zhengruifeng commented on code in PR #37995: URL: https://github.com/apache/spark/pull/37995#discussion_r981915981
########## python/pyspark/pandas/series.py: ########## @@ -6442,6 +6445,8 @@ def argmin(self, axis: Axis = None, skipna: bool = True) -> int: raise ValueError("axis can only be 0 or 'index'") sdf = self._internal.spark_frame.select(self.spark.column, NATURAL_ORDER_COLUMN_NAME) seq_col_name = verify_temp_column_name(sdf, "__distributed_sequence_column__") + + cached = sdf.cache() Review Comment: Maybe we can avoid recomputation in another way: For a big input dataframe `sdf`: 1. have a subquery that compute the size of partitions on `sdf.select(lit(0))`, in this case the original expressions in `sdf` will not be evaluated? 2. with the sizes array `Array[Long]`, generate the result dataframe just like the `zipWithIndex` -- This is an automated message from the Apache Git Service. To respond to the message, please log on to GitHub and use the URL above to go to the specific comment. To unsubscribe, e-mail: reviews-unsubscr...@spark.apache.org For queries about this service, please contact Infrastructure at: us...@infra.apache.org --------------------------------------------------------------------- To unsubscribe, e-mail: reviews-unsubscr...@spark.apache.org For additional commands, e-mail: reviews-h...@spark.apache.org