Github user liancheng commented on a diff in the pull request:
https://github.com/apache/spark/pull/10333#discussion_r47875650
--- Diff:
sql/core/src/test/scala/org/apache/spark/sql/DataFrameJoinSuite.scala ---
@@ -48,11 +48,13 @@ class DataFrameJoinSuite extends QueryTest with
SharedSQLContext {
checkAnswer(
df.join(df2, Seq("int", "str"), "left"),
- Row(1, 2, "1", null) :: Row(2, 3, "2", null) :: Row(3, 4, "3", null)
:: Nil)
+ Row(1, 2, "1", null, null, null) :: Row(2, 3, "2", null, null, null)
::
+ Row(3, 4, "3", null, null, null) :: Nil)
checkAnswer(
df.join(df2, Seq("int", "str"), "right"),
- Row(null, null, null, 2) :: Row(null, null, null, 3) :: Row(null,
null, null, 4) :: Nil)
+ Row(null, null, null, 1, 2, "2") :: Row(null, null, null, 2, 3, "3")
::
+ Row(null, null, null, 3, 4, "4") :: Nil)
--- End diff --
But there does exist bugs other than the nullability issue in the original
`DataFrame.join` method. For example it doesn't handle full outer join
correctly. Using the same example tables mentioned above, the following
`spark-shell` snippet
```scala
import sqlContext._
val t1 = table("t1")
val t2 = table("t2")
t1.join(t2, Seq("num"), "fullouter").show()
```
produces wrong query result:
```
+----+----+-----+
| num|name|value|
+----+----+-----+
| 1| a| xxx|
| 2| b| null|
| 3| c| yyy|
|null|null| zzz|
+----+----+-----+
```
Here's the result from PostgreSQL:
```
postgres=# SELECT * FROM t1 FULL JOIN t2 USING (num);
num | name | value
-----+------+-------
1 | a | xxx
2 | b |
3 | c | yyy
5 | | zzz
(4 rows)
```
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