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 voilĂ ! 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. ....
Related
I'm working on a table and need to get specific output with additional columns.
In the first column of the table I have usernames and second column has email addresses. Users can have one or two email addresses. so column one will have duplicate values. I need return the data on the table using a SQL query with with three columns: username, first email address and second email address.
Could please assist with the query?
Example:
| username1 | email1#test.com |
| username1 | email2#test.com |
Output:
| username1 | email1#test.com | email2#test.com |
Firstly welcome to Stackoverflow.
Assuming you are on at least SQL Server 2008, you can achieve this using row_number() and a self-join
To show how this works, I give a simple example:
declare #test table(username varchar(50), email varchar(50))
insert INTO #test values('username1', 'email1#test.com')
insert INTO #test values('username1', 'email2#test.com')
insert INTO #test values('username2', 'email3#test.com')
;with cte as
(SELECT username, email, row_number() OVER (PARTITION BY username order by username) rn
from #test)
SELECT t1.username, t1.email as email1, t2.email as email2
FROM cte t1
LEFT JOIN cte t2 ON t1.username = t2.username AND t2.rn = 2
WHERE t1.rn = 1
By way of explanation, row_number() gives a unique number for each line, determined by the ORDER BY within the OVER. Adding PARTITION BY resets the row count for each new value specified by the PARTITION. In this case PARTITION BY and ORDER BY are the same field, but they need not be. Putting this all in a common table expression, then allows you to do a self-join (in this case an outer self-join) to pick up both those users with two emails (where rn will be 1 and 2) and those with just one. The left side of the join contains those with rn 1 (which will be all users), whilst the right side picks up the 2s.
Hope this helps
Jonathan
I have the following three tables that I am trying to join together and create an overview of all desktops and whoever has one assigned to their UserID if any.
dbo.Users
ID Name Lastname JobTitle
118 Ryan Doe Field Engineer
119 Jessica Braun Technical Consultant
120 Daniel Sous Web developer
121 Amy Amyson Intern
.. etc
dbo.LightDesktops
ID Model MACAddress UserID
1 HP1234 AA:AA:AA:AA:AA:AA 118
2 HP1234 BB:BB:BB:BB:BB:BB 121
3 HP1234 AA:BB:BB:AA:BB:AA NULL
4 HP1234 BB:AA:BB:AA:AA:BB 124
dbo.MediumDesktops
ID Model MACAddress UserID
1 HP12PRO AA:AB:AA:BB:AA:BA 132
2 HP12PRO BB:BA:AB:BA:BB:AA 119
3 HP12PRO AA:BA:BA:AB:AA:BA 123
4 HP12PRO BB:BB:BB:AB:BA:BB 241
I managed to figure out how to do it per type of desktop, for example LightDesktops:
SELECT * FROM LightDesktops LEFT OUTER JOIN Users ON LightDesktops.UserID = Users.UserID
That will show me a nice overview of the light desktops with their information as well as whoever has one assigned to if any.
If I'd like to have an overview of the light desktops that are not used and therefore in stock I can do
SELECT * FROM LightDesktops LEFT OUTER JOIN Users ON LightDesktops.UserID = Users.UserID WHERE LightDesktops.UserID IS NULL
How can I accomplish the same results, but for both tables containing information of our desktops? I tried to use an UNION but returned me lots of duplicate values.
Using UNION to bring the light and medium desktops tables together as a single dataset shouldn't give you duplicates unless the tables contain duplicate values in rows accross all columns in your SELECT clauses and you use UNION ALL. If you know your tables have unique values use UNION ALL to give a performance boost.
I would combine the two tables in a common table expression (cte) and then join the resultant table with a LEFT OUTER JOIN to your user table which can also be filtered to find entries where there is no match WHERE [user].[UserID] IS NULL, NB, that would return orphaned rows in your desktops tables where the user has been deleted; alternatively drop the left outer join and use WHERE [desktop].[UserID] IS NULL to return only dekstops without assiged users.
