Merk
Tilgang til denne siden krever autorisasjon. Du kan prøve å logge på eller endre kataloger.
Tilgang til denne siden krever autorisasjon. Du kan prøve å endre kataloger.
Converts the DataFrame into a TableArg object, which can be used as a table argument in a TVF (Table-Valued Function) including UDTF (User-Defined Table Function).
Syntax
asTable()
Returns
TableArg: A TableArg object representing a table argument.
Notes
After obtaining a TableArg from a DataFrame using this method, you can specify partitioning and ordering for the table argument by calling methods such as partitionBy, orderBy, and withSinglePartition on the TableArg instance.
Examples
from pyspark.sql.functions import udtf
@udtf(returnType="id: int, doubled: int")
class DoubleUDTF:
def eval(self, row):
yield row["id"], row["id"] * 2
df = spark.createDataFrame([(1,), (2,), (3,)], ["id"])
result = DoubleUDTF(df.asTable())
result.show()
# +---+-------+
# | id|doubled|
# +---+-------+
# | 1| 2|
# | 2| 4|
# | 3| 6|
# +---+-------+
df2 = spark.createDataFrame(
[(1, "a"), (1, "b"), (2, "c"), (2, "d")], ["key", "value"]
)
@udtf(returnType="key: int, value: string")
class ProcessUDTF:
def eval(self, row):
yield row["key"], row["value"]
result2 = ProcessUDTF(df2.asTable().partitionBy("key").orderBy("value"))
result2.show()
# +---+-----+
# |key|value|
# +---+-----+
# | 1| a|
# | 1| b|
# | 2| c|
# | 2| d|
# +---+-----+