Erin Stellato shows the benefit of digging through the plan cache, Query Store, and third-party performance tool databases (using SentryOne’s SQL Sentry as an example):
As much as I love all this extra data, it’s important to note that some information is more relevant for an actual execution plan, versus an estimated one (e.g. tempdb spill information). Some days we can capture and use the actual plan for troubleshooting, other times we have to use the estimated plan. Very often we get that estimated plan – the plan that has been used for problematic executions potentially – from SQL Server’s plan cache. And pulling individual plans is appropriate when tuning a specific query or set or queries. But what about when you want ideas on where to focus your tuning efforts in terms of patterns?
The SQL Server plan cache is a prodigious source of information when it comes to performance tuning, and I don’t simply mean troubleshooting and trying to understand what’s been running in a system. In this case, I’m talking about mining information from the plans themselves, which are found in sys.dm_exec_query_plan, stored as XML in the query_plan column.
When you combine this data with information from sys.dm_exec_sql_text (so you can easily view the text of the query) and sys.dm_exec_query_stats (execution statistics), you can suddenly start to look for not just those queries that are the heavy hitters or execute most frequently, but those plans that contain a particular join type, or index scan, or those that have the highest cost. This is commonly referred to as mining the plan cache, and there are several blog posts that talk about how to do this. My colleague, Jonathan Kehayias, says he hates to write XML yet he has several posts with queries for mining the plan cache:
It’s a good article with a lot of useful information.