vachan-shetty commented on a change in pull request #15185:
URL: https://github.com/apache/beam/pull/15185#discussion_r681125336



##########
File path: sdks/python/apache_beam/io/gcp/bigquery.py
##########
@@ -883,6 +895,221 @@ def _export_files(self, bq):
     return table.schema, metadata_list
 
 
+class _CustomBigQueryStorageSourceBase(BoundedSource):
+  """A base class for BoundedSource implementations which read from BigQuery
+  using the BigQuery Storage API.
+
+  Args:
+    table (str, TableReference): The ID of the table. The ID must contain only
+      letters ``a-z``, ``A-Z``, numbers ``0-9``, or underscores ``_``  If
+      **dataset** argument is :data:`None` then the table argument must
+      contain the entire table reference specified as:
+      ``'PROJECT:DATASET.TABLE'`` or must specify a TableReference.
+    dataset (str): The ID of the dataset containing this table or
+      :data:`None` if the table argument specifies a TableReference.
+    project (str): The ID of the project containing this table or
+      :data:`None` if the table argument specifies a TableReference.
+    selected_fields (List[str]): Names of the fields in the table that should 
be
+      read. If empty, all fields will be read. If the specified field is a
+      nested field, all the sub-fields in the field will be selected. The 
output
+      field order is unrelated to the order of fields in selected_fields.
+    row_restriction (str): SQL text filtering statement, similar to a WHERE
+      clause in a query. Aggregates are not supported.Restricted to a maximum
+      length for 1 MB.
+  """
+
+  # The maximum number of streams which will be requested when creating a read
+  # session, regardless of the desired bundle size.
+  MAX_SPLIT_COUNT = 10000
+  # The minimum number of streams which will be requested when creating a read
+  # session, regardless of the desired bundle size. Note that the server may
+  # still choose to return fewer than ten streams based on the layout of the
+  # table.
+  MIN_SPLIT_COUNT = 10
+
+  def __init__(
+      self,
+      table: Union[str, TableReference],
+      dataset: str = None,
+      project: str = None,
+      selected_fields: List[str] = None,
+      row_restriction: str = None,
+      pipeline_options: GoogleCloudOptions = None):
+
+    self.table_reference = bigquery_tools.parse_table_reference(
+        table, dataset, project)
+    self.project = self.table_reference.projectId
+    self.dataset = self.table_reference.datasetId
+    self.table = self.table_reference.tableId
+    self.selected_fields = selected_fields
+    self.row_restriction = row_restriction
+    self.pipeline_options = pipeline_options
+    self.split_result = None
+
+  def _get_parent_project(self):
+    """Returns the project that will be billed."""
+    project = self.pipeline_options.view_as(GoogleCloudOptions).project
+    if isinstance(project, vp.ValueProvider):
+      project = project.get()
+    if not project:
+      project = self.project
+    return project
+
+  def _get_table_size(self, table, dataset, project):
+    if project is None:
+      project = self._get_parent_project()
+
+    bq = bigquery_tools.BigQueryWrapper()
+    table = bq.get_table(project, dataset, table)
+    return table.numBytes
+
+  def display_data(self):
+    return {
+        'project': str(self.project),
+        'dataset': str(self.dataset),
+        'table': str(self.table),
+        'selected_fields': str(self.selected_fields),
+        'row_restriction': str(self.row_restriction)
+    }
+
+  def estimate_size(self):
+    # The size of stream source cannot be estimate due to server-side liquid
+    # sharding
+    return None
+
+  def split(self, desired_bundle_size, start_position=None, 
stop_position=None):
+    requested_session = bq_storage.types.ReadSession()
+    requested_session.table = 'projects/{}/datasets/{}/tables/{}'.format(
+        self.project, self.dataset, self.table)
+    requested_session.data_format = bq_storage.types.DataFormat.AVRO
+    if self.selected_fields is not None:
+      requested_session.read_options.selected_fields = self.selected_fields
+    if self.row_restriction is not None:
