Respect progress_bar_type in to_dataframe when used with BQ Stora…

…ge API (#7697)

* fix: `to_dataframe` respects `progress_bar_type` with BQ Storage API

* Add unit test for progress bar.

* Add test for full queue.

* Add worker queue for progress bar to prevent lost tqdm updates.

The worker queue runs in a background thread, so it's more likely to be
able to keep up with the other workers that are adding to the worker
queue.

* Test that progress bar updates more than once.

bigquery/google/cloud/bigquery/table.py

@@ -22,9 +22,12 @@
 import datetime
 import json
 import operator
+import threading
+import time
 import warnings
 
 import six
+from six.moves import queue
 
 try:
     from google.cloud import bigquery_storage_v1beta1
@@ -66,7 +69,12 @@
 )
 _TABLE_HAS_NO_SCHEMA = 'Table has no schema:  call "client.get_table()"'
 _MARKER = object()
-_PROGRESS_INTERVAL = 1.0  # Time between download status updates, in seconds.
+_PROGRESS_INTERVAL = 0.2  # Time between download status updates, in seconds.
+
+# Send multiple updates from the worker threads, so there are at least a few
+# waiting next time the prgrogess bar is updated.
+_PROGRESS_UPDATES_PER_INTERVAL = 3
+_PROGRESS_WORKER_INTERVAL = _PROGRESS_INTERVAL / _PROGRESS_UPDATES_PER_INTERVAL
 
 
 def _reference_getter(table):
@@ -1274,6 +1282,16 @@ def __repr__(self):
         return "Row({}, {})".format(self._xxx_values, f2i)
 
 
+class _NoopProgressBarQueue(object):
+    """A fake Queue class that does nothing.
+
+    This is used when there is no progress bar to send updates to.
+    """
+
+    def put_nowait(self, item):
+        """Don't actually do anything with the item."""
+
+
 class RowIterator(HTTPIterator):
     """A class for iterating through HTTP/JSON API row list responses.
 
@@ -1392,7 +1410,7 @@ def _to_dataframe_tabledata_list(self, dtypes, progress_bar=None):
         return pandas.concat(frames)
 
     def _to_dataframe_bqstorage_stream(
-        self, bqstorage_client, dtypes, columns, session, stream
+        self, bqstorage_client, dtypes, columns, session, stream, worker_queue
     ):
         position = bigquery_storage_v1beta1.types.StreamPosition(stream=stream)
         rowstream = bqstorage_client.read_rows(position).rows(session)
@@ -1403,6 +1421,13 @@ def _to_dataframe_bqstorage_stream(
                 return
             frames.append(page.to_dataframe(dtypes=dtypes))
 
+            try:
+                worker_queue.put_nowait(page.num_items)
+            except queue.Full:
+                # It's okay if we miss a few progress updates. Don't slow
+                # down parsing for that.
+                pass
+
         # Avoid errors on unlucky streams with no blocks. pandas.concat
         # will fail on an empty list.
         if not frames:
@@ -1412,7 +1437,47 @@ def _to_dataframe_bqstorage_stream(
         # the end using manually-parsed schema.
         return pandas.concat(frames)[columns]
 
-    def _to_dataframe_bqstorage(self, bqstorage_client, dtypes):
+    def _process_worker_updates(self, worker_queue, progress_queue):
+        last_update_time = time.time()
+        current_update = 0
+
+        # Sum all updates in a contant loop.
+        while True:
+            try:
+                current_update += worker_queue.get(timeout=_PROGRESS_INTERVAL)
+
+                # Time to send to the progress bar queue?
+                current_time = time.time()
+                elapsed_time = current_time - last_update_time
+                if elapsed_time > _PROGRESS_WORKER_INTERVAL:
+                    progress_queue.put(current_update)
+                    last_update_time = current_time
+                    current_update = 0
+
+            except queue.Empty:
+                # Keep going, unless there probably aren't going to be any
+                # additional updates.
+                if self._to_dataframe_finished:
+                    progress_queue.put(current_update)
+                    return
+
+    def _process_progress_updates(self, progress_queue, progress_bar):
+        if progress_bar is None:
+            return
+
+        # Output all updates since the last interval.
+        while True:
+            try:
+                next_update = progress_queue.get_nowait()
+                progress_bar.update(next_update)
+            except queue.Empty:
+                break
+
+        if self._to_dataframe_finished:
+            progress_bar.close()
+            return
+
+    def _to_dataframe_bqstorage(self, bqstorage_client, dtypes, progress_bar=None):
         """Use (faster, but billable) BQ Storage API to construct DataFrame."""
         if bigquery_storage_v1beta1 is None:
             raise ValueError(_NO_BQSTORAGE_ERROR)
@@ -1451,6 +1516,18 @@ def _to_dataframe_bqstorage(self, bqstorage_client, dtypes):
         # See: https://stackoverflow.com/a/29237343/101923
         self._to_dataframe_finished = False
 
