@@ -26,7 +26,7 @@ def groupby_agg(self, df: pl.DataFrame, group_keys, agg_ops) -> pl.DataFrame:
             getattr(pl.col(col), self._POLARS_FUNC_MAP.get(func, func))().alias(alias)
             for alias, (func, col) in agg_ops.items()
         ]
-        return df.groupby(group_keys).agg(agg_exprs)
+        return df.group_by(group_keys).agg(agg_exprs)
 
     def filter(self, df: pl.DataFrame, expr: str) -> pl.DataFrame:
         return df.filter(pl.sql_expr(expr))
 
@@ -3,6 +3,7 @@
 
 import pandas as pd
 import pyarrow as pa
+import pytest
 
 from feast.infra.compute_engines.backends.pandas_backend import PandasBackend
 from feast.infra.compute_engines.dag.context import ColumnInfo, ExecutionContext
@@ -104,6 +105,34 @@ def test_local_aggregation_node():
     assert result_df["sum_value"].iloc[1] == 70
 
 
+def test_local_aggregation_node_polars_backend():
+    pytest.importorskip("polars")
+    from feast.infra.compute_engines.backends.polars_backend import PolarsBackend
+
+    context = create_context(
+        node_outputs={"source": ArrowTableValue(pa.Table.from_pandas(sample_df))}
+    )
+
+    agg_ops = {
+        "sum_value": ("sum", "value"),
+        "unique_value": ("nunique", "value"),
+    }
+    agg_node = LocalAggregationNode(
+        name="agg",
+        backend=PolarsBackend(),
+        group_keys=["entity_id"],
+        agg_ops=agg_ops,
+    )
+    agg_node.add_input(MagicMock())
+    agg_node.inputs[0].name = "source"
+
+    result = agg_node.execute(context)
+    assert isinstance(result, ArrowTableValue)
+    result_df = result.data.to_pandas().sort_values("entity_id")
+    assert result_df["sum_value"].tolist() == [30, 70]
+    assert result_df["unique_value"].tolist() == [2, 2]
+
+
 def test_local_join_node():
     context = create_context(
         node_outputs={"source": ArrowTableValue(pa.Table.from_pandas(sample_df))}
Original file line number	Diff line number	Diff line change
`@@ -26,7 +26,7 @@ def groupby_agg(self, df: pl.DataFrame, group_keys, agg_ops) -> pl.DataFrame:`
`26`	`26`	`getattr(pl.col(col), self._POLARS_FUNC_MAP.get(func, func))().alias(alias)`
`27`	`27`	`for alias, (func, col) in agg_ops.items()`
`28`	`28`	`]`
`29`		`- return df.groupby(group_keys).agg(agg_exprs)`
	`29`	`+ return df.group_by(group_keys).agg(agg_exprs)`
`30`	`30`
`31`	`31`	`def filter(self, df: pl.DataFrame, expr: str) -> pl.DataFrame:`
`32`	`32`	`return df.filter(pl.sql_expr(expr))`