| /* |
| * 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: _*)) |
| } |
| |
| } |