Reputation: 383
I have the below data frame -
+----+-----+---+
| val|count| id|
+----+-----+---+
| a| 10| m1|
| b| 20| m1|
|null| 30| m1|
| b| 30| m2|
| c| 40| m2|
|null| 50| m2|
+----+-----+---+
created by -
val df1=Seq(
("a","10","m1"),
("b","20","m1"),
(null,"30","m1"),
("b","30","m2"),
("c","40","m2"),
(null,"50","m2")
)toDF("val","count","id")
I am trying to make a rank with the help of row_number() and window fuction as below.
df1.withColumn("rannk_num", row_number() over Window.partitionBy("id").orderBy("count")).show
+----+-----+---+---------+
| val|count| id|rannk_num|
+----+-----+---+---------+
| a| 10| m1| 1|
| b| 20| m1| 2|
|null| 30| m1| 3|
| b| 30| m2| 1|
| c| 40| m2| 2|
|null| 50| m2| 3|
+----+-----+---+---------+
But I have to filter those records with null values for column - val.
Expected output --
+----+-----+---+---------+
| val|count| id|rannk_num|
+----+-----+---+---------+
| a| 10| m1| 1|
| b| 20| m1| 2|
|null| 30| m1| NULL|
| b| 30| m2| 1|
| c| 40| m2| 2|
|null| 50| m2| NULL|
+----+-----+---+---------+
wondering if this is possible with minimal change. Also there can be 'n' number of values for the columns val and count.
Upvotes: 1
Views: 3948
Reputation: 42332
Filter those rows with null val, assign them a null row number, and union back to the original dataframe.
val df1=Seq(
("a","10","m1"),
("b","20","m1"),
(null,"30","m1"),
("b","30","m2"),
("c","40","m2"),
(null,"50","m2")
).toDF("val","count","id")
df1.filter("val is not null").withColumn(
"rannk_num", row_number() over Window.partitionBy("id").orderBy("count")
).union(
df1.filter("val is null").withColumn("rannk_num", lit(null))
).show
+----+-----+---+---------+
| val|count| id|rannk_num|
+----+-----+---+---------+
| a| 10| m1| 1|
| b| 20| m1| 2|
| b| 30| m2| 1|
| c| 40| m2| 2|
|null| 30| m1| null|
|null| 50| m2| null|
+----+-----+---+---------+
Upvotes: 4