Technology innovations over years have made personal computing and the infrastructure inside our datacenters even more powerful. Gone are the days when our laptops used to come with single processors and single cores. I wonder even if they ever sell such configurations in the market.
Talking about multi-cores on our desktops and servers, these days software like SQL Server just use them to the max. When working with SQL Server, there are a number of settings that influence using parallelism. Check blog “SQL SERVER – MAXDOP Settings to Limit Query to Run on Specific CPU”, “SQL SERVER – CXPACKET – Parallelism – Usual Solution – Wait Type” and many other posts on this topic.
Having said that, I have seen people struggle to identify parallel queries in their environments. So here is the first shot at this requirement.
FROM sys.dm_exec_cached_plans cp
CROSS APPLY sys.dm_exec_query_plan(cp.plan_handle) AS p
CROSS APPLY sys.dm_exec_sql_text(cp.plan_handle) AS q
WHERE cp.cacheobjtype = 'Compiled Plan' AND p.query_plan.value('declare namespace
p="http://schemas.microsoft.com/sqlserver/2004/07/showplan"; max(//p:RelOp/@Parallel)', 'float') > 0
Queries that run in Parallel can be found with the above query. Remember, if a query runs in parallel it is a query that SQL Server thinks is expensive enough to run in parallel. MAX_DOP and the cost_threshold_for_parallelism drive the behavior. MAX_DOP should be configured to match the number of physical processors in the server if required.
The next step is to understand what to do when you find them? When you find them look for ways to make them run more efficiently if they are run often and their performance during business hours is critical. Check indexing in DTA for recommendations, simplify the query, remove ORDER BYs, GROUP BYs, if they aren’t necessary – these are some steps to help you guided.
Another way to find parallelism is to get queries where the amount of time spent by the workers are more than the query execution time. You can also use the below method to get the same too:
FROM sys.dm_exec_query_stats qs
CROSS APPLY sys.dm_exec_sql_text(qs.plan_handle) AS q
WHERE qs.total_worker_time > qs.total_elapsed_time
I hope these two scripts will be of use and you have something similar in your environments. Please share me scenario’s where you saw parallelism perform slower and how did you find them? Do let me know via comments.
Reference: Pinal Dave (https://blog.sqlauthority.com)