I want to build a dynamic SQL query where I can use data from another table as where condition. Let's assume I have two tables: one table with financial data and the other one with conditions. They look something like this:
Table sales
c006 mesocomp c048 c020 c021
----- ---------- ------- ----- ----
120 01TA MICROSOFT 2 239
and a condition table with the following data:
dimension operator wert_db
--------- -------- -------
sales.c006 < 700
sales.c048 not like 'MIC%'
sales.c021 in (203,206)
I want to select all data from sales with the conditions stated in the condition table. So I have an SQL Query as follows:
SELECT *
FROM sales
WHERE sales.c006 < 700
AND sales.c048 NOT LIKE 'MIC%'
AND sales.c021 IN (203, 206)
Since you've posted no attempt to solve or research this yourself, I'll point you in a direction to get you started.
Your question already mentions using Dynamic SQL, so I assume you know at least what that is. You're going to populate a string variable, starting with 'SELECT * FROM Sales '.
You can use the STUFF...FOR XML PATH technique to assemble the conditions rows into a WHERE clause.
One change to the linked example is that you'll need to concatenate dimension, operator and wert_db into one artificial column in the innermost SELECT. Also instead of separating with a comma, you'll separate with ' AND '. And change the parameters of the STUFF function to take off the length of ' AND ' instead of the length of a comma.
DECLARE #tblSales TABLE
(
c006 VARCHAR(10),
mesocomp VARCHAR(100),
c048 VARCHAR(100),
c020 VARCHAR(100),
c021 VARCHAR(100)
)
INSERT INTO #tblSales(c006, mesocomp, c048, c020, c021)
VALUES(120,'01Ta','Microsoft','2','239')
SELECT * FROM #tblSales
DECLARE #tblCondition TABLE
(
Id INT,
dimension VARCHAR(100),
operator VARCHAR(10),
wert_db VARCHAR(100)
)
INSERT INTO #tblCondition(Id, dimension, operator, wert_db) VALUES(1,'sales.c006','<','700')
INSERT INTO #tblCondition(Id, dimension, operator, wert_db) VALUES(1,'sales.c048','not like','''MIC%''')
INSERT INTO #tblCondition(Id, dimension, operator, wert_db) VALUES(1,'sales.c021','in','(203,206)')
DECLARE #whereCondition VARCHAR(400)
SELECT #whereCondition = COALESCE(#whereCondition + ' ', '') + dimension + ' ' + operator + ' ' + wert_db + ' AND '
FROM #tblCondition
SET #whereCondition = SUBSTRING(#whereCondition,0, LEN(#whereCondition) - 3)
PRINT #whereCondition
DECLARE #sql VARCHAR(4000)
SET #sql = 'SELECT * FROM #tblSales Where ' + #whereCondition
PRINT #sql
EXEC(#sql)
--please use real tables so you will get everything working.
Related
Suppose I have a row of data, store such as the following:
------------------------
| Col 1 | Col 2 | Col 3 |
|------------------------|
| Foo | Bar | Foobar |
How might I concatinate this into a single string, such as the below?
Foo-Bar-Foobar
The column headings (and number of column headings) in this table will not be known, so selecting by column name is not an option(?).
Please note that I am not trying to concatinate a list of values in a column, I am trying to concatinate the values stores in one single row. I would also prefer to avoid using pivots, as I will be working with large sets of data and do not want to take the hit to performance.
In such cases I really adore the mighty abilities of XML in dealing with generic sets:
SELECT STUFF(b.query('
for $element in ./*
return
<x>;{$element/text()}</x>
').value('.','nvarchar(max)'),1,1,'')
FROM
(
SELECT TOP 3 * FROM sys.objects o FOR XML PATH('row'),ELEMENTS XSINIL,TYPE
) A(a)
CROSS APPLY a.nodes('/row') B(b);
The result
sysrscols;3;4;0;S ;SYSTEM_TABLE;2017-08-22T19:38:02.860;2017-08-22T19:38:02.867;1;0;0
sysrowsets;5;4;0;S ;SYSTEM_TABLE;2009-04-13T12:59:05.513;2017-08-22T19:38:03.197;1;0;0
sysclones;6;4;0;S ;SYSTEM_TABLE;2017-08-22T19:38:03.113;2017-08-22T19:38:03.120;1;0;0
Remarks
Some things to mention
I use the ; as delimiter, as the - might break with values containing hyphens (e.g. DATE)
I use TOP 3 from sys.objects to create an easy-cheesy-stand-alone sample
Thx to Zohard Peled I added ELEMENTS XSINIL to force the engine not to omit NULL values.
