org.apache.spark.sql.expressions.UserDefinedFunction.scala Maven / Gradle / Ivy
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* contributor license agreements. See the NOTICE file distributed with
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* The ASF licenses this file to You under the Apache License, Version 2.0
* (the "License"); you may not use this file except in compliance with
* the License. You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
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package org.apache.spark.sql.expressions
import org.apache.spark.annotation.Experimental
import org.apache.spark.sql.catalyst.expressions.ScalaUDF
import org.apache.spark.sql.Column
import org.apache.spark.sql.functions
import org.apache.spark.sql.types.DataType
/**
* A user-defined function. To create one, use the `udf` functions in [[functions]].
* Note that the user-defined functions must be deterministic. Due to optimization,
* duplicate invocations may be eliminated or the function may even be invoked more times than
* it is present in the query.
* As an example:
* {{{
* // Defined a UDF that returns true or false based on some numeric score.
* val predict = udf((score: Double) => if (score > 0.5) true else false)
*
* // Projects a column that adds a prediction column based on the score column.
* df.select( predict(df("score")) )
* }}}
*
* @since 1.3.0
*/
@Experimental
case class UserDefinedFunction protected[sql] (
f: AnyRef,
dataType: DataType,
inputTypes: Option[Seq[DataType]]) {
def apply(exprs: Column*): Column = {
Column(ScalaUDF(f, dataType, exprs.map(_.expr), inputTypes.getOrElse(Nil)))
}
}