com.microsoft.ml.spark.stages.Lambda.scala Maven / Gradle / Ivy
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// Copyright (C) Microsoft Corporation. All rights reserved.
// Licensed under the MIT License. See LICENSE in project root for information.
package com.microsoft.ml.spark.stages
import com.microsoft.ml.spark.core.contracts.Wrappable
import org.apache.spark.SparkContext
import org.apache.spark.ml.{ComplexParamsReadable, ComplexParamsWritable, Transformer}
import org.apache.spark.ml.param.{ParamMap, UDFParam}
import org.apache.spark.ml.util.Identifiable
import org.apache.spark.sql.functions.udf
import org.apache.spark.sql.types.{StringType, StructType}
import org.apache.spark.sql.{DataFrame, Dataset, Row, SparkSession}
object Lambda extends ComplexParamsReadable[Lambda] {
def apply(f: Dataset[_] => DataFrame): Lambda = {
new Lambda().setTransform(f)
}
}
class Lambda(val uid: String) extends Transformer with Wrappable with ComplexParamsWritable {
def this() = this(Identifiable.randomUID("Lambda"))
val transformFunc = new UDFParam(this, "transformFunc", "holder for dataframe function")
def setTransform(f: Dataset[_] => DataFrame): this.type = {
set(transformFunc, udf(f, StringType))
}
def getTransform: Dataset[_] => DataFrame = {
$(transformFunc).f.asInstanceOf[Dataset[_] => DataFrame]
}
val transformSchemaFunc = new UDFParam(this, "transformSchemaFunc", "the output schema after the transformation")
def setTransformSchema(f: StructType => StructType): this.type = {
set(transformSchemaFunc, udf(f, StringType))
}
def getTransformSchema: StructType => StructType = {
$(transformSchemaFunc).f.asInstanceOf[StructType => StructType]
}
override def transform(dataset: Dataset[_]): DataFrame = {
getTransform(dataset)
}
def transformSchema(schema: StructType): StructType = {
if (get(transformSchemaFunc).isEmpty) {
val sc = SparkContext.getOrCreate()
val df = SparkSession.builder().getOrCreate().createDataFrame(sc.emptyRDD[Row], schema)
transform(df).schema
} else {
getTransformSchema(schema)
}
}
def copy(extra: ParamMap): Lambda = defaultCopy(extra)
}