UPDATE Create JSON in pre-2016 versions
You can try this to create a JSON-string in versions before 2016
SELECT '{'
+ STUFF(b.query('
for $element in ./*
return
<x>,"{local-name($element)}":"{$element/text()}"</x>
').value('.','nvarchar(max)'),1,1,'')
+ '}'
FROM
(
SELECT TOP 3 * FROM sys.objects o FOR XML PATH('row'),TYPE
) A(a)
CROSS APPLY a.nodes('/row') B(b);
The result
{"name":"sysrscols","object_id":"3","schema_id":"4","parent_object_id":"0","type":"S ","type_desc":"SYSTEM_TABLE","create_date":"2017-08-22T19:38:02.860","modify_date":"2017-08-22T19:38:02.867","is_ms_shipped":"1","is_published":"0","is_schema_published":"0"}
{"name":"sysrowsets","object_id":"5","schema_id":"4","parent_object_id":"0","type":"S ","type_desc":"SYSTEM_TABLE","create_date":"2009-04-13T12:59:05.513","modify_date":"2017-08-22T19:38:03.197","is_ms_shipped":"1","is_published":"0","is_schema_published":"0"}
{"name":"sysclones","object_id":"6","schema_id":"4","parent_object_id":"0","type":"S ","type_desc":"SYSTEM_TABLE","create_date":"2017-08-22T19:38:03.113","modify_date":"2017-08-22T19:38:03.120","is_ms_shipped":"1","is_published":"0","is_schema_published":"0"}
Hint
You might add ELEMENTS XSINIL to this query as well. This depends, if you'd like NULLs to simply miss, or if you want to include them as "SomeColumn":""
I use UnitE and this is what I would use to select the columns dynamically from the person table.
INFORMATION_SCHEMA.COLUMNS stores the column list for the table and the SELECT statement is built around that.
Declare #Columns NVARCHAR(MAX)
Declare #Table varchar(15) = 'capd_person'
SELECT #Columns=COALESCE(#Columns + ',', '') + COLUMN_NAME
FROM INFORMATION_SCHEMA.COLUMNS
WHERE (TABLE_NAME=#Table )
EXEC('SELECT DISTINCT ' + #Columns + ' FROM ' + #Table)
You would need to change the EXEC command to suit your needs, using CONCAT as described before.
Simply do a SELECT CONCAT(col1,col2,col3) FROM table
However if you wish to make it neat
Use:
SELECT CONCAT(col1,'-',col2,'-',col3) FROM table.
Find more help here.
An improved version of JonTout's answer:
Declare #Columns NVARCHAR(MAX)
Declare #Table varchar(15) = 'TableName'
SELECT #Columns=COALESCE(#Columns + '+', '') +'CONVERT(varchar(max),ISNULL('+ COLUMN_NAME+',''''))+''-'''
FROM INFORMATION_SCHEMA.COLUMNS
WHERE (TABLE_NAME=#Table )
EXEC('SELECT ' + #Columns + ' FROM ' + #Table)
Given a table as below where fn contains the name of an existing table valued functions and param contains the param to be passed to the function
fn | param
----------------
'fn_one' | 1001
'fn_two' | 1001
'fn_one' | 1002
'fn_two' | 1002
Is there a way to get a resulting table like this by using set-based operations?
The resulting table would contain 0-* lines for each line from the first table.
param | resultval
---------------------------
1001 | 'fn_one_result_a'
1001 | 'fn_one_result_b'
1001 | 'fn_two_result_one'
1002 | 'fn_two_result_one'
I thought I could do something like (pseudo)
select t1.param, t2.resultval
from table1 t1
cross join exec sp_executesql('select * from '+t1.fn+'('+t1.param+')') t2
but that gives a syntax error at exec sp_executesql.
Currently we're using cursors to loop through the first table and insert into a second table with exec sp_executesql. While this does the job correctly, it is also the heaviest part of a frequently used stored procedure and I'm trying to optimize it. Changes to the data model would probably imply changes to most of the core of the application and that would cost more then just throwing hardware at sql server.
