itholic commented on a change in pull request #35191:
URL: https://github.com/apache/spark/pull/35191#discussion_r798208506
##########
File path: python/pyspark/pandas/series.py
##########
@@ -5228,22 +5228,128 @@ def asof(self, where: Union[Any, List]) ->
Union[Scalar, "Series"]:
where = [where]
index_scol = self._internal.index_spark_columns[0]
index_type = self._internal.spark_type_for(index_scol)
+
+ # e.g where = [10, 20]
+ # In the comments below , will explain how the dataframe will look
after transformations.
+ # e.g pd.Series([2, 1, np.nan, 4], index=[10, 20, 30, 40],
name="Koalas")
+
+ column_prefix_constant = "col_"
cond = [
- F.max(F.when(index_scol <= SF.lit(index).cast(index_type),
self.spark.column))
- for index in where
+ F.when(
+ index_scol <= SF.lit(index).cast(index_type),
+ F.struct(
+ F.lit(column_prefix_constant + str(index) + "_" +
str(idx)).alias("identifier"),
+ self.spark.column.alias("col_value"),
+ ),
+ ).alias(column_prefix_constant + str(index) + "_" + str(idx))
Review comment:
Can we make `column_prefix_constant + str(index) + "_" + str(idx)` as
variable and reuse here and there ??
##########
File path: python/pyspark/pandas/series.py
##########
@@ -5228,22 +5228,128 @@ def asof(self, where: Union[Any, List]) ->
Union[Scalar, "Series"]:
where = [where]
index_scol = self._internal.index_spark_columns[0]
index_type = self._internal.spark_type_for(index_scol)
+
+ # e.g where = [10, 20]
+ # In the comments below , will explain how the dataframe will look
after transformations.
+ # e.g pd.Series([2, 1, np.nan, 4], index=[10, 20, 30, 40],
name="Koalas")
+
+ column_prefix_constant = "col_"
cond = [
- F.max(F.when(index_scol <= SF.lit(index).cast(index_type),
self.spark.column))
- for index in where
+ F.when(
+ index_scol <= SF.lit(index).cast(index_type),
+ F.struct(
+ F.lit(column_prefix_constant + str(index) + "_" +
str(idx)).alias("identifier"),
+ self.spark.column.alias("col_value"),
+ ),
+ ).alias(column_prefix_constant + str(index) + "_" + str(idx))
Review comment:
I think we can simply use `F.last` with `ignorenulls=True` instead of
`F.max` ??
(https://spark.apache.org/docs/3.1.1/api/python/reference/api/pyspark.sql.functions.last.html)
e.g.
```python
cond = [
F.last(F.when(index_scol <= SF.lit(index).cast(index_type),
self.spark.column), ignorenulls=True)
for index in where
]
```
It returns the last non-null value from given column.
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