You could try the following code;
WITH cte_Desktop AS
(
SELECT
[ID] as [DesktopID],
'Light Desktop' as [DekstopType],
[Model],
[MACAddress],
[UserID]
FROM [dbo].[LightDesktops]
UNION
SELECT
[ID],
'Medium Desktop',
[Model],
[MACAddress],
[UserID]
FROM [dbo].[MediumDesktops]
)
SELECT
[desktop].*
FROM cte_Desktop AS [desktop]
LEFT OUTER JOIN [dbo].[Users] AS [user]
on [user].[UserID] = [desktop].[UserID]
WHERE [user].[UserID] IS NULL
Use Full join to get report of all users present. it will give you the full report. On top of this results Query for the userid is NULL
SELECT U.ID userid,
U.NAME,
LD.USERID LD_USERID,
LD.MODEL LIGHT_MODEL,
LD.MACADDRESS LIGHT_MAC,
LM.USERID LM_USERID,
LM.MODEL MEDIUM_MODEL,
LM.MACADDRESS MEDIUM_MAC
FROM #USERS U
FULL OUTER JOIN #LIGHTD LD
ON (U.ID = LD.USERID )
FULL OUTER JOIN #LIGHTM LM
ON (LM.USERID = U.ID)
While you can achieve what you need in a single query, it may be more supportable to break the table union out into a view which allows that logic to be reused across multiple queries and also allows for easier refactoring at a later date.
Nod to destination-data for reminding me of this.
View
CREATE VIEW [dbo].[Desktops] AS
(
SELECT
[ID] as [DesktopID],
'Light Desktop' as [DekstopType],
[Model],
[MACAddress],
[UserID]
FROM [dbo].[LightDesktops]
UNION
SELECT
[ID],
'Medium Desktop',
[Model],
[MACAddress],
[UserID]
FROM [dbo].[MediumDesktops]
)
Query
SELECT
[desktop].*
FROM [dbo].[Desktops] AS [desktop]
LEFT OUTER JOIN [dbo].[Users] AS [user]
on [user].[UserID] = [desktop].[UserID]
WHERE [user].[UserID] IS NULL
Try
WITH all as (
select model , userid from LightDesktops
union
select model , userid from MediumDesktops
)
select * FROM all where UserId IS NULL
I have pictures in a database which I now need to extract. The image column is of type varbinary(max).
I tried several examples using either a JOIN or subquery to no avail. The query developed would work if it wasn't for the image. Using DISTINCT and MAX(date) still can't eliminnate the older image. Many IDs have multiple pictures. Using the Max(Date) would extract the most recent date, but adding in the picture eliminates all the filtering.
The query looks like this:
SELECT DISTINCT ID, Image, DateModified, GETDate()
FROM images
WHERE
TYPE = 'B'
ID Image DateMod Type
1 0x789 01-02-2014 B
1 0x791 11-12-2015 B <-- this is a tgt record
2 0x675 12-01-2015 A
5 0x324 06-26-2015 B <-- this is a tgt record
If I use MAX(DateModified), that forces a GROUP BY and it still doesn't eliminate the older images. I need the newest Type 'B' image for each ID. I am working on SQL Server 2012.
What I need for output is
image, ID, DateModified, TodaysDate (GetDate)
Pretty sure you want something like this.
with SortedResults as
(
select ID
, Image
, DateMod
, Type
, ROW_NUMBER() over (partition by ID order by DateMod desc) as RowNum
from images
where Type = 'B'
)
select ID
, Image
, DateMod
, GetDate()
from SortedResults
where RowNum = 1
Try following query
SELECT
I.[Image],
I.DateMod,
GetDate()
FROM
(
SELECT
ID,
MAX(DateModified) AS DateModified
FROM
images
WHERE
[TYPE] = 'B'
GROUP BY
ID
) A INNER JOIN
images I ON A.ID = I.ID AND A.DateModified = I.DateModified
The problem is likely twofold:
1) You are confusing the logical order of the clauses used in SQL Server.
2) Your DISTINCT is the culprit.
I suggest you study and memorize the Logical order of SQL Clauses so that you understand logically how SQL Server is reading your prescribed query. For simplicity, start with the Classic list, which is used in many places.
Classic Complete
FROM | FROM
WHERE | ON
GROUP BY | JOIN
HAVING | WHERE
SELECT | GROUP BY
ORDER BY | WITH CUBE, WITH ROLLUP
| HAVING
| SELECT
| DISTINCT
| ORDER BY
| TOP
Already we can see why your query is returning the results wrong, since SQL Server is not smashing the column sets together but rather smashing distinct rows across your columns.
