Related
Does any one know how to create crosstab queries in PostgreSQL?
For example I have the following table:
Section Status Count
A Active 1
A Inactive 2
B Active 4
B Inactive 5
I would like the query to return the following crosstab:
Section Active Inactive
A 1 2
B 4 5
Is this possible?
Install the additional module tablefunc once per database, which provides the function crosstab(). Since Postgres 9.1 you can use CREATE EXTENSION for that:
CREATE EXTENSION IF NOT EXISTS tablefunc;
Improved test case
CREATE TABLE tbl (
section text
, status text
, ct integer -- "count" is a reserved word in standard SQL
);
INSERT INTO tbl VALUES
('A', 'Active', 1), ('A', 'Inactive', 2)
, ('B', 'Active', 4), ('B', 'Inactive', 5)
, ('C', 'Inactive', 7); -- ('C', 'Active') is missing
Simple form - not fit for missing attributes
crosstab(text) with 1 input parameter:
SELECT *
FROM crosstab(
'SELECT section, status, ct
FROM tbl
ORDER BY 1,2' -- needs to be "ORDER BY 1,2" here
) AS ct ("Section" text, "Active" int, "Inactive" int);
Returns:
Section | Active | Inactive
---------+--------+----------
A | 1 | 2
B | 4 | 5
C | 7 | -- !!
No need for casting and renaming.
Note the incorrect result for C: the value 7 is filled in for the first column. Sometimes, this behavior is desirable, but not for this use case.
The simple form is also limited to exactly three columns in the provided input query: row_name, category, value. There is no room for extra columns like in the 2-parameter alternative below.
Safe form
crosstab(text, text) with 2 input parameters:
SELECT *
FROM crosstab(
'SELECT section, status, ct
FROM tbl
ORDER BY 1,2' -- could also just be "ORDER BY 1" here
, $$VALUES ('Active'::text), ('Inactive')$$
) AS ct ("Section" text, "Active" int, "Inactive" int);
Returns:
Section | Active | Inactive
---------+--------+----------
A | 1 | 2
B | 4 | 5
C | | 7 -- !!
Note the correct result for C.
The second parameter can be any query that returns one row per attribute matching the order of the column definition at the end. Often you will want to query distinct attributes from the underlying table like this:
'SELECT DISTINCT attribute FROM tbl ORDER BY 1'
That's in the manual.
Since you have to spell out all columns in a column definition list anyway (except for pre-defined crosstabN() variants), it is typically more efficient to provide a short list in a VALUES expression like demonstrated:
$$VALUES ('Active'::text), ('Inactive')$$)
Or (not in the manual):
$$SELECT unnest('{Active,Inactive}'::text[])$$ -- short syntax for long lists
I used dollar quoting to make quoting easier.
You can even output columns with different data types with crosstab(text, text) - as long as the text representation of the value column is valid input for the target type. This way you might have attributes of different kind and output text, date, numeric etc. for respective attributes. There is a code example at the end of the chapter crosstab(text, text) in the manual.
db<>fiddle here
Effect of excess input rows
Excess input rows are handled differently - duplicate rows for the same ("row_name", "category") combination - (section, status) in the above example.
The 1-parameter form fills in available value columns from left to right. Excess values are discarded.
Earlier input rows win.
The 2-parameter form assigns each input value to its dedicated column, overwriting any previous assignment.
Later input rows win.
Typically, you don't have duplicates to begin with. But if you do, carefully adjust the sort order to your requirements - and document what's happening.
Or get fast arbitrary results if you don't care. Just be aware of the effect.
Advanced examples
Pivot on Multiple Columns using Tablefunc - also demonstrating mentioned "extra columns"
Dynamic alternative to pivot with CASE and GROUP BY
\crosstabview in psql
Postgres 9.6 added this meta-command to its default interactive terminal psql. You can run the query you would use as first crosstab() parameter and feed it to \crosstabview (immediately or in the next step). Like:
db=> SELECT section, status, ct FROM tbl \crosstabview
Similar result as above, but it's a representation feature on the client side exclusively. Input rows are treated slightly differently, hence ORDER BY is not required. Details for \crosstabview in the manual. There are more code examples at the bottom of that page.
