posexplode_outer
table-valued generator function
Applies to: Databricks SQL Databricks Runtime
Returns rows by un-nesting the array with numbering of positions using OUTER
semantics.
In Databricks Runtime 16.1 and above this function supports named parameter invocation.
Syntax
posexplode_outer(collection)
Arguments
collection
: An ARRAY or MAP expression.
Returns
A set of rows composed of the position and the elements of the array or the keys and values of the map.
The columns produced by posexplode_outer
of an array are named pos
and col
.
The columns for a map are called pos
, key
and value
.
If collection
is NULL
, a single row with NULLs for the array or map values.
Applies to: Databricks Runtime 12.1 and earlier:
posexplode_outer
can only be placed in theSELECT
list as the root of an expression or following a LATERAL VIEW. When placing the function in theSELECT
list there must be no other generator function in the sameSELECT
list or UNSUPPORTED_GENERATOR.MULTI_GENERATOR is raised.Applies to: Databricks SQL Databricks Runtime 12.2 LTS and above:
Invocation from the LATERAL VIEW clause or the
SELECT
list is deprecated. Instead, invokeposexplode_outer
as a table_reference.
Examples
Applies to: Databricks Runtime 12.1 and earlier:
> SELECT posexplode_outer(array(10, 20)) AS elem, 'Spark';
0 10 Spark
1 20 Spark
> SELECT posexplode_outer(map(1, 'a', 2, 'b')) AS (num, val), 'Spark';
0 1 a Spark
1 2 b Spark
> SELECT posexplode_outer(array(1, 2)), posexplode_outer(array(3, 4));
Error: UNSUPPORTED_GENERATOR.MULTI_GENERATOR
Applies to: Databricks SQL Databricks Runtime 12.2 LTS and above:
> SELECT pos, col FROM posexplode_outer(array(10, 20));
0 10
1 20
> SELECT pos, key, value FROM posexplode_outer(map(10, 'a', 20, 'b'));
0 10 a
1 22 b
> SELECT p1.*, p2.* FROM posexplode_outer(array(1, 2)) AS p1, posexplode_outer(array(3, 4)) AS p2;
0 1 0 3
0 1 1 4
1 2 0 3
1 2 1 4
-- Using lateral correlation in Databricks 12.2 and above
> SELECT p1.*, p2.* FROM posexplode_outer(array(1, 2)) AS p1, LATERAL posexplode_outer(array(3 * p1.col, 4 * p1.col)) AS p2;
0 1 0 3
0 1 1 4
1 2 0 6
1 2 1 8