Need to count specific letters from a search, why does it show as zero? the data is formatted as ntext - tsql

===CLICK ME FOR THE IMAGE OF THE CODE== I need the count to be (3 for example on the first row) but it shows zero, what is wrong with the code, this is ntext which is why it was casted to nvarchar
I am trying to count the occurrence of the letter 'a' on a column named Description, however using the query below I am getting the result of zero.
SELECT Description,
(
datalength(Description) -
datalength(replace(cast(Description as nvarchar(max)), 'a', ''))
)
/datalength(Description) [a]
FROM Categories

An int divided by an int will return an int. Notice the *1.0
Example
Declare #Description nvarchar(max)='Cat in the Hat was never seen'
SELECT #Description, (( datalength(#Description) - datalength(replace(cast(#Description as nvarchar(max)), 'a', '')) )*100) / datalength(#Description) [a]
Returns
(No column name) a
Cat in the Hat was never seen 10

Related

PGSQL - How to efficiently flatten key/value table [duplicate]

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)

Make rows to Columns in Postgresql [duplicate]

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)

Postgresql order by case when {someCase} then json type column

I need order result from select by few ways.
It's working when it's some column from table TenderItem.
But NOT working if it some key from json type column TenderItem.ItemInfo, f.e.
select * from "TenderItem" order by "ItemInfo" ->> 'Name'; -- working in simple select
with sortingParams (columnName, isAsc) AS (VALUES ('ItemId', true))
select *
FROM "TenderItem" i, sortingParams
WHERE i."TenderId" = 1
AND i."ItemInfo" ->> 'Name' like '%Transcend%'
ORDER BY
case
WHEN columnName like '%ItemId%' THEN i."ItemId" --*work
WHEN columnName like '%ABCSegment%' THEN i."ItemInfo" ->> 'ABCSegment' --**
end desc;
**on this string i have message "ERROR: CASE types bigint and text cannot be matched"
It's not clear how you'd sort the itemID against the ItemInfo segment (unless this points to an item id) since they are not all text values (and if they are all text but some are text strings like '12345' then you do not want to use text sort since then '100' would come before '99'). You probably want them to be separate sort conditions to give more flexibility in ordering:
with sortingParams (columnName, isAsc) AS (VALUES ('ItemId', true))
select *
FROM "TenderItem" i, sortingParams
WHERE i."TenderId" = 1
AND i."ItemInfo" ->> 'Name' like '%Transcend%'
ORDER BY
case
WHEN columnName like '%ItemId%' THEN i."ItemId"::bigint end asc nulls last --puts things with an itemID ahead of those without, or could use nulls first
--if two items have same item id, then sort by segment
, case
WHEN columnName like '%ABCSegment%' THEN i."ItemInfo" ->> 'ABCSegment'
end desc;
Note that each sort condition must give the same datatype for each row being evaluated! This is what gives the error your described where the case statement gives a biting for ItemId and a text value for ItemInfo ->> 'ABCSegment'
ItemId is BIGINT and i."ItemInfo" ->> 'ABCSegment' is text which are incompatible types to do sorting on.
Try casting the value explicitly to BIGINT, i.e
..WHEN columnName like '%ABCSegment%' THEN (i."ItemInfo" ->> 'ABCSegment')::BIGINT
or make i."ItemId" a text if the above fails due to invalid bigint values.
i."ItemId"::TEXT