Related answer on dba.SE by Daniel Vérité (the author of the psql feature):
How do I generate a pivoted CROSS JOIN where the resulting table definition is unknown?
SELECT section,
SUM(CASE status WHEN 'Active' THEN count ELSE 0 END) AS active, --here you pivot each status value as a separate column explicitly
SUM(CASE status WHEN 'Inactive' THEN count ELSE 0 END) AS inactive --here you pivot each status value as a separate column explicitly
FROM t
GROUP BY section
You can use the crosstab() function of the additional module tablefunc - which you have to install once per database. Since PostgreSQL 9.1 you can use CREATE EXTENSION for that:
CREATE EXTENSION tablefunc;
In your case, I believe it would look something like this:
CREATE TABLE t (Section CHAR(1), Status VARCHAR(10), Count integer);
INSERT INTO t VALUES ('A', 'Active', 1);
INSERT INTO t VALUES ('A', 'Inactive', 2);
INSERT INTO t VALUES ('B', 'Active', 4);
INSERT INTO t VALUES ('B', 'Inactive', 5);
SELECT row_name AS Section,
category_1::integer AS Active,
category_2::integer AS Inactive
FROM crosstab('select section::text, status, count::text from t',2)
AS ct (row_name text, category_1 text, category_2 text);
DB Fiddle here:
Everything works: https://dbfiddle.uk/iKCW9Uhh
Without CREATE EXTENSION tablefunc; you get this error: https://dbfiddle.uk/j8W1CMvI
ERROR: function crosstab(unknown, integer) does not exist
LINE 4: FROM crosstab('select section::text, status, count::text fro...
^
HINT: No function matches the given name and argument types. You might need to add explicit type casts.
Solution with JSON aggregation:
CREATE TEMP TABLE t (
section text
, status text
, ct integer -- don't use "count" as column name.
);
INSERT INTO t VALUES
('A', 'Active', 1), ('A', 'Inactive', 2)
, ('B', 'Active', 4), ('B', 'Inactive', 5)
, ('C', 'Inactive', 7);
SELECT section,
(obj ->> 'Active')::int AS active,
(obj ->> 'Inactive')::int AS inactive
FROM (SELECT section, json_object_agg(status,ct) AS obj
FROM t
GROUP BY section
)X
Sorry this isn't complete because I can't test it here, but it may get you off in the right direction. I'm translating from something I use that makes a similar query:
select mt.section, mt1.count as Active, mt2.count as Inactive
from mytable mt
left join (select section, count from mytable where status='Active')mt1
on mt.section = mt1.section
left join (select section, count from mytable where status='Inactive')mt2
on mt.section = mt2.section
group by mt.section,
mt1.count,
mt2.count
order by mt.section asc;
The code I'm working from is:
select m.typeID, m1.highBid, m2.lowAsk, m1.highBid - m2.lowAsk as diff, 100*(m1.highBid - m2.lowAsk)/m2.lowAsk as diffPercent
from mktTrades m
left join (select typeID,MAX(price) as highBid from mktTrades where bid=1 group by typeID)m1
on m.typeID = m1.typeID
left join (select typeID,MIN(price) as lowAsk from mktTrades where bid=0 group by typeID)m2
on m1.typeID = m2.typeID
group by m.typeID,
m1.highBid,
m2.lowAsk
order by diffPercent desc;
which will return a typeID, the highest price bid and the lowest price asked and the difference between the two (a positive difference would mean something could be bought for less than it can be sold).
There's a different dynamic method that I've devised, one that employs a dynamic rec. type (a temp table, built via an anonymous procedure) & JSON. This may be useful for an end-user who can't install the tablefunc/crosstab extension, but can still create temp tables or run anon. proc's.
