original query looks like this :
UPDATE reponse_question_finale t1, reponse_question_finale t2 SET
t1.nb_question_repondu = (9-(ISNULL(t1.valeur_question_4)+ISNULL(t1.valeur_question_6)+ISNULL(t1.valeur_question_7)+ISNULL(t1.valeur_question_9))) WHERE t1.APPLICATION = t2.APPLICATION;
I know you cannot update 2 tables in a single query so i tried this :
UPDATE reponse_question_finale t1
SET nb_question_repondu = (9-(COALESCE(t1.valeur_question_4,'')::int+COALESCE(t1.valeur_question_6,'')::int+COALESCE(t1.valeur_question_7)::int+COALESCE(t1.valeur_question_9,'')::int))
WHERE t1.APPLICATION = t1.APPLICATION;
But this query gaves me an error : invalid input syntax for integer: ""
I saw that the Postgres equivalent to MySQL is COALESCE() so i think i'm on the good way here.
I also know you cannot add varchar to varchar so i tried to cast it to integer to do that. I'm not sure if i casted it correctly with parenthesis at the good place and regarding to error maybe i cannot cast to int with coalesce.
Last thing, i can certainly do a co-related sub-select to update my two tables but i'm a little lost at this point.
The output must be an integer matching the number of questions answered to a backup survey.
Any thoughts?
Thanks.
coalesce() returns the first non-null value from the list supplied. So, if the column value is null the expression COALESCE(t1.valeur_question_4,'') returns an empty string and that's why you get the error.
But it seems you want something completely different: you want check if the column is null (or empty) and then subtract a value if it is to count the number of non-null columns.
To return 1 if a value is not null or 0 if it isn't you can use:
(nullif(valeur_question_4, '') is null)::int
nullif returns null if the first value equals the second. The IS NULL condition returns a boolean (something that MySQL doesn't have) and that can be cast to an integer (where false will be cast to 0 and true to 1)
So the whole expression should be:
nb_question_repondu = 9 - (
(nullif(t1.valeur_question_4,'') is null)::int
+ (nullif(t1.valeur_question_6,'') is null)::int
+ (nullif(t1.valeur_question_7,'') is null)::int
+ (nullif(t1.valeur_question_9,'') is null)::int
)
Another option is to unpivot the columns and do a select on them in a sub-select:
update reponse_question_finale
set nb_question_repondu = (select count(*)
from (
values
(valeur_question_4),
(valeur_question_6),
(valeur_question_7),
(valeur_question_9)
) as t(q)
where nullif(trim(q),'') is not null);
Adding more columns to be considered is quite easy then, as you just need to add a single line to the values() clause
Related
I have field that has up to 9 comma separated values each of which have a string value and a numeric value separated by colon. After parsing them all some of the values between 0 and 1 are being set to an integer rather than a numeric as cast. The problem is obviously related to data type but I am unsure what is causing it or how to fix it. The problem only exists in the case statement, the split_part function seems to be working perfect.
Things I have tried:
nvl(split_part(one,':',2),0) = COALESCE types text and integer cannot be matched
nvl(split_part(one,':',2)::numeric,0) => Invalid input syntax for type numeric
numerous other cast/convert variations
(CASE WHEN split_part(one,':',2) = '' THEN 0::numeric ELSE split_part(one,':',2)::numeric END)::numeric => runs but get int value of 0
When using the split_part function outside of case statement it does work correctly. However, I need the result to be zero for null values.
split_part(one,':',2) => 0.02068278096187390979 (expected result)
When running the code above I get zero but expect 0.02068278096187390979
Field "one" has the following value 'xyz: 0.02068278096187390979' before the split_part function.
EXAMPLE:
create table test(one varchar);
insert into test values('XYZ: 0.50000000000000000000')
select
one ,split_part(one,':',2) as correct_value_for_those_that_are_not_null ,
case
when split_part(one,':',2) = '' then null
else split_part(one,':',2)::numeric
end::numeric as this_one_is_the_problem
from test
However, I need the result to be zero for null values.
Your example does not deal with NULL values at all, though. Only addressing the empty string ('').
