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.
Returns a new DataFrame sorted by the specified column(s).
Syntax
sort(*cols: Union[int, str, Column, List[Union[int, str, Column]]], **kwargs: Any)
Parameters
| Parameter | Type | Description |
|---|---|---|
cols |
int, str, list, or Column, optional | list of Column or column names or column ordinals to sort by. |
ascending |
bool or list, optional, default True | boolean or list of boolean. Sort ascending vs. descending. Specify list for multiple sort orders. If a list is specified, the length of the list must equal the length of the cols. |
Returns
DataFrame: Sorted DataFrame.
Notes
A column ordinal starts from 1, which is different from the 0-based __getitem__. If a column ordinal is negative, it means sort descending.
Examples
from pyspark.sql import functions as sf
df = spark.createDataFrame([
(2, "Alice"), (5, "Bob")], schema=["age", "name"])
df.sort(sf.asc("age")).show()
# +---+-----+
# |age| name|
# +---+-----+
# | 2|Alice|
# | 5| Bob|
# +---+-----+
df.sort(df.age.desc()).show()
# +---+-----+
# |age| name|
# +---+-----+
# | 5| Bob|
# | 2|Alice|
# +---+-----+
df.sort("age", ascending=False).show()
# +---+-----+
# |age| name|
# +---+-----+
# | 5| Bob|
# | 2|Alice|
# +---+-----+
df = spark.createDataFrame([
(2, "Alice"), (2, "Bob"), (5, "Bob")], schema=["age", "name"])
df.orderBy(sf.desc("age"), "name").show()
# +---+-----+
# |age| name|
# +---+-----+
# | 5| Bob|
# | 2|Alice|
# | 2| Bob|
# +---+-----+