As the title says, I am trying to INNER JOIN on columns that have different values/data types.
In one database table, let's call it Table A I want to do a select statement to get the values of a few columns (Subject, Name, Description, Date). Though I also want a relation name. The problem is however that the relation name (which is set in the relation table, Table B) is displayed in Table A as a string value (D0001001) - so not as a literal name.
To get the literal relation name there is a link with Table B that has an ID column 1001 - 1000~ and a relation 'literal' name column. So for example in table B ID 1001 matches company name MC DONALDS and in table A the RelationID is D0001001 (MC DONALDS).
Don't ask me why the RelationID in table A is with the weird D000 in front of it, I don't know either but it had some functionality.
So back to the problem. I want to get a few fields from table A but also the literal relation name from table B where it matches the table A relationID values.
So the question is, how can I INNER JOIN on these 2 different values/types? RelationID in table A is of string type (nvarchar to be precise) and in Table B the ID that matches the relation name is an Integer type.
I thought I could fix it by:
Do a LIKE statement in the query where the ID of table B (1001 integer) partly matches the RelationID of table A (D0001001 string). This however didn't work
do a REPLACE statement by replacing the RelationID 'D000' values by nothing: "". This would probably still require some sort of cast to integer for the table A value. Had some error here probably because of a syntax error.
What I have so far:
SELECT
TableA.subject, TableA.Name, TableA.Description, TableA.Date,
TableB.RelationName
INNER JOIN
TableB ON TableA.RelationID = TableB.ID
This returned a conversion that isn't possible (string / integer).
So then I tried:
SELECT
TableA.subject, TableA.Name, TableA.Description, TableA.Date,
TableB.RelationName
INNER JOIN
TableB ON TableB.ID LIKE '% TableA.RelationID %'
This didn't work either (EOF).
To make it a bit clearer my tables:
Table A
+------------+-----------+------------------+---------------------+-----------+
| RelationID | Subject | Description | Name | Date |
+------------+-----------+------------------+---------------------+-----------+
| D0001001 | Fast Food | Some description | Name of form filler | 13-3-2015 |
| D0001002 | Drinks | Some description | Name of form filler | 10-3-2015 |
| D0001003 | Cars | Some description | Name of form filler | 7-3-2015 |
+------------+-----------+------------------+---------------------+-----------+
Table B
+------+--------------+
| ID | RelationName |
+------+--------------+
| 1001 | MC DONALDS |
| 1002 | COCA COLA |
| 1003 | MERCEDES |
+------+--------------+
--> INNER joins in ID and RelationID
Any alternatives? Thanks in advance!
To escape from the convertion error remove the first characters in RelationID using Substring then convert the RelationID to INT then JOIN with the ID column in tableA
SELECT TableA.subject,
TableA.Name,
TableA.Description,
TableA.Date,
TableB.RelationName
FROM tableA
INNER JOIN TableB
ON CONVERT(INT, Substring(TableA.RelationID, 2, Len(TableA.RelationID))) = TableB.ID
Do a LIKE statement in the query where the ID of table B (1001
integer) partly matches the RelationID of table A (D0001001 string).
This however didnt worked.
Try the other way round:
SELECT TableA.Subject,
TableA.Name,
TableA.Description,
TableA.Date,
TableB.RelationName
FROM TableA
INNER JOIN TableB ON TableA.ID LIKE '%' + CAST(TableB.RelationID AS NVARCHAR(50)) + '%'
You could use LIKE in the INNER JOIN, but this gonna slow down performance of your Query, since LIKE sometimes prevents efficient index usage.
SELECT TableA.subject, TableA.Name, TableA.Description, TableA.Date, TableB.RelationName1
FROM TableA -- insert this line here
INNER JOIN TableB
ON TableB.ID LIKE '%TableA.RelationID%'
In order to make your second query run you need to insert the from clause. Unless this was a mistype on upload that should make it work, although it may not give you exactly what you want.
If the RelationalID column always has the same addition I would consider just cutting it out of the string. With something like:
ON TableB.ID = RIGHT(TableA.RelationalID,4)
SQL should do the conversion from string to integer for you doing an implicit cast in the comparison. If not just add the cast statement:
ON TableB.ID = CAST(RIGHT(TableA.RelationalID,4) AS INT)
Let's say I have two tables:
TABLE A
MessageID | Message
1 | Hello
2 | Bonjour
etc..
