spark-instrumented-optimizer/sql/core
Nattavut Sutyanyong 6eac96823c [SPARK-18966][SQL] NOT IN subquery with correlated expressions may return incorrect result
## What changes were proposed in this pull request?

This PR fixes the following problem:
````
Seq((1, 2)).toDF("a1", "a2").createOrReplaceTempView("a")
Seq[(java.lang.Integer, java.lang.Integer)]((1, null)).toDF("b1", "b2").createOrReplaceTempView("b")

// The expected result is 1 row of (1,2) as shown in the next statement.
sql("select * from a where a1 not in (select b1 from b where b2 = a2)").show
+---+---+
| a1| a2|
+---+---+
+---+---+

sql("select * from a where a1 not in (select b1 from b where b2 = 2)").show
+---+---+
| a1| a2|
+---+---+
|  1|  2|
+---+---+
````
There are a number of scenarios to consider:

1. When the correlated predicate yields a match (i.e., B.B2 = A.A2)
1.1. When the NOT IN expression yields a match (i.e., A.A1 = B.B1)
1.2. When the NOT IN expression yields no match (i.e., A.A1 = B.B1 returns false)
1.3. When A.A1 is null
1.4. When B.B1 is null
1.4.1. When A.A1 is not null
1.4.2. When A.A1 is null

2. When the correlated predicate yields no match (i.e.,B.B2 = A.A2 is false or unknown)
2.1. When B.B2 is null and A.A2 is null
2.2. When B.B2 is null and A.A2 is not null
2.3. When the value of A.A2 does not match any of B.B2

````
 A.A1   A.A2      B.B1   B.B2
-----  -----     -----  -----
    1      1         1      1    (1.1)
    2      1                     (1.2)
 null      1                     (1.3)

    1      3      null      3    (1.4.1)
 null      3                     (1.4.2)

    1   null         1   null    (2.1)
 null      2                     (2.2 & 2.3)
````

We can divide the evaluation of the above correlated NOT IN subquery into 2 groups:-

Group 1: The rows in A when there is a match from the correlated predicate (A.A1 = B.B1)

In this case, the result of the subquery is not empty and the semantics of the NOT IN depends solely on the evaluation of the equality comparison of the columns of NOT IN, i.e., A1 = B1, which says

- If A.A1 is null, the row is filtered (1.3 and 1.4.2)
- If A.A1 = B.B1, the row is filtered (1.1)
- If B.B1 is null, any rows of A in the same group (A.A2 = B.B2) is filtered (1.4.1 & 1.4.2)
- Otherwise, the row is qualified.

Hence, in this group, the result is the row from (1.2).

Group 2: The rows in A when there is no match from the correlated predicate (A.A2 = B.B2)

In this case, all the rows in A, including the rows where A.A1, are qualified because the subquery returns an empty set and by the semantics of the NOT IN, all rows from the parent side qualifies as the result set, that is, the rows from (2.1, 2.2 and 2.3).

In conclusion, the correct result set of the above query is
````
 A.A1   A.A2
-----  -----
    2      1    (1.2)
    1   null    (2.1)
 null      2    (2.2 & 2.3)
````
## How was this patch tested?
unit tests, regression tests, and new test cases focusing on the problem being fixed.

Author: Nattavut Sutyanyong <nsy.can@gmail.com>

Closes #17294 from nsyca/18966.
2017-03-14 20:34:59 +01:00
..
benchmarks [SPARK-17335][SQL] Fix ArrayType and MapType CatalogString. 2016-09-03 19:02:20 +02:00
src [SPARK-18966][SQL] NOT IN subquery with correlated expressions may return incorrect result 2017-03-14 20:34:59 +01:00
pom.xml [SPARK-19409][BUILD][TEST-MAVEN] Fix ParquetAvroCompatibilitySuite failure due to test dependency on avro 2017-02-08 12:21:49 +00:00