Github user gatorsmile commented on the pull request:
https://github.com/apache/spark/pull/11658#issuecomment-195672850
```SQL
SELECT x.key, x.value, y.a, y.b, y.c, y.d FROM parquet_t1 x JOIN parquet_t2
y ON x.key = y.a
```
The generated SQL is
```SQL
SELECT `gen_attr_30` AS `key`, `gen_attr_31` AS `value`, `gen_attr_32` AS
`a`, `gen_attr_33` AS `b`, `gen_attr_34` AS `c`, `gen_attr_35` AS `d` FROM
(SELECT `gen_attr_30`, `gen_attr_31`, `gen_attr_32`, `gen_attr_33`,
`gen_attr_34`, `gen_attr_35` FROM (SELECT `key` AS `gen_attr_30`, `value` AS
`gen_attr_31` FROM `default`.`parquet_t1`) AS gen_subquery_0 INNER JOIN (SELECT
`a` AS `gen_attr_32`, `b` AS `gen_attr_33`, `c` AS `gen_attr_34`, `d` AS
`gen_attr_35` FROM `default`.`parquet_t2`) AS gen_subquery_1 ON (`gen_attr_30`
= `gen_attr_32`)) AS gen_subquery_2
```
I compared the Optimized Logical Plan of these two queries:
```
Join Inner, Some((key#30L = a#32L))
:- Filter isnotnull(key#30L)
: +- Relation[key#30L,value#31] ParquetFormat part: struct<>, data:
struct<key:bigint,value:string>
+- Filter isnotnull(a#32L)
+- Relation[a#32L,b#33L,c#34L,d#35L] ParquetFormat part: struct<>, data:
struct<a:bigint,b:bigint,c:bigint,d:bigint>
```
```
Project [gen_attr_30#71L AS key#77L,gen_attr_31#72 AS
value#78,gen_attr_32#73L AS a#79L,gen_attr_33#74L AS b#80L,gen_attr_34#75L AS
c#81L,gen_attr_35#76L AS d#82L]
+- Join Inner, Some((gen_attr_30#71L = gen_attr_32#73L))
:- Project [key#30L AS gen_attr_30#71L,value#31 AS gen_attr_31#72]
: +- Filter isnotnull(key#30L)
: +- Relation[key#30L,value#31] ParquetFormat part: struct<>, data:
struct<key:bigint,value:string>
+- Project [a#32L AS gen_attr_32#73L,b#33L AS gen_attr_33#74L,c#34L AS
gen_attr_34#75L,d#35L AS gen_attr_35#76L]
+- Filter isnotnull(a#32L)
+- Relation[a#32L,b#33L,c#34L,d#35L] ParquetFormat part: struct<>,
data: struct<a:bigint,b:bigint,c:bigint,d:bigint>
```
Here, we always add extra `Project`s in SQL generation. I am just thinking
if we need to do it even if no name ambiguity exists?
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