The #1 factor in ADX/KQL database performance
The most important thing determining the performance of a KQL query is making sure that the minimum part of the data is scanned. In almost all cases a filter on a datetime column is used to determine what part of the data is relevant for the query results. The filter can be expressed in many ways on the actual table or a joined table. All variations are returning the correct results but the difference in performance can be 50X The different variations are described, and the reasons why are performant, and some are not.Using .show queries to understand and optimize the KQL sent from PBI to Kusto
You use Kusto /ADX / KQL databases in Fabric with Power BI. You want to see the queries send to the backend from PBI and try to optimize the behavior. This article includes a query starting with the ".show queries" command that can help you identify the queries that need your attentionHow to force filtering on at least one criterion when querying ADX data in direct query mode
We have two (or more) filters that can limit the amount of data scanned from a large table. How can we enforce a selection on at least one criterion so to avoid open queries that can drain the cluster resources? Using a KQL function and M dynamic parameters, we can prevent the query from running
