za.co.absa.enceladus.conformance.interpreter.rules.SingleColumnRuleInterpreter.scala Maven / Gradle / Ivy

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/*
 * Copyright 2018 ABSA Group Limited
 *
 * Licensed 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 za.co.absa.enceladus.conformance.interpreter.rules

import org.apache.spark.sql.functions._
import org.apache.spark.sql.{Dataset, Row, SparkSession}
import za.co.absa.spark.hats.Extensions._
import za.co.absa.enceladus.conformance.interpreter.{ExplosionState, InterpreterContextArgs, RuleValidators}
import za.co.absa.enceladus.dao.EnceladusDAO
import za.co.absa.enceladus.model.conformanceRule.{ConformanceRule, SingleColumnConformanceRule}

case class SingleColumnRuleInterpreter(rule: SingleColumnConformanceRule) extends RuleInterpreter {

  final val ruleName = "Single column rule"

  override def conformanceRule: Option[ConformanceRule] = Some(rule)

  def conform(df: Dataset[Row])
             (implicit spark: SparkSession, explosionState: ExplosionState,
              dao: EnceladusDAO, progArgs: InterpreterContextArgs): Dataset[Row] = {
    // Validate the rule parameters
    RuleValidators.validateFieldExistence(progArgs.datasetName, ruleName, df.schema, rule.inputColumn)
    RuleValidators.validateOutputField(progArgs.datasetName, ruleName, df.schema, rule.outputColumn)
    RuleValidators.validateSameParent(progArgs.datasetName, ruleName, rule.inputColumn, rule.outputColumn)

    if (rule.inputColumn.contains('.')) {
      conformNestedField(df)
    } else {
      conformRootField(df)
    }
  }

  /** Handles single column conformance rule for nested fields. */
  private def conformNestedField(df: Dataset[Row])(implicit spark: SparkSession): Dataset[Row] = {
    df.nestedMapColumn(rule.inputColumn, rule.outputColumn, c =>
      struct(c as rule.inputColumnAlias)
    )
  }

  /** Handles single column conformance rule for root (non-nested) fields. */
  private def conformRootField(df: Dataset[Row])(implicit spark: SparkSession): Dataset[Row] = {
    // Applying the rule
    df.withColumn(rule.outputColumn, struct(col(rule.inputColumn) as rule.inputColumnAlias))
  }

}