TABLE B
CommentID | MessageID | Comment
1 | 2 | This is a comment to someone saying Bonjour
2 | 2 | This is another comment to Bonjour
What I'm trying to do is run one query that pulls all the records from Table A ("the messages") along with a count of all the comments for each message from Table B.
The result would be:
Hello - 0 comments
Bonjour - 2 comments
I know this is probably some combination of using a join with a count(*), but I can't seem to hit on just the right syntax.
Any ideas?
For a message based approach:
SELECT message, count(commentID)
FROM tableA LEFT JOIN tableB ON tableA.messageID = tableB.messageID
GROUP BY message
You'll want a LEFT JOIN to include records in Table A that don't have any comments in Table B.
Give this a try:
SELECT a.MessageID, COUNT(*)
FROM TABLEA a
JOIN TABlEB b
ON b.MessageID = a.MessageID
GROUP BY a.MessageID
Just an addendum to what's already posted since, if you're using this for a scripting language, you'll likely need named columns for everything in the SELECT list:
SELECT tableA.messageID, message, count(commentID) AS commentCount
FROM tableA LEFT JOIN tableB ON tableA.messageID = tableB.messageID
GROUP BY message
Something like this:
SELECT MessageID, COUNT(CommentID)
FROM "TABLE B"
GROUP BY MessageID
If you need Message in addition to MessageID, you should be able to do something like this:
SELECT MessageID, MIN(Message), COUNT(CommentID)
FROM "TABLE A" LEFT JOIN "TABLE B" USING (MessageID)
GROUP BY MessageID
(Oracle syntax, probably same for MSSQL)
For example, I have the following tables:
animal
-----------------------
animal_id | animal_name
-----------------------
owners
-----------------------
owner_id | owner_name
-----------------------
owners_animals
--------------------
owner_id | animal_id
--------------------
I want to find the animals with no owners so I do the query:
select animal_name
from (select * from animals) as a
left join (select * from owners_animals) as o on (a.animal_id = o.animal_id)
where owner_id is NULL
Is this way of filtering data using a join acceptable and safe? With the same schema, is there a better alternative to get the same result?
Use a Not Exists clause:
Select animal_name
From animals as a
Where Not Exists(Select 1
From owners_animals oa
Where oa.animal_id = a.animal_id)
Also, put an index of owners_animals.animal_id to make this filter as fast as possible
Assuming there's nothing postgres specific going on (I'm not familiar with postgres) then the following is easier to follow.
Select *
From animals a
left outer join owners_animals oa On a.animal_id = oa.animal_id
Where oa.owner_id is NULL
Don't ever do, FROM (SELECT * FROM table), just do FROM table, same goes with the LEFT JOIN. What you wrote is just an overly verbose
SELECT animal_name
FROM animals
LEFT JOIN owners_animals
USING ( animal_id )
WHERE owner_id IS NULL;
With that said, I often like the NOT EXISTS() option, because it keeps the owner_id IS NULL fragment out.
USING (foo) is the same as foo = foo, on the joined tables, except only one of them will be in the result set.
What is the main purpose of using CROSS APPLY?
I have read (vaguely, through posts on the Internet) that cross apply can be more efficient when selecting over large data sets if you are partitioning. (Paging comes to mind)
I also know that CROSS APPLY doesn't require a UDF as the right-table.
In most INNER JOIN queries (one-to-many relationships), I could rewrite them to use CROSS APPLY, but they always give me equivalent execution plans.
Can anyone give me a good example of when CROSS APPLY makes a difference in those cases where INNER JOIN will work as well?
