Github user viirya commented on the issue:
https://github.com/apache/spark/pull/17874
`select a from t where b > 0` works. However, it can be seen logically as:
Project [a]
Filter [b > 0]
Relation t [a, b]
It seems to me Spark also parses the above SQL query like this way.
There is an order of evaluation in SQL systems. E.g, MySQL:
select a from test where b > 2; // works. where is evaluated before
select
select a from test having b > 2; // not works. having is evaluated
after select
`df.select("y").where("x=1")` sematically asks a projection of just `y`
attribute before filtering. It seems to me that it is different with the SQL
query.
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