To replace either with 0 reliably, efficiently and without casting issues:
SELECT part1, CASE WHEN part2 <> '' THEN part2::numeric ELSE numeric '0' END AS part2
FROM (
SELECT split_part(one, ':', 1) AS part1
, split_part(one, ':', 2) AS part2
FROM test
) sub;
See:
Best way to check for "empty or null value"
Also note that all SQL CASE branches must agree on a common data type. There have been minor adjustments in the logic that determines the resulting type in the past, so the version of Postgres may play a role in corner cases. Don't recall the details now.
nvl()is not a Postgres function. You probably meant COALESCE. The manual:
This SQL-standard function provides capabilities similar to NVL and IFNULL, which are used in some other database systems.
This question already has an answer here:
How to handle an optional value returned by a query using the postgres crate?
(1 answer)
Closed 5 years ago.
I am using the rust-postgres library and I want to do a SELECT and check if the first column of the first row is NULL or not.
This is how I get my data:
let result = connection.query(
r#"
SELECT structure::TEXT
FROM sentence
WHERE id = $1
"#,
&[&uuid]
);
let rows = result.expect("problem while getting sentence");
let row = rows
.iter()
.next() // there's only 1 result
.expect("0 results, expected one...");
The only simple way I found to figure it out is the following code:
match row.get_opt(0) {
Some(Ok(data)) => some data found,
Some(Err(_)) => the column is null,
None => out of bound column index
}
Unfortunately, it seems that Some(Err(_)) is the executed path for any kind of SQL/database error, and not only if the retrieved column is NULL.
Which condition should I use to check that the column is NULL ?
If all you need to know is whether the column is NULL, you could try changing your query to:
SELECT COUNT(1) FROM sentence WHERE id = $1 AND structure IS NOT NULL
with or without the NOT.
If you want to make the logic simpler so any error is an actual error, I'd consider changing the select value to something like:
COALESCE( structure::TEXT, ''::TEXT ) AS "structure"
so it should never be NULL. That should work as long as an empty string isn't a valid non-NULL value for that column.
Otherwise, I may have misunderstood your problem.
I have the problem with the following CTE expression because prev_count in new_values is being interpreted as text, but the column I'm updating in counts is type integer. I'm getting this error on the marked line:
ERROR: column "prev_count" is of type integer but expression is of type text
LINE 12: prev_count = new_values.prev_count
Here's the query:
WITH
new_values (word,count,txid,prev_count) AS (
VALUES ('cat',1,5,NULL)),
updated AS (
UPDATE
counts t
SET
count = new_values.count,
txid = new_values.txid,
prev_count = new_values.prev_count -- ERROR HERE
FROM
new_values
WHERE (
t.word = new_values.word
)
RETURNING t.*)
INSERT INTO counts(
word,count,txid,prev_count
) SELECT
word,count,txid,prev_count FROM new_values
WHERE NOT EXISTS (
SELECT 1 FROM updated WHERE (updated.word = new_values.word))
My question is, what's an elegant way to fix the error? I would rather specify the type of prev_count in new_values instead of adding an explicit cast, but I don't see anything like that in the docs.
Adding this here as an explicit answer along with a detailed explanation.
The fix is:
WITH
new_values (word,count,txid,prev_count) AS (
VALUES ('cat',1,5,NULL::text)),
As a_horse_with_no_name suggested in the comments.
Why is this necessary? Because the row specification comes from the VALUES section and NULL is unknown. In this case PostgreSQL helpfully casts to text. But that is not what you want so you have to give a type to the NULL.
This often comes up in other cases too, such as UNION statements where a NULL in the first segment in the column list can be given an implicit type which clashes with the type of the column in another segment. So this is a tricky corner worth knowing about.
I have a table with a varchar column, and I want to find values that match a certain number. So lets say that column contains the following entries (except with millions of rows in real life):
123456789012
2345678
3456
23 45
713?2
00123456789012
So I decide I want all the rows which are numerically 123456789012 write a statement that looks something like this:
SELECT * FROM MyTable WHERE CAST(MyColumn as bigint) = 123456789012
It should return the first and last row, but instead the whole query blows up because it can't convert the "23 45" and "713?2" to bigint.