Edit:
Here's a trivial example, where the execution plans are exactly the same. (Show me one where they differ and where cross apply is faster/more efficient)
create table Company (
companyId int identity(1,1)
, companyName varchar(100)
, zipcode varchar(10)
, constraint PK_Company primary key (companyId)
)
GO
create table Person (
personId int identity(1,1)
, personName varchar(100)
, companyId int
, constraint FK_Person_CompanyId foreign key (companyId) references dbo.Company(companyId)
, constraint PK_Person primary key (personId)
)
GO
insert Company
select 'ABC Company', '19808' union
select 'XYZ Company', '08534' union
select '123 Company', '10016'
insert Person
select 'Alan', 1 union
select 'Bobby', 1 union
select 'Chris', 1 union
select 'Xavier', 2 union
select 'Yoshi', 2 union
select 'Zambrano', 2 union
select 'Player 1', 3 union
select 'Player 2', 3 union
select 'Player 3', 3
/* using CROSS APPLY */
select *
from Person p
cross apply (
select *
from Company c
where p.companyid = c.companyId
) Czip
/* the equivalent query using INNER JOIN */
select *
from Person p
inner join Company c on p.companyid = c.companyId
Can anyone give me a good example of when CROSS APPLY makes a difference in those cases where INNER JOIN will work as well?
See the article in my blog for detailed performance comparison:
INNER JOIN vs. CROSS APPLY
CROSS APPLY works better on things that have no simple JOIN condition.
This one selects 3 last records from t2 for each record from t1:
SELECT t1.*, t2o.*
FROM t1
CROSS APPLY
(
SELECT TOP 3 *
FROM t2
WHERE t2.t1_id = t1.id
ORDER BY
t2.rank DESC
) t2o
It cannot be easily formulated with an INNER JOIN condition.
You could probably do something like that using CTE's and window function:
WITH t2o AS
(
SELECT t2.*, ROW_NUMBER() OVER (PARTITION BY t1_id ORDER BY rank) AS rn
FROM t2
)
SELECT t1.*, t2o.*
FROM t1
INNER JOIN
t2o
ON t2o.t1_id = t1.id
AND t2o.rn <= 3
, but this is less readable and probably less efficient.
Update:
Just checked.
master is a table of about 20,000,000 records with a PRIMARY KEY on id.
This query:
WITH q AS
(
SELECT *, ROW_NUMBER() OVER (ORDER BY id) AS rn
FROM master
),
t AS
(
SELECT 1 AS id
UNION ALL
SELECT 2
)
SELECT *
FROM t
JOIN q
ON q.rn <= t.id
runs for almost 30 seconds, while this one:
WITH t AS
(
SELECT 1 AS id
UNION ALL
SELECT 2
)
SELECT *
FROM t
CROSS APPLY
(
SELECT TOP (t.id) m.*
FROM master m
ORDER BY
id
) q
is instant.
Consider you have two tables.
MASTER TABLE
x------x--------------------x
| Id | Name |
x------x--------------------x
| 1 | A |
| 2 | B |
| 3 | C |
x------x--------------------x
DETAILS TABLE
x------x--------------------x-------x
| Id | PERIOD | QTY |
x------x--------------------x-------x
| 1 | 2014-01-13 | 10 |
| 1 | 2014-01-11 | 15 |
| 1 | 2014-01-12 | 20 |
| 2 | 2014-01-06 | 30 |
| 2 | 2014-01-08 | 40 |
x------x--------------------x-------x
There are many situations where we need to replace INNER JOIN with CROSS APPLY.
1. Join two tables based on TOP n results
Consider if we need to select Id and Name from Master and last two dates for each Id from Details table.
SELECT M.ID,M.NAME,D.PERIOD,D.QTY
FROM MASTER M
INNER JOIN
(
SELECT TOP 2 ID, PERIOD,QTY
FROM DETAILS D
ORDER BY CAST(PERIOD AS DATE)DESC
)D
ON M.ID=D.ID
SQL FIDDLE
The above query generates the following result.
x------x---------x--------------x-------x
| Id | Name | PERIOD | QTY |
x------x---------x--------------x-------x
| 1 | A | 2014-01-13 | 10 |
| 1 | A | 2014-01-12 | 20 |
x------x---------x--------------x-------x
See, it generated results for last two dates with last two date's Id and then joined these records only in the outer query on Id, which is wrong. This should be returning both Ids 1 and 2 but it returned only 1 because 1 has the last two dates. To accomplish this, we need to use CROSS APPLY.
