cloud-fan commented on code in PR #42828:
URL: https://github.com/apache/spark/pull/42828#discussion_r1338141627
##########
python/pyspark/sql/tests/test_dataframe.py:
##########
@@ -63,6 +62,51 @@
class DataFrameTestsMixin:
+ def test_getitem_invalid_indices(self):
+ df = self.spark.sql(
+ "SELECT * FROM VALUES "
+ "(1, 1.1, 'a'), "
+ "(2, 2.2, 'b'), "
+ "(4, 4.4, 'c') "
+ "AS TAB(a, b, c)"
+ )
+
+ # accepted type and values
+ for index in [False, True, 0, 1, 2, -1, -2, -3]:
+ df[index]
Review Comment:
This is really a bad API. `df.col` can be ambiguous as people may use the
column reference far away from the dataframe, e.g.
`df1.join(df2).select...filter...select(df1.col)`. We recommend users use
qualified unresolved column instead, like `col("t1.col")`. Now `df[index]` is
even worse as it only makes sense to use it intermediately in current df's
transformation.
Why do we add such an API? To support order by ordinal, we can just order by
integer literals. The SQL parser also parses `ORDER BY 1, 2` as ordering by
integer literal 1 and 2, and analyzer will properly resolve it.
cc @HyukjinKwon @zhengruifeng
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