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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