If True, then the sort will be in ascending order.
If False, then the sort will be in descending order.
If a list of booleans is passed, then sort will respect this order. For example, if [True,False] is passed and cols=["colA","colB"], then the DataFrame will first be sorted in ascending order of colA, and then in descending order of colB. Note that the second sort will be relevant only when there are duplicate values in colA.

By default, ascending=True.

Return Value

A PySpark DataFrame (pyspark.sql.dataframe.DataFrame).

Examples

Consider the following PySpark DataFrame:


        
        
            
                
                
                    df = spark.createDataFrame([["Alex", 22, 200], ["Bob", 24, 300], ["Cathy", 22, 100]], ["name", "age", "salary"])
df.show()
                
            
            +-----+---+------+
| name|age|salary|
+-----+---+------+
| Alex| 22|   200|
|  Bob| 24|   300|
|Cathy| 22|   100|
+-----+---+------+

Sorting PySpark DataFrame by single column in ascending order

To sort by age in ascending order:


        
        
            
                
                
                    df.orderBy("age").show()
                
            
            +-----+---+------+
| name|age|salary|
+-----+---+------+
| Alex| 22|   200|
|Cathy| 22|   100|
|  Bob| 24|   300|
+-----+---+------+

Sorting PySpark DataFrame by multiple columns in ascending order

To sort by age, and then by salary (both by ascending order):


        
        
            
                
                
                    df.orderBy(["age","salary"]).show()
                
            
            +-----+---+------+
| name|age|salary|
+-----+---+------+
|Cathy| 22|   100|
| Alex| 22|   200|
|  Bob| 24|   300|
+-----+---+------+

Sorting PySpark DataFrame by descending order

To sort by descending order, set ascending=False:


        
        
            
                
                
                    df.orderBy("age", ascending=False).show()
                
            
            +-----+---+------+
| name|age|salary|
+-----+---+------+
|  Bob| 24|   300|
| Alex| 22|   200|
|Cathy| 22|   100|
+-----+---+------+

Published by Isshin Inada

Edited by 0 others

Did you find this page useful?

thumb_up

thumb_down

Comment

Citation

Ask a question or leave a feedback...

Official PySpark Documentation

https://spark.apache.org/docs/latest/api/python/reference/api/pyspark.sql.DataFrame.orderBy.html

thumb_up

thumb_down

chat_bubble_outline

settings

Enjoy our search

Hit / to insta-search docs and recipes!