+        # Create a queue to track progress updates across threads.
+        worker_queue = _NoopProgressBarQueue()
+        progress_queue = None
+        progress_thread = None
+        if progress_bar is not None:
+            worker_queue = queue.Queue()
+            progress_queue = queue.Queue()
+            progress_thread = threading.Thread(
+                target=self._process_worker_updates, args=(worker_queue, progress_queue)
+            )
+            progress_thread.start()
+
         def get_frames(pool):
             frames = []
 
@@ -1466,6 +1543,7 @@ def get_frames(pool):
                     columns,
                     session,
                     stream,
+                    worker_queue,
                 )
                 for stream in session.streams
             ]
@@ -1475,6 +1553,11 @@ def get_frames(pool):
                     not_done, timeout=_PROGRESS_INTERVAL
                 )
                 frames.extend([future.result() for future in done])
+
+                # The progress bar needs to update on the main thread to avoid
+                # contention over stdout / stderr.
+                self._process_progress_updates(progress_queue, progress_bar)
+
             return frames
 
         with concurrent.futures.ThreadPoolExecutor() as pool:
@@ -1486,6 +1569,14 @@ def get_frames(pool):
                 # definition (enforced by the global interpreter lock).
                 self._to_dataframe_finished = True
 
+                # Shutdown all background threads, now that they should know to
+                # exit early.
+                pool.shutdown(wait=True)
+                if progress_thread is not None:
+                    progress_thread.join()
+
+        # Update the progress bar one last time to close it.
+        self._process_progress_updates(progress_queue, progress_bar)
         return pandas.concat(frames)
 
     def _get_progress_bar(self, progress_bar_type):
@@ -1585,7 +1676,9 @@ def to_dataframe(self, bqstorage_client=None, dtypes=None, progress_bar_type=Non
 
         if bqstorage_client is not None:
             try:
-                return self._to_dataframe_bqstorage(bqstorage_client, dtypes)
+                return self._to_dataframe_bqstorage(
+                    bqstorage_client, dtypes, progress_bar=progress_bar
+                )
             except google.api_core.exceptions.Forbidden:
                 # Don't hide errors such as insufficient permissions to create
                 # a read session, or the API is not enabled. Both of those are

bigquery/tests/unit/test_table.py

@@ -22,6 +22,7 @@
 import mock
 import pytest
 import six
+from six.moves import queue
 
 import google.api_core.exceptions
 
@@ -1816,9 +1817,12 @@ def test_to_dataframe_w_bqstorage_nonempty(self):
         bqstorage_client = mock.create_autospec(
             bigquery_storage_v1beta1.BigQueryStorageClient
         )
-        session = bigquery_storage_v1beta1.types.ReadSession(
-            streams=[{"name": "/projects/proj/dataset/dset/tables/tbl/streams/1234"}]
-        )
+        streams = [
+            # Use two streams we want to check frames are read from each stream.
+            {"name": "/projects/proj/dataset/dset/tables/tbl/streams/1234"},
+            {"name": "/projects/proj/dataset/dset/tables/tbl/streams/5678"},
+        ]
+        session = bigquery_storage_v1beta1.types.ReadSession(streams=streams)
         session.avro_schema.schema = json.dumps(
             {
                 "fields": [
@@ -1836,20 +1840,25 @@ def test_to_dataframe_w_bqstorage_nonempty(self):
 
         mock_rows = mock.create_autospec(reader.ReadRowsIterable)
         mock_rowstream.rows.return_value = mock_rows
+        page_items = [
+            {"colA": 1, "colB": "abc", "colC": 2.0},
+            {"colA": -1, "colB": "def", "colC": 4.0},
+        ]
 
         def blocking_to_dataframe(*args, **kwargs):
             # Sleep for longer than the waiting interval so that we know we're
             # only reading one page per loop at most.
             time.sleep(2 * mut._PROGRESS_INTERVAL)
-            return pandas.DataFrame(
-                {"colA": [1, -1], "colB": ["abc", "def"], "colC": [2.0, 4.0]},
-                columns=["colA", "colB", "colC"],
-            )
+            return pandas.DataFrame(page_items, columns=["colA", "colB", "colC"])
 
         mock_page = mock.create_autospec(reader.ReadRowsPage)
         mock_page.to_dataframe.side_effect = blocking_to_dataframe
-        mock_pages = mock.PropertyMock(return_value=(mock_page, mock_page, mock_page))
-        type(mock_rows).pages = mock_pages
+        mock_pages = (mock_page, mock_page, mock_page)
+        type(mock_rows).pages = mock.PropertyMock(return_value=mock_pages)
+
+        # Test that full queue errors are ignored.
+        mock_queue = mock.create_autospec(mut._NoopProgressBarQueue)
+        mock_queue().put_nowait.side_effect = queue.Full
 
         schema = [
             schema.SchemaField("colA", "IGNORED"),
@@ -1866,17 +1875,100 @@ def blocking_to_dataframe(*args, **kwargs):
             selected_fields=schema,
         )
 
