Michael Chirico created SPARK-26331: ---------------------------------------
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. -- This message was sent by Atlassian JIRA (v7.6.3#76005) --------------------------------------------------------------------- To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org For additional commands, e-mail: issues-h...@spark.apache.org