pyspark.sql.tvf.TableValuedFunction

class pyspark.sql.tvf.TableValuedFunction(sparkSession)

Interface for invoking table-valued functions in Spark SQL.

Methods

collations()	Get all of the Spark SQL string collations.
explode(collection)	Returns a DataFrame containing a new row for each element in the given array or map.
explode_outer(collection)	Returns a DataFrame containing a new row for each element with position in the given array or map.
inline(input)	Explodes an array of structs into a table.
inline_outer(input)	Explodes an array of structs into a table.
json_tuple(input, *fields)	Creates a new row for a json column according to the given field names.
posexplode(collection)	Returns a DataFrame containing a new row for each element with position in the given array or map.
posexplode_outer(collection)	Returns a DataFrame containing a new row for each element with position in the given array or map.
range(start[, end, step, numPartitions])	Create a DataFrame with single pyspark.sql.types.LongType column named id, containing elements in a range from start to end (exclusive) with step value step.
sql_keywords()	Get Spark SQL keywords.
stack(n, *fields)	Separates col1, ..., colk into n rows.
variant_explode(input)	Separates a variant object/array into multiple rows containing its fields/elements.
variant_explode_outer(input)	Separates a variant object/array into multiple rows containing its fields/elements.