The example assumes all the xtab columns are the same type (INTEGER), but the # of columns is data-driven & variadic. That said, JSON aggregate functions do allow for mixed data types, so there's potential for innovation via the use of embedded composite (mixed) types.
The real meat of it can be reduced down to one step if you want to statically define the rec. type inside the JSON recordset function (via nested SELECTs that emit a composite type).
dbfiddle.uk
https://dbfiddle.uk/N1EzugHk
Crosstab function is available under the tablefunc extension. You'll have to create this extension one time for the database.
CREATE EXTENSION tablefunc;
You can use the below code to create pivot table using cross tab:
create table test_Crosstab( section text,
status text,
count numeric)
insert into test_Crosstab values ( 'A','Active',1)
,( 'A','Inactive',2)
,( 'B','Active',4)
,( 'B','Inactive',5)
select * from crosstab(
'select section
,status
,count
from test_crosstab'
)as ctab ("Section" text,"Active" numeric,"Inactive" numeric)
Does any one know how to create crosstab queries in PostgreSQL?
For example I have the following table:
Section Status Count
A Active 1
A Inactive 2
B Active 4
B Inactive 5
I would like the query to return the following crosstab:
Section Active Inactive
A 1 2
B 4 5
Is this possible?
Install the additional module tablefunc once per database, which provides the function crosstab(). Since Postgres 9.1 you can use CREATE EXTENSION for that:
CREATE EXTENSION IF NOT EXISTS tablefunc;
Improved test case
CREATE TABLE tbl (
section text
, status text
, ct integer -- "count" is a reserved word in standard SQL
);
INSERT INTO tbl VALUES
('A', 'Active', 1), ('A', 'Inactive', 2)
, ('B', 'Active', 4), ('B', 'Inactive', 5)
, ('C', 'Inactive', 7); -- ('C', 'Active') is missing
Simple form - not fit for missing attributes
crosstab(text) with 1 input parameter:
SELECT *
FROM crosstab(
'SELECT section, status, ct
FROM tbl
ORDER BY 1,2' -- needs to be "ORDER BY 1,2" here
) AS ct ("Section" text, "Active" int, "Inactive" int);
Returns:
Section | Active | Inactive
---------+--------+----------
A | 1 | 2
B | 4 | 5
C | 7 | -- !!
No need for casting and renaming.
Note the incorrect result for C: the value 7 is filled in for the first column. Sometimes, this behavior is desirable, but not for this use case.
The simple form is also limited to exactly three columns in the provided input query: row_name, category, value. There is no room for extra columns like in the 2-parameter alternative below.
Safe form
crosstab(text, text) with 2 input parameters:
SELECT *
FROM crosstab(
'SELECT section, status, ct
FROM tbl
ORDER BY 1,2' -- could also just be "ORDER BY 1" here
, $$VALUES ('Active'::text), ('Inactive')$$
) AS ct ("Section" text, "Active" int, "Inactive" int);
Returns:
Section | Active | Inactive
---------+--------+----------
A | 1 | 2
B | 4 | 5
C | | 7 -- !!
Note the correct result for C.
The second parameter can be any query that returns one row per attribute matching the order of the column definition at the end. Often you will want to query distinct attributes from the underlying table like this:
'SELECT DISTINCT attribute FROM tbl ORDER BY 1'
That's in the manual.
Since you have to spell out all columns in a column definition list anyway (except for pre-defined crosstabN() variants), it is typically more efficient to provide a short list in a VALUES expression like demonstrated:
$$VALUES ('Active'::text), ('Inactive')$$)
Or (not in the manual):
$$SELECT unnest('{Active,Inactive}'::text[])$$ -- short syntax for long lists
I used dollar quoting to make quoting easier.