SELECT M.ID,M.NAME,D.PERIOD,D.QTY
FROM MASTER M
CROSS APPLY
(
SELECT TOP 2 ID, PERIOD,QTY
FROM DETAILS D
WHERE M.ID=D.ID
ORDER BY CAST(PERIOD AS DATE)DESC
)D
SQL FIDDLE
and forms the following result.
x------x---------x--------------x-------x
| Id | Name | PERIOD | QTY |
x------x---------x--------------x-------x
| 1 | A | 2014-01-13 | 10 |
| 1 | A | 2014-01-12 | 20 |
| 2 | B | 2014-01-08 | 40 |
| 2 | B | 2014-01-06 | 30 |
x------x---------x--------------x-------x
Here's how it works. The query inside CROSS APPLY can reference the outer table, where INNER JOIN cannot do this (it throws compile error). When finding the last two dates, joining is done inside CROSS APPLY i.e., WHERE M.ID=D.ID.
2. When we need INNER JOIN functionality using functions.
CROSS APPLY can be used as a replacement with INNER JOIN when we need to get result from Master table and a function.
SELECT M.ID,M.NAME,C.PERIOD,C.QTY
FROM MASTER M
CROSS APPLY dbo.FnGetQty(M.ID) C
And here is the function
CREATE FUNCTION FnGetQty
(
#Id INT
)
RETURNS TABLE
AS
RETURN
(
SELECT ID,PERIOD,QTY
FROM DETAILS
WHERE ID=#Id
)
SQL FIDDLE
which generated the following result
x------x---------x--------------x-------x
| Id | Name | PERIOD | QTY |
x------x---------x--------------x-------x
| 1 | A | 2014-01-13 | 10 |
| 1 | A | 2014-01-11 | 15 |
| 1 | A | 2014-01-12 | 20 |
| 2 | B | 2014-01-06 | 30 |
| 2 | B | 2014-01-08 | 40 |
x------x---------x--------------x-------x
ADDITIONAL ADVANTAGE OF CROSS APPLY
APPLY can be used as a replacement for UNPIVOT. Either CROSS APPLY or OUTER APPLY can be used here, which are interchangeable.
Consider you have the below table(named MYTABLE).
x------x-------------x--------------x
| Id | FROMDATE | TODATE |
x------x-------------x--------------x
| 1 | 2014-01-11 | 2014-01-13 |
| 1 | 2014-02-23 | 2014-02-27 |
| 2 | 2014-05-06 | 2014-05-30 |
| 3 | NULL | NULL |
x------x-------------x--------------x
The query is below.
SELECT DISTINCT ID,DATES
FROM MYTABLE
CROSS APPLY(VALUES (FROMDATE),(TODATE))
COLUMNNAMES(DATES)
SQL FIDDLE
which brings you the result
x------x-------------x
| Id | DATES |
x------x-------------x
| 1 | 2014-01-11 |
| 1 | 2014-01-13 |
| 1 | 2014-02-23 |
| 1 | 2014-02-27 |
| 2 | 2014-05-06 |
| 2 | 2014-05-30 |
| 3 | NULL |
x------x-------------x
cross apply sometimes enables you to do things that you cannot do with inner join.
Example (a syntax error):
select F.* from sys.objects O
inner join dbo.myTableFun(O.name) F
on F.schema_id= O.schema_id
This is a syntax error, because, when used with inner join, table functions can only take variables or constants as parameters. (I.e., the table function parameter cannot depend on another table's column.)
However:
select F.* from sys.objects O
cross apply ( select * from dbo.myTableFun(O.name) ) F
where F.schema_id= O.schema_id
This is legal.
Edit:
Or alternatively, shorter syntax: (by ErikE)
select F.* from sys.objects O
cross apply dbo.myTableFun(O.name) F
where F.schema_id= O.schema_id
Edit:
Note:
Informix 12.10 xC2+ has Lateral Derived Tables and Postgresql (9.3+) has Lateral Subqueries which can be used to a similar effect.
It seems to me that CROSS APPLY can fill a certain gap when working with calculated fields in complex/nested queries, and make them simpler and more readable.
Simple example: you have a DoB and you want to present multiple age-related fields that will also rely on other data sources (such as employment), like Age, AgeGroup, AgeAtHiring, MinimumRetirementDate, etc. for use in your end-user application (Excel PivotTables, for example).
Options are limited and rarely elegant:
JOIN subqueries cannot introduce new values in the dataset based on data in the parent query (it must stand on its own).
UDFs are neat, but slow as they tend to prevent parallel operations. And being a separate entity can be a good (less code) or a bad (where is the code) thing.