I believe that this should do what you need, using dynamic SQL to generate a single statement that can give you your results and then using that with EXEC to put them into your table. The FOR XML trick is a common one for concatenating VARCHAR values together from multiple rows. It has to be written with the AS [text()] for it to work.
--=========================================================
-- Set up
--=========================================================
CREATE TABLE dbo.TestTableFunctions (function_name VARCHAR(50) NOT NULL, parameter VARCHAR(20) NOT NULL)
INSERT INTO dbo.TestTableFunctions (function_name, parameter)
VALUES ('fn_one', '1001'), ('fn_two', '1001'), ('fn_one', '1002'), ('fn_two', '1002')
CREATE TABLE dbo.TestTableFunctionsResults (function_name VARCHAR(50) NOT NULL, parameter VARCHAR(20) NOT NULL, result VARCHAR(200) NOT NULL)
GO
CREATE FUNCTION dbo.fn_one
(
#parameter VARCHAR(20)
)
RETURNS TABLE
AS
RETURN
SELECT 'fn_one_' + #parameter AS result
GO
CREATE FUNCTION dbo.fn_two
(
#parameter VARCHAR(20)
)
RETURNS TABLE
AS
RETURN
SELECT 'fn_two_' + #parameter AS result
GO
--=========================================================
-- The important stuff
--=========================================================
DECLARE #sql VARCHAR(MAX)
SELECT #sql =
(
SELECT 'SELECT ''' + T1.function_name + ''', ''' + T1.parameter + ''', F.result FROM ' + T1.function_name + '(' + T1.parameter + ') F UNION ALL ' AS [text()]
FROM
TestTableFunctions T1
FOR XML PATH ('')
)
SELECT #sql = SUBSTRING(#sql, 1, LEN(#sql) - 10)
INSERT INTO dbo.TestTableFunctionsResults
EXEC(#sql)
SELECT * FROM dbo.TestTableFunctionsResults
--=========================================================
-- Clean up
--=========================================================
DROP TABLE dbo.TestTableFunctions
DROP TABLE dbo.TestTableFunctionsResults
DROP FUNCTION dbo.fn_one
DROP FUNCTION dbo.fn_two
GO
The first SELECT statement (ignoring the setup) builds a string which has the syntax to run all of the functions in your table, returning the results all UNIONed together. That makes it possible to run the string with EXEC, which means that you can then INSERT those results into your table.
A couple of quick notes though... First, the functions must all return identical result set structures - the same number of columns with the same data types (technically, they might be able to be different data types if SQL Server can always do implicit conversions on them, but it's really not worth the risk). Second, if someone were able to update your functions table they could use SQL injection to wreak havoc on your system. You'll need that to be tightly controlled and I wouldn't let users just enter in function names, etc.
You cannot access objects by referencing their names in a SQL statement. One method would be to use a case statement:
select t1.*,
(case when fn = 'fn_one' then dbo.fn_one(t1.param)
when fn = 'fn_two' then dbo.fn_two(t1.param)
end) as resultval
from table1 t1 ;
Interestingly, you could encapsulate the case as another function, and then do:
select t1.*, dbo.fn_generic(t1.fn, t1.param) as resultval
from table1 t1 ;
However, in SQL Server, you cannot use dynamic SQL in a user-defined function (defined in T-SQL), so you would still need to use case or similar logic.
Either of these methods is likely to be much faster than a cursor, because they do not require issuing multiple queries.
I have data that is 192 separate columns. They are column pairs so that there is data for a 15 minute time slice and a quality control number. The way it is setup now each row represents a single day. I would like to insert the data into another table with fewer columns (Date,ReadTime,QualityControlNumber,Reading,...)
I started with trying a while loop like this but using a variable to change the column header doesn't seem possible.
