[jira] [Created] (SPARK-26331) Allow SQL UDF registration to recognize default function values from Scala

["Michael Chirico (JIRA)" <ji...@apache.org>]

Michael Chirico created SPARK-26331:
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             Summary: Allow SQL UDF registration to recognize default function values from Scala
                 Key: SPARK-26331
                 URL: https://issues.apache.org/jira/browse/SPARK-26331
             Project: Spark
          Issue Type: Improvement
          Components: PySpark, SQL
    Affects Versions: 2.4.0
            Reporter: Michael Chirico


As described here:

[https://stackoverflow.com/q/53702727/3576984]

I have a UDF I would like to be flexible enough to accept 3 arguments (or in general n+k), but for the most part, only 2 (in general, n) are required. The natural approach to this is to implement the UDF with 3 arguments, one of which has a standard default value.

Copying a toy example from SO:

{{package myUDFs import org.apache.spark.sql.api.java.UDF3 class my_udf extends UDF3[Int, Int, Int, Int] { override def call(a: Int, b: Int, c: Int = 6): Int = { c*(a + b) } }}}

I would prefer the following to give the expected output of 18:

{{from pyspark.conf import SparkConf from pyspark.sql import SparkSession from pyspark.sql.types import IntType spark_conf = SparkConf().setAll([ ('spark.jars', 'myUDFs-assembly-0.1.1.jar') ]) spark = SparkSession.builder.appName('my_app').config(conf = spark_conf).enableHiveSupport().getOrCreate() spark.udf.registerJavaFunction("my_udf", "myUDFs.my_udf", IntType())}}

{{spark.sql('select my_udf(1, 2)').collect()}}

But it seems this is currently impossible.



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