Your example list:
ID Image DateMod Type
1 0x789 01-02-2014 B
1 0x791 11-12-2015 B <-- this is a tgt record
2 0x675 12-01-2015 A
5 0x324 06-26-2015 B <-- this is a tgt record
Has unique rows and therefore returns all of the records. Clearly, DISTINCT is the problem.
One solution is to keep your predicate the same and use the GROUP BY clause to smash sets of columns and use the MAX() aggregate function to return the largest value.
;WITH C AS
( SELECT ID
, MAX(DateMod) AS DateModified
, CONVERT(VARCHAR(10), GETDATE(), 110) AS [Current_Time]
FROM #Images
WHERE Type = 'B'
GROUP BY ID, Type)
SELECT C.ID, B.Image, C.DateModified, C.[Current_Time]
FROM C
LEFT OUTER JOIN (SELECT ID, DateMod, Image FROM #Images) B ON C.ID = B.ID
AND C.DateModified = B.DateMod
-- results
ID Image DateModified Current_Time
1 0x3078373931 11-12-2015 07-16-2016
5 0x3078333234 06-26-2015 07-16-2016
I am attempting to create a query that pulls information from two other tables, however I only know which table to pull from based on a column in another table. I'm currently looking into doing this using a stored procedure (e.g. build the query and then run it) but I wanted to know if there is a better way to do this, or if I could accomplish it in a single query.
In terms of the connections, ID's are unique accross the entire database, so no two ID's will overlap. However I do not know which subtable the ID relates. I am able to find this by pulling in an unrelated table that happens to have the information (call it the Object Table). One of the columns will give me the table name for the information (in my example below, Person). I have drafted a simple example below. Can you see any way I could accomplish this in a single query? Something like this is what I am aiming for but I am starting to think its not possible.
SELECT * FROM base_table
LEFT JOIN object ON object.id = base_table.role
LEFT JOIN [object.type] tmp ON tmp.entity_id = base_table.entity_id
id | role | entity_id (Base Table)
---------------------
1 | 101 | 1000
id | type (Objects Table)
------------
101| person
entity_id | name | etc.. (Person Table)
------------------------
1000 | Bob | ...
I also expect unions might be a possible solution - but other then just joining all the possible tables and parsing the columns to match up properly (which it could be as many as 20 tables) I'd rather not. This solution is also a bit of a nusience since the columns don't always match in a good way (e.g. the Person table doesn't have similar columns to the Address table)
I don't think the left join idea is that bad if you just ignore object type.
Since each ID is unique you don't need to look at type at all if you use coalesce. So to use #TT model as an example:
SELECT bt.*,
COALESCE(P.f1, L.f1, C.f1) AS f1,
-- ...,
COALESCE(P.fn, L.fn, C.fn) AS fn
FROM
base_table AS bt
LEFT JOIN Person AS P ON P.entity_id = bt.entity_id
LEFT JOIN [Legal Person] AS L ON L.entity_id = bt.entity_id
LEFT JOIN Counterpart AS C ON C.entity_id = bt.entity_id
Depending on your data size and indexes this might perform faster or the same as TT's example -- remember there is only 1 select with N joins while TT's has N selects, 2N joins. It really depends on your data.
If there is some field (fz) that does not show up in all types then you just don't inlcude that in the coalesce clause.
I think this style might be easier to maintain and understand and will be the same or faster as TT code.
What you probably want to do is the following: for each possible detail-table (ie the possible values in [object.value]), write a query that only links with that one detail-table and have a WHERE clause to restrict to the proper entities. Then do a UNION ALL for all those queries.
