# Find Customers Who Bought "A" and "B" But Not "C" (SQL Spackle)

• Comments posted to this topic are about the item Find Customers Who Bought "A" and "B" But Not "C" (SQL Spackle)

--Jeff Moden

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• @jeff

Did you compare the speed of this query against one where your first (Group By) From clause is a Select Distinct (sub) query?

Nice article. It builds nicely for the reader.

I love seeing the Except clause being introduced to the reader who, like me, cut our teeth on SQL92 and need to learn newer language features to be more productive.

• Another way to get the result would be to use Intersect and then combine it with Except. The distinct part is handled implicitly.

`--===== Find Customers that bought both "A" AND "B"`

` SELECT CustomerID`

` FROM #Purchase`

` WHERE ProductCode IN ('A')`

`INTERSECT`

` SELECT CustomerID`

` FROM #Purchase`

` WHERE ProductCode IN ('B')`

`EXCEPT`

`--===== Find Customers that bought "C".`

` SELECT CustomerID`

` FROM #Purchase`

` WHERE ProductCode IN ('C')`

`;`

• Wouldnt something like this work just as well?

`SELECT`

` CustomerId`

`FROM #Purchase`

`WHERE ProductCode IN ('A','B', 'C')`

`GROUP BY CustomerID`

`having sum(case when ProductCode = 'A' then 1 else 0 end) > 0`

` and sum(case when ProductCode = 'B' then 1 else 0 end) > 0`

` and sum(case when ProductCode = 'C' then 1 else 0 end) = 0`

/T

• tommyh (3/28/2012)

Wouldnt something like this work just as well?

`SELECT`

` CustomerId`

`FROM #Purchase`

`WHERE ProductCode IN ('A','B', 'C')`

`GROUP BY CustomerID`

`having sum(case when ProductCode = 'A' then 1 else 0 end) > 0`

` and sum(case when ProductCode = 'B' then 1 else 0 end) > 0`

` and sum(case when ProductCode = 'C' then 1 else 0 end) = 0`

/T

Yep, this is how i once implemented it! Cant remember the thread now.

Proved to elimate the EXCEPT part; also does a single scan on the table.

• Nice spackle Jeff, and great alternatives in the discussion!

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• OH yeah, Nice one Jeff. As always! Thanks a lot for taking time to teach us some of the tricks of the game. Thaks a lot 🙂

• Had a play with this and was very impressed - nice job.

I played around and added this index

`CREATE INDEX IX_#Purchase_ProductCode`

` ON #Purchase (`

` ProductCode)`

` INCLUDE (CustomerID)`

One concern I had was looking at the query plan, the EXCEPT does a clustered index scan. That may be a function of the small data set, but I am not sure.

My preference for these types of queries has always been to do an OUTER JOIN on the one we don't want selected and then say that we only want the ones that didn't match returned.

`SELECT a.CustomerID`

` FROM #Purchase a`

` LEFT OUTER JOIN #Purchase b`

` ON b.CustomerID = a.CustomerID`

` AND b.ProductCode IN ('C')`

` WHERE a.ProductCode IN ('A','B')`

` AND b.CustomerID IS NULL`

` GROUP BY a.CustomerID`

` HAVING COUNT(DISTINCT a.ProductCode) = 2`

Any thoughts?

• "Left Join Where Is Null" gets complicated to read/understand and is subject to cardinalities issues that will impact performance if the right set has many records for 1 record in the left hand side.

There is also this way, probably the closest to natural language.

`SelectDistinct`

`CustomerID`

`From#Purchase`

`WhereProductCode = 'A'`

`AndCustomerID In`

`(`

`SelectCustomerID`

`From#Purchase`

`WhereProductCode = 'B'`

`)`

`AndCustomerID Not In`

`(`

`SelectCustomerID`

`From#Purchase`

`WhereProductCode = 'C'`

`)`

I would be interested to have this table filled by 100,000+ rows of sample data and then compare execution plans and statistics of the proposed approaches.