+      requested_session.read_options.row_restriction = self.row_restriction
+
+    storage_client = bq_storage.BigQueryReadClient()
+    stream_count = 0
+    if (desired_bundle_size > 0):
+      table_size = self._get_table_size(self.table, self.dataset, self.project)
+      stream_count = min(
+          int(table_size / desired_bundle_size),
+          _CustomBigQueryStorageSourceBase.MAX_SPLIT_COUNT)
+    stream_count = max(
+        stream_count, _CustomBigQueryStorageSourceBase.MIN_SPLIT_COUNT)
+
+    parent = 'projects/{}'.format(self.project)
+    read_session = storage_client.create_read_session(
+        parent=parent,
+        read_session=requested_session,
+        max_stream_count=stream_count)
+
+    self.split_result = [
+        _CustomBigQueryStorageStreamSource(stream.name)
+        for stream in read_session.streams
+    ]
+
+    for source in self.split_result:
+      yield SourceBundle(
+          weight=1.0, source=source, start_position=None, stop_position=None)
+
+  def get_range_tracker(self, start_position, stop_position):
+    class NonePositionRangeTracker(RangeTracker):
+      """A RangeTracker that always returns positions as None. Prevents the
+      BigQuery Storage source from being read() before being split()."""
+      def start_position(self):
+        return None
+
+      def stop_position(self):
+        return None
+
+    return NonePositionRangeTracker()
+
+  def read(self, range_tracker):
+    raise NotImplementedError(
+        'BigQuery storage source must be split before being read')
+
+
+class _CustomBigQueryStorageStreamSource(BoundedSource):
+  """A source representing a single stream in a read session."""
+  def __init__(self, read_stream_name: str):
+    self.read_stream_name = read_stream_name
+
+  def display_data(self):
+    return {
+        'read_stream': str(self.read_stream_name),
+    }
+
+  def estimate_size(self):
+    # The size of stream source cannot be estimate due to server-side liquid
+    # sharding
+    return None
+
+  def split(self, desired_bundle_size, start_position=None, 
stop_position=None):
+    # A stream source can't be split without reading from it due to
+    # server-side liquid sharding.
+    raise NotImplementedError('BigQuery storage stream source cannot be 
split.')
+
+  def get_range_tracker(self, start_position, stop_position):
+    if start_position is None:
+      # Defaulting to the start of the stream.
+      start_position = 0
+    # Since the streams are unsplittable we choose OFFSET_INFINITY as the
+    # default end offset so that all data of the source gets read.
+    stop_position = range_trackers.OffsetRangeTracker.OFFSET_INFINITY
+    range_tracker = range_trackers.OffsetRangeTracker(
+        start_position, stop_position)
+    # Ensuring that all try_split() calls will be ignored by the Rangetracker.
+    range_tracker = range_trackers.UnsplittableRangeTracker(range_tracker)
+
+    return range_tracker
+
+  def read(self, range_tracker):
+    storage_client = bq_storage.BigQueryReadClient()
+    read_rows_iterator = iter(storage_client.read_rows(self.read_stream_name))
+    # Handling the case where the user might provide very selective filters
+    # which can result in read_rows_response being empty.
+    first_read_rows_response = next(read_rows_iterator, None)
+    if first_read_rows_response is None:
+      return iter([])
+    row_reader = _ReadRowsResponseReader(

Review comment:
       We need to keep track of the both the current row number being 
deserialized (for each response) and also ensure that `read_rows_iterator` 
progresses through its contents correctly. This requires recursive calls to any 
generator that can be used here. In other words, this would work well only by 
using `yield from` (Py 3.3+)
   
   The iterator class makes this state tracking more explicit and easier to 
follow IMO. And since it is version agnostic might be safer to use as well.




-- 
This is an automated message from the Apache Git Service.
To respond to the message, please log on to GitHub and use the
URL above to go to the specific comment.

To unsubscribe, e-mail: [email protected]

For queries about this service, please contact Infrastructure at:
[email protected]


Reply via email to