- Categories:
AS_<object_type>¶
You can use this family of functions to perform strict casting of VARIANT values to values of other data types:
- See also:
General usage notes¶
If the type of the value in the VARIANT argument doesn’t match the output value, then NULL is returned. For example, if the AS_DATE function is passed a VARIANT value that doesn’t contain a DATE value, then NULL is returned.
If the input is NULL, the output is NULL.
Examples¶
The following examples use AS_object_type
functions.
Cast values in VARIANT columns to different data types¶
Create the table and load data into it:
CREATE OR REPLACE TABLE multiple_types_example (
array1 VARIANT,
array2 VARIANT,
boolean1 VARIANT,
char1 VARIANT,
varchar1 VARIANT,
decimal1 VARIANT,
double1 VARIANT,
integer1 VARIANT,
object1 VARIANT);
INSERT INTO multiple_types_example
(array1, array2, boolean1, char1, varchar1,
decimal1, double1, integer1, object1)
SELECT
TO_VARIANT(TO_ARRAY('Example')),
TO_VARIANT(ARRAY_CONSTRUCT('Array-like', 'example')),
TO_VARIANT(TRUE),
TO_VARIANT('X'),
TO_VARIANT('Y'),
TO_VARIANT(1.23::DECIMAL(6, 3)),
TO_VARIANT(3.21::DOUBLE),
TO_VARIANT(15),
TO_VARIANT(TO_OBJECT(PARSE_JSON('{"Tree": "Pine"}')));
Query the table and cast values in the VARIANT columns to values of different data types:
SELECT AS_ARRAY(array1) AS array1,
AS_ARRAY(array2) AS array2,
AS_BOOLEAN(boolean1) AS boolean,
AS_CHAR(char1) AS char,
AS_VARCHAR(varchar1) AS varchar,
AS_DECIMAL(decimal1, 6, 3) AS decimal,
AS_DOUBLE(double1) AS double,
AS_INTEGER(integer1) AS integer,
AS_OBJECT(object1) AS object
FROM multiple_types_example;
+-------------+-----------------+---------+------+---------+---------+--------+---------+------------------+
| ARRAY1 | ARRAY2 | BOOLEAN | CHAR | VARCHAR | DECIMAL | DOUBLE | INTEGER | OBJECT |
|-------------+-----------------+---------+------+---------+---------+--------+---------+------------------|
| [ | [ | True | X | Y | 1.230 | 3.21 | 15 | { |
| "Example" | "Array-like", | | | | | | | "Tree": "Pine" |
| ] | "example" | | | | | | | } |
| | ] | | | | | | | |
+-------------+-----------------+---------+------+---------+---------+--------+---------+------------------+
Compute the average of numeric values in a VARIANT column¶
Compute the average of all numeric values from a VARIANT column in the vartab
table:
Create the table and load data into it:
CREATE OR REPLACE TABLE vartab (n NUMBER(2), v VARIANT);
INSERT INTO vartab
SELECT column1 AS n, PARSE_JSON(column2) AS v
FROM VALUES (1, 'null'),
(2, null),
(3, 'true'),
(4, '-17'),
(5, '123.12'),
(6, '1.912e2'),
(7, '"Om ara pa ca na dhih" '),
(8, '[-1, 12, 289, 2188, false,]'),
(9, '{ "x" : "abc", "y" : false, "z": 10} ')
AS vals;
Show the data types of the values (some of which are numeric):
SELECT n, AS_REAL(v), TYPEOF(v)
FROM vartab
ORDER BY n;
+---+------------+------------+
| N | AS_REAL(V) | TYPEOF(V) |
|---+------------+------------|
| 1 | NULL | NULL_VALUE |
| 2 | NULL | NULL |
| 3 | NULL | BOOLEAN |
| 4 | -17 | INTEGER |
| 5 | 123.12 | DECIMAL |
| 6 | 191.2 | DOUBLE |
| 7 | NULL | VARCHAR |
| 8 | NULL | ARRAY |
| 9 | NULL | OBJECT |
+---+------------+------------+
Use the AS_REAL function with the AVG function to compute the average of all numeric values
from the VARIANT column v
:
SELECT AVG(AS_REAL(v)) FROM vartab;
+-----------------+
| AVG(AS_REAL(V)) |
|-----------------|
| 99.106666667 |
+-----------------+