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The following screenshot shows a day of SQL queries and the amount of resources they consume.
As you can see, single queries, while there are many don't seem to consume much resources.
The bar chart shows a load of 0.08% of Data IO load. The line chart below on the other hand shows a constant utilization of about 15% to 25%. Even if the line is a running average, it does not match the bar chart. The single queries in the table below also don't seem to consume much resources.
Where does this overhead come from? Does it just hide internal queries? Do I read the visualization wrong?
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APPLIES TO: Azure SQL Database. Query Performance Insight provides intelligent query analysis for single and pooled databases. It helps identify the top resource consuming and long-running queries in your workload.
Use the Query Store page in SQL Server Management StudioIn Object Explorer, right-click a database, and then select Properties. Requires at least version 16 of Management Studio. In the Database Properties dialog box, select the Query Store page. In the Operation Mode (Requested) box, select Read Write.
The ability to drill down into details of a query, to view the query text and history of resource utilization Query Performance Insight requires that Query Store is active on your database. It's automatically enabled for all databases in Azure SQL Database by default. If Query Store is not running, the Azure portal will prompt you to enable it.
Open the Azure portal and find a database that you want to examine. From the left-side menu, open Intelligent Performance > Query Performance Insight. On the first tab, review the list of top resource-consuming queries. Select an individual query to view its details.
Use sliders or zoom icons to change the observed interval. For Azure SQL Database to render the information in Query Performance Insight, Query Store needs to capture a couple hours of data.
Today we announced significant query performance improvements for Azure SQL Data Warehouse (SQL DW) customers enabled through enhancements in the distributed query execution layer. Analytics workload performance is determined by two major factors, I/O bandwidth to storage and repartitioning speed, also known as shuffle speed.
Click on query id with highest IO, copy the query text and execute in SQL server to get queries which are taking huge resources to optimize them further
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