diff --git a/python/pyspark/sql/pandas/serializers.py b/python/pyspark/sql/pandas/serializers.py
index 43a42d7fc3b4..f7597c3bdafa 100644
--- a/python/pyspark/sql/pandas/serializers.py
+++ b/python/pyspark/sql/pandas/serializers.py
@@ -500,13 +500,11 @@ def load_stream(self, stream):
         Deserialize ArrowRecordBatches to an Arrow table and return as a list of pandas.Series.
         """
         batches = super().load_stream(stream)
-        import pyarrow as pa
         import pandas as pd
 
         for batch in batches:
             pandas_batches = [
-                self.arrow_to_pandas(c, i)
-                for i, c in enumerate(pa.Table.from_batches([batch]).itercolumns())
+                self.arrow_to_pandas(batch.column(i), i) for i in range(batch.num_columns)
             ]
             if len(pandas_batches) == 0:
                 yield [pd.Series([pyspark._NoValue] * batch.num_rows)]
@@ -1225,8 +1223,7 @@ def process_group(batches: "Iterator[pa.RecordBatch]"):
             for batch in batches:
                 # The batch from ArrowStreamSerializer is already flattened (no struct wrapper)
                 series = [
-                    self.arrow_to_pandas(c, i)
-                    for i, c in enumerate(pa.Table.from_batches([batch]).itercolumns())
+                    self.arrow_to_pandas(batch.column(i), i) for i in range(batch.num_columns)
                 ]
                 yield series