Comparing syntax without an idea of the performance signature is a bit useless IMHO.

So here is another version of the initialization script from which the difference will be more blatant:

`--===== Conditionally drop the test table to make`

` -- reruns in SSMS easier.`

` IF OBJECT_ID('tempdb..#Purchase','U') IS NOT NULL`

` DROP TABLE #Purchase`

`;`

`--===== Create the test table`

` CREATE TABLE #Purchase`

` (`

` PurchaseID INT IDENTITY(1,1),`

` CustomerID INT,`

` ProductCode VARCHAR(1000)`

` PRIMARY KEY CLUSTERED (PurchaseID)`

` )`

`;`

`--===== Populate the test table with known data.`

` INSERT INTO #Purchase`

` (CustomerID, ProductCode)`

`------- Customer #1 precisely meets the criteria.`

` -- Bought 'A' and 'B' but not 'C'.`

` SELECT 1, 'A' UNION ALL`

` SELECT 1, 'B' UNION ALL`

`------- Customer #2 also meets the criteria.`

` -- Bought 'A' and 'B' and somthing else,`

` -- but not 'C'.`

` SELECT 2, 'A' UNION ALL`

` SELECT 2, 'B' UNION ALL`

` SELECT 2, 'D' UNION ALL`

`------- Customer #3 also meets the criteria.`

` -- Bought 'A' and 'B' and something else,`

` -- but not 'C'.`

` SELECT 3, 'A' UNION ALL`

` SELECT 3, 'B' UNION ALL`

` SELECT 3, 'D' UNION ALL`

` SELECT 3, 'A' UNION ALL`

` SELECT 3, 'D' UNION ALL`

`------- Customer #4 doesn't meet the criteria.`

` -- Bought 'A' and 'B' but also bought 'C'.`

` SELECT 4, 'A' UNION ALL`

` SELECT 4, 'B' UNION ALL`

` SELECT 4, 'C' UNION ALL`

`------- Customer #5 doesn't meet the criteria.`

` -- Bought 'A' and 'B' and something else,`

` -- but also bought 'C'.`

` SELECT 5, 'A' UNION ALL`

` SELECT 5, 'B' UNION ALL`

` SELECT 5, 'A' UNION ALL`

` SELECT 5, 'B' UNION ALL`

` SELECT 5, 'C' UNION ALL`

` SELECT 5, 'D' UNION ALL`

`------- Customer #6 doesn't meet the criteria.`

` -- Bought more than 1 of 'A' and something else`

` -- but not 'B'.`

` SELECT 6, 'A' UNION ALL`

` SELECT 6, 'A' UNION ALL`

` SELECT 6, 'D' UNION ALL`

` SELECT 6, 'E' UNION ALL`

`------- Customer #7 doesn't meet the criteria.`

` -- Bought more than 1 of 'B' and something else`

` -- but not 'A'.`

` SELECT 7, 'B' UNION ALL`

` SELECT 7, 'B' UNION ALL`

` SELECT 7, 'D' UNION ALL`

` SELECT 7, 'E'`

`go`

`declare @i int = 10;`

`while @i < 100000`

`begin`

`insert into #Purchase (CustomerID, ProductCode)`

`select CustomerID + @i, ProductCode + Left(ProductCode, 1)`

`From #Purchase`

`set @i = @i * 2`

`end`

Then turn on statistics or open your SQL profiler

`SET STATISTICS IO ON`

And now you're ready.

Then you will also need an index on ProductCode.

