pyspark.sql.DataFrame.sort¶
-
DataFrame.sort(*cols: Union[str, pyspark.sql.column.Column, List[Union[str, pyspark.sql.column.Column]]], **kwargs: Any) → pyspark.sql.dataframe.DataFrame¶ Returns a new
DataFramesorted by the specified column(s).- Parameters
- 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')]