[exporter/awsemfexporter]Split EMF log with larger than 100 buckets.

.chloggen/split-emf-log-when-buckets-larger-than-100.yaml

@@ -0,0 +1,27 @@
+# Use this changelog template to create an entry for release notes.
+
+# One of 'breaking', 'deprecation', 'new_component', 'enhancement', 'bug_fix'
+change_type: enhancement
+
+# The name of the component, or a single word describing the area of concern, (e.g. filelogreceiver)
+component: awsemfexporter
+
+# A brief description of the change.  Surround your text with quotes ("") if it needs to start with a backtick (`).
+note: Split EMF log to multiple log splits when buckets larger than 100.
+
+# Mandatory: One or more tracking issues related to the change. You can use the PR number here if no issue exists.
+issues: [242]
+
+# (Optional) One or more lines of additional information to render under the primary note.
+# These lines will be padded with 2 spaces and then inserted directly into the document.
+# Use pipe (|) for multiline entries.
+subtext:
+
+# If your change doesn't affect end users or the exported elements of any package,
+# you should instead start your pull request title with [chore] or use the "Skip Changelog" label.
+# Optional: The change log or logs in which this entry should be included.
+# e.g. '[user]' or '[user, api]'
+# Include 'user' if the change is relevant to end users.
+# Include 'api' if there is a change to a library API.
+# Default: '[user]'
+change_logs: []

exporter/awsemfexporter/datapoint.go

@@ -109,6 +109,33 @@ type summaryMetricEntry struct {
 	count uint64
 }
 
+// dataPointSplit is a structure used to manage segments of data points split from a histogram.
+// It is not safe for concurrent use.
+type dataPointSplit struct {
+	cWMetricHistogram *cWMetricHistogram
+	length            int
+	capacity          int
+}
+
+func (split *dataPointSplit) isFull() bool {
+	return split.length >= split.capacity
+}
+
+func (split *dataPointSplit) setMax(maxVal float64) {
+	split.cWMetricHistogram.Max = maxVal
+}
+
+func (split *dataPointSplit) setMin(minVal float64) {
+	split.cWMetricHistogram.Min = minVal
+}
+
+func (split *dataPointSplit) appendMetricData(metricVal float64, count uint64) {
+	split.cWMetricHistogram.Values = append(split.cWMetricHistogram.Values, metricVal)
+	split.cWMetricHistogram.Counts = append(split.cWMetricHistogram.Counts, float64(count))
+	split.length++
+	split.cWMetricHistogram.Count += count
+}
+
 // CalculateDeltaDatapoints retrieves the NumberDataPoint at the given index and performs rate/delta calculation if necessary.
 func (dps numberDataPointSlice) CalculateDeltaDatapoints(i int, instrumentationScopeName string, _ bool, calculators *emfCalculators) ([]dataPoint, bool) {
 	metric := dps.NumberDataPointSlice.At(i)
@@ -193,85 +220,195 @@ func (dps histogramDataPointSlice) IsStaleNaNInf(i int) (bool, pcommon.Map) {
 }
 
 // CalculateDeltaDatapoints retrieves the ExponentialHistogramDataPoint at the given index.
+// As CloudWatch EMF logs allows in maximum of 100 target members, the exponential histogram metric are split into multiple data points as needed,
+// each containing a maximum of 100 buckets, to comply with CloudWatch EMF log constraints.
+// Note that the number of values and counts in each split may not be less than splitThreshold as we are only adding non-zero bucket counts.
+//
+// For each split data point:
+// - Min and Max values are recalculated based on the bucket boundary within that specific split.
+// - Sum is only assigned to the first split to ensure the total sum of the datapoints after aggregation is correct.
+// - Count is accumulated based on the bucket counts within each split.
 func (dps exponentialHistogramDataPointSlice) CalculateDeltaDatapoints(idx int, instrumentationScopeName string, _ bool, _ *emfCalculators) ([]dataPoint, bool) {
 	metric := dps.ExponentialHistogramDataPointSlice.At(idx)
 