You can even output columns with different data types with crosstab(text, text) - as long as the text representation of the value column is valid input for the target type. This way you might have attributes of different kind and output text, date, numeric etc. for respective attributes. There is a code example at the end of the chapter crosstab(text, text) in the manual.
db<>fiddle here
Effect of excess input rows
Excess input rows are handled differently - duplicate rows for the same ("row_name", "category") combination - (section, status) in the above example.
The 1-parameter form fills in available value columns from left to right. Excess values are discarded.
Earlier input rows win.
The 2-parameter form assigns each input value to its dedicated column, overwriting any previous assignment.
Later input rows win.
Typically, you don't have duplicates to begin with. But if you do, carefully adjust the sort order to your requirements - and document what's happening.
Or get fast arbitrary results if you don't care. Just be aware of the effect.
Advanced examples
Pivot on Multiple Columns using Tablefunc - also demonstrating mentioned "extra columns"
Dynamic alternative to pivot with CASE and GROUP BY
\crosstabview in psql
Postgres 9.6 added this meta-command to its default interactive terminal psql. You can run the query you would use as first crosstab() parameter and feed it to \crosstabview (immediately or in the next step). Like:
db=> SELECT section, status, ct FROM tbl \crosstabview
Similar result as above, but it's a representation feature on the client side exclusively. Input rows are treated slightly differently, hence ORDER BY is not required. Details for \crosstabview in the manual. There are more code examples at the bottom of that page.
Related answer on dba.SE by Daniel Vérité (the author of the psql feature):
How do I generate a pivoted CROSS JOIN where the resulting table definition is unknown?
SELECT section,
SUM(CASE status WHEN 'Active' THEN count ELSE 0 END) AS active, --here you pivot each status value as a separate column explicitly
SUM(CASE status WHEN 'Inactive' THEN count ELSE 0 END) AS inactive --here you pivot each status value as a separate column explicitly
FROM t
GROUP BY section
You can use the crosstab() function of the additional module tablefunc - which you have to install once per database. Since PostgreSQL 9.1 you can use CREATE EXTENSION for that:
CREATE EXTENSION tablefunc;
In your case, I believe it would look something like this:
CREATE TABLE t (Section CHAR(1), Status VARCHAR(10), Count integer);
INSERT INTO t VALUES ('A', 'Active', 1);
INSERT INTO t VALUES ('A', 'Inactive', 2);
INSERT INTO t VALUES ('B', 'Active', 4);
INSERT INTO t VALUES ('B', 'Inactive', 5);
SELECT row_name AS Section,
category_1::integer AS Active,
category_2::integer AS Inactive
FROM crosstab('select section::text, status, count::text from t',2)
AS ct (row_name text, category_1 text, category_2 text);
DB Fiddle here:
Everything works: https://dbfiddle.uk/iKCW9Uhh
Without CREATE EXTENSION tablefunc; you get this error: https://dbfiddle.uk/j8W1CMvI
ERROR: function crosstab(unknown, integer) does not exist
LINE 4: FROM crosstab('select section::text, status, count::text fro...
^
HINT: No function matches the given name and argument types. You might need to add explicit type casts.
Solution with JSON aggregation:
CREATE TEMP TABLE t (
section text
, status text
, ct integer -- don't use "count" as column name.
);
INSERT INTO t VALUES
('A', 'Active', 1), ('A', 'Inactive', 2)
, ('B', 'Active', 4), ('B', 'Inactive', 5)
, ('C', 'Inactive', 7);
SELECT section,
(obj ->> 'Active')::int AS active,
(obj ->> 'Inactive')::int AS inactive
FROM (SELECT section, json_object_agg(status,ct) AS obj
FROM t
GROUP BY section
)X
Sorry this isn't complete because I can't test it here, but it may get you off in the right direction. I'm translating from something I use that makes a similar query:
select mt.section, mt1.count as Active, mt2.count as Inactive
from mytable mt
left join (select section, count from mytable where status='Active')mt1
on mt.section = mt1.section
left join (select section, count from mytable where status='Inactive')mt2
on mt.section = mt2.section
group by mt.section,
mt1.count,
mt2.count
order by mt.section asc;
The code I'm working from is:
select m.typeID, m1.highBid, m2.lowAsk, m1.highBid - m2.lowAsk as diff, 100*(m1.highBid - m2.lowAsk)/m2.lowAsk as diffPercent
from mktTrades m
left join (select typeID,MAX(price) as highBid from mktTrades where bid=1 group by typeID)m1
on m.typeID = m1.typeID
left join (select typeID,MIN(price) as lowAsk from mktTrades where bid=0 group by typeID)m2
on m1.typeID = m2.typeID
group by m.typeID,
m1.highBid,
m2.lowAsk
order by diffPercent desc;
which will return a typeID, the highest price bid and the lowest price asked and the difference between the two (a positive difference would mean something could be bought for less than it can be sold).