Say you have Person, Legal Person and Counterpart as possible values in [object.type]. Suppose the detail-tables have the same names. You can write:
SELECT
bt.*,
dt.f1,
-- ...,
dt.fn
FROM
base_table AS bt
INNER JOIN object AS o ON o.id = bt.role
INNER JOIN Person AS dt ON dt.entity_id = bt.entity_id
WHERE
o.type='Person'
UNION ALL
SELECT
bt.*,
dt.f1,
-- ...,
dt.fn
FROM
base_table AS bt
INNER JOIN object AS o ON o.id = bt.role
INNER JOIN [Legal Person] AS dt ON dt.entity_id = bt.entity_id
WHERE
o.type='Legal Person'
UNION ALL
SELECT
bt.*,
dt.f1,
-- ...,
dt.fn
FROM
base_table AS bt
INNER JOIN object AS o ON o.id = bt.role
INNER JOIN Counterpart AS dt ON dt.entity_id = bt.entity_id
WHERE
o.type='Counterpart'
I want to learn how to combine two db tables which have no fields in common. I've checked UNION but MSDN says :
The following are basic rules for combining the result sets of two queries by using UNION:
The number and the order of the columns must be the same in all queries.
The data types must be compatible.
But I have no fields in common at all. All I want is to combine them in one table like a view.
So what should I do?
There are a number of ways to do this, depending on what you really want. With no common columns, you need to decide whether you want to introduce a common column or get the product.
Let's say you have the two tables:
parts: custs:
+----+----------+ +-----+------+
| id | desc | | id | name |
+----+----------+ +-----+------+
| 1 | Sprocket | | 100 | Bob |
| 2 | Flange | | 101 | Paul |
+----+----------+ +-----+------+
Forget the actual columns since you'd most likely have a customer/order/part relationship in this case; I've just used those columns to illustrate the ways to do it.
A cartesian product will match every row in the first table with every row in the second:
> select * from parts, custs;
id desc id name
-- ---- --- ----
1 Sprocket 101 Bob
1 Sprocket 102 Paul
2 Flange 101 Bob
2 Flange 102 Paul
That's probably not what you want since 1000 parts and 100 customers would result in 100,000 rows with lots of duplicated information.
Alternatively, you can use a union to just output the data, though not side-by-side (you'll need to make sure column types are compatible between the two selects, either by making the table columns compatible or coercing them in the select):
> select id as pid, desc, null as cid, null as name from parts
union
select null as pid, null as desc, id as cid, name from custs;
pid desc cid name
--- ---- --- ----
101 Bob
102 Paul
1 Sprocket
2 Flange
In some databases, you can use a rowid/rownum column or pseudo-column to match records side-by-side, such as:
id desc id name
-- ---- --- ----
1 Sprocket 101 Bob
2 Flange 101 Bob
The code would be something like:
select a.id, a.desc, b.id, b.name
from parts a, custs b
where a.rownum = b.rownum;
It's still like a cartesian product but the where clause limits how the rows are combined to form the results (so not a cartesian product at all, really).
I haven't tested that SQL for this since it's one of the limitations of my DBMS of choice, and rightly so, I don't believe it's ever needed in a properly thought-out schema. Since SQL doesn't guarantee the order in which it produces data, the matching can change every time you do the query unless you have a specific relationship or order by clause.
I think the ideal thing to do would be to add a column to both tables specifying what the relationship is. If there's no real relationship, then you probably have no business in trying to put them side-by-side with SQL.
If you just want them displayed side-by-side in a report or on a web page (two examples), the right tool to do that is whatever generates your report or web page, coupled with two independent SQL queries to get the two unrelated tables. For example, a two-column grid in BIRT (or Crystal or Jasper) each with a separate data table, or a HTML two column table (or CSS) each with a separate data table.
This is a very strange request, and almost certainly something you'd never want to do in a real-world application, but from a purely academic standpoint it's an interesting challenge. With SQL Server 2005 you could use common table expressions and the row_number() functions and join on that:
with OrderedFoos as (
select row_number() over (order by FooName) RowNum, *
from Foos (nolock)
),
OrderedBars as (
select row_number() over (order by BarName) RowNum, *
from Bars (nolock)
)
select *
from OrderedFoos f
full outer join OrderedBars u on u.RowNum = f.RowNum
This works, but it's supremely silly and I offer it only as a "community wiki" answer because I really wouldn't recommend it.
SELECT *
FROM table1, table2
This will join every row in table1 with table2 (the Cartesian product) returning all columns.
select
status_id,
status,
null as path,
null as Description
from
zmw_t_status
union
select
null,
null,
path as cid,
Description from zmw_t_path;
try:
select * from table 1 left join table2 as t on 1 = 1;
This will bring all the columns from both the table.
