Spark Scala
In this section, you will find information about Errors, Warnings, and Issues on the ApacheSpark Scala
Issue Codes
Parsing errors, conversion exceptions caused by ApacheSpark Scala. The user should contact to us (sma-support@snowflake.com) to fix the issue.
Code
Description
Category
Deprecated since
Not supported spark version.
File with parsing errors.
Repartition is not supported
Broadcast is not supported
Spark session builder method is not supported
Spark session builder option is not supported
Writer format value is not supported
Writer option is not supported
Writer method is not supported
Reader format value is not supported
Reader option is not supported
Reader method is not supported
CreateDecimalType is not supported
org.apache.spark.sql.functions.next_day has a workaround
org.apache.spark.sql.functions.repeat has a workaround
org.apache.spark.sql.functions.round has a workaround
org.apache.spark.sql.functions.split has a workaround
org.apache.spark.sql.functions.translate has a workaround
org.apache.spark.sql.functions.trunc has a workaround
org.apache.spark.sql.Column.endsWith has a workaround
org.apache.spark.sql.functions.asin has a workaround
org.apache.spark.sql.functions.atan has a workaround
org.apache.spark.sql.functions.corr has a workaround
org.apache.spark.sql.functions.cos has a workaround
org.apache.spark.sql.functions.cosh has a workaround
org.apache.spark.sql.functions.count has a workaround
org.apache.spark.sql.functions.covar_pop has a workaround
org.apache.spark.sql.functions.covar_samp has a workaround
org.apache.spark.sql.functions.exp has a workaround
org.apache.spark.sql.functions.floor has a workaround
org.apache.spark.sql.functions.greatest has a workaround
org.apache.spark.sql.functions.grouping has a workaround
org.apache.spark.sql.functions.grouping_id has a workaround
org.apache.spark.sql.functions.least has a workaround
org.apache.spark.sql.functions.log has a workaround
org.apache.spark.sql.functions.mean has a workaround
org.apache.spark.sql.functions.min has a workaround
org.apache.spark.sql.functions.sin has a workaround
org.apache.spark.sql.functions.sinh has a workaround
org.apache.spark.sql.functions.sqrt has a workaround
org.apache.spark.sql.functions.stddev has a workaround
org.apache.spark.sql.functions.stddev_pop has a workaround
An error occurred when loading the symbol table
The symbol table could not be loaded
org.apache.spark.sql.functions.sumDistinct has a workaround
org.apache.spark.sql.functions.tan has a workaround
org.apache.spark.sql.functions.tanh has a workaround
org.apache.spark.sql.functions.toDegrees has a workaround
org.apache.spark.sql.functions.toRadians has a workaround
org.apache.spark.sql.functions.var_pop has a workaround
org.apache.spark.sql.functions.var_samp has a workaround
org.apache.spark.sql.functions.variance has a workaround
org.apache.spark.sql.functions.max has a workaround
org.apache.spark.sql.functions.ceil has a workaround
org.apache.spark.sql.functions.countDistinct has a workaround
org.apache.spark.sql.functions.degrees has a workaround
org.apache.spark.sql.functions.kurtosis has a workaround
org.apache.spark.sql.functions.skewness has a workaround
org.apache.spark.sql.functions.stddev_samp has a workaround
org.apache.spark.sql.functions.sum has a workaround
Element is not a literal.
Parameter is not supported for reader option.
Reader format on DataFrameReader is undefined.
Parameter is not supported for reader format.
Spark element with a given argument is not supported.
Spark element is missing on the method chaining.
The single-parameter udf function is supported in Snowpark but it might require manual intervention.
The two-parameter udf function is not supported in Snowpark.
