Update HiveToDynamoDBOperator to support Polars

providers/amazon/src/airflow/providers/amazon/aws/transfers/hive_to_dynamodb.py

@@ -21,7 +21,7 @@
 
 import json
 from collections.abc import Callable, Sequence
-from typing import TYPE_CHECKING
+from typing import TYPE_CHECKING, Literal
 
 from airflow.providers.amazon.aws.hooks.dynamodb import DynamoDBHook
 from airflow.providers.amazon.version_compat import BaseOperator
@@ -53,6 +53,7 @@ class HiveToDynamoDBOperator(BaseOperator):
     :param hiveserver2_conn_id: Reference to the
         :ref: `Hive Server2 thrift service connection id <howto/connection:hiveserver2>`.
     :param aws_conn_id: aws connection
+    :param df_type: DataFrame type to use ("pandas" or "polars").
     """
 
     template_fields: Sequence[str] = ("sql",)
@@ -73,6 +74,7 @@ def __init__(
         schema: str = "default",
         hiveserver2_conn_id: str = "hiveserver2_default",
         aws_conn_id: str | None = "aws_default",
+        df_type: Literal["pandas", "polars"] = "pandas",
         **kwargs,
     ) -> None:
         super().__init__(**kwargs)
@@ -86,14 +88,15 @@ def __init__(
         self.schema = schema
         self.hiveserver2_conn_id = hiveserver2_conn_id
         self.aws_conn_id = aws_conn_id
+        self.df_type = df_type
 
     def execute(self, context: Context):
         hive = HiveServer2Hook(hiveserver2_conn_id=self.hiveserver2_conn_id)
 
         self.log.info("Extracting data from Hive")
         self.log.info(self.sql)
 
-        data = hive.get_df(self.sql, schema=self.schema, df_type="pandas")
+        data = hive.get_df(self.sql, schema=self.schema, df_type=self.df_type)
         dynamodb = DynamoDBHook(
             aws_conn_id=self.aws_conn_id,
             table_name=self.table_name,
@@ -104,7 +107,10 @@ def execute(self, context: Context):
         self.log.info("Inserting rows into dynamodb")
 
         if self.pre_process is None:
-            dynamodb.write_batch_data(json.loads(data.to_json(orient="records")))
+            if self.df_type == "polars":
+                dynamodb.write_batch_data(data.to_dicts())  # type:ignore[operator]
+            elif self.df_type == "pandas":
+                dynamodb.write_batch_data(json.loads(data.to_json(orient="records")))  # type:ignore[union-attr]
         else:
             dynamodb.write_batch_data(
                 self.pre_process(data=data, args=self.pre_process_args, kwargs=self.pre_process_kwargs)

providers/amazon/tests/unit/amazon/aws/transfers/test_hive_to_dynamodb.py

@@ -22,6 +22,8 @@
 from unittest import mock
 
 import pandas as pd
+import polars as pl
+import pytest
 from moto import mock_aws
 
 import airflow.providers.amazon.aws.transfers.hive_to_dynamodb
@@ -110,3 +112,43 @@ def test_pre_process_records_with_schema(self, mock_get_df):
         table = self.hook.get_conn().Table("test_airflow")
         table.meta.client.get_waiter("table_exists").wait(TableName="test_airflow")
         assert table.item_count == 1
+
+    @pytest.mark.parametrize("df_type", ["pandas", "polars"])
+    @mock_aws
+    def test_df_type_parameter(self, df_type):
+        if df_type == "polars" and pl is None:
+            pytest.skip("Polars not installed")
+
+        if df_type == "pandas":
+            test_df = pd.DataFrame(data=[("1", "sid")], columns=["id", "name"])
+        else:
+            test_df = pl.DataFrame({"id": ["1"], "name": ["sid"]})
+
+        with mock.patch(
+            "airflow.providers.apache.hive.hooks.hive.HiveServer2Hook.get_df",
+            return_value=test_df,
+        ) as mock_get_df:
+            self.hook.get_conn().create_table(
+                TableName="test_airflow",
+                KeySchema=[
+                    {"AttributeName": "id", "KeyType": "HASH"},
+                ],
+                AttributeDefinitions=[{"AttributeName": "id", "AttributeType": "S"}],
+                ProvisionedThroughput={"ReadCapacityUnits": 10, "WriteCapacityUnits": 10},
+            )
+
+            operator = airflow.providers.amazon.aws.transfers.hive_to_dynamodb.HiveToDynamoDBOperator(
+                sql=self.sql,
+                table_name="test_airflow",
+                task_id="hive_to_dynamodb_check",
+                table_keys=["id"],
+                df_type=df_type,
+                dag=self.dag,
+            )
+
+            operator.execute(None)
+            mock_get_df.assert_called_once_with(self.sql, schema="default", df_type=df_type)
+
+            table = self.hook.get_conn().Table("test_airflow")
+            table.meta.client.get_waiter("table_exists").wait(TableName="test_airflow")
+            assert table.item_count == 1