SPRKSCL1127

org.apache.spark.sql.functions.covar_samp

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

Scenario

Input

Below is an example of the org.apache.spark.sql.functions.covar_samp function, first used with column names as the arguments and then with column objects.

val df = Seq(
  (10.0, 20.0),
  (15.0, 25.0),
  (20.0, 30.0),
  (25.0, 35.0),
  (30.0, 40.0)
).toDF("value1", "value2")

val result1 = df.select(covar_samp("value1", "value2").as("sample_covariance"))
val result2 = df.select(covar_samp(col("value1"), col("value2")).as("sample_covariance"))

Output

The SMA adds the EWI SPRKSCL1127 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(
  (10.0, 20.0),
  (15.0, 25.0),
  (20.0, 30.0),
  (25.0, 35.0),
  (30.0, 40.0)
).toDF("value1", "value2")

/*EWI: SPRKSCL1127 => org.apache.spark.sql.functions.covar_samp has a workaround, see documentation for more info*/
val result1 = df.select(covar_samp("value1", "value2").as("sample_covariance"))
/*EWI: SPRKSCL1127 => org.apache.spark.sql.functions.covar_samp has a workaround, see documentation for more info*/
val result2 = df.select(covar_samp(col("value1"), col("value2")).as("sample_covariance"))

Recommended fix

Snowpark has an equivalent covar_samp function that receives two column objects as arguments. For that reason, the Spark overload that receives two column objects as arguments is directly supported by Snowpark and does not require any changes.

For the overload that receives two string arguments, you can convert the strings into column objects using the com.snowflake.snowpark.functions.col function as a workaround.

val df = Seq(
  (10.0, 20.0),
  (15.0, 25.0),
  (20.0, 30.0),
  (25.0, 35.0),
  (30.0, 40.0)
).toDF("value1", "value2")

val result1 = df.select(covar_samp(col("value1"), col("value2")).as("sample_covariance"))
val result2 = df.select(covar_samp(col("value1"), col("value2")).as("sample_covariance"))

Additional recommendations

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