postgres `order by` argument type

What is the argument type for the order by clause in Postgresql?
I came across a very strange behaviour (using Postgresql 9.5). Namely, the query
select * from unnest(array[1,4,3,2]) as x order by 1;
produces 1,2,3,4 as expected. However the query
select * from unnest(array[1,4,3,2]) as x order by 1::int;
produces 1,4,3,2, which seems strange. Similarly, whenever I replace 1::int with whatever function (e.g. greatest(0,1)) or even case operator, the results are unordered (on the contrary to what I would expect).
So which type should an argument of order by have, and how do I get the expected behaviour?
This is expected (and documented) behaviour:
A sort_expression can also be the column label or number of an output column
So the expression:
order by 1
sorts by the first column of the result set (as defined by the SQL standard)
However the expression:
order by 1::int
sorts by the constant value 1, it's essentially the same as:
order by 'foo'
By using a constant value for the order by all rows have the same sort value and thus aren't really sorted.
To sort by an expression, just use that:
order by
case
when some_column = 'foo' then 1
when some_column = 'bar' then 2
else 3
end
The above sorts the result based on the result of the case expression.
Actually I have a function with an integer argument which indicates the column to be used in the order by clause.
In a case when all columns are of the same type, this can work: :
SELECT ....
ORDER BY
CASE function_to_get_a_column_number()
WHEN 1 THEN column1
WHEN 2 THEN column2
.....
WHEN 1235 THEN column1235
END
If columns are of different types, you can try:
SELECT ....
ORDER BY
CASE function_to_get_a_column_number()
WHEN 1 THEN column1::varchar
WHEN 2 THEN column2::varchar
.....
WHEN 1235 THEN column1235::varchar
END
But these "workarounds" are horrible. You need some other approach than the function returning a column number.
Maybe a dynamic SQL ?
I would say that dynamic SQL (thanks #kordirko and the others for the hints) is the best solution to the problem I originally had in mind:
create temp table my_data (
id serial,
val text
);
insert into my_data(id, val)
values (default, 'a'), (default, 'c'), (default, 'd'), (default, 'b');
create function fetch_my_data(col text)
returns setof my_data as
$f$
begin
return query execute $$
select * from my_data
order by $$|| quote_ident(col);
end
$f$ language plpgsql;
select * from fetch_my_data('val'); -- order by val
select * from fetch_my_data('id'); -- order by id
In the beginning I thought this could be achieved using case expression in the argument of the order by clause - the sort_expression. And here comes the tricky part which confused me: when sort_expression is a kind of identifier (name of a column or a number of a column), the corresponding column is used when ordering the results. But when sort_expression is some value, we actually order the results using that value itself (computed for each row). This is #a_horse_with_no_name's answer rephrased.
So when I queried ... order by 1::int, in a way I have assigned value 1 to each row and then tried to sort an array of ones, which clearly is useless.
There are some workarounds without dynamic queries, but they require writing more code and do not seem to have any significant advantages.

How can I query 'between' numeric data on a not numeric field?

I've got a query that I've just found in the database that is failing causing a report to fall over. The basic gist of the query:
Select *
From table
Where IsNull(myField, '') <> ''
And IsNumeric(myField) = 1
And Convert(int, myField) Between #StartRange And #EndRange
Now, myField doesn't contain numeric data in all the rows [it is of nvarchar type]... but this query was obviously designed such that it only cares about rows where the data in this field is numeric.
The problem with this is that T-SQL (near as I understand) doesn't shortcircuit the Where clause thus causing it to ditch out on records where the data is not numeric with the exception:
Msg 245, Level 16, State 1, Line 1
Conversion failed when converting the nvarchar value '/A' to data type int.
Short of dumping all the rows where myField is numeric into a temporary table and then querying that for rows where the field is in the specified range, what can I do that is optimal?
My first parse purely to attempt to analyse the returned data and see what was going on was:
Select *
From (
Select *
From table
Where IsNull(myField, '') <> ''
And IsNumeric(myField) = 1
) t0
Where Convert(int, myField) Between #StartRange And #EndRange
But I get the same error I did for the first query which I'm not sure I understand as I'm not converting any data that shouldn't be numeric at this point. The subquery should only have returned rows where myField contains numeric data.
Maybe I need my morning tea, but does this make sense to anyone? Another set of eyes would help.
Thanks in advance
IsNumeric only tells you that the string can be converted to one of the numeric types in SQL Server. It may be able to convert it to money, or to a float, but may not be able to convert it to an int.
Change your
IsNumeric(myField) = 1
to be:
not myField like '%[^0-9]%' and LEN(myField) < 9
(that is, you want myField to contain only digits, and fit in an int)
Edit examples:
select ISNUMERIC('.'),ISNUMERIC('£'),ISNUMERIC('1d9')
result:
----------- ----------- -----------
1 1 1
(1 row(s) affected)
You'd have to force SQL to evaluate the expressions in a certain order.
Here is one solution
Select *
From ( TOP 2000000000
Select *
From table
Where IsNumeric(myField) = 1
And IsNull(myField, '') <> ''
ORDER BY Key
) t0
Where Convert(int, myField) Between #StartRange And #EndRange
and another
Select *
From table
Where
CASE
WHEN IsNumeric(myField) = 1 And IsNull(myField, '') <> ''
THEN Convert(int, myField) ELSE #StartRange-1
END Between #StartRange And #EndRange
The first technique is "intermediate materialisation": it forces a sort on a working table.
The 2nd relies on CASE ORDER evaluation is guaranteed
Neither is pretty or whizzy
SQL is declarative: you tell the optimiser what you want, not how to do it. The tricks above force things to be done in a certain order.
Not sure if this helps you, but I did read somewhere that incorrect conversion using CONVERT will always generate error in SQL. So I think it would be better to use CASE in where clause to avoid having CONVERT to run on all rows
Use a CASE statement.
declare #StartRange int
declare #EndRange int
set #StartRange = 1
set #EndRange = 3
select *
from TestData
WHERE Case WHEN ISNUMERIC(Value) = 0 THEN 0
WHEN Value IS NULL THEN 0
WHEN Value = '' THEN 0
WHEN CONVERT(int, Value) BETWEEN #StartRange AND #EndRange THEN 1
END = 1