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.
Related
I have a table with 2 varchar columns (name and value)
and I have such a query:
select * from attribute
where name = 'width' and cast( value as integer) > 12
This query works but I suppose there are could be an issue with execution plan because of index build over value column because it is technically varchar but we convert it to integer.
Are there ways to fix it ?
P.S. I can't change type to int because the database design implies that value could be any type.
Performance should not be your first worry here.
Your statement is prone to failures. You read this as:
read all rows with name = 'width'
of these rows cast all values to integer and only keep those with a value graeter than 12
But the DBMS is free to check conditions in the WHERE clause in any order. If the DBMS does that:
cast all values to integer and only keep the rows with a value graeter than 12
of these rows keep all with name = 'width'
the first step will already cause a runtime error, if there is a non-integer value in that table, which is likely.
So first get your query safe. The following should work:
select *
from
(
select *
from attribute
where name = 'width'
) widths
where cast(value as integer) > 12;
This will still fail, when your width contains non-integers. So, to get this even safe in case of invalid data in the table, you may want to add a check that the value only contains digits in the subquery.
And yes, this won't become super-fast. You sacrifice speed (and data consistency checks) for flexibility with this data model.
What you can do, however, is create an index on both columns, so the DBMS can quickly find all width rows and then have the value directly at hand, before it accesses the table:
create index idx on attribute (name, value);
As far as I know, there is no fail-safe cast function in PostgreSQL. Otherwise you could use this and have a function index instead. I may be wrong, so maybe someone can come up with a better solution here.
How do I specify a literal number with a limited precision in the SELECT clause of an Oracle PL/SQL query? Is CAST the only way?
I want to do this, but the column's type ends up as NUMBER, whereas I want the type to match l.changed_rows_log_id, which is a NUMBER(18,0).
SELECT COALESCE(l.changed_rows_log_id, 1) AS Col1 FROM mytable l;
If I leave it at that, consuming processes may balk at type NUMBER since it might contain very large numbers--all because of a literal 1.
Instead I have to do this, awkwardly. Is there a better way?
SELECT CAST(COALESCE(l.changed_rows_log_id, 1) AS NUMBER(18,0)) AS Col1 FROM mytable l;
There seems to be no other way than using CAST as in the question. Seems like a real shortcoming of PL/SQL syntax.
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
When performing a select query from a data base the returned result will have columns of a certain type.
If you perform a simple query like
select name as FirstName
from database
then the type of the resulting FirstName column will be that of database.name.
If you perform a query like
select age*income
from database
then the resulting data type will be that of the return value from the age*income expression.
What happens you use something like
select try_convert(float, mycolumn)
from database
where database.mycolumn has type of nvarchar. I assume that the resulting column has type of float which is decided by the return type of the first call to try_convert.
But consider this example
select coalesce(try_convert(float, mycolumn), mycolumn)
from database
which should give a column with the values of mycolumn unchanged if try_convert fails, but mycolumn as a float when/if that is possible.
Is this determination made as the first row is handled?
Or will the type always be determined by the function called independently of the data in the rows?
Is it possible to conditionally perform a conversion?
I would like to convert to float in the case where this is possible for all rows and leave unchanged in case it fails for any row.
Update 1
It seems that the answer to the first part of the question is that the column type is determined by the expression at compile time which means that you cannot have a dynamic type of your column depending on the data.
I see two workaround for this
Option 1
For each column count the number of not null rows of try_convert(float, mycolumn) and if this number is 0 then do not perform conversion. This will of course read the rows many times and might be inefficient.
Option 2
Simple repeat all columns; once without conversion and once with conversion and then simply use the interesting one.
One could also perform another select statement where only columns with non-null values are included.
Background
I have a dynamically generated pivot table with many (~200 columns) of which some have string values and others have numbers.
I would like to cast all columns as float where this is possible and leave the other columns unchanged (or cast as nvarchar).
The data
The data is mostly NULL values with some columns having text string and other columns having numbers. There are no columns with "mixed" content.
The types are determined at compile time, not at execution. try_convert(float, ...) knows exactly the type at parse/compile time, because float here is a keyword, not a value. As for expressions like COALESCE(foo, bar) the type similarly determined at compile time, following the rules of data type precedence lad already linked.
When you build your dynamic pivot you'll have to know the result type, using the same inference rules the SQL parser/compiler uses. I understand some rules are counter intuitive, when in doubt, test it out.
For the detail oriented: some expressions types can be determined at parse time, eg. N'foo'. But most have to be resolved at compile time, when the names of tables and columns are bind to actual object in the database, because only then the type is discovered.
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.