SPRKSCL1131

org.apache.spark.sql.functions.grouping

Message: org.apache.spark.sql.functions.grouping has a workaround, see documentation for more info

Category: Warning

Description

This issue appears when the SMA detects a use of the org.apache.spark.sql.functions.grouping function, which has a workaround.

Scenario

Input

Below is an example of the org.apache.spark.sql.functions.grouping function, first used with a column name as an argument and then with a column object.

val df = Seq(("Alice", 2), ("Bob", 5)).toDF("name", "age")
val result1 = df.cube("name").agg(grouping("name"), sum("age"))
val result2 = df.cube("name").agg(grouping(col("name")), sum("age"))

Output

The SMA adds the EWI SPRKSCL1131 to the output code to let you know that this function is not fully supported by Snowpark, but it has a workaround.

val df = Seq(("Alice", 2), ("Bob", 5)).toDF("name", "age")
/*EWI: SPRKSCL1131 => org.apache.spark.sql.functions.grouping has a workaround, see documentation for more info*/
val result1 = df.cube("name").agg(grouping("name"), sum("age"))
/*EWI: SPRKSCL1131 => org.apache.spark.sql.functions.grouping has a workaround, see documentation for more info*/
val result2 = df.cube("name").agg(grouping(col("name")), sum("age"))

Recommended fix

Snowpark has an equivalent grouping function that receives a column object as an argument. For that reason, the Spark overload that receives a column object as an argument is directly supported by Snowpark and does not require any changes.

For the overload that receives a string argument, you can convert the string into a column object using the com.snowflake.snowpark.functions.col function as a workaround.

val df = Seq(("Alice", 2), ("Bob", 5)).toDF("name", "age")
val result1 = df.cube("name").agg(grouping(col("name")), sum("age"))
val result2 = df.cube("name").agg(grouping(col("name")), sum("age"))

Additional recommendations

• For more support, you can email us at [e-mail] or post an issue in the SMA.