Should I nest while loops to increment the column headers or is there another trick I should be using
Code tried:
Declare #count varchar (10),
#QC varchar (10),
#Interval varchar(10)
set #count = 1
set #QC = 'QC#' + #count
set #Interval = 'Interval#' + #count
While (#count<97)
BEGIN
insert into Data_DATEstr (Number,[ReadDate],TimeInterval,QCReading,IntervalReading,ConversionFactor)
select [Number], [Start Date], #count, ['QC#'+#count], [Interval# +#count] ,[Conversion Factor]
from table
where [Number] = '103850581'
and [Start Date] = '060112'
set #count = (#count+1)
END
There is no need to use a while-loop for this. You want an UNPIVOT If you are trying to convert 192 separate columns to rows, then you will definitely want to use an UNPIVOT function. This can be written using dynamic SQL so then you will have have to code all of the fields:
DECLARE #cols AS NVARCHAR(MAX),
#query AS NVARCHAR(MAX)
select #cols = stuff((select ','+quotename(C.name)
from sys.columns as C
where C.object_id = object_id('test') and
C.name like 'col%'
for xml path('')), 1, 1, '')
set #query = 'SELECT QualityControlNumber, replace(col, ''col'', '''') as col, value
from test
unpivot
(
value
for col in (' + #cols + ')
) p '
execute(#query)
See SQL Fiddle with Demo
Using dynamic SQL for this will get the list of fields that you want to transpose when the query is executed. This also prevents you having to manually code for 192 separate columns.
Although your question is not entirely clear, it sounds like you need some form of operation similar to UNPIVOT. This lets you rotate columns into rows. I'd suggest reading up on it and seeing if it will work for you -- even if it doesn't, it might suggest an approach that would work.
The command that you want is unpivot. Something like:
select Date, ReadTime, QualityControlNumber, Reading
from t
unpivot (Reading for date in (day1, . . . , dayn) as unpvt
You will find that you won't really get the date, but instead the original column name. You can fix this by putting the unpivot query in a subquery (or CTE) and then using string manipulations and cast to convert the column name to a date.
I am tryin to get a column from DB that returns Variable Column Name which depends on Row data. I know I can have variable Column name with using Dynamic SQL, but what if the name actually depends on the row's information.
SELECT name,age FROM dbo.Names
--Reurns 'name' as column name
SELECT name as [xyz],age FROM dbo.Names
--Returns 'xyz' as column name
EXEC 'SELECT name as [' + #var + '], age FROM dbo.Names'
--Returns #var value as Column name
SELECT name AS ['Hi: ' + age ] FROM dbo.Name ?????
--So I am trying to get 'Hi: 25' or 'Hi: 40' as column name
How would I do that? Any help please?
You can combine the approaches for one line, but not for selecting all rows:
DECLARE #age INT
SET #age = SELECT TOP 1 #age FROM dbo.NAMES
EXEC 'SELECT name as [Hi ' + #age + '], age FROM dbo.Names'
Why do you need to do this in SQL and not in application logic?
I am gonna have to change on Application Side. I don't think that's possible to change in the SQL Side. That logic only works for the 1 row, I need multiple rows.
Is there any RDBMS that implements something like SELECT * EXCEPT? What I'm after is getting all of the fields except a specific TEXT/BLOB field, and I'd like to just select everything else.
Almost daily I complain to my coworkers that someone should implement this... It's terribly annoying that it doesn't exist.
Edit: I understand everyone's concern for SELECT *. I know the risks associated with SELECT *. However, this, at least in my situation, would not be used for any Production level code, or even Development level code; strictly for debugging, when I need to see all of the values easily.
As I've stated in some of the comments, where I work is strictly a commandline shop, doing everything over ssh. This makes it difficult to use any gui tools (external connections to the database aren't allowed), etc etc.
Thanks for the suggestions though.
As others have said, it is not a good idea to do this in a query because it is prone to issues when someone changes the table structure in the future. However, there is a way to do this... and I can't believe I'm actually suggesting this, but in the spirit of answering the ACTUAL question...
Do it with dynamic SQL... this does all the columns except the "description" column. You could easily turn this into a function or stored proc.
declare #sql varchar(8000),
#table_id int,
#col_id int
set #sql = 'select '
select #table_id = id from sysobjects where name = 'MY_Table'
select #col_id = min(colid) from syscolumns where id = #table_id and name <> 'description'
while (#col_id is not null) begin
select #sql = #sql + name from syscolumns where id = #table_id and colid = #col_id
select #col_id = min(colid) from syscolumns where id = #table_id and colid > #col_id and name <> 'description'
if (#col_id is not null) set #sql = #sql + ','
print #sql
end
set #sql = #sql + ' from MY_table'
exec #sql
Create a view on the table which doesn't include the blob columns
Is there any RDBMS that implements something like SELECT * EXCEPT?
Yes, Google Big Query implements SELECT * EXCEPT:
A SELECT * EXCEPT statement specifies the names of one or more columns to exclude from the result. All matching column names are omitted from the output.
