zhengruifeng commented on a change in pull request #27488: [SPARK-26580][SQL][ML][FOLLOW-UP] Throw exception when use untyped UDF by default URL: https://github.com/apache/spark/pull/27488#discussion_r380500081
########## File path: docs/sql-migration-guide.md ########## @@ -63,8 +63,8 @@ license: | - Since Spark 3.0, JSON datasource and JSON function `schema_of_json` infer TimestampType from string values if they match to the pattern defined by the JSON option `timestampFormat`. Set JSON option `inferTimestamp` to `false` to disable such type inferring. - - In Spark version 2.4 and earlier, if `org.apache.spark.sql.functions.udf(Any, DataType)` gets a Scala closure with primitive-type argument, the returned UDF will return null if the input values is null. Since Spark 3.0, the UDF will return the default value of the Java type if the input value is null. For example, `val f = udf((x: Int) => x, IntegerType)`, `f($"x")` will return null in Spark 2.4 and earlier if column `x` is null, and return 0 in Spark 3.0. This behavior change is introduced because Spark 3.0 is built with Scala 2.12 by default. - + - Since Spark 3.0, using `org.apache.spark.sql.functions.udf(AnyRef, DataType)` is not allowed by default. Set `spark.sql.legacy.allowUntypedScalaUDF` to true to keep using it. But please note that, in Spark version 2.4 and earlier, if `org.apache.spark.sql.functions.udf(AnyRef, DataType)` gets a Scala closure with primitive-type argument, the returned UDF will return null if the input values is null. However, since Spark 3.0, the UDF will return the default value of the Java type if the input value is null. For example, `val f = udf((x: Int) => x, IntegerType)`, `f($"x")` will return null in Spark 2.4 and earlier if column `x` is null, and return 0 in Spark 3.0. This behavior change is introduced because Spark 3.0 is built with Scala 2.12 by default. + Review comment: nit: remove spaces here? ---------------------------------------------------------------- This is an automated message from the Apache Git Service. To respond to the message, please log on to GitHub and use the URL above to go to the specific comment. For queries about this service, please contact Infrastructure at: us...@infra.apache.org With regards, Apache Git Services --------------------------------------------------------------------- To unsubscribe, e-mail: reviews-unsubscr...@spark.apache.org For additional commands, e-mail: reviews-h...@spark.apache.org
