pyspark.sql.DataFrame.sort

DataFrame.sort(*cols, **kwargs)

Returns a new DataFrame sorted by the specified column(s).

New in version 1.3.0.

Parameters:

colsstr, list, or Column, optional

list of Column or column names to sort by.

Other Parameters:

ascendingbool or list, optional

boolean or list of boolean (default True). Sort ascending vs. descending. Specify list for multiple sort orders. If a list is specified, length of the list must equal length of the cols.

Examples

>>> df.sort(df.age.desc()).collect()
[Row(age=5, name='Bob'), Row(age=2, name='Alice')]
>>> df.sort("age", ascending=False).collect()
[Row(age=5, name='Bob'), Row(age=2, name='Alice')]
>>> df.orderBy(df.age.desc()).collect()
[Row(age=5, name='Bob'), Row(age=2, name='Alice')]
>>> from pyspark.sql.functions import *
>>> df.sort(asc("age")).collect()
[Row(age=2, name='Alice'), Row(age=5, name='Bob')]
>>> df.orderBy(desc("age"), "name").collect()
[Row(age=5, name='Bob'), Row(age=2, name='Alice')]
>>> df.orderBy(["age", "name"], ascending=[0, 1]).collect()
[Row(age=5, name='Bob'), Row(age=2, name='Alice')]

pyspark.sql.DataFrame.show pyspark.sql.DataFrame.sortWithinPartitions