+	const splitThreshold = 100
+	currentBucketIndex := 0
+	currentPositiveIndex := metric.Positive().BucketCounts().Len() - 1
+	currentZeroIndex := 0
+	currentNegativeIndex := 0
+	var datapoints []dataPoint
+	totalBucketLen := metric.Positive().BucketCounts().Len() + metric.Negative().BucketCounts().Len()
+	if metric.ZeroCount() > 0 {
+		totalBucketLen++
+	}
+
+	for currentBucketIndex < totalBucketLen {
+		// Create a new dataPointSplit with a capacity of up to splitThreshold buckets
+		capacity := min(splitThreshold, totalBucketLen-currentBucketIndex)
+
+		sum := 0.0
+		// Only assign `Sum` if this is the first split to make sure the total sum of the datapoints after aggregation is correct.
+		if currentBucketIndex == 0 {
+			sum = metric.Sum()
+		}
+
+		split := dataPointSplit{
+			cWMetricHistogram: &cWMetricHistogram{
+				Values: []float64{},
+				Counts: []float64{},
+				Max:    metric.Max(),
+				Min:    metric.Min(),
+				Count:  0,
+				Sum:    sum,
+			},
+			length:   0,
+			capacity: capacity,
+		}
+
+		// Set collect values from positive buckets and save into split.
+		currentBucketIndex, currentPositiveIndex = collectDatapointsWithPositiveBuckets(&split, metric, currentBucketIndex, currentPositiveIndex)
+		// Set collect values from zero buckets and save into split.
+		currentBucketIndex, currentZeroIndex = collectDatapointsWithZeroBucket(&split, metric, currentBucketIndex, currentZeroIndex)
+		// Set collect values from negative buckets and save into split.
+		currentBucketIndex, currentNegativeIndex = collectDatapointsWithNegativeBuckets(&split, metric, currentBucketIndex, currentNegativeIndex)
+
+		if split.length > 0 {
+			// Add the current split to the datapoints list
+			datapoints = append(datapoints, dataPoint{
+				name:        dps.metricName,
+				value:       split.cWMetricHistogram,
+				labels:      createLabels(metric.Attributes(), instrumentationScopeName),
+				timestampMs: unixNanoToMilliseconds(metric.Timestamp()),
+			})
+		}
+	}
+
+	if len(datapoints) == 0 {
+		return []dataPoint{{
+			name: dps.metricName,
+			value: &cWMetricHistogram{
+				Values: []float64{},
+				Counts: []float64{},
+				Count:  metric.Count(),
+				Sum:    metric.Sum(),
+				Max:    metric.Max(),
+				Min:    metric.Min(),
+			},
+			labels:      createLabels(metric.Attributes(), instrumentationScopeName),
+			timestampMs: unixNanoToMilliseconds(metric.Timestamp()),
+		}}, true
+	}
+
+	// Override the min and max values of the first and last splits with the raw data of the metric.
+	datapoints[0].value.(*cWMetricHistogram).Max = metric.Max()
+	datapoints[len(datapoints)-1].value.(*cWMetricHistogram).Min = metric.Min()
+
+	return datapoints, true
+}
+
+func collectDatapointsWithPositiveBuckets(split *dataPointSplit, metric pmetric.ExponentialHistogramDataPoint, currentBucketIndex int, currentPositiveIndex int) (int, int) {
+	if split.isFull() || currentPositiveIndex < 0 {
+		return currentBucketIndex, currentPositiveIndex
+	}
+
 	scale := metric.Scale()
 	base := math.Pow(2, math.Pow(2, float64(-scale)))
-	arrayValues := []float64{}
-	arrayCounts := []float64{}
-	var bucketBegin float64
-	var bucketEnd float64
-
-	// Set mid-point of positive buckets in values/counts array.
 	positiveBuckets := metric.Positive()
 	positiveOffset := positiveBuckets.Offset()
 	positiveBucketCounts := positiveBuckets.BucketCounts()
-	bucketBegin = 0
-	bucketEnd = 0
-	for i := 0; i < positiveBucketCounts.Len(); i++ {
-		index := i + int(positiveOffset)
-		if bucketBegin == 0 {
-			bucketBegin = math.Pow(base, float64(index))
+	bucketBegin := 0.0
+	bucketEnd := 0.0
+
+	for !split.isFull() && currentPositiveIndex >= 0 {
+		index := currentPositiveIndex + int(positiveOffset)
+		if bucketEnd == 0 {
+			bucketEnd = math.Pow(base, float64(index+1))
 		} else {
-			bucketBegin = bucketEnd
+			bucketEnd = bucketBegin
 		}
-		bucketEnd = math.Pow(base, float64(index+1))
+		bucketBegin = math.Pow(base, float64(index))
 		metricVal := (bucketBegin + bucketEnd) / 2
-		count := positiveBucketCounts.At(i)
+		count := positiveBucketCounts.At(currentPositiveIndex)
 		if count > 0 {
-			arrayValues = append(arrayValues, metricVal)
-			arrayCounts = append(arrayCounts, float64(count))
+			split.appendMetricData(metricVal, count)
+
+			// The value are append from high to low, set Max from the first bucket (highest value) and Min from the last bucket (lowest value)
+			if split.length == 1 {
+				split.setMax(bucketEnd)
+			}
+			if split.isFull() {
+				split.setMin(bucketBegin)
+			}
 		}
+		currentBucketIndex++
+		currentPositiveIndex--
 	}
 
