I'm having trouble understanding the behavior of the estimated query plans for my statement in SQL Server when a change from a parameterized query to a non-parameterized query.
I have the following query:
DECLARE #p0 UniqueIdentifier = '1fc66e37-6eaf-4032-b374-e7b60fbd25ea'
SELECT [t5].[value2] AS [Date], [t5].[value] AS [New]
FROM (
SELECT COUNT(*) AS [value], [t4].[value] AS [value2]
FROM (
SELECT CONVERT(DATE, [t3].[ServerTime]) AS [value]
FROM (
SELECT [t0].[CookieID]
FROM [dbo].[Usage] AS [t0]
WHERE ([t0].[CookieID] IS NOT NULL) AND ([t0].[ProductID] = #p0)
GROUP BY [t0].[CookieID]
) AS [t1]
OUTER APPLY (
SELECT TOP (1) [t2].[ServerTime]
FROM [dbo].[Usage] AS [t2]
WHERE ((([t1].[CookieID] IS NULL) AND ([t2].[CookieID] IS NULL))
OR (([t1].[CookieID] IS NOT NULL) AND ([t2].[CookieID] IS NOT NULL)
AND ([t1].[CookieID] = [t2].[CookieID])))
AND ([t2].[CookieID] IS NOT NULL)
AND ([t2].[ProductID] = #p0)
ORDER BY [t2].[ServerTime]
) AS [t3]
) AS [t4]
GROUP BY [t4].[value]
) AS [t5]
ORDER BY [t5].[value2]
This query is generated by a Linq2SQL expression and extracted from LINQPad. This produces a nice query plan (as far as I can tell) and executes in about 10 seconds on the database. However, if I replace the two uses of parameters with the exact value, that is replace the two '= #p0' parts with '= '1fc66e37-6eaf-4032-b374-e7b60fbd25ea' ' I get a different estimated query plan and the query now runs much longer (more than 60 seconds, haven't seen it through).
Why is it that performing the seemingly innocent replacement produces a much less efficient query plan and execution? I have cleared the procedure cache with 'DBCC FreeProcCache' to ensure that I was not caching a bad plan, but the behavior remains.
My real problem is that I can live with the 10 seconds execution time (at least for a good while) but I can't live with the 60+ sec execution time. My query will (as hinted above) by produced by Linq2SQL so it is executed on the database as
exec sp_executesql N'
...
WHERE ([t0].[CookieID] IS NOT NULL) AND ([t0].[ProductID] = #p0)
...
AND ([t2].[ProductID] = #p0)
...
',N'#p0 uniqueidentifier',#p0='1FC66E37-6EAF-4032-B374-E7B60FBD25EA'
which produces the same poor execution time (which I think is doubly strange since this seems to be using parameterized queries.
I'm not looking for advise on which indexes to create or the like, I'm just trying to understand why the query plan and execution are so dissimilar on three seemingly similar queries.
EDIT: I have uploaded execution plans for the non-parameterized and the parameterized query as well as an execution plan for a parameterized query (as suggested by Heinz) with a different GUID here
Hope it helps you help me :)
If you provide an explicit value, SQL Server can use statistics of this field to make a "better" query plan decision. Unfortunately (as I've experienced myself recently), if the information contained in the statistics is misleading, sometimes SQL Server just makes the wrong choices.
If you want to dig deeper into this issue, I recommend you to check what happens if you use other GUIDs: If it uses a different query plan for different concrete GUIDs, that's an indication that statistics data is used. In that case, you might want to look at sp_updatestats and related commands.
EDIT: Have a look at DBCC SHOW_STATISTICS: The "slow" and the "fast" GUID are probably in different buckets in the histogram. I've had a similar problem, which I solved by adding an INDEX table hint to the SQL, which "guides" SQL Server towards finding the "right" query plan. Basically, I've looked at what indices are used during a "fast" query and hard-coded those into the SQL. This is far from an optimal or elegant solution, but I haven't found a better one yet...
I'm not looking for advise on which indexes to create or the like, I'm just trying to understand why the query plan and execution are so dissimilar on three seemingly similar queries.
You seem to have two indexes:
IX_NonCluster_Config (ProductID, ServerTime)
IX_NonCluster_ProductID_CookieID_With_ServerTime (ProductID, CookieID) INCLUDE (ServerTime)
The first index does not cover CookieID but is ordered on ServerTime and hence is more efficient for the less selective ProductID's (i. e. those that you have many)
The second index does cover all columns but is not ordered, and hence is more efficient for more selective ProductID's (those that you have few).