`Create Index IX_ProductCode On #Purchase (ProductCode) Include (CustomerID);`

• How about this? Although i agree query might get longer when there would be more than 3 items

` SELECT DISTINCT CustomerID`

` FROM #Purchase P`

` WHERE EXISTS (SELECT 1 FROM #Purchase P1`

`WHERE P.customerid = P1.customerid`

`AND P1.productcode = 'A'`

`)`

` AND EXISTS (SELECT 1 FROM #Purchase P2`

`WHERE P.customerid = P2.customerid`

`AND P2.productcode = 'B'`

`)`

` AND NOT EXISTS (SELECT 1 FROM #Purchase P3`

`WHERE P.customerid = P3.customerid`

`AND P3.productcode = 'C'`

`)`

• chintan.j.gandhi (3/29/2012)

How about this? Although i agree query might get longer when there would be more than 3 items

` SELECT DISTINCT CustomerID`

` FROM #Purchase P`

` WHERE EXISTS (SELECT 1 FROM #Purchase P1`

`WHERE P.customerid = P1.customerid`

`AND P1.productcode = 'A'`

`)`

` AND EXISTS (SELECT 1 FROM #Purchase P2`

`WHERE P.customerid = P2.customerid`

`AND P2.productcode = 'B'`

`)`

` AND NOT EXISTS (SELECT 1 FROM #Purchase P3`

`WHERE P.customerid = P3.customerid`

`AND P3.productcode = 'C'`

`)`

YOu can combine A and B code chunks and leave the NOT EXISTS as it, reducing it tp 2x slower than the others.

• Great article and discussion. Learned some new stuff, got some "food for thought" - nice one, peeps.

• You need to eliminate hash join and Index scan.

With this query you can do that using INTERSECT AND EXCEPT

`SELECT CustomerID`

`FROM #Purchase`

`WHERE ProductCode = 'A'`

`INTERSECT`

`SELECT CustomerID`

`FROM #Purchase`

`WHERE ProductCode = 'B'`

`EXCEPT`

`SELECT CustomerID`

`FROM #Purchase`

`WHERE ProductCode = 'C'`

Or, this one using CTE AND JOINS:

`;WITH CTE AS`

`(`

`SELECT CustomerID`

`FROM #Purchase`

`WHERE ProductCode = 'A'`

`GROUP BY CustomerID`

`)`

`,CTE2 AS`

`(`

`SELECT CustomerID`

`FROM #Purchase`

`WHERE ProductCode = 'B'`

`GROUP BY CustomerID`

`)`

`,CTE3 AS`

`(`

`SELECT CustomerID`

`FROM #Purchase`

`WHERE ProductCode = 'C'`

`GROUP BY CustomerID`

`)`

`select CTE.CustomerID from CTE`

`left join CTE3 ON`

`CTE.CustomerID = CTE3.CustomerID`

`where CTE.CustomerID in (SELECT CustomerID FROM CTE2)`

`AND CTE3.CustomerID IS NULL`

`GROUP BY CTE.CustomerID`

• Dalibor Margotic (3/29/2012)

You need to eliminate hash join and Index scan.

With this query you can do that using INTERSECT AND EXCEPT

...

Or, this one using CTE AND JOINS:

...

In the CTE and JOINS query, I would replace the IN clause with an EXISTS clause.

But that could be personal preference.

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My blog at https://sqlkover.com.
MCSE Business Intelligence - Microsoft Data Platform MVP

• Another great SQL Spackle, Jeff :w00t:

Koen Verbeeck (3/29/2012)

Dalibor Margotic (3/29/2012)

You need to eliminate hash join and Index scan.

With this query you can do that using INTERSECT AND EXCEPT

...

Or, this one using CTE AND JOINS:

...

In the CTE and JOINS query, I would replace the IN clause with an EXISTS clause.

But that could be personal preference.

One should certainly replace the IN by EXISTS or a left join adding a where clause containing the "outer-joined object key " is null

or at least compare their performance 😉

interesting series to read on this matter:

Johan

Learn to play, play to learn !

Dont drive faster than your guardian angel can fly ...
but keeping both feet on the ground wont get you anywhere :w00t:

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- How to post data/code to get the best help[/url]

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