Kousuke Saruta created SPARK-17154:
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Summary: Wrong result can be returned or AnalysisException can be
thrown after self-join or similar operations
Key: SPARK-17154
URL: https://issues.apache.org/jira/browse/SPARK-17154
Project: Spark
Issue Type: Bug
Components: SQL
Affects Versions: 2.0.0, 1.6.2
Reporter: Kousuke Saruta
When we join two DataFrames which are originated from a same DataFrame,
operations to the joined DataFrame can fail.
One reproducible example is as follows.
{code}
val df = Seq(
(1, "a", "A"),
(2, "b", "B"),
(3, "c", "C"),
(4, "d", "D"),
(5, "e", "E")).toDF("col1", "col2", "col3")
val filtered = df.filter("col1 != 3").select("col1", "col2")
val joined = filtered.join(df, filtered("col1") === df("col1"), "inner")
val selected1 = joined.select(df("col3"))
{code}
In this case, AnalysisException is thrown.
Another example is as follows.
{code}
val df = Seq(
(1, "a", "A"),
(2, "b", "B"),
(3, "c", "C"),
(4, "d", "D"),
(5, "e", "E")).toDF("col1", "col2", "col3")
val filtered = df.filter("col1 != 3").select("col1", "col2")
val rightOuterJoined = filtered.join(df, filtered("col1") === df("col1"),
"right")
val selected2 = rightOuterJoined.select(df("col1"))
selected2.show
{code}
In this case, we will expect to get the answer like as follows.
{code}
1
2
3
4
5
{code}
But the actual result is as follows.
{code}
1
2
null
4
5
{code}
The cause of the problems in the examples is that the logical plan related to
the right side DataFrame and the expressions of its output are re-created in
the analyzer (at ResolveReference rule) when a DataFrame has expressions which
have a same exprId each other.
Re-created expressions are equally to the original ones except exprId.
This will happen when we do self-join or similar pattern operations.
In the first example, df("col3") returns a Column which includes an expression
and the expression have an exprId (say id1 here).
After join, the expresion which the right side DataFrame (df) has is re-created
and the old and new expressions are equally but exprId is renewed (say id2 for
the new exprId here).
Because of the mismatch of those exprIds, AnalysisException is thrown.
In the second example, df("col1") returns a column and the expression contained
in the column is assigned an exprId (say id3).
On the other hand, a column returned by filtered("col1") has an expression
which has the same exprId (id3).
After join, the expressions in the right side DataFrame are re-created and the
expression assigned id3 is no longer present in the right side but present in
the left side.
So, referring df("col1") to the joined DataFrame, we get col1 of right side
which includes null.
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