In average, you ProductID cardinality is so that SQL Server expects the second method to be efficient, which is what it uses when you use parametrized queries or explicitly provide selective GUID's.
However, your original GUID is considered less selective, that's why the first method is used.
Unfortunately, the first method requires additional filtering on CookieID which is why it's less efficient in fact.
My guess is that when you take the non paramaterized route, your guid has to be converted from a varchar to a UniqueIdentifier which may cause an index not to be used, while it will be used taking the paramatarized route.
I've seen this happen with using queries that have a smalldatetime in the where clause against a column that uses a datetime.
Its difficult to tell without looking at the execution plans, however if I was going to guess at a reason I'd say that its a combinaton of parameter sniffing and poor statistics - In the case where you hard-code the GUID into the query, the query optimiser attempts to optimise the query for that value of the parameter. I believe that the same thing happens with the parameterised / prepared query (this is called parameter sniffing - the execution plan is optimised for the parameters used the first time that the prepared statement is executed), however this definitely doesn't happen when you declare the parameter and use it in the query.
Like I said, SQL server attempt to optimise the execution plan for that value, and so usually you should see better results. It seems here that that information it is basing its decisions on is incorrect / misleading, and you are better off (for some reason) when it optimises the query for a generic parameter value.
This is mostly guesswork however - its impossible to tell really without the execution - if you can upload the executuion plan somewhere then I'm sure someone will be able to help you with the real reason.
Related
Below is a snippet of code similar to what I am using.
DECLARE
#UserParam = NULL --optional paramater
SELECT
rtrim(item) [aKey]
INTO
#aKeyTable
FROM
myDB.dbo.fnSplit(#UserParam,',')
SELECT
/* Lots of columns, not important to the question */
FROM
myDB.dbo.tableB b
JOIN myDB.dbo.tableC c ON c.cKey = b.bKEY
AND (c.columnA IN
(
SELECT
aKey
FROM
#aKeyTable
)
OR #UserParam IS NULL)
My question is this: How do I remove the subquery to improve performance.
Requirements:
#UserParam is optional
#UserParam can have multiple comma separated parameters
#UserParam has to either match columnA in tableC OR be NULL
Using a WHERE clause isn't an option either, it impacts performance too much as well
I am using SQL Server 2014
UPDATE: My entire query is very long and it takes about 15-20 secs on average to run depending on parameters but according to the Execution Plan this subquery is using 89% of the performance. I had it in a WHERE clause previous to this and the performance was comparable and sometimes slower.
Thanks
Hard to know for sure without a query plan to see; that said, perhaps create an index on column aKey?
Did You consider using TVP? They are best for this purpose. Read also Erland Sommarskog for more details.
It is problematic to combine different cases into into one execution plan. When #UserParam is empty the situation is entirely different than when it is not. You should have execution plan for each case. You can induce an IF and make two queries. For more parameters You would end up with dynamic sql as exponential growth of combinations is not manageable otherwise.
Number of rows for table variable should be estimated by optimizer as 1, leading to index seeks. If the selectivity of parameters is good, this should work.
Recently, one of my colleague working in SQL development got into a problem like this: a procedure ran fine on all environments, but production, which has the most resources. Typical case of parameter sniffing, but the profiler indicated that only one query in the whole procedure took very much to execute:
UPDATE a
SET status_id = 6
FROM usr.tpt_udef_article_grouping_buffer a
LEFT JOIN (SELECT DISTINCT buying_domain_id, suppl_no FROM usr.buyingdomain_supplier_article) b ON a.buying_domain_id = b.buying_domain_id
AND a.suppl_no = b.suppl_no
WHERE a.tpt_file_id = #tpt_file_id
AND a.status_id IS NULL
AND b.suppl_no IS NULL
As I am biased towards development (I have little administration experience), I suggested that this query should be rewritten:
replace LEFT JOIN (SELECT DISTINCT ...) with NOT EXISTS (SELECT 1 ...)
put the appropriate index on table usr.tpt_udef_article_grouping_buffer(SSMS suggested an effort reduced by 95% when query was run outside the procedure)
Also, multiple queries from the procedure shared the same pattern.
I know that parameter sniffing is more related to the plan constructing when running the procedure for the first time after its (re)creation and I think it is also favored by high cyclomatic complexity.
My question is:
Does the way queries in the procedure are written (bad execution plans from the beginning) favor parameter sniffing appearance or just worsen their effects?
Your only parameter here is a.tpt_file_id = #tpt_file_id and if this is parameter sniffing, then the cases must be such that for certain tpt_file_id there are thousands (or more) records, and for certain there is few (or none).
