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feat: move robust literal handling for PySpark #1880

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merged 2 commits into from
Jan 28, 2025
Merged

feat: move robust literal handling for PySpark #1880

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64656b7
better scalar support in pyspark
MarcoGorelli Jan 28, 2025
dbd31a5
horizontal aggs
MarcoGorelli Jan 28, 2025
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25 changes: 10 additions & 15 deletions narwhals/_spark_like/dataframe.py
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Original file line number Diff line number Diff line change
Expand Up @@ -9,6 +9,7 @@
from pyspark.sql import Window
from pyspark.sql import functions as F # noqa: N812

from narwhals._spark_like.utils import ExprKind
from narwhals._spark_like.utils import native_to_narwhals_dtype
from narwhals._spark_like.utils import parse_exprs_and_named_exprs
from narwhals.typing import CompliantLazyFrame
Expand Down Expand Up @@ -97,9 +98,7 @@ def select(
*exprs: SparkLikeExpr,
**named_exprs: SparkLikeExpr,
) -> Self:
new_columns, returns_scalar = parse_exprs_and_named_exprs(
self, *exprs, **named_exprs
)
new_columns, expr_kinds = parse_exprs_and_named_exprs(self, *exprs, **named_exprs)

if not new_columns:
# return empty dataframe, like Polars does
Expand All @@ -110,19 +109,17 @@ def select(

return self._from_native_frame(spark_df)

if all(returns_scalar):
if not any(expr_kind is ExprKind.TRANSFORM for expr_kind in expr_kinds):
new_columns_list = [
col.alias(col_name) for col_name, col in new_columns.items()
]
return self._from_native_frame(self._native_frame.agg(*new_columns_list))
else:
new_columns_list = [
col.over(Window.partitionBy(F.lit(1))).alias(col_name)
if _returns_scalar
if expr_kind is ExprKind.AGGREGATION
else col.alias(col_name)
for (col_name, col), _returns_scalar in zip(
new_columns.items(), returns_scalar
)
for (col_name, col), expr_kind in zip(new_columns.items(), expr_kinds)
]
return self._from_native_frame(self._native_frame.select(*new_columns_list))

Expand All @@ -131,15 +128,13 @@ def with_columns(
*exprs: SparkLikeExpr,
**named_exprs: SparkLikeExpr,
) -> Self:
new_columns, returns_scalar = parse_exprs_and_named_exprs(
self, *exprs, **named_exprs
)
new_columns, expr_kinds = parse_exprs_and_named_exprs(self, *exprs, **named_exprs)

new_columns_map = {
col_name: col.over(Window.partitionBy(F.lit(1))) if _returns_scalar else col
for (col_name, col), _returns_scalar in zip(
new_columns.items(), returns_scalar
)
col_name: col.over(Window.partitionBy(F.lit(1)))
if expr_kind is ExprKind.AGGREGATION
else col
for (col_name, col), expr_kind in zip(new_columns.items(), expr_kinds)
}
return self._from_native_frame(self._native_frame.withColumns(new_columns_map))

Expand Down
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