ai.h2o.sparkling.ml.features.ColumnPruner.scala Maven / Gradle / Ivy

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/*
 * Licensed to the Apache Software Foundation (ASF) under one or more
 * contributor license agreements.  See the NOTICE file distributed with
 * this work for additional information regarding copyright ownership.
 * 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
 *
 * Unless required by applicable law or agreed to in writing, software
 * distributed under the License is distributed on an "AS IS" BASIS,
 * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 * See the License for the specific language governing permissions and
 * limitations under the License.
 */
package ai.h2o.sparkling.ml.features

import ai.h2o.sparkling.ml.params.ColumnPrunerParams
import ai.h2o.sparkling.ml.utils.H2OParamsReadable
import org.apache.spark.annotation.DeveloperApi
import org.apache.spark.ml.Transformer
import org.apache.spark.ml.param._
import org.apache.spark.ml.util.{DefaultParamsWritable, Identifiable}
import org.apache.spark.sql.types.{StructField, StructType}
import org.apache.spark.sql.{DataFrame, Dataset}

/**
  * Column pruner removes specified columns in the input dataset
  */
class ColumnPruner(override val uid: String) extends Transformer with ColumnPrunerParams with DefaultParamsWritable {

  def this() = this(Identifiable.randomUID("columnPruner"))

  @DeveloperApi
  override def transformSchema(schema: StructType): StructType = {
    val columnsToLeft = if (getKeep()) {
      schema.fieldNames.filter(getColumns().contains(_))
    } else {
      schema.fieldNames.filter(!getColumns().contains(_))
    }

    StructType(columnsToLeft.map { col =>
      StructField(col, schema(col).dataType, schema(col).nullable, schema(col).metadata)
    })
  }

  override def transform(dataset: Dataset[_]): DataFrame = {
    val columnsToRemove = if (getKeep()) {
      dataset.columns.filter(!getColumns().contains(_))
    } else {
      dataset.columns.filter(getColumns().contains(_))
    }
    var resultDataset = dataset
    columnsToRemove.foreach { col =>
      resultDataset = resultDataset.drop(col)
    }
    resultDataset.toDF()
  }

  override def copy(extra: ParamMap): Transformer = defaultCopy(extra)
}

object ColumnPruner extends H2OParamsReadable[ColumnPruner]