SNOW-1476313: Wait for result with AsyncJob.result("no_result") (#1764)

CHANGELOG.md

@@ -14,6 +14,7 @@
 
 - Fixed a bug where python stored procedure with table return type fails when run in a task.
 - Fixed a bug where df.dropna fails due to `RecursionError: maximum recursion depth exceeded` when the DataFrame has more than 500 columns.
+- Fixed a bug where `AsyncJob.result("no_result")` doesn't wait for the query to finish execution.
 
 ### Snowpark Local Testing Updates
 

src/snowflake/snowpark/async_job.py

@@ -1,12 +1,13 @@
 #
 # Copyright (c) 2012-2024 Snowflake Computing Inc. All rights reserved.
 #
-
+import time
 from enum import Enum
 from logging import getLogger
 from typing import TYPE_CHECKING, Iterator, List, Literal, Optional, Union
 
 import snowflake.snowpark
+from snowflake.connector.cursor import ASYNC_RETRY_PATTERN
 from snowflake.connector.errors import DatabaseError
 from snowflake.connector.options import pandas
 from snowflake.snowpark._internal.analyzer.analyzer_utils import result_scan_statement
@@ -318,7 +319,7 @@ def result(
                   type of :meth:`DataFrame.collect`.
                 - "row_iterator": returns an iterator of :class:`Row` objects, which is the same as
                   the return type of :meth:`DataFrame.to_local_iterator`.
-                - "row": returns a ``pandas.DataFrame``, which is the same as the return type of
+                - "pandas": returns a ``pandas.DataFrame``, which is the same as the return type of
                   :meth:`DataFrame.to_pandas`.
                 - "pandas_batches": returns an iterator of ``pandas.DataFrame`` s, which is the same
                   as the return type of :meth:`DataFrame.to_pandas_batches`.
@@ -355,6 +356,19 @@ def result(
                 )
 
         if async_result_type == _AsyncResultType.NO_RESULT:
+            # The following section is copied from python connector.
+            # Later we should expose it from python connector and reuse it.
+            retry_pattern_pos = 0
+            while True:
+                status = self._session.connection.get_query_status(self.query_id)
+                if not self._session.connection.is_still_running(status):
+                    break
+                time.sleep(
+                    0.5 * ASYNC_RETRY_PATTERN[retry_pattern_pos]
+                )  # Same wait as JDBC
+                # If we can advance in ASYNC_RETRY_PATTERN then do so
+                if retry_pattern_pos < (len(ASYNC_RETRY_PATTERN) - 1):
+                    retry_pattern_pos += 1
             result = None
         elif async_result_type == _AsyncResultType.PANDAS:
             result = self._session._conn._to_data_or_iter(

tests/integ/scala/test_async_job_suite.py

@@ -473,3 +473,12 @@ def test_async_job_to_df(session, create_async_job_from_query_id):
     new_df = async_job.to_df()
     assert "result_scan" in new_df.queries["queries"][0].lower()
     Utils.check_answer(df, new_df)
+
+
+def test_async_job_result_wait_no_result(session):
+    async_job = session.sql("select system$wait(3)").collect_nowait()
+    t0 = time()
+    result = async_job.result("no_result")
+    t1 = time()
+    assert t1 - t0 >= 3.0
+    assert result is None