-        with mock.patch(
+        with mock.patch.object(mut, "_NoopProgressBarQueue", mock_queue), mock.patch(
             "concurrent.futures.wait", wraps=concurrent.futures.wait
         ) as mock_wait:
             got = row_iterator.to_dataframe(bqstorage_client=bqstorage_client)
 
+        # Are the columns in the expected order?
         column_names = ["colA", "colC", "colB"]
         self.assertEqual(list(got), column_names)
-        self.assertEqual(len(got.index), 6)
+
+        # Have expected number of rows?
+        total_pages = len(streams) * len(mock_pages)
+        total_rows = len(page_items) * total_pages
+        self.assertEqual(len(got.index), total_rows)
+
         # Make sure that this test looped through multiple progress intervals.
         self.assertGreaterEqual(mock_wait.call_count, 2)
 
+        # Make sure that this test pushed to the progress queue.
+        self.assertEqual(mock_queue().put_nowait.call_count, total_pages)
+
+    @unittest.skipIf(pandas is None, "Requires `pandas`")
+    @unittest.skipIf(
+        bigquery_storage_v1beta1 is None, "Requires `google-cloud-bigquery-storage`"
+    )
+    @unittest.skipIf(tqdm is None, "Requires `tqdm`")
+    @mock.patch("tqdm.tqdm")
+    def test_to_dataframe_w_bqstorage_updates_progress_bar(self, tqdm_mock):
+        from google.cloud.bigquery import schema
+        from google.cloud.bigquery import table as mut
+        from google.cloud.bigquery_storage_v1beta1 import reader
+
+        # Speed up testing.
+        mut._PROGRESS_INTERVAL = 0.01
+
+        bqstorage_client = mock.create_autospec(
+            bigquery_storage_v1beta1.BigQueryStorageClient
+        )
+        streams = [
+            # Use two streams we want to check that progress bar updates are
+            # sent from each stream.
+            {"name": "/projects/proj/dataset/dset/tables/tbl/streams/1234"},
+            {"name": "/projects/proj/dataset/dset/tables/tbl/streams/5678"},
+        ]
+        session = bigquery_storage_v1beta1.types.ReadSession(streams=streams)
+        session.avro_schema.schema = json.dumps({"fields": [{"name": "testcol"}]})
+        bqstorage_client.create_read_session.return_value = session
+
+        mock_rowstream = mock.create_autospec(reader.ReadRowsStream)
+        bqstorage_client.read_rows.return_value = mock_rowstream
+
+        mock_rows = mock.create_autospec(reader.ReadRowsIterable)
+        mock_rowstream.rows.return_value = mock_rows
+        mock_page = mock.create_autospec(reader.ReadRowsPage)
+        page_items = [-1, 0, 1]
+        type(mock_page).num_items = mock.PropertyMock(return_value=len(page_items))
+
+        def blocking_to_dataframe(*args, **kwargs):
+            # Sleep for longer than the waiting interval. This ensures the
+            # progress_queue gets written to more than once because it gives
+            # the worker->progress updater time to sum intermediate updates.
+            time.sleep(2 * mut._PROGRESS_INTERVAL)
+            return pandas.DataFrame({"testcol": page_items})
+
+        mock_page.to_dataframe.side_effect = blocking_to_dataframe
+        mock_pages = (mock_page, mock_page, mock_page, mock_page, mock_page)
+        type(mock_rows).pages = mock.PropertyMock(return_value=mock_pages)
+
+        schema = [schema.SchemaField("testcol", "IGNORED")]
+
+        row_iterator = mut.RowIterator(
+            _mock_client(),
+            None,  # api_request: ignored
+            None,  # path: ignored
+            schema,
+            table=mut.TableReference.from_string("proj.dset.tbl"),
+            selected_fields=schema,
+        )
+
+        row_iterator.to_dataframe(
+            bqstorage_client=bqstorage_client, progress_bar_type="tqdm"
+        )
+
+        # Make sure that this test updated the progress bar once per page from
+        # each stream.
+        total_pages = len(streams) * len(mock_pages)
+        expected_total_rows = total_pages * len(page_items)
+        progress_updates = [
+            args[0] for args, kwargs in tqdm_mock().update.call_args_list
+        ]
+        # Should have sent >1 update due to delay in blocking_to_dataframe.
+        self.assertGreater(len(progress_updates), 1)
+        self.assertEqual(sum(progress_updates), expected_total_rows)
+        tqdm_mock().close.assert_called_once()
+
     @unittest.skipIf(pandas is None, "Requires `pandas`")
     @unittest.skipIf(
         bigquery_storage_v1beta1 is None, "Requires `google-cloud-bigquery-storage`"