I would have guessed that when a query includes TOP n the database
engine would run the query ignoring the the TOP clause, and then at
the end just shrink that result set down to the n number of rows that
was requested. The graphical execution plan seems to indicate this is
the case -- TOP is the "last" step. But it appears there is more going
on.
The way the above is phrased makes me think you may have an incorrect mental picture of how a query executes. An operator in a query plan is not a step (where the full result set of a previous step is evaluated by the next one.
SQL Server uses a pipelined execution model, where each operator exposes methods like Init(), GetRow(), and Close(). As the GetRow() name suggests, an operator produces one row at a time on demand (as required by its parent operator). This is documented in the Books Online Logical and Physical Operators reference, with more detail in my blog post Why Query Plans Run Backwards. This row-at-a-time model is essential in forming a sound intuition for query execution.
My question is, how (and why) does a TOP n clause impact the execution
plan of a query?
Some logical operations like TOP, semi joins and the FAST n query hint affect the way the query optimizer costs execution plan alternatives. The basic idea is that one possible plan shape might return the first n rows more quickly than a different plan that was optimized to return all rows.
For example, indexed nested loops join is often the fastest way to return a small number of rows, though hash or merge join with scans might be more efficient on larger sets. The way the query optimizer reasons about these choices is by setting a Row Goal at a particular point in the logical tree of operations.
A row goal modifies the way query plan alternatives are costed. The essence of it is that the optimizer starts by costing each operator as if the full result set were required, sets a row goal at the appropriate point, and then works back down the plan tree estimating the number of rows it expects to need to examine to meet the row goal.
For example, a logical TOP(10) sets a row goal of 10 at a particular point in the logical query tree. The costs of operators leading up to the row goal are modified to estimate how many rows they need to produce to meet the row goal. This calculation can become complex, so it is easier to understand all this with a fully worked example and annotated execution plans. Row goals can affect more than the choice of join type or whether seeks and lookups are preferred to scans. More details on that here.
As always, an execution plan selected on the basis of a row goal is subject to the optimizer's reasoning abilities and the quality of information provided to it. Not every plan with a row goal will produce the required number of rows faster in practice, but according to the costing model it will.
Where a row goal plan proves not to be faster, there are usually ways to modify the query or provide better information to the optimizer such that the naturally selected plan is best. Which option is appropriate in your case depends on the details of course. The row goal feature is generally very effective (though there is a bug to watch out for when used in parallel execution plans).
Your particular query and plan may not be suitable for detailed analysis here (by all means provide an actual execution plan if you wish) but hopefully the ideas outlined here will allow you to make forward progress.
CXPACKET can be accompanied with a LATCH_XX (possibly with PAGEIOLATCH_XX or SOS_SCHEDULER_YIELD as well). If this is the case (and I believe it is, based on the question) then the MAXDOP value should be lowered to fit your hardware.
Besides this, here are some more recommended steps in diagnosing the cause of high CXPACKET wait stats values (before changing something on SQL Server):
Do not set MAXDOP to 1, as this is never the solution
Investigate the query and CXPACKET history to understand and determine whether it is something that occurred just once or twice, as it could be just the exception in the system that is normally working correctly
Check the indexes and statistics on tables used by the query and make sure they are up to date
Check the Cost Threshold for Parallelism (CTFP) and make sure that the value used is appropriate for your system
Check whether the CXPACKET is accompanied with a LCK_M_XX (usually accompanied with IO_COMPLETION and ASYNC_IO_COMPLETION). If this is the case, then parallelism is not the bottleneck. Troubleshoot those wait stats to find the root cause of the problem and solution
If you really need to understand the CXPACKET wait type in depth, I would advise reading the Troubleshooting the CXPACKET wait type in SQL Server article
Best Answer
It appears your request for an actual execution plan triggered stats updates. Since you mention this happens in the mornings, I imagine there's an overnight process that does a lot of modifications to the tables involved?
Thus SQL Server uses the stats to create the plan, has hit the modification threshold, and executes automatic stats updates as part of the operation.
In the XML for the estimated plan you shared, I see these close-together update dates for stats from this morning:
If these are very large, busy tables (seems likely based on the sampling percentages), then it's not too surprising that the stats updates are taking a lot of horsepower.