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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 org.apache.griffin.measure.utils
import org.apache.spark.sql.DataFrame
import org.apache.spark.sql.functions._
object DataFrameUtil {
def unionDfOpts(dfOpt1: Option[DataFrame], dfOpt2: Option[DataFrame]): Option[DataFrame] = {
(dfOpt1, dfOpt2) match {
case (Some(df1), Some(df2)) => Some(unionByName(df1, df2))
case (Some(_), _) => dfOpt1
case (_, Some(_)) => dfOpt2
case _ => None
}
}
def unionByName(a: DataFrame, b: DataFrame): DataFrame = {
val columns = a.columns.toSet.intersect(b.columns.toSet).map(col).toSeq
a.select(columns: _*).union(b.select(columns: _*))
}
}