WITH orders AS(
SELECT 5 as order_id,
"sprocket" as item_name,
200 as quantity
)
SELECT * EXCEPT (order_id)
FROM orders;
Output:
+-----------+----------+
| item_name | quantity |
+-----------+----------+
| sprocket | 200 |
+-----------+----------+
EDIT:
H2 database also supports SELECT * EXCEPT (col1, col2, ...) syntax.
Wildcard expression
A wildcard expression in a SELECT statement. A wildcard expression represents all visible columns. Some columns can be excluded with optional EXCEPT clause.
EDIT 2:
Hive supports: REGEX Column Specification
A SELECT statement can take regex-based column specification in Hive releases prior to 0.13.0, or in 0.13.0 and later releases if the configuration property hive.support.quoted.identifiers is set to none.
The following query selects all columns except ds and hr.
SELECT `(ds|hr)?+.+` FROM sales
EDIT 3:
Snowflake also now supports: SELECT * EXCEPT (and a RENAME option equivalent to REPLACE in BigQuery)
EXCLUDE col_name EXCLUDE (col_name, col_name, ...)
When you select all columns (SELECT *), specifies the columns that should be excluded from the results.
RENAME col_name AS col_alias RENAME (col_name AS col_alias, col_name AS col_alias, ...)
When you select all columns (SELECT *), specifies the column aliases that should be used in the results.
and so does Databricks SQL (since Runtime 11.0)
star_clause
[ { table_name | view_name } . ] * [ except_clause ]
except_clause
EXCEPT ( { column_name | field_name } [, ...] )
and also DuckDB
-- select all columns except the city column from the addresses table
SELECT * EXCLUDE (city) FROM addresses;
-- select all columns from the addresses table, but replace city with LOWER(city)
SELECT * REPLACE (LOWER(city) AS city) FROM addresses;
-- select all columns matching the given regex from the table
SELECT COLUMNS('number\d+') FROM addresses;
DB2 allows for this. Columns have an attribute/specifier of Hidden.
From the syscolumns documentation
HIDDEN
CHAR(1) NOT NULL WITH DEFAULT 'N'
Indicates whether the column is implicitly hidden:
P Partially hidden. The column is implicitly hidden from SELECT *.
N Not hidden. The column is visible to all SQL statements.
Create table documentation As part of creating your column, you would specify the IMPLICITLY HIDDEN modifier
An example DDL from Implicitly Hidden Columns follows
CREATE TABLE T1
(C1 SMALLINT NOT NULL,
C2 CHAR(10) IMPLICITLY HIDDEN,
C3 TIMESTAMP)
IN DB.TS;
Whether this capability is such a deal maker to drive the adoption of DB2 is left as an exercise to future readers.
Is there any RDBMS that implements something like SELECT * EXCEPT
Yes! The truly relational language Tutorial D allows projection to be expressed in terms of the attributes to be removed instead of the ones to be kept e.g.
my_relvar { ALL BUT description }
In fact, its equivalent to SQL's SELECT * is { ALL BUT }.
Your proposal for SQL is a worthy one but I heard it has already been put to the SQL standard's committee by the users' group and rejected by the vendor's group :(
It has also been explicitly requested for SQL Server but the request was closed as 'won't fix'.
Yes, finally there is :) SQL Standard 2016 defines Polymorphic Table Functions
SQL:2016 introduces polymorphic table functions (PTF) that don't need to specify the result type upfront. Instead, they can provide a describe component procedure that determines the return type at run time. Neither the author of the PTF nor the user of the PTF need to declare the returned columns in advance.
