I have a query like this
select *
from MyTable
where (#Param is null or (FieldCode = 'Whatever' and FieldValue like '%' + #Param + '%'))
As I'm adding more statements to my where clause, my query is slowing down. I think it's because it's evaluating the AND part before the OR (which contains a LIKE, which can be slow). I want it to skip the query with the AND if #Param is null, how should i do this?
I would highly suggest you check your indexes you are definitely missing one then.
Beside of that do you really need to use every column? Use (NOLOCK) for reading data.
Furthermore like is very bad for indexes look if you would really need the first % for your program or if you could search for the data on the clientside (Filter a larger subset of data)
You could always break it apart and just do a different select statement if the #param is null.
If #Param is not null
select *
from MyTable
where (FieldCode = 'Whatever' and FieldValue like '%' + #Param + '%')
Else
select *
from MyTable
Try this for better performance:
select *
from MyTable
where #Param is null or case when #Param is not null and FieldCode = 'Whatever'
then case when FieldValue like '%' + #Param + '%' then 1 end end = 1
This will prevent the heavy wildchar compare when it isn't necessary
I am using this version of Sybase -
Adaptive Server Enterprise/15.5/EBF 18164 SMP ESD#2/P/x86_64/Enterprise Linux.
When I try to run the below query I get an error saying Incorrect syntax near 'regexp'.
SELECT * FROM T1 WHERE C1 regexp '.*'
Can someone suggest an alternative if this is not supported in this version of ASE.
Try this way:
SELECT * FROM T1 WHERE C1 like '%.%'
or
SELECT * FROM T1 WHERE C1 like '%[.]%'
Naively, you could either construct a varchar(nn) of characters that you want to find, or conversely, know the set of valid characters and search for any NOT in that set.
declare #mySet varchar(255)
select #mySet = '%[' + char(128) + char(129) + ... + ']%'
-- OR
select #mySet = '%[^A-Z0-9_-#.]%' -- for example, case insensitive
-- then
select * from T where C like #mySet
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.