There's a different dynamic method that I've devised, one that employs a dynamic rec. type (a temp table, built via an anonymous procedure) & JSON. This may be useful for an end-user who can't install the tablefunc/crosstab extension, but can still create temp tables or run anon. proc's.
The example assumes all the xtab columns are the same type (INTEGER), but the # of columns is data-driven & variadic. That said, JSON aggregate functions do allow for mixed data types, so there's potential for innovation via the use of embedded composite (mixed) types.
The real meat of it can be reduced down to one step if you want to statically define the rec. type inside the JSON recordset function (via nested SELECTs that emit a composite type).
dbfiddle.uk
https://dbfiddle.uk/N1EzugHk
Crosstab function is available under the tablefunc extension. You'll have to create this extension one time for the database.
CREATE EXTENSION tablefunc;
You can use the below code to create pivot table using cross tab:
create table test_Crosstab( section text,
status text,
count numeric)
insert into test_Crosstab values ( 'A','Active',1)
,( 'A','Inactive',2)
,( 'B','Active',4)
,( 'B','Inactive',5)
select * from crosstab(
'select section
,status
,count
from test_crosstab'
)as ctab ("Section" text,"Active" numeric,"Inactive" numeric)
I have a very complex CTE and I would like to insert the result into a physical table.
Is the following valid?
INSERT INTO dbo.prf_BatchItemAdditionalAPartyNos
(
BatchID,
AccountNo,
APartyNo,
SourceRowID
)
WITH tab (
-- some query
)
SELECT * FROM tab
I am thinking of using a function to create this CTE which will allow me to reuse. Any thoughts?
You need to put the CTE first and then combine the INSERT INTO with your select statement. Also, the "AS" keyword following the CTE's name is not optional:
WITH tab AS (
bla bla
)
INSERT INTO dbo.prf_BatchItemAdditionalAPartyNos (
BatchID,
AccountNo,
APartyNo,
SourceRowID
)
SELECT * FROM tab
Please note that the code assumes that the CTE will return exactly four fields and that those fields are matching in order and type with those specified in the INSERT statement.
If that is not the case, just replace the "SELECT *" with a specific select of the fields that you require.
As for your question on using a function, I would say "it depends". If you are putting the data in a table just because of performance reasons, and the speed is acceptable when using it through a function, then I'd consider function to be an option.
On the other hand, if you need to use the result of the CTE in several different queries, and speed is already an issue, I'd go for a table (either regular, or temp).
WITH common_table_expression (Transact-SQL)
The WITH clause for Common Table Expressions go at the top.
Wrapping every insert in a CTE has the benefit of visually segregating the query logic from the column mapping.
Spot the mistake:
WITH _INSERT_ AS (
SELECT
[BatchID] = blah
,[APartyNo] = blahblah
,[SourceRowID] = blahblahblah
FROM Table1 AS t1
)
INSERT Table2
([BatchID], [SourceRowID], [APartyNo])
SELECT [BatchID], [APartyNo], [SourceRowID]
FROM _INSERT_
Same mistake:
INSERT Table2 (
[BatchID]
,[SourceRowID]
,[APartyNo]
)
SELECT
[BatchID] = blah
,[APartyNo] = blahblah
,[SourceRowID] = blahblahblah
FROM Table1 AS t1
A few lines of boilerplate make it extremely easy to verify the code inserts the right number of columns in the right order, even with a very large number of columns. Your future self will thank you later.
