lostluck commented on a change in pull request #13505:
URL: https://github.com/apache/beam/pull/13505#discussion_r539556727



##########
File path: sdks/go/pkg/beam/runners/dataflow/dataflowlib/metrics.go
##########
@@ -0,0 +1,125 @@
+// Licensed to the Apache Software Foundation (ASF) under one or more
+// contributor license agreements.  See the NOTICE file distributed with
+// this work for additional information regarding copyright ownership.
+// The ASF licenses this file to You under the Apache License, Version 2.0
+// (the "License"); you may not use this file except in compliance with
+// the License.  You may obtain a copy of the License at
+//
+//    http://www.apache.org/licenses/LICENSE-2.0
+//
+// Unless required by applicable law or agreed to in writing, software
+// distributed under the License is distributed on an "AS IS" BASIS,
+// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+// See the License for the specific language governing permissions and
+// limitations under the License.
+
+// Package dataflowlib translates a Beam pipeline model to the
+// Dataflow API job model, for submission to Google Cloud Dataflow.
+
+package dataflowlib
+
+import (
+       "encoding/json"
+       "fmt"
+
+       "github.com/apache/beam/sdks/go/pkg/beam/core/metrics"
+       df "google.golang.org/api/dataflow/v1b3"
+)
+
+// FromMetricUpdates extracts metrics from a slice of MetricUpdate objects and
+// groups them into counters, distributions and gauges.
+//
+// Dataflow currently only reports Counter and Distribution metrics to Cloud
+// Monitoring. Gauge metrics are not supported. The output metrics.Results will
+// not contain any gauges.
+func FromMetricUpdates(allMetrics []*df.MetricUpdate, job *df.Job) 
*metrics.Results {
+       ac, ad := groupByType(allMetrics, job, true)
+       cc, cd := groupByType(allMetrics, job, false)
+
+       return metrics.NewResults(metrics.MergeCounters(ac, cc), 
metrics.MergeDistributions(ad, cd), make([]metrics.GaugeResult, 0))
+}
+
+func groupByType(allMetrics []*df.MetricUpdate, job *df.Job, tentative bool) (
+       map[metrics.StepKey]int64,
+       map[metrics.StepKey]metrics.DistributionValue) {
+       counters := make(map[metrics.StepKey]int64)
+       distributions := make(map[metrics.StepKey]metrics.DistributionValue)
+
+       for _, metric := range allMetrics {
+               isTentative := metric.Name.Context["tentative"] == "true"
+               // Returns true when variables differ (exclusive or)
+               if (isTentative || tentative) && (!isTentative || !tentative) {

Review comment:
       No worries. I've been there myself.




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