tracing/tracing/metrics/v8/runtime_stats_metric.html - Issue 2639993002: Adds runtimeStatsTotalMetric to collect v8 metrics and bucket them based on UE.

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Issue 2639993002: Adds runtimeStatsTotalMetric to collect v8 metrics and bucket them based on UE. (Closed)

Patch Set: Fixed to add only one sample for each UE. Created 3 years, 10 months ago

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1 <!DOCTYPE html>	1 <!DOCTYPE html>

2 <!--	2 <!--

3 Copyright 2016 The Chromium Authors. All rights reserved.	3 Copyright 2016 The Chromium Authors. All rights reserved.

4 Use of this source code is governed by a BSD-style license that can be	4 Use of this source code is governed by a BSD-style license that can be

5 found in the LICENSE file.	5 found in the LICENSE file.

6 -->	6 -->

7	7

8 <link rel="import" href="/tracing/base/range.html">	8 <link rel="import" href="/tracing/base/range.html">

9 <link rel="import" href="/tracing/base/unit.html">	9 <link rel="import" href="/tracing/base/unit.html">

10 <link rel="import" href="/tracing/extras/v8/runtime_stats_entry.html">	10 <link rel="import" href="/tracing/extras/v8/runtime_stats_entry.html">

(...skipping 63 matching lines...) Expand 10 before \| Expand all \| Expand 10 after Loading...
74 std: false, count: false, sum: false, min: false, max: false	74 std: false, count: false, sum: false, min: false, max: false

75 });	75 });

76 return histogram;	76 return histogram;

77 }	77 }

78	78

79 function convertMicroToMilli_(time) {	79 function convertMicroToMilli_(time) {

80 return tr.b.convertUnit(time,	80 return tr.b.convertUnit(time,

81 tr.b.UnitPrefixScale.METRIC.MICRO, tr.b.UnitPrefixScale.METRIC.MILLI);	81 tr.b.UnitPrefixScale.METRIC.MICRO, tr.b.UnitPrefixScale.METRIC.MILLI);

82 }	82 }

83	83

84 function computeRuntimeStats(values, model, endTime) {	84 // TODO(crbug.com/688342): Remove this function when runtimeStatsMetric is

85 var slices = [...model.getDescendantEvents()].filter(event =>	85 // removed.

86 event instanceof tr.e.v8.V8ThreadSlice &&	86 function computeRuntimeStats(histograms, slices) {

87 event.start <= endTime);

88	87

89 var runtimeGroupCollection = new tr.e.v8.RuntimeStatsGroupCollection();	88 var runtimeGroupCollection = new tr.e.v8.RuntimeStatsGroupCollection();

90 runtimeGroupCollection.addSlices(slices);	89 runtimeGroupCollection.addSlices(slices);

91	90

92 for (var runtimeGroup of runtimeGroupCollection.runtimeGroups) {	91 for (var runtimeGroup of runtimeGroupCollection.runtimeGroups) {

93 var durationSamples = new tr.v.d.RelatedHistogramBreakdown();	92 var durationSamples = new tr.v.d.RelatedHistogramBreakdown();

94 var countSamples = new tr.v.d.RelatedHistogramBreakdown();	93 var countSamples = new tr.v.d.RelatedHistogramBreakdown();

95 for (var entry of runtimeGroup.values) {	94 for (var entry of runtimeGroup.values) {

96 var durationSampleHistogram = createDurationHistogram_(entry.name);	95 var durationSampleHistogram = createDurationHistogram_(entry.name);

97 durationSampleHistogram.addSample(convertMicroToMilli_(entry.time));	96 durationSampleHistogram.addSample(convertMicroToMilli_(entry.time));

98 durationSamples.set(entry.name + ':duration', durationSampleHistogram);	97 durationSamples.set(entry.name + ':duration', durationSampleHistogram);

99 values.addHistogram(durationSampleHistogram);	98 histograms.addHistogram(durationSampleHistogram);

100	99

101 var countSampleHistogram = createCountHistogram_(entry.name);	100 var countSampleHistogram = createCountHistogram_(entry.name);

102 countSampleHistogram.addSample(entry.count);	101 countSampleHistogram.addSample(entry.count);

103 countSamples.set(entry.name + ':count', countSampleHistogram);	102 countSamples.set(entry.name + ':count', countSampleHistogram);