-	// Set count of zero bucket in values/counts array.
-	if metric.ZeroCount() > 0 {
-		arrayValues = append(arrayValues, 0)
-		arrayCounts = append(arrayCounts, float64(metric.ZeroCount()))
+	return currentBucketIndex, currentPositiveIndex
+}
+
+func collectDatapointsWithZeroBucket(split *dataPointSplit, metric pmetric.ExponentialHistogramDataPoint, currentBucketIndex int, currentZeroIndex int) (int, int) {
+	if metric.ZeroCount() > 0 && !split.isFull() && currentZeroIndex == 0 {
+		split.appendMetricData(0, metric.ZeroCount())
+
+		// The value are append from high to low, set Max from the first bucket (highest value) and Min from the last bucket (lowest value)
+		if split.length == 1 {
+			split.setMax(0)
+		}
+		if split.isFull() {
+			split.setMin(0)
+		}
+		currentZeroIndex++
+		currentBucketIndex++
 	}
 
-	// Set mid-point of negative buckets in values/counts array.
+	return currentBucketIndex, currentZeroIndex
+}
+
+func collectDatapointsWithNegativeBuckets(split *dataPointSplit, metric pmetric.ExponentialHistogramDataPoint, currentBucketIndex int, currentNegativeIndex int) (int, int) {
 	// According to metrics spec, the value in histogram is expected to be non-negative.
 	// https://opentelemetry.io/docs/specs/otel/metrics/api/#histogram
 	// However, the negative support is defined in metrics data model.
 	// https://opentelemetry.io/docs/specs/otel/metrics/data-model/#exponentialhistogram
 	// The negative is also supported but only verified with unit test.
+	if split.isFull() || currentNegativeIndex >= metric.Negative().BucketCounts().Len() {
+		return currentBucketIndex, currentNegativeIndex
+	}
 
+	scale := metric.Scale()
+	base := math.Pow(2, math.Pow(2, float64(-scale)))
 	negativeBuckets := metric.Negative()
 	negativeOffset := negativeBuckets.Offset()
 	negativeBucketCounts := negativeBuckets.BucketCounts()
-	bucketBegin = 0
-	bucketEnd = 0
-	for i := 0; i < negativeBucketCounts.Len(); i++ {
-		index := i + int(negativeOffset)
+	bucketBegin := 0.0
+	bucketEnd := 0.0
+
+	for !split.isFull() && currentNegativeIndex < metric.Negative().BucketCounts().Len() {
+		index := currentNegativeIndex + int(negativeOffset)
 		if bucketEnd == 0 {
 			bucketEnd = -math.Pow(base, float64(index))
 		} else {
 			bucketEnd = bucketBegin
 		}
 		bucketBegin = -math.Pow(base, float64(index+1))
 		metricVal := (bucketBegin + bucketEnd) / 2
-		count := negativeBucketCounts.At(i)
+		count := negativeBucketCounts.At(currentNegativeIndex)
 		if count > 0 {
-			arrayValues = append(arrayValues, metricVal)
-			arrayCounts = append(arrayCounts, float64(count))
+			split.appendMetricData(metricVal, count)
+
+			// The value are append from high to low, set Max from the first bucket (highest value) and Min from the last bucket (lowest value)
+			if split.length == 1 {
+				split.setMax(bucketEnd)
+			}
+			if split.isFull() {
+				split.setMin(bucketBegin)
+			}
 		}
+		currentBucketIndex++
+		currentNegativeIndex++
 	}
 
-	return []dataPoint{{
-		name: dps.metricName,
-		value: &cWMetricHistogram{
-			Values: arrayValues,
-			Counts: arrayCounts,
-			Count:  metric.Count(),
-			Sum:    metric.Sum(),
-			Max:    metric.Max(),
-			Min:    metric.Min(),
-		},
-		labels:      createLabels(metric.Attributes(), instrumentationScopeName),
-		timestampMs: unixNanoToMilliseconds(metric.Timestamp()),
-	}}, true
+	return currentBucketIndex, currentNegativeIndex
 }
 
 func (dps exponentialHistogramDataPointSlice) IsStaleNaNInf(i int) (bool, pcommon.Map) {