[BEAM-9945] [release-2.21.0] Report data channel progress via a designated counter.

Author: Kyle Weaver

model/pipeline/src/main/proto/metrics.proto

@@ -292,6 +292,21 @@ message MonitoringInfoSpecs {
         value: "The remaining amount of work for each active element. Each active element represents an independent amount of work not shared with any other active element."
       }]
     }];
+
+    // The (0-based) index of the latest item processed from the data channel.
+    // This gives an indication of the SDKs progress through the data channel,
+    // and is a lower bound on where it is able to split.
+    // For an SDK that processes items sequentially, this is equivalently the
+    // number of items fully processed (or -1 if processing has not yet started).
+    DATA_CHANNEL_READ_INDEX = 18 [(monitoring_info_spec) = {
+      urn: "beam:metric:data_channel:read_index:v1",
+      type: "beam:metrics:sum_int64:v1",
+      required_labels: [ "PTRANSFORM" ],
+      annotations: [{
+        key: "description",
+        value: "The read index of the data channel."
+      }]
+    }];
   }
 }
 
@@ -511,4 +526,3 @@ message MonitoringInfoTypeUrns {
 //   repeated string column_names = 1;
 //   repeated MonitoringRow row_data = 2;
 // }
-

sdks/python/apache_beam/metrics/monitoring_infos.py

@@ -56,6 +56,8 @@
     [USER_COUNTER_URN, USER_DISTRIBUTION_URN, USER_GAUGE_URN])
 WORK_REMAINING_URN = common_urns.monitoring_info_specs.WORK_REMAINING.spec.urn
 WORK_COMPLETED_URN = common_urns.monitoring_info_specs.WORK_COMPLETED.spec.urn
+DATA_CHANNEL_READ_INDEX = (
+    common_urns.monitoring_info_specs.DATA_CHANNEL_READ_INDEX.spec.urn)
 
 # TODO(ajamato): Implement the remaining types, i.e. Double types
 # Extrema types, etc. See:

sdks/python/apache_beam/runners/worker/bundle_processor.py

@@ -217,6 +217,18 @@ def process_encoded(self, encoded_windowed_values):
           input_stream, True)
       self.output(decoded_value)
 
+  def monitoring_infos(self, transform_id, tag_to_pcollection_id):
+    # type: (str, Dict[str, str]) -> Dict[FrozenSet, metrics_pb2.MonitoringInfo]
+    all_monitoring_infos = super(DataInputOperation, self).monitoring_infos(
+        transform_id, tag_to_pcollection_id)
+    read_progress_info = monitoring_infos.int64_counter(
+        monitoring_infos.DATA_CHANNEL_READ_INDEX,
+        self.index,
+        ptransform=transform_id)
+    all_monitoring_infos[monitoring_infos.to_key(
+        read_progress_info)] = read_progress_info
+    return all_monitoring_infos
+
   def try_split(
       self, fraction_of_remainder, total_buffer_size, allowed_split_points):
     # type: (...) -> Optional[Tuple[int, Optional[operations.SdfSplitResultsPrimary], Optional[operations.SdfSplitResultsResidual], int]]