The other reason you get different plans in production than test environment is that the machines are different. You usually have a lot more memory and more CPUs / cores in production environment, causing optimizer to choose different plan and of course if your row counts in the tables are not the same, it of course can lead to into a totally different plan.
You can check this with using option (recompile) to see if the plan changes or look at plan cache that what was the value of the parameter used to create the plan. It can be seen in the properties of the leftmost object in the plan.
Changing the select distinct into exists clause is probably a good idea, and of course indexing the tables properly.
I'm having problems with slow performance in a sql select statement with some parameters, for the same query, executing this select using sp_executesql way it takes double time that the inline-way.
The problem is that in sp_execute-way sql server is not using optimal execution plan. Although plans are different, it seems that in both cases indexes of tables are being used correctly. I really don't understand why performance are so different.
My original query is more complex but to try to figure out what's happening I have simplify the original query to a select with 3 tables and 2 joins. The main difference is the use of Hash Match in optimal , I really don't know the meaning of this but is the only difference I can see.
Optimal plan (hash match, over 3 seconds)
Wrong plan (no hash match, same indexes than above, over 12 seconds)
I think my problem is not "parameter sniffing", in my case the query is always slow for all distinct parameter values because the execution plan is always incorrect.
OPTION (RECOMPILE) doesn't help, sp_executesql keeps going slow and inline-way take more time (because the query always compile the execution plan)
Statistics for tables are updated
I have to use sp_executesql way because it seems that reporting services encapsulates the select in sp_executesql calls
Does anybody know why sp_executesql generates a different (wrong) execution plan than the inline query?
EDIT: Queries wasn't using same indexes I guess that because the execution tree is not the same and sqlserver takes indexes as it pleases, attached you can find new execution plans to force to use the same indexes, performance is now even worst, from 12 seconds to more than 15 minutes (I have cancelled) in slow query. I'm really not interested in run this specific query more speed, as I say this is not the real query I'm dealing with, what I'm trying to figure out is why execution plans are so different between inline-query and sp_executesql-query.
Is there any magic option in sp_executesql that do this works properly? :)
Optimal
Slow
My understanding is that sp_executesql keeps a cached plan after the first execution. Subsequent queries maybe using a bad cached plan. You can use the following command to clear out the ENTIRE SQL Server procedure cache.
DBCC FREEPROCCACHE
http://msdn.microsoft.com/en-us/library/ms174283.aspx
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
The subquery or CTE may be being repeatedly re-evaluated.
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.
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.
I do not believe there is a query hint that instructs the engine to spool each subquery in turn.
There is the OPTION (FORCE ORDER) query hint which forces the engine to perform the JOINs in the order specified, which could potentially coax it into achieving that result in some instances. This hint will sometimes result in a more efficient plan for a complex query and the engine keeps insisting on a sub-optimal plan. Of course, the optimizer should usually be trusted to determine the best plan.
Ideally there would be a query hint that would allow you to designate a CTE or subquery as "materialized" or "anonymous temp table", but there is not.
Another option (for future readers of this article) is to use a user-defined function. Multi-statement functions (as described in How to Share Data between Stored Procedures) appear to force the SQL Server to materialize the results of your subquery. In addition, they allow you to specify primary keys and indexes on the resulting table to help the query optimizer. This function can then be used in a select statement as part of your view. For example:
CREATE FUNCTION SalesByStore (#storeid varchar(30))
RETURNS #t TABLE (title varchar(80) NOT NULL PRIMARY KEY,
qty smallint NOT NULL) AS
BEGIN
INSERT #t (title, qty)
SELECT t.title, s.qty
FROM sales s
JOIN titles t ON t.title_id = s.title_id
WHERE s.stor_id = #storeid
RETURN
END
CREATE VIEW SalesData As
SELECT * FROM SalesByStore('6380')
Having run into this problem, I found out that (in my case) SQL Server was evaluating the conditions in incorrect order, because I had an index that could be used (IDX_CreatedOn on TableFoo).
SELECT bar.*
FROM
(SELECT * FROM TableFoo WHERE Deleted = 1) foo
JOIN TableBar bar ON (bar.FooId = foo.Id)
WHERE
foo.CreatedOn > DATEADD(DAY, -7, GETUTCDATE())
I managed to work around it by forcing the subquery to use another index (i.e. one that would be used when the subquery was executed without the parent query). In my case I switched to PK, which was meaningless for the query, but allowed the conditions from the subquery to be evaluated first.
