| /* |
| * 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 org.apache.griffin.measure.execution.impl |
| |
| import org.apache.spark.sql.{Column, DataFrame, SparkSession} |
| import org.apache.spark.sql.functions._ |
| |
| import org.apache.griffin.measure.configuration.dqdefinition.MeasureParam |
| import org.apache.griffin.measure.execution.Measure |
| |
| case class CompletenessMeasure(measureParam: MeasureParam) extends Measure { |
| |
| import Measure._ |
| |
| private final val Complete: String = "complete" |
| private final val InComplete: String = "incomplete" |
| |
| override val supportsRecordWrite: Boolean = true |
| |
| override val supportsMetricWrite: Boolean = true |
| |
| override def impl(sparkSession: SparkSession): (DataFrame, DataFrame) = { |
| val exprOpt = Option(getFromConfig[String](Expression, null)) |
| |
| val column = exprOpt match { |
| case Some(exprStr) => when(expr(exprStr), 1.0).otherwise(0.0) |
| case None => |
| error( |
| s"$Expression was not defined for completeness measure.", |
| new IllegalArgumentException(s"$Expression was not defined for completeness measure.")) |
| throw new IllegalArgumentException( |
| s"$Expression was not defined for completeness measures") |
| } |
| |
| val selectCols = Seq(Total, Complete, InComplete).flatMap(e => Seq(lit(e), col(e))) |
| val metricColumn: Column = map(selectCols: _*).as(valueColumn) |
| |
| val input = sparkSession.read.table(measureParam.getDataSource) |
| val badRecordsDf = input.withColumn(valueColumn, column) |
| |
| val metricDf = badRecordsDf |
| .withColumn(Total, lit(1)) |
| .agg(sum(Total).as(Total), sum(valueColumn).as(InComplete)) |
| .withColumn(Complete, col(Total) - col(InComplete)) |
| .select(metricColumn) |
| |
| (badRecordsDf, metricDf) |
| } |
| } |