Is there another way to do the conversion that will return NULL for values that can't convert?
SQL Server does NOT guarantee boolean operator short-circuit, see On SQL Server boolean operator short-circuit. So all solution using ISNUMERIC(...) AND CAST(...) are fundamentally flawed (they may work, but hey can arbitrarily fail later dependiong on the generated plan). A better solution is using CASE, as Thomas suggests: CASE ISNUMERIC(...) WHEN 1 THEN CAST(...) ELSE NULL END. But, as gbn pointed out, ISNUMERIC is notoriously finicky in identifying what 'numeric' means and many cases where one would expect it to return 0 it returns 1. So mixing the CASE with the LIKE:
CASE WHEN MyRow NOT LIKE '%[^0-9]%' THEN CAST(MyRow as bigint) ELSE NULL END
But the real problem is that if you have millions of rows and you have to search them like this, you'll always end up scanning end-to-end since the expression is not SARG-able (no matter how we rewrite it). The real issue here is data purity, and should be addressed at the appropriate level, where the data is populated. Another thing to consider is if is possible to create a persisted computed column with this expression and create a filtered index on it which eliminates NULL (ie. non-numeric). That would speed up things a little.
If you are using SQL Server 2012 you can use the 2 new methods:
TRY_CAST()
TRY_CONVERT()
Both methods are equivalent. They return a value cast to the specified data type if the cast succeeds; otherwise, returns null. The only difference is that CONVERT is SQL Server specific, CAST is ANSI. using CAST will make your code more portable (although not sure if any other database provider implements TRY_CAST)
ISNUMERIC will accept empty string and values like 1.23 or 5E-04 so could be unreliable.
And you don't know what order things will be evaluated in so it could still fail (SQL is declarative, not procedural, so the WHERE clause probably won't be evaluated left to right)
So:
you want to accept value that consist only of the characters 0-9
you need to materialise the "number" filter so it's applied before CAST
Something like:
SELECT
*
FROM
(
SELECT TOP 2000000000 *
FROM MyTable
WHERE MyColumn NOT LIKE '%[^0-9]%' --double negative rejects anything except 0-9
ORDER BY MyColumn
) foo
WHERE
CAST(MyColumn as bigint) = 123456789012 --applied after number check
Edit: quick example that fails.
CREATE TABLE #foo (bigintstring varchar(100))
INSERT #foo (bigintstring )VALUES ('1.23')
INSERT #foo (bigintstring )VALUES ('1 23')
INSERT #foo (bigintstring )VALUES ('123')
SELECT * FROM #foo
WHERE
ISNUMERIC(bigintstring) = 1
AND
CAST(bigintstring AS bigint) = 123
SELECT *
FROM MyTable
WHERE ISNUMERIC(MyRow) = 1
AND CAST(MyRow as float) = 123456789012
The ISNUMERIC() function should give you what you need.
SELECT * FROM MyTable
WHERE ISNUMERIC(MyRow) = 1
AND CAST(MyRow as bigint) = 123456789012
And to add a case statement like Thomas suggested:
SELECT * FROM MyTable
WHERE CASE(ISNUMERIC(MyRow)
WHEN 1 THEN CAST(MyRow as bigint)
ELSE NULL
END = 123456789012
http://msdn.microsoft.com/en-us/library/ms186272.aspx
SELECT *
FROM MyTable
WHERE (ISNUMERIC(MyColumn) = 1) AND (CAST(MyColumn as bigint) = 123456789012)
Additionally you can use a CASE statement in order to get null values.
SELECT
CASE
WHEN (ISNUMERIC(MyColumn) = 1) THEN CAST(MyColumn as bigint)
ELSE NULL
END AS 'MyColumnAsBigInt'
FROM tableName
If you require additional filtering, for numerics which are not valid to be cast to bigint, you can use the following instead of ISNUMERIC:
PATINDEX('%[^0-9]%',MyColumn)) = 0
If you need decimal values instead of integers, cast to float instead and change the regex to '%[^0-9.]%'
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