नोट
इस पेज तक पहुँच के लिए प्रमाणन की आवश्यकता होती है. आप साइन इन करने या निर्देशिकाओं को बदलने का प्रयास कर सकते हैं.
इस पेज तक पहुँच के लिए प्रमाणन की आवश्यकता होती है. आप निर्देशिकाओं को बदलने का प्रयास कर सकते हैं.
Converts a column containing a StructType into a CSV string. Throws an exception, in the case of an unsupported type.
Syntax
from pyspark.sql import functions as sf
sf.to_csv(col, options=None)
Parameters
| Parameter | Type | Description |
|---|---|---|
col |
pyspark.sql.Column or str |
Name of column containing a struct. |
options |
dict, optional | Options to control converting. Accepts the same options as the CSV datasource. |
Returns
pyspark.sql.Column: A CSV string converted from the given StructType.
Examples
Example 1: Converting a simple StructType to a CSV string
from pyspark.sql import Row, functions as sf
data = [(1, Row(age=2, name='Alice'))]
df = spark.createDataFrame(data, ("key", "value"))
df.select(sf.to_csv(df.value)).show()
+-------------+
|to_csv(value)|
+-------------+
| 2,Alice|
+-------------+
Example 2: Converting a complex StructType to a CSV string
from pyspark.sql import Row, functions as sf
data = [(1, Row(age=2, name='Alice', scores=[100, 200, 300]))]
df = spark.createDataFrame(data, ("key", "value"))
df.select(sf.to_csv(df.value)).show(truncate=False)
+-------------------------+
|to_csv(value) |
+-------------------------+
|2,Alice,"[100, 200, 300]"|
+-------------------------+
Example 3: Converting a StructType with null values to a CSV string
from pyspark.sql import Row, functions as sf
from pyspark.sql.types import StructType, StructField, IntegerType, StringType
data = [(1, Row(age=None, name='Alice'))]
schema = StructType([
StructField("key", IntegerType(), True),
StructField("value", StructType([
StructField("age", IntegerType(), True),
StructField("name", StringType(), True)
]), True)
])
df = spark.createDataFrame(data, schema)
df.select(sf.to_csv(df.value)).show()
+-------------+
|to_csv(value)|
+-------------+
| ,Alice|
+-------------+
Example 4: Converting a StructType with different data types to a CSV string
from pyspark.sql import Row, functions as sf
data = [(1, Row(age=2, name='Alice', isStudent=True))]
df = spark.createDataFrame(data, ("key", "value"))
df.select(sf.to_csv(df.value)).show()
+-------------+
|to_csv(value)|
+-------------+
| 2,Alice,true|
+-------------+