您可以手动在两个Dataframe中创建缺少的列，然后合并它们：

import org.apache.spark.sql.DataFrame

val allCols = df1.columns.toSet.union(df2.columns.toSet).toArray

val createMissingCols = (df: DataFrame, allCols: Array[String]) => allCols.foldLeft(df)(
  (_df, _col) => if (_df.columns.contains(_col)) _df else _df.withColumn(_col, lit(""))
).select(allCols.head, allCols.tail: _*)  
// select is needed to make sure the two data frames have the same order of columns

createMissingCols(df1, allCols).union(createMissingCols(df2, allCols)).show
+---+---+---+---+---+---+
|  E|  F|  A|  B|  C|  D|
+---+---+---+---+---+---+
|   |   |  1|  2|  3|   |
|   |   |  4|  5|  6|   |
| 22| 33|   |   |   | 11|
| 55| 66|   |   |   | 44|
+---+---+---+---+---+---+

一种更简单的方法是创建一个完整的外部联接，并将联接表达式/条件设置为false：

val df1 = Seq(("1","2","3"),("4","5","6")).toDF("A","B","C")
val df2 = Seq(("11","22","33"),("44","55","66")).toDF("D","E","F")

val joined = df1.join(df2, lit(false), "full")

joined.show() 

+----+----+----+----+----+----+
|   A|   B|   C|   D|   E|   F|
+----+----+----+----+----+----+
|   1|   2|   3|null|null|null|
|   4|   5|   6|null|null|null|
|null|null|null|  11|  22|  33|
|null|null|null|  44|  55|  66|
+----+----+----+----+----+----+

如果要将空值实际设置为空字符串，只需添加：

val withEmptyString = joined.na.fill("")

withEmptyString.show() 

+---+---+---+---+---+---+
|  A|  B|  C|  D|  E|  F|
+---+---+---+---+---+---+
|  1|  2|  3|   |   |   |
|  4|  5|  6|   |   |   |
|   |   |   | 11| 22| 33|
|   |   |   | 44| 55| 66|
+---+---+---+---+---+---+

总而言之 df1.join(df2, lit(false), "full").na.fill("") 应该会成功的。