[GitHub] [spark] cloud-fan commented on a diff in pull request #42864: [WIP][SPARK-45112][SQL] Use UnresolvedFunction based resolution in SQL Dataset functions

["cloud-fan (via GitHub)" <gi...@apache.org>]

cloud-fan commented on code in PR #42864:
URL: https://github.com/apache/spark/pull/42864#discussion_r1328209431


##########
python/pyspark/sql/column.py:
##########
@@ -712,11 +712,11 @@ def __getitem__(self, k: Any) -> "Column":
         --------
         >>> df = spark.createDataFrame([('abcedfg', {"key": "value"})], ["l", "d"])
         >>> df.select(df.l[slice(1, 3)], df.d['key']).show()
-        +------------------+------+
-        |substring(l, 1, 3)|d[key]|
-        +------------------+------+
-        |               abc| value|
-        +------------------+------+
+        +---------------+------+
+        |substr(l, 1, 3)|d[key]|

Review Comment:
   To avoid this change, I think we can call `self.substring` in this method. `df.l[slice(1, 3)]` does not require a certain function name, so keeping it as it was is better.



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