Junction tables. Sometimes they can work, but soon enough you're joining subqueries with tons of UNIONs. Big mess.
Create yet another single-purpose view, assuming your calculations don't require data obtained mid-way through your main query.
Intermediary tables. Yes... that usually works, and often a good option as they can be indexed and fast, but performance can also drop due to to UPDATE statements not being parallel and not allowing to cascade formulas (reuse results) to update several fields within the same statement. And sometimes you'd just prefer to do things in one pass.
Nesting queries. Yes at any point you can put parenthesis on your entire query and use it as a subquery upon which you can manipulate source data and calculated fields alike. But you can only do this so much before it gets ugly. Very ugly.
Repeating code. What is the greatest value of 3 long (CASE...ELSE...END) statements? That's gonna be readable!
Tell your clients to calculate the damn things themselves.
Did I miss something? Probably, so feel free to comment. But hey, CROSS APPLY is like a godsend in such situations: you just add a simple CROSS APPLY (select tbl.value + 1 as someFormula) as crossTbl and voilà! Your new field is now ready for use practically like it had always been there in your source data.
Values introduced through CROSS APPLY can...
be used to create one or multiple calculated fields without adding performance, complexity or readability issues to the mix
like with JOINs, several subsequent CROSS APPLY statements can refer to themselves: CROSS APPLY (select crossTbl.someFormula + 1 as someMoreFormula) as crossTbl2
you can use values introduced by a CROSS APPLY in subsequent JOIN conditions
As a bonus, there's the Table-valued function aspect
Dang, there's nothing they can't do!
This has already been answered very well technically, but let me give a concrete example of how it's extremely useful:
Lets say you have two tables, Customer and Order. Customers have many Orders.
I want to create a view that gives me details about customers, and the most recent order they've made. With just JOINS, this would require some self-joins and aggregation which isn't pretty. But with Cross Apply, its super easy:
SELECT *
FROM Customer
CROSS APPLY (
SELECT TOP 1 *
FROM Order
WHERE Order.CustomerId = Customer.CustomerId
ORDER BY OrderDate DESC
) T
Cross apply works well with an XML field as well. If you wish to select node values in combination with other fields.
For example, if you have a table containing some xml
<root>
<subnode1>
<some_node value="1" />
<some_node value="2" />
<some_node value="3" />
<some_node value="4" />
</subnode1>
</root>
Using the query
SELECT
id as [xt_id]
,xmlfield.value('(/root/#attribute)[1]', 'varchar(50)') root_attribute_value
,node_attribute_value = [some_node].value('#value', 'int')
,lt.lt_name
FROM dbo.table_with_xml xt
CROSS APPLY xmlfield.nodes('/root/subnode1/some_node') as g ([some_node])
LEFT OUTER JOIN dbo.lookup_table lt
ON [some_node].value('#value', 'int') = lt.lt_id
Will return a result
xt_id root_attribute_value node_attribute_value lt_name
----------------------------------------------------------------------
1 test1 1 Benefits
1 test1 4 FINRPTCOMPANY
Cross apply can be used to replace subquery's where you need a column of the subquery
subquery
select * from person p where
p.companyId in(select c.companyId from company c where c.companyname like '%yyy%')
here i won't be able to select the columns of company table
so, using cross apply
select P.*,T.CompanyName
from Person p
cross apply (
select *
from Company C
where p.companyid = c.companyId and c.CompanyName like '%yyy%'
) T
Here's a brief tutorial that can be saved in a .sql file and executed in SSMS that I wrote for myself to quickly refresh my memory on how CROSS APPLY works and when to use it:
-- Here's the key to understanding CROSS APPLY: despite the totally different name, think of it as being like an advanced 'basic join'.
-- A 'basic join' gives the Cartesian product of the rows in the tables on both sides of the join: all rows on the left joined with all rows on the right.
-- The formal name of this join in SQL is a CROSS JOIN. You now start to understand why they named the operator CROSS APPLY.