Yep:
WITH tab (
bla bla
)
INSERT INTO dbo.prf_BatchItemAdditionalAPartyNos ( BatchID, AccountNo,
APartyNo,
SourceRowID)
SELECT * FROM tab
Note that this is for SQL Server, which supports multiple CTEs:
WITH x AS (), y AS () INSERT INTO z (a, b, c) SELECT a, b, c FROM y
Teradata allows only one CTE and the syntax is as your example.
Late to the party here, but for my purposes I wanted to be able to run the code the user inputted and store in a temp table. Using oracle no such issues.. the insert is at the start of the statement before the with clause.
For this to work in sql server, the following worked:
INSERT into #stagetable execute (#InputSql)
(so the select statement #inputsql can start as a with clause).
I am trying to create the following select statement in a stored proc
#dealerids nvarchar(256)
SELECT *
FROM INVOICES as I
WHERE convert(nvarchar(20), I.DealerID) in (#dealerids)
I.DealerID is an INT in the table. and the Parameter for dealerids would be formatted such as
(8820, 8891, 8834)
When I run this with parameters provided I get no rows back. I know these dealerIDs should provided rows as if I do it individually I get back what I expect.
I think I am doing
WHERE convert(nvarchar(20), I.DealerID) in (#dealerids)
incorrectly. Can anyone point out what I am doing wrong here?
Use a table values parameter (new in SQl Server 2008). Set it up by creating the actual table parameter type:
CREATE TYPE IntTableType AS TABLE (ID INTEGER PRIMARY KEY)
Your procedure would then be:
Create Procedure up_TEST
#Ids IntTableType READONLY
AS
SELECT *
FROM ATable a
WHERE a.Id IN (SELECT ID FROM #Ids)
RETURN 0
GO
if you can't use table value parameters, see: "Arrays and Lists in SQL Server 2005 and Beyond, When Table Value Parameters Do Not Cut it" by Erland Sommarskog, then there are many ways to split string in SQL Server. This article covers the PROs and CONs of just about every method. in general, you need to create a split function. This is how a split function can be used:
SELECT
*
FROM YourTable y
INNER JOIN dbo.yourSplitFunction(#Parameter) s ON y.ID=s.Value
I prefer the number table approach to split a string in TSQL but there are numerous ways to split strings in SQL Server, see the previous link, which explains the PROs and CONs of each.
For the Numbers Table method to work, you need to do this one time table setup, which will create a table Numbers that contains rows from 1 to 10,000:
SELECT TOP 10000 IDENTITY(int,1,1) AS Number
INTO Numbers
FROM sys.objects s1
CROSS JOIN sys.objects s2
ALTER TABLE Numbers ADD CONSTRAINT PK_Numbers PRIMARY KEY CLUSTERED (Number)
Once the Numbers table is set up, create this split function:
CREATE FUNCTION [dbo].[FN_ListToTable]
(
#SplitOn char(1) --REQUIRED, the character to split the #List string on
,#List varchar(8000)--REQUIRED, the list to split apart
)
RETURNS TABLE
AS
RETURN
(
----------------
--SINGLE QUERY-- --this will not return empty rows
----------------
SELECT
ListValue
FROM (SELECT
LTRIM(RTRIM(SUBSTRING(List2, number+1, CHARINDEX(#SplitOn, List2, number+1)-number - 1))) AS ListValue
FROM (
SELECT #SplitOn + #List + #SplitOn AS List2
) AS dt
INNER JOIN Numbers n ON n.Number < LEN(dt.List2)
WHERE SUBSTRING(List2, number, 1) = #SplitOn
) dt2
WHERE ListValue IS NOT NULL AND ListValue!=''
);
GO
You can now easily split a CSV string into a table and join on it:
Create Procedure up_TEST
#Ids VARCHAR(MAX)
AS
SELECT * FROM ATable a
WHERE a.Id IN (SELECT ListValue FROM dbo.FN_ListToTable(',',#Ids))
You can't use #dealerids like that, you need to use dynamic SQL, like this:
#dealerids nvarchar(256)
EXEC('SELECT *
FROM INVOICES as I
WHERE convert(nvarchar(20), I.DealerID) in (' + #dealerids + ')'
The downside is that you open yourself up to SQL injection attacks unless you specifically control the data going into #dealerids.
