_history()) order by refresh_start_time desc; section 5.4

select *
from table(information_schema.dynamic_table_refresh_history())
order by refresh_start_time desc;

Run the supplied SQL listing to inspect the newest dynamic table refresh attempts first. section 5.4

Use the returned records to:

  • Confirm that refreshes occur at the configured target-lag frequency, such as once per minute. section 5.4
  • Troubleshoot failed refreshes and investigate reported errors. section 5.4

How Snowflake Data Engineering covers it

How deep it goes
Explains scheduled refresh records and troubleshooting value, but does not detail returned columns or error-handling procedures.
Examples
Uses the SPEEDY_ORDERS dynamic table and a query ordered by refresh_start_time descending.
What it assumes
Assumes a dynamic table with a configured target lag, such as the one-minute SPEEDY_ORDERS schedule.
What you can do after
Diagnose failed refreshes and investigate execution errors using refresh-history records.
How it connects
Connects dynamic tables with target lag, Snowflake built-in functions, and dynamic_table_graph_history.

This explainer was generated by Manning's knowledge graph from the text of Snowflake Data Engineering. The section links point to the parts of the book it draws on.