-- Given the following (very) simple tables and data:
CREATE TABLE #TempStrings ([SomeString] [nvarchar](10) NOT NULL);
CREATE TABLE #TempNumbers ([SomeNumber] [int] NOT NULL);
CREATE TABLE #TempNumbers2 ([SomeNumber] [int] NOT NULL);
INSERT INTO #TempStrings VALUES ('111'); INSERT INTO #TempStrings VALUES ('222');
INSERT INTO #TempNumbers VALUES (111); INSERT INTO #TempNumbers VALUES (222);
INSERT INTO #TempNumbers2 VALUES (111); INSERT INTO #TempNumbers2 VALUES (222); INSERT INTO #TempNumbers2 VALUES (222);
-- Basic join is like CROSS APPLY; 2 rows on each side gives us an output of 4 rows, but 2 rows on the left and 0 on the right gives us an output of 0 rows:
SELECT
st.SomeString, nbr.SomeNumber
FROM -- Basic join ('CROSS JOIN')
#TempStrings st, #TempNumbers nbr
-- Note: this also works:
--#TempStrings st CROSS JOIN #TempNumbers nbr
-- Basic join can be used to achieve the functionality of INNER JOIN by first generating all row combinations and then whittling them down with a WHERE clause:
SELECT
st.SomeString, nbr.SomeNumber
FROM -- Basic join ('CROSS JOIN')
#TempStrings st, #TempNumbers nbr
WHERE
st.SomeString = nbr.SomeNumber
-- However, for increased readability, the SQL standard introduced the INNER JOIN ... ON syntax for increased clarity; it brings the columns that two tables are
-- being joined on next to the JOIN clause, rather than having them later on in the WHERE clause. When multiple tables are being joined together, this makes it
-- much easier to read which columns are being joined on which tables; but make no mistake, the following syntax is *semantically identical* to the above syntax:
SELECT
st.SomeString, nbr.SomeNumber
FROM -- Inner join
#TempStrings st INNER JOIN #TempNumbers nbr ON st.SomeString = nbr.SomeNumber
-- Because CROSS APPLY is generally used with a subquery, the subquery's WHERE clause will appear next to the join clause (CROSS APPLY), much like the aforementioned
-- 'ON' keyword appears next to the INNER JOIN clause. In this sense, then, CROSS APPLY combined with a subquery that has a WHERE clause is like an INNER JOIN with
-- an ON keyword, but more powerful because it can be used with subqueries (or table-valued functions, where said WHERE clause can be hidden inside the function).
SELECT
st.SomeString, nbr.SomeNumber
FROM
#TempStrings st CROSS APPLY (SELECT * FROM #TempNumbers tempNbr WHERE st.SomeString = tempNbr.SomeNumber) nbr
-- CROSS APPLY joins in the same way as a CROSS JOIN, but what is joined can be a subquery or table-valued function. You'll still get 0 rows of output if
-- there are 0 rows on either side, and in this sense it's like an INNER JOIN:
SELECT
st.SomeString, nbr.SomeNumber
FROM
#TempStrings st CROSS APPLY (SELECT * FROM #TempNumbers tempNbr WHERE 1 = 2) nbr
-- OUTER APPLY is like CROSS APPLY, except that if one side of the join has 0 rows, you'll get the values of the side that has rows, with NULL values for
-- the other side's columns. In this sense it's like a FULL OUTER JOIN:
SELECT
st.SomeString, nbr.SomeNumber
FROM
#TempStrings st OUTER APPLY (SELECT * FROM #TempNumbers tempNbr WHERE 1 = 2) nbr
-- One thing CROSS APPLY makes it easy to do is to use a subquery where you would usually have to use GROUP BY with aggregate functions in the SELECT list.
-- In the following example, we can get an aggregate of string values from a second table based on matching one of its columns with a value from the first
-- table - something that would have had to be done in the ON clause of the LEFT JOIN - but because we're now using a subquery thanks to CROSS APPLY, we
-- don't need to worry about GROUP BY in the main query and so we don't have to put all the SELECT values inside an aggregate function like MIN().
SELECT
st.SomeString, nbr.SomeNumbers
FROM
#TempStrings st CROSS APPLY (SELECT SomeNumbers = STRING_AGG(tempNbr.SomeNumber, ', ') FROM #TempNumbers2 tempNbr WHERE st.SomeString = tempNbr.SomeNumber) nbr
-- ^ First the subquery is whittled down with the WHERE clause, then the aggregate function is applied with no GROUP BY clause; this means all rows are
-- grouped into one, and the aggregate function aggregates them all, in this case building a comma-delimited string containing their values.
