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[SPARK-22335][SQL] Clarify union behavior on Dataset of typed objects in the document #19570

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[SPARK-22335][SQL] Clarify union behavior on Dataset of typed objects in the document #19570

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Add notice into the document of `union` to clarity the usage for type…
viirya Oct 25, 2017
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viirya Oct 26, 2017
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viirya Oct 28, 2017
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viirya Oct 28, 2017
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21 changes: 20 additions & 1 deletion sql/core/src/main/scala/org/apache/spark/sql/Dataset.scala
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Expand Up @@ -1751,7 +1751,26 @@ class Dataset[T] private[sql](
* This is equivalent to `UNION ALL` in SQL. To do a SQL-style set union (that does
* deduplication of elements), use this function followed by a [[distinct]].
*
* Also as standard in SQL, this function resolves columns by position (not by name).
* Also as standard in SQL, this function resolves columns by position (not by name):
*
* {{{
* val df1 = Seq((1, 2, 3)).toDF("col0", "col1", "col2")
* val df2 = Seq((4, 5, 6)).toDF("col1", "col2", "col0")
* df1.union(df2).show
*
* // output:
* // +----+----+----+
* // |col0|col1|col2|
* // +----+----+----+
* // | 1| 2| 3|
* // | 4| 5| 6|
* // +----+----+----+
* }}}
*
* Notice that the column positions in the schema aren't necessarily matched with the
* fields in the strongly typed objects in a Dataset. This function resolves columns
* by their positions in the schema, not the fields in the strongly typed objects. Use
* [[unionByName]] to resolve columns by field name in the typed objects.
*
* @group typedrel
* @since 2.0.0
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