za.co.absa.enceladus.conformance.interpreter.rules.DropRuleInterpreter.scala Maven / Gradle / Ivy
/*
* 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.{Dataset, Row, SparkSession}
import za.co.absa.spark.hats.Extensions._
import za.co.absa.enceladus.conformance.interpreter.{ExplosionState, InterpreterContextArgs}
import za.co.absa.enceladus.dao.MenasDAO
import za.co.absa.enceladus.model.conformanceRule.{ConformanceRule, DropConformanceRule}
import za.co.absa.enceladus.utils.schema.SchemaUtils
case class DropRuleInterpreter(rule: DropConformanceRule) extends RuleInterpreter {
override def conformanceRule: Option[ConformanceRule] = Some(rule)
def conform(df: Dataset[Row])
(implicit spark: SparkSession, explosionState: ExplosionState, dao: MenasDAO,
progArgs: InterpreterContextArgs): Dataset[Row] = {
if (SchemaUtils.fieldExists(rule.outputColumn, df.schema)) {
if (rule.outputColumn.contains('.')) {
conformNestedField(df)
} else {
conformRootField(df)
}
} else {
log.warn(s"Could not drop ${rule.outputColumn}. Column is not present in the dataset")
df
}
}
/** Handles drop conformance rule for nested fields. */
private def conformNestedField(df: Dataset[Row])(implicit spark: SparkSession): Dataset[Row] = {
df.nestedDropColumn(rule.outputColumn)
}
/** Handles drop conformance rule for root (non-nested) fields. */
private def conformRootField(df: Dataset[Row])(implicit spark: SparkSession): Dataset[Row] = {
// Applying the rule
df.drop(rule.outputColumn)
}
}