[SOLVED] How can I force a subquery to perform as well as a #temp table?


I am re-iterating the question asked by Mongus Pong Why would using a temp table be faster than a nested query? which doesn’t have an answer that works for me.

Most of us at some point find that when a nested query reaches a certain complexity it needs to broken into temp tables to keep it performant. It is absurd that this could ever be the most practical way forward and means these processes can no longer be made into a view. And often 3rd party BI apps will only play nicely with views so this is crucial.

I am convinced there must be a simple queryplan setting to make the engine just spool each subquery in turn, working from the inside out. No second guessing how it can make the subquery more selective (which it sometimes does very successfully) and no possibility of correlated subqueries. Just the stack of data the programmer intended to be returned by the self-contained code between the brackets.

It is common for me to find that simply changing from a subquery to a #table takes the time from 120 seconds to 5. Essentially the optimiser is making a major mistake somewhere. Sure, there may be very time consuming ways I could coax the optimiser to look at tables in the right order but even this offers no guarantees. I’m not asking for the ideal 2 second execute time here, just the speed that temp tabling offers me within the flexibility of a view.

I’ve never posted on here before but I have been writing SQL for years and have read the comments of other experienced people who’ve also just come to accept this problem and now I would just like the appropriate genius to step forward and say the special hint is X…


There are a few possible explanations as to why you see this behavior. Some common ones are

  1. The subquery or CTE may be being repeatedly re-evaluated.
  2. Materialising partial results into a #temp table may force a more optimum join order for that part of the plan by removing some possible options from the equation.
  3. Materialising partial results into a #temp table may improve the rest of the plan by correcting poor cardinality estimates.

The most reliable method is simply to use a #temp table and materialize it yourself.

Failing that regarding point 1 see Provide a hint to force intermediate materialization of CTEs or derived tables. The use of TOP(large_number) ... ORDER BY can often encourage the result to be spooled rather than repeatedly re evaluated.

Even if that works however there are no statistics on the spool.

For points 2 and 3 you would need to analyse why you weren’t getting the desired plan. Possibly rewriting the query to use sargable predicates, or updating statistics might get a better plan. Failing that you could try using query hints to get the desired plan.

Answered By – Martin Smith

Answer Checked By – Candace Johnson (BugsFixing Volunteer)

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