104 values.addHistogram(countSampleHistogram);	103 histograms.addHistogram(countSampleHistogram);

105 }	104 }

106	105

107 var durationHistogram = createDurationHistogram_(runtimeGroup.name);	106 var durationHistogram = createDurationHistogram_(runtimeGroup.name);

108 durationHistogram.addSample(convertMicroToMilli_(runtimeGroup.time), {	107 durationHistogram.addSample(convertMicroToMilli_(runtimeGroup.time), {

109 samples: durationSamples	108 samples: durationSamples

110 });	109 });

111 var countHistogram = createCountHistogram_(runtimeGroup.name);	110 var countHistogram = createCountHistogram_(runtimeGroup.name);

112 countHistogram.addSample(runtimeGroup.count, {	111 countHistogram.addSample(runtimeGroup.count, {

113 samples: countSamples	112 samples: countSamples

114 });	113 });

115	114

116 values.addHistogram(durationHistogram);	115 histograms.addHistogram(durationHistogram);

117 values.addHistogram(countHistogram);	116 histograms.addHistogram(countHistogram);

118 }	117 }

119 }	118 }

120	119

121 function runtimeStatsMetric(values, model) {	120 // TODO(crbug.com/688342): Remove this metric and use runtimeStatsTotalMetric

	121 // instead when the runtimeStatsTotalMetric is stable.

	122 function runtimeStatsMetric(histograms, model) {

122 var interactiveTime = computeInteractiveTime_(model);	123 var interactiveTime = computeInteractiveTime_(model);

123 var domContentLoadedTime = computeDomContentLoadedTime_(model);	124 var domContentLoadedTime = computeDomContentLoadedTime_(model);

124 var endTime = Math.max(interactiveTime, domContentLoadedTime);	125 var endTime = Math.max(interactiveTime, domContentLoadedTime);

125 computeRuntimeStats(values, model, endTime);	126 var slices = [...model.getDescendantEvents()].filter(event =>

	127 event instanceof tr.e.v8.V8ThreadSlice && event.start <= endTime);

	128 computeRuntimeStats(histograms, slices);

126 }	129 }

127	130

	131 function computeRuntimeStatsBucketOnUE(histograms, slices,

	132 histogramNamePrefix) {

	133 var runtimeGroupCollection = new tr.e.v8.RuntimeStatsGroupCollection();

	134 runtimeGroupCollection.addSlices(slices);

	135

	136 for (var runtimeGroup of runtimeGroupCollection.runtimeGroups) {

	137 var histogramName = histogramNamePrefix + '_' + runtimeGroup.name;

	138 var durationHistogram = createDurationHistogram_(histogramName);

	139 durationHistogram.addSample(convertMicroToMilli_(runtimeGroup.time));

	140 histograms.addHistogram(durationHistogram);

	141

	142 var countHistogram = createCountHistogram_(histogramName);

	143 countHistogram.addSample(runtimeGroup.count);

	144 histograms.addHistogram(countHistogram);

	145 }

	146 }

	147

	148 function runtimeStatsTotalMetric(histograms, model) {

	149 var v8ThreadSlices = [...model.getDescendantEvents()].filter(event =>

	150 event instanceof tr.e.v8.V8ThreadSlice).sort((e1, e2) =>

	151 e1.start - e2.start);

	152 var v8SlicesBucketOnUEMap = {};
	benjhayden 2017/02/10 17:59:25 Please use ES6 Maps instead of dictionaries. Please use ES6 Maps instead of dictionaries. mythria 2017/02/13 15:54:49 Done. Show quoted text On 2017/02/10 17:59:25, benjhayden wrote: > Please use ES6 Maps instead of dictionaries. Done.
	153 // User expectations can sometime overlap. So, certain v8 slices can be

	154 // included in more than one expectation. We count such slices in each

	155 // of the expectations. This is done so as to minimize the noise due to

	156 // the differences in the extent of overlap between the runs.

	157 for (var expectation of model.userModel.expectations) {

	158 var slices = expectation.range.filterArray(v8ThreadSlices,

	159 event => event.start);

	160 if (slices.length === 0) continue;

	161 // filterArray filters the array that intersects the range inclusively.

	162 // Expectations are not inclusive i.e. expectations are like