There are better ways to handle this depending on your version of SQL Server, which are documented in this great article.
Split #dealerids into a table then JOIN
SELECT *
FROM INVOICES as I
JOIN
ufnSplit(#dealerids) S ON I.DealerID = S.ParsedIntDealerID
Assorted split functions here (I'd probably a numbers table in this case for a small string
I have a very complex CTE and I would like to insert the result into a physical table.
Is the following valid?
INSERT INTO dbo.prf_BatchItemAdditionalAPartyNos
(
BatchID,
AccountNo,
APartyNo,
SourceRowID
)
WITH tab (
-- some query
)
SELECT * FROM tab
I am thinking of using a function to create this CTE which will allow me to reuse. Any thoughts?
You need to put the CTE first and then combine the INSERT INTO with your select statement. Also, the "AS" keyword following the CTE's name is not optional:
WITH tab AS (
bla bla
)
INSERT INTO dbo.prf_BatchItemAdditionalAPartyNos (
BatchID,
AccountNo,
APartyNo,
SourceRowID
)
SELECT * FROM tab
Please note that the code assumes that the CTE will return exactly four fields and that those fields are matching in order and type with those specified in the INSERT statement.
If that is not the case, just replace the "SELECT *" with a specific select of the fields that you require.
As for your question on using a function, I would say "it depends". If you are putting the data in a table just because of performance reasons, and the speed is acceptable when using it through a function, then I'd consider function to be an option.
On the other hand, if you need to use the result of the CTE in several different queries, and speed is already an issue, I'd go for a table (either regular, or temp).
WITH common_table_expression (Transact-SQL)
The WITH clause for Common Table Expressions go at the top.
Wrapping every insert in a CTE has the benefit of visually segregating the query logic from the column mapping.
Spot the mistake:
WITH _INSERT_ AS (
SELECT
[BatchID] = blah
,[APartyNo] = blahblah
,[SourceRowID] = blahblahblah
FROM Table1 AS t1
)
INSERT Table2
([BatchID], [SourceRowID], [APartyNo])
SELECT [BatchID], [APartyNo], [SourceRowID]
FROM _INSERT_
Same mistake:
INSERT Table2 (
[BatchID]
,[SourceRowID]
,[APartyNo]
)
SELECT
[BatchID] = blah
,[APartyNo] = blahblah
,[SourceRowID] = blahblahblah
FROM Table1 AS t1
A few lines of boilerplate make it extremely easy to verify the code inserts the right number of columns in the right order, even with a very large number of columns. Your future self will thank you later.
Yep:
WITH tab (
bla bla
)
INSERT INTO dbo.prf_BatchItemAdditionalAPartyNos ( BatchID, AccountNo,
APartyNo,
SourceRowID)
SELECT * FROM tab
Note that this is for SQL Server, which supports multiple CTEs:
WITH x AS (), y AS () INSERT INTO z (a, b, c) SELECT a, b, c FROM y
Teradata allows only one CTE and the syntax is as your example.
Late to the party here, but for my purposes I wanted to be able to run the code the user inputted and store in a temp table. Using oracle no such issues.. the insert is at the start of the statement before the with clause.
For this to work in sql server, the following worked:
INSERT into #stagetable execute (#InputSql)
(so the select statement #inputsql can start as a with clause).