PTFs as described by SQL:2016 are not yet available in any tested database.10 Interested readers may refer to the free technical report “Polymorphic table functions in SQL” released by ISO. The following are some of the examples discussed in the report:
CSVreader, which reads the header line of a CVS file to determine the number and names of the return columns
Pivot (actually unpivot), which turns column groups into rows (example: phonetype, phonenumber) -- me: no more harcoded strings :)
TopNplus, which passes through N rows per partition and one extra row with the totals of the remaining rows
Oracle 18c implements this mechanism. 18c Skip_col Polymorphic Table Function Example Oracle Live SQL and Skip_col Polymorphic Table Function Example
This example shows how to skip data based on name/specific datatype:
CREATE PACKAGE skip_col_pkg AS
-- OVERLOAD 1: Skip by name
FUNCTION skip_col(tab TABLE, col columns)
RETURN TABLE PIPELINED ROW POLYMORPHIC USING skip_col_pkg;
FUNCTION describe(tab IN OUT dbms_tf.table_t,
col dbms_tf.columns_t)
RETURN dbms_tf.describe_t;
-- OVERLOAD 2: Skip by type --
FUNCTION skip_col(tab TABLE,
type_name VARCHAR2,
flip VARCHAR2 DEFAULT 'False')
RETURN TABLE PIPELINED ROW POLYMORPHIC USING skip_col_pkg;
FUNCTION describe(tab IN OUT dbms_tf.table_t,
type_name VARCHAR2,
flip VARCHAR2 DEFAULT 'False')
RETURN dbms_tf.describe_t;
END skip_col_pkg;
and body:
CREATE PACKAGE BODY skip_col_pkg AS
/* OVERLOAD 1: Skip by name
* NAME: skip_col_pkg.skip_col
* ALIAS: skip_col_by_name
*
* PARAMETERS:
* tab - The input table
* col - The name of the columns to drop from the output
*
* DESCRIPTION:
* This PTF removes all the input columns listed in col from the output
* of the PTF.
*/
FUNCTION describe(tab IN OUT dbms_tf.table_t,
col dbms_tf.columns_t)
RETURN dbms_tf.describe_t
AS
new_cols dbms_tf.columns_new_t;
col_id PLS_INTEGER := 1;
BEGIN
FOR i IN 1 .. tab.column.count() LOOP
FOR j IN 1 .. col.count() LOOP
tab.column(i).pass_through := tab.column(i).description.name != col(j);
EXIT WHEN NOT tab.column(i).pass_through;
END LOOP;
END LOOP;
RETURN NULL;
END;
/* OVERLOAD 2: Skip by type
* NAME: skip_col_pkg.skip_col
* ALIAS: skip_col_by_type
*
* PARAMETERS:
* tab - Input table
* type_name - A string representing the type of columns to skip
* flip - 'False' [default] => Match columns with given type_name
* otherwise => Ignore columns with given type_name
*
* DESCRIPTION:
* This PTF removes the given type of columns from the given table.
*/
FUNCTION describe(tab IN OUT dbms_tf.table_t,
type_name VARCHAR2,
flip VARCHAR2 DEFAULT 'False')
RETURN dbms_tf.describe_t
AS
typ CONSTANT VARCHAR2(1024) := upper(trim(type_name));
BEGIN
FOR i IN 1 .. tab.column.count() LOOP
tab.column(i).pass_through :=
CASE upper(substr(flip,1,1))
WHEN 'F' THEN dbms_tf.column_type_name(tab.column(i).description)
!=typ
ELSE dbms_tf.column_type_name(tab.column(i).description)
=typ
END /* case */;
END LOOP;
RETURN NULL;
END;
END skip_col_pkg;
And sample usage:
-- skip number cols
SELECT * FROM skip_col_pkg.skip_col(scott.dept, 'number');
-- only number cols
SELECT * FROM skip_col_pkg.skip_col(scott.dept, 'number', flip => 'True')
-- skip defined columns
SELECT *
FROM skip_col_pkg.skip_col(scott.emp, columns(comm, hiredate, mgr))
WHERE deptno = 20;
I highly recommend to read entire example(creating standalone functions instead of package calls).
You could easily overload skip method for example: skip columns that does not start/end with specific prefix/suffix.
db<>fidde demo
Related: How to Dynamically Change the Columns in a SQL Query By Chris Saxon
Stay away from SELECT *, you are setting yourself for trouble. Always specify exactly which columns you want. It is in fact quite refreshing that the "feature" you are asking for doesn't exist.
I believe the rationale for it not existing is that the author of a query should (for performance sake) only request what they're going to look at/need (and therefore know what columns to specify) -- if someone adds a couple more blobs in the future, you'd be pulling back potentially large fields you're not going to need.
Temp table option here, just drop the columns not required and select * from the altered temp table.
/* Get the data into a temp table */
SELECT * INTO #TempTable
FROM
table
/* Drop the columns that are not needed */
ALTER TABLE #TempTable
DROP COLUMN [columnname]
SELECT * from #TempTable
declare #sql nvarchar(max)
#table char(10)
set #sql = 'select '
set #table = 'table_name'
SELECT #sql = #sql + '[' + COLUMN_NAME + '],'
FROM INFORMATION_SCHEMA.Columns
WHERE TABLE_NAME = #table
and COLUMN_NAME <> 'omitted_column_name'
SET #sql = substring(#sql,1,len(#sql)-1) + ' from ' + #table
EXEC (#sql);
I needed something like what #Glen asks for easing my life with HASHBYTES().
