Beginning Microsoft SQL Server 2008 ... - S3 Tech Training

Chapter 4: JOINs
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Let’s use this notion of being able to identify non-matching records to locate some of the missing records
from one of our earlier INNER JOINs. Remember these two queries, which you ran against Adventure-
Works2008?
SELECT pbe.BusinessEntityID, hre.JobTitle, pp.FirstName, pp.LastName
FROM Person.BusinessEntity pbe
INNER JOIN HumanResources.Employee hre
ON pbe.BusinessEntityID = hre.BusinessEntityID
INNER JOIN Person.Person pp
ON pbe.BusinessEntityID = pp.BusinessEntityID
WHERE hre.BusinessEntityID < 4
And . . .
SELECT COUNT(*)
FROM Person.BusinessEntity
The first was one of our queries where we explored the INNER JOIN. We discovered by running the
second query that the first had excluded (by design) some rows. Now let’s identify the excluded rows by
using an OUTER JOIN.
We know from our SELECT COUNT(*) query that our first query is missing thousands of records from
the BusinessEntity table. (It could conceivably be missing records from the Employee table, but we’re
not interested in that at the moment.) The implication is that there are records in the BusinessEntity
table that do not have corresponding Employee records. This makes sense, of course, because we know
that some of our persons are customers or vendor contacts. While our manager’s first question was about
all the employee contact information, it would be very common to ask just the opposite: “Which persons
are not employees?” That question is answered with the same result obtained by asking, “Which records
exist in Person that don’t have corresponding records in the Employee table?” The solution has the
same structure as the query to find special offers that aren’t associated with any products:
SELECT pp.BusinessEntityID, pp.FirstName, pp.LastName
FROM Person.Person pp
LEFT OUTER JOIN HumanResources.Employee hre
ON pp.BusinessEntityID = hre.BusinessEntityID
WHERE hre.BusinessEntityID IS NULL
Just that quickly we have a list of contacts that is somewhat cleaned up to contain just customers:
BusinessEntityID FirstName LastName
---------------- --------------------- --------------------------------
293 Catherine Abel
295 Kim Abercrombie
2170 Kim Abercrombie
…
…
2088 Judy Zugelder
12079 Jake Zukowski
2089 Michael Zwilling
(19682 row(s) affected)