Denton Cockburn created SPARK-14040:
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Summary: Null-safe and equality join produces incorrect result
with filtered dataframe
Key: SPARK-14040
URL: https://issues.apache.org/jira/browse/SPARK-14040
Project: Spark
Issue Type: Bug
Components: SQL
Affects Versions: 1.6.0
Environment: Ubuntu Linux 15.10
Reporter: Denton Cockburn
Initial issue reported here:
http://stackoverflow.com/questions/36131942/spark-join-produces-wrong-results
```
val b = Seq(("a", "b", 1), ("a", "b", 2)).toDF("a", "b", "c")
val a = b.where("c = 1").withColumnRenamed("a", "filta").withColumnRenamed("b",
"filtb")
a.join(b, $"filta" <=> $"a" and $"filtb" <=> $"b" and a("c") <=> b("c"),
"left_outer").show
```
Produces 2 rows instead of the expected 1.
```
a.withColumn("newc", $"c").join(b, $"filta" === $"a" and $"filtb" === $"b" and
$"newc" === b("c"), "left_outer").show
```
Also produces 2 rows instead of the expected 1.
The only one that seemed to work correctly was:
```
a.join(b, $"filta" === $"a" and $"filtb" === $"b" and a("c") === b("c"),
"left_outer").show
```
But that produced a warning for : ``` WARN Column: Constructing trivially true
equals predicate, 'c#18232 = c#18232' ```
As pointed out by commenter zero323:
"The second behavior looks indeed like a bug related to the fact that you still
have a.c in your data. It looks like it is picked downstream before b.c and the
evaluated condition is actually a.newc = a.c"
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