My inspiration was #Jasmine and #Zerubbabel answers. In my case I've different schemas, so the same table name appears more than once at sys.objects. As this may help someone with the same scenario, here it goes:
ALTER PROCEDURE [dbo].[_getLineExceptCol]
#table SYSNAME,
#schema SYSNAME,
#LineId int,
#exception VARCHAR(500)
AS
DECLARE #SQL NVARCHAR(MAX)
BEGIN
SET NOCOUNT ON;
SELECT #SQL = COALESCE(#SQL + ', ', ' ' ) + name
FROM sys.columns
WHERE name <> #exception
AND object_id = (SELECT object_id FROM sys.objects
WHERE name LIKE #table
AND schema_id = (SELECT schema_id FROM sys.schemas WHERE name LIKE #schema))
SELECT #SQL = 'SELECT ' + #SQL + ' FROM ' + #schema + '.' + #table + ' WHERE Id = ' + CAST(#LineId AS nvarchar(50))
EXEC(#SQL)
END
GO
It's an old question, but I hope this answer can still be helpful to others. It can also be modified to add more than one except fields. This can be very handy if you want to unpivot a table with many columns.
DECLARE #SQL NVARCHAR(MAX)
SELECT #SQL = COALESCE(#SQL + ', ', ' ' ) + name FROM sys.columns WHERE name <> 'colName' AND object_id = (SELECT id FROM sysobjects WHERE name = 'tblName')
SELECT #SQL = 'SELECT ' + #SQL + ' FROM ' + 'tblName'
EXEC sp_executesql #SQL
Stored Procedure:
usp_SelectAllExcept 'tblname', 'colname'
ALTER PROCEDURE [dbo].[usp_SelectAllExcept]
(
#tblName SYSNAME
,#exception VARCHAR(500)
)
AS
DECLARE #SQL NVARCHAR(MAX)
SELECT #SQL = COALESCE(#SQL + ', ', ' ' ) + name from sys.columns where name <> #exception and object_id = (Select id from sysobjects where name = #tblName)
SELECT #SQL = 'SELECT ' + #SQL + ' FROM ' + #tblName
EXEC sp_executesql #SQL
For the sake of completeness, this is possible in DremelSQL dialect, doing something like:
WITH orders AS
(SELECT 5 as order_id,
"foobar12" as item_name,
800 as quantity)
SELECT * EXCEPT (order_id)
FROM orders;
Result:
+-----------+----------+
| item_name | quantity |
+-----------+----------+
| foobar12 | 800 |
+-----------+----------+
There also seems to be another way to do it here without Dremel.
Your question was about what RDBMS supports the * EXCEPT (...) syntax, so perhaps, looking at the jOOQ manual page for * EXCEPT can be useful in the future, as that page will keep track of new dialects supporting the syntax.
Currently (mid 2022), among the jOOQ supported RDBMS, at least BigQuery, H2, and Snowflake support the syntax natively. The others need to emulate it by listing the columns explicitly:
-- ACCESS, ASE, AURORA_MYSQL, AURORA_POSTGRES, COCKROACHDB, DB2, DERBY, EXASOL,
-- FIREBIRD, HANA, HSQLDB, INFORMIX, MARIADB, MEMSQL, MYSQL, ORACLE, POSTGRES,
-- REDSHIFT, SQLDATAWAREHOUSE, SQLITE, SQLSERVER, SYBASE, TERADATA, VERTICA,
-- YUGABYTEDB
SELECT LANGUAGE.CD, LANGUAGE.DESCRIPTION
FROM LANGUAGE
-- BIGQUERY, H2
SELECT * EXCEPT (ID)
FROM LANGUAGE
-- SNOWFLAKE
SELECT * EXCLUDE (ID)
FROM LANGUAGE
Disclaimer: I work for the company behind jOOQ
As others are saying: SELECT * is a bad idea.
Some reasons:
Get only what you need (anything more is a waste)
Indexing (index what you need and you can get it more quickly. If you ask for a bunch of non-indexed columns, too, your query plans will suffer.