spooq.transformer.mapper_transformations.to_str

to_str(source_column=None, name=None, **kwargs: Any) → Union[partial, Column]

Convenience transformation that only casts to string.

Parameters

• source_column (str or Column) – Input column. Can be a name, pyspark column or pyspark function

• name (str, default -> derived from input column) – Name of the output column. (.alias(name))

Keyword Arguments

alt_src_cols (str, default -> no coalescing, only source_column) – Coalesce with source_column and columns from this parameter.

Examples

>>> input_df = spark.createDataFrame(
...     [
...         Row(input_key=123456),
...         Row(input_key=-123456),
...     ], schema="input_key int"
... )
>>>
>>> input_df.select(spq.to_str("input_key")).show(truncate=False)
+---------+
|123456   |
|-123456  |
+---------+
>>>
>>> mapping = [
...     ("original_value",    "input_key", spq.as_is),
...     ("transformed_value", "input_key", spq.to_str)
... ]
>>> output_df = Mapper(mapping).transform(input_df)
>>> output_df.show(truncate=False)
+--------------+-----------------+
|original_value|transformed_value|
+--------------+-----------------+
|123456        |123456           |
|-123456       |-123456          |
+--------------+-----------------+

Returns

This method returns a suitable type depending on how it was called. This ensures compability with Spooq’s mapper transformer - with or without explicit parameters - as well as direct calls via select, withColumn, where, …

Return type

partial or Column