I need help with a SQL convert statement. I have NetQuanity (masterTable) which is a varchar(15) and I have another table with Purchase price (PO TABLE) which is money. When I try to multiply them in a SQL view is gives me the error:
If your field is a VARCHAR, you'll need to CAST to the appropriate data type prior to your operation. e.g.
CAST(myVarCharField as INT) * myIntField
Be forewarned however, if you attempt to CAST this field to a numeric data type and it's not numeric, you'll be in the same boat.
I would recommend using CAST over CONVERT in your example, for the following reason defined in this SO post:
Related: T-SQL Cast versus Convert
Maybe try using the CONVERT function? CONVERT(money,NetQuantity).
First of all you have a data definition problem.
The first thing is to eliminate any non-numeric entries in the master table.
SELECT whatever FROM masterTable WHERE ISNUMERIC(NetQuanity)=1
The next step is to include this as a sub-query in the calculation.
In this query use CONVERT or CAST to convert the valid quanities to integer.
i.e.
CONVERT(INT, NetQuantity)
Related
I have a table of cars in my Postgres database, but a created the price column with varchar.
I want to convert this type to numeric or integer.
car database
You can change the table definition with ALTER TYPE, but you'll need a USING clause with your particular conversion. Related:
Rails Migrations: tried to change the type of column from string to integer
If your data sample tells the full story, this should work:
ALTER TABLE tbl
ALTER COLUMN price TYPE numeric USING right(price, -1)::numeric
right(price, -1) trims the first character, which is always $ in your sample. Remaining leading and trailing white space is no problem. Related:
Postgres data type cast
For anything else, adapt the expression.
The operation triggers a table rewrite, taking an exclusive lock on the table for the duration.
I chose numeric to cover fractional digits. See:
Which datatype should be used for currency?
I have a column that has the type of the dataset in text.
So I want to do something like this:
SELECT CAST ('100' AS %INTEGER%);
SELECT CAST (100 AS %TEXT%);
SELECT CAST ('100' AS (SELECT type FROM dataset_types WHERE id = 2));
Is that possible with PostgreSQL?
SQL is strongly typed and static. Postgres demands to know the number of columns and their data type a the time of the call. So you need dynamic SQL in one of the procedural language extensions for this. And then you still face the obstacle that functions (necessarily) have a fixed return type. Related:
Dynamically define returning row types based on a passed given table in plpgsql?
Function to return dynamic set of columns for given table
Or you go with a two-step flow. First concatenate the query string (with another SELECT query). Then execute the generated query string. Two round trips to the server.
SELECT '100::' || type FROM dataset_types WHERE id = 2; -- record resulting string
Execute the result. (And make sure you didn't open any vectors for SQL injection!)
About the short cast syntax:
Postgres data type cast
i have subquery, that returns me varchar column, in some cases this column contains only numeric values and in this cases i need to cast this column to bigint, i`ve trying to use CAST(case...) construction, but CASE is an expression that returns a single result and regardless of the path it always needs to result in the same data type (or implicitly convertible to the same data type). Is there any tricky way to change column datatype depending on condition in PostgreSQL or not? google cant help me((
SELECT
prefix,
module,
postfix,
id,
created_date
FROM
(SELECT
s."prefix",
coalesce(m."replica", to_char(CAST((m."id_type" * 10 ^ 12) AS bigint) + m."id", 'FM0000000000000000')) "module",
s."postfix",
s."id",
s."created_date"
FROM some_subquery
There is really no way to do what you want.
A SQL query returns a fixed set of columns, with the names and types being fixed. So, a priori what you want to do does not fit well within SQL.
You could work around this, by inventing your own type, that is either a big integer or a string. You could store the value as JSON. But those are work-arounds. The SQL query itself is really returning one "type" for each column; that is how SQL works.
I have searched both this great forum and googled around but unable to resolve this.
We have two tables (and trust me I have nothing to do with these tables). Both tables have a column called eventId.
However, in one table, data type for eventId is float and in the other table, it is nvarchar.
We are selecting from table1 where eventI is defined as float and saving that Id into table2 where eventId is defined as nvarchar(50).
As a result of descrepancy in data types, we are getting error converting datatype nvarchar to float.
Without fooling around with the database, I would like to cast the eventId to get rid of this error.
Any ideas what I am doing wrong with the code below?
SELECT
CAST(CAST(a.event_id AS NVARCHAR(50)) AS FLOAT) event_id_vre,
The problem is most likely because some of the rows have event_id that is empty. There are two ways to go about solving this:
Convert your float to nvarchar, rather than the other way around - This conversion will always succeed. The only problem here is if the textual representations differ - say, the table with float-as-nvarchar uses fewer decimal digits, or
Add a condition to check for empty IDs before the conversion - This may not work if some of the event IDs are non-empty strings, but they are not float-convertible either (e.g. there's a word in the field instead of a number).
The second solution would look like this:
SELECT
case when a.eventid <> ''
then cast(cast(a.event_id as nvarchar(50)) as float)
ELSE 0.0
END AS event_id_vre,
Convert float to nvarchar instead of nvarchar to float. Of course!
I have data greater to this number, if I attempt to get several sums of them like::
1,22826520941614E+24+1,357898350941614E+34+1,228367878888764E+26 I get as Result NULL, How to define the table Datatype for that kind of fields??
I am using float, but it does not work.
If you're getting NULL back, it's not the data type. It's because you have a null value in one of the rows of data. NULL + anything is NULL.
Change your Sum() to include a WHERE YourNumericColumn IS NOT NULL, or use COALESCE().
A float is sufficiently large to contain data of that range. It can store binary floating-point values from -1.79E+308 to 1.79E+308. I suspect an error elsewhere in your statement.