SELECT bar.*
FROM
(SELECT * FROM TableFoo WITH (INDEX([PK_Id]) WHERE Deleted = 1) foo
JOIN TableBar bar ON (bar.FooId = foo.Id)
WHERE
foo.CreatedOn > DATEADD(DAY, -7, GETUTCDATE())
Filtering by the Deleted column was really simple and filtering the few results by CreatedOn afterwards was even easier. I was able to figure it out by comparing the Actual Execution Plan of the subquery and the parent query.
A more hacky solution (and not really recommended) is to force the subquery to get executed first by limiting the results using TOP, however this could lead to weird problems in the future if the results of the subquery exceed the limit (you could always set the limit to something ridiculous). Unfortunately TOP 100 PERCENT can't be used for this purpose since SQL Server just ignores it.
I have a query that has been running every day for a little over 2 years now and has typically taken less than 30 seconds to complete. All of a sudden, yesterday, the query started taking 3+ hours to complete and was using 100% CPU the entire time.
The SQL is:
SELECT
#id,
alpha.A, alpha.B, alpha.C,
beta.X, beta.Y, beta.Z,
alpha.P, alpha.Q
FROM
[DifferentDatabase].dbo.fnGetStuff(#id) beta
INNER JOIN vwSomeData alpha ON beta.id = alpha.id
alpha.id is a BIGINT type and beta.id is an INT type. dbo.fnGetStuff() is a simple SELECT statement with 2 INNER JOINs on tables in the same DB, using a WHERE id = #id. The function returns approximately 11000 results.
The view vwSomeData is a simple SELECT statement with two INNER JOINs that returns about 590000 results.
Both the view and the function will complete in less than 10 seconds when executed by themselves. Selecting the results of the function into a temporary table first and then joining on that makes the query finish in < 10 seconds.
How do I troubleshoot what's going on? I don't see any locks in the activity manager.
Look at the query plan. My guess is that there is a table scan or more in the execution plan. This will cause huge amounts of I/O for the few record you get in the result.
You could use the SQL Server Profiler tool to monitor what queries are running on SQL Server. It doesn't show the locks, but it can for instance also give you hints on how to improve your query by suggesting indexes.
If you've got a reasonably recent version of SQL Server Management Studio, it has a Database Tuning Adviser as well, under Tools. It takes a trace from the Profiler and makes some, sometimes highly useful, suggestions. Makes sure there's not too many queries - it takes a long time to build advice.
I'm not an expert on it, but have had some luck with it in the past.
Do you need to use a function? Can you re-write the entire thing into a stored procedure in which you pass in the #ID as a parameter.
Even if your table has indexes because you pass the #ID as a variable to the WHERE clause potentially greatly increasing the amount of time for the query to run.
The reason the indexes may not be used is because the Query Analyzer does not know the value of the variables when it selects an access method to perform the query. Because this is a batch file, only one pass is made of the Transact-SQL code, preventing the Query Optimizer from knowing what it needs to know in order to select an access method that uses the indexes.
You might want to consider an INDEX query hint if you cannot re-write the SQL.
it might also be possible, since this just started happening, that the INDEXes have become fragmented and might need to be rebuilt.
I've had similar problems with joining functions that return large datasets. I had to do what you've already suggested. Put the results in a temp table and join on that.
Look at the estimated plan, this will probably shed some light. Typically when query cost gets orders of magnitude more expensive it is because a loop or merge join is being used where a hash join is more appropriate. If you see a loop or merge join in the estimated plan, look at the number of rows it expects to process - is it far smaller than the number of rows you know will actually be in play? You can also specify a hint to use a hash join and see if it performs much better. If so, try updating statistics and see if it goes back to a hash join without a hint.
SELECT
#id,
alpha.A, alpha.B, alpha.C,
beta.X, beta.Y, beta.Z,
alpha.P, alpha.Q
FROM
[DifferentDatabase].dbo.fnGetStuff(#id) beta
INNER HASH JOIN vwSomeData alpha ON beta.id = alpha.id
-- having no idea what type of schema is in place and just trying to throw out ideas:
Like others have said... use Profiler and find the source of pain... but I'm thinking it is the function on the other database. Since that function might be a source of pain, have you thought about a little denormalization or anything on [DifferentDatabase]. I think you'll find a bit more scalability in joining to a more flattened table with indexes than a costly function.
Run this command:
SET SHOWPLAN_ALL ON
Then run your query. It will display the execution plan, look for a "SCAN" on an index or a table. That is most likely what is happening to your query now. If that is the case, try to figure out why it is not using indexes now (refresh statistics, etc)