If the tables have no common fields then there is no way to combine the data in any meaningful view. You would more likely end up with a view that contains duplicated data from both tables.
To get a meaningful/useful view of the two tables, you normally need to determine an identifying field from each table that can then be used in the ON clause in a JOIN.
THen in your view:
SELECT T1.*, T2.* FROM T1 JOIN T2 ON T1.IDFIELD1 = T2.IDFIELD2
You mention no fields are "common", but although the identifying fields may not have the same name or even be the same data type, you could use the convert / cast functions to join them in some way.
why don't you use simple approach
SELECT distinct *
FROM
SUPPLIER full join
CUSTOMER on (
CUSTOMER.OID = SUPPLIER.OID
)
It gives you all columns from both tables and returns all records from customer and supplier if Customer has 3 records and supplier has 2 then supplier'll show NULL in all columns
Select
DISTINCT t1.col,t2col
From table1 t1, table2 t2
OR
Select
DISTINCT t1.col,t2col
From table1 t1
cross JOIN table2 t2
if its hug data , its take long time ..
SELECT t1.col table1col, t2.col table2col
FROM table1 t1
JOIN table2 t2 on t1.table1Id = x and t2.table2Id = y
Joining Non-Related Tables
Demo SQL Script
IF OBJECT_ID('Tempdb..#T1') IS NOT NULL DROP TABLE #T1;
CREATE TABLE #T1 (T1_Name VARCHAR(75));
INSERT INTO #T1 (T1_Name) VALUES ('Animal'),('Bat'),('Cat'),('Duet');
SELECT * FROM #T1;
IF OBJECT_ID('Tempdb..#T2') IS NOT NULL DROP TABLE #T2;
CREATE TABLE #T2 (T2_Class VARCHAR(10));
INSERT INTO #T2 (T2_Class) VALUES ('Z'),('T'),('H');
SELECT * FROM #T2;
To Join Non-Related Tables , we are going to introduce one common joining column of Serial Numbers like below.
SQL Script
SELECT T1.T1_Name,ISNULL(T2.T2_Class,'') AS T2_Class FROM
( SELECT T1_Name,ROW_NUMBER() OVER(ORDER BY (SELECT NULL)) AS S_NO FROM #T1) T1
LEFT JOIN
( SELECT T2_Class,ROW_NUMBER() OVER(ORDER BY (SELECT NULL)) AS S_NO FROM #T2) T2
ON t1.S_NO=T2.S_NO;
select * from this_table;
select distinct person from this_table
union select address as location from that_table
drop wrong_table from this_database;
Very hard when you have to do this with three select statments
I tried all proposed techniques up there but it's in-vain
Please see below script. please advice if you have alternative solution
select distinct x.best_Achiver_ever,y.Today_best_Achiver ,z.Most_Violator from
(SELECT Top(4) ROW_NUMBER() over (order by tl.username) AS conj, tl.
[username] + '-->' + str(count(*)) as best_Achiver_ever
FROM[TiketFollowup].[dbo].N_FCR_Tikect_Log_Archive tl
group by tl.username
order by count(*) desc) x
left outer join
(SELECT
Top(4) ROW_NUMBER() over (order by tl.username) as conj, tl.[username] + '-->' + str(count(*)) as Today_best_Achiver
FROM[TiketFollowup].[dbo].[N_FCR_Tikect_Log] tl
where convert(date, tl.stamp, 121) = convert(date,GETDATE(),121)
group by tl.username
order by count(*) desc) y
on x.conj=y.conj
left outer join
(
select ROW_NUMBER() over (order by count(*)) as conj,username+ '--> ' + str( count(dbo.IsViolated(stamp))) as Most_Violator from N_FCR_Ticket
where dbo.IsViolated(stamp) = 'violated' and convert(date,stamp, 121) < convert(date,GETDATE(),121)
group by username
order by count(*) desc) z
on x.conj = z.conj
Please try this query:
Combine two tables that have no common columns:
SELECT *
FROM table1
UNION
SELECT *
FROM table2
ORDER BY orderby ASC