SPRKSCL1128

org.apache.spark.sql.functions.exp

Message: org.apache.spark.sql.functions.exp 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.exp function, which has a workaround.

Scenario

Input

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

val df = Seq(1.0, 2.0, 3.0).toDF("value")
val result1 = df.withColumn("exp_value", exp("value"))
val result2 = df.withColumn("exp_value", exp(col("value")))

Output

The SMA adds the EWI SPRKSCL1128 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(1.0, 2.0, 3.0).toDF("value")
/*EWI: SPRKSCL1128 => org.apache.spark.sql.functions.exp has a workaround, see documentation for more info*/
val result1 = df.withColumn("exp_value", exp("value"))
/*EWI: SPRKSCL1128 => org.apache.spark.sql.functions.exp has a workaround, see documentation for more info*/
val result2 = df.withColumn("exp_value", exp(col("value")))

Recommended fix

Snowpark has an equivalent exp 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(1.0, 2.0, 3.0).toDF("value")
val result1 = df.withColumn("exp_value", exp(col("value")))
val result2 = df.withColumn("exp_value", exp(col("value")))

Additional recommendations

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