DROP TABLE #TempStrings;
DROP TABLE #TempNumbers;
DROP TABLE #TempNumbers2;
I guess it should be readability ;)
CROSS APPLY will be somewhat unique for people reading to tell them that a UDF is being used which will be applied to each row from the table on the left.
Ofcourse, there are other limitations where a CROSS APPLY is better used than JOIN which other friends have posted above.
The essence of the APPLY operator is to allow correlation between left and right side of the operator in the FROM clause.
In contrast to JOIN, the correlation between inputs is not allowed.
Speaking about correlation in APPLY operator, I mean on the right hand side we can put:
a derived table - as a correlated subquery with an alias
a table valued function - a conceptual view with parameters, where the parameter can refer to the left side
Both can return multiple columns and rows.
Here is an article that explains it all, with their performance difference and usage over JOINS.
SQL Server CROSS APPLY and OUTER APPLY over JOINS
As suggested in this article, there is no performance difference between them for normal join operations (INNER AND CROSS).
The usage difference arrives when you have to do a query like this:
CREATE FUNCTION dbo.fn_GetAllEmployeeOfADepartment(#DeptID AS INT)
RETURNS TABLE
AS
RETURN
(
SELECT * FROM Employee E
WHERE E.DepartmentID = #DeptID
)
GO
SELECT * FROM Department D
CROSS APPLY dbo.fn_GetAllEmployeeOfADepartment(D.DepartmentID)
That is, when you have to relate with function. This cannot be done using INNER JOIN, which would give you the error "The multi-part identifier "D.DepartmentID" could not be bound." Here the value is passed to the function as each row is read. Sounds cool to me. :)
Well I am not sure if this qualifies as a reason to use Cross Apply versus Inner Join, but this query was answered for me in a Forum Post using Cross Apply, so I am not sure if there is an equalivent method using Inner Join:
Create PROCEDURE [dbo].[Message_FindHighestMatches]
-- Declare the Topical Neighborhood
#TopicalNeighborhood nchar(255)
AS
BEGIN
-- SET NOCOUNT ON added to prevent extra result sets from
-- interfering with SELECT statements.
SET NOCOUNT ON
Create table #temp
(
MessageID int,
Subjects nchar(255),
SubjectsCount int
)
Insert into #temp Select MessageID, Subjects, SubjectsCount From Message
Select Top 20 MessageID, Subjects, SubjectsCount,
(t.cnt * 100)/t3.inputvalues as MatchPercentage
From #temp
cross apply (select count(*) as cnt from dbo.Split(Subjects,',') as t1
join dbo.Split(#TopicalNeighborhood,',') as t2
on t1.value = t2.value) as t
cross apply (select count(*) as inputValues from dbo.Split(#TopicalNeighborhood,',')) as t3
Order By MatchPercentage desc
drop table #temp
END
This is perhaps an old question, but I still love the power of CROSS APPLY to simplify the re-use of logic and to provide a "chaining" mechanism for results.
I've provided a SQL Fiddle below which shows a simple example of how you can use CROSS APPLY to perform complex logical operations on your data set without things getting at all messy. It's not hard to extrapolate from here more complex calculations.
http://sqlfiddle.com/#!3/23862/2
While most queries which employ CROSS APPLY can be rewritten using an INNER JOIN, CROSS APPLY can yield better execution plan and better performance, since it can limit the set being joined yet before the join occurs.
Stolen from Here
We use CROSS APPLY to update a table with JSON from another (update request) table -- joins won't work for this as we use OPENJSON, to read the content of the JSON, and OPENJSON is a "table-valued function".
I was going to put a simplified version of one of our UPDATE commands here as a example but, even simplified, it is rather large and overly complex for an example. So this much simplied "sketch" of just part of the command will have to suffice:
SELECT
r.UserRequestId,
j.xxxx AS xxxx,
FROM RequestTable as r WITH (NOLOCK)
CROSS APPLY
OPENJSON(r.JSON, '$.requesttype.recordtype')
WITH(
r.userrequestid nvarchar(50) '$.userrequestid',
j.xxx nvarchar(20) '$.xxx
)j
WHERE r.Id > #MaxRequestId
and ... etc. ....