Add max_result_size feature to Pandas.read_sql_athena.

awswrangler/pandas.py

@@ -268,7 +268,20 @@ def _read_csv_once(
         buff.close()
         return dataframe
 
-    def read_sql_athena(self, sql, database, s3_output=None):
+    def read_sql_athena(self,
+                        sql,
+                        database,
+                        s3_output=None,
+                        max_result_size=None):
+        """
+        Executes any SQL query on AWS Athena and return a Dataframe of the result.
+        P.S. If max_result_size is passed, then a iterator of Dataframes is returned.
+        :param sql: SQL Query
+        :param database: Glue/Athena Databease
+        :param s3_output: AWS S3 path
+        :param max_result_size: Max number of bytes on each request to S3
+        :return: Pandas Dataframe or Iterator of Pandas Dataframes if max_result_size != None
+        """
         if not s3_output:
             account_id = (self._session.boto3_session.client(
                 service_name="sts", config=self._session.botocore_config).
@@ -290,8 +303,8 @@ def read_sql_athena(self, sql, database, s3_output=None):
             raise AthenaQueryError(message_error)
         else:
             path = f"{s3_output}{query_execution_id}.csv"
-            dataframe = self.read_csv(path=path)
-        return dataframe
+            ret = self.read_csv(path=path, max_result_size=max_result_size)
+        return ret
 
     def to_csv(
             self,

awswrangler/session.py

@@ -227,6 +227,7 @@ class SessionPrimitives:
     It is required to "share" the session attributes to other processes.
     That must be "pickable"!
     """
+
     def __init__(
             self,
             profile_name=None,

testing/test_awswrangler/test_pandas.py

@@ -181,3 +181,27 @@ def test_to_s3(
             break
         sleep(1)
     assert factor * len(dataframe.index) == len(dataframe2.index)
+
+
+@pytest.mark.parametrize("sample, row_num", [("data_samples/micro.csv", 30),
+                                             ("data_samples/small.csv", 100)])
+def test_read_sql_athena_iterator(session, bucket, database, sample, row_num):
+    dataframe_sample = pandas.read_csv(sample)
+    path = f"s3://{bucket}/test/"
+    session.pandas.to_parquet(dataframe=dataframe_sample,
+                              database=database,
+                              path=path,
+                              preserve_index=False,
+                              mode="overwrite")
+    total_count = 0
+    for counter in range(10):
+        dataframe_iter = session.pandas.read_sql_athena(
+            sql="select * from test", database=database, max_result_size=200)
+        total_count = 0
+        for dataframe in dataframe_iter:
+            total_count += len(dataframe.index)
+        if total_count == row_num:
+            break
+        sleep(1)
+    session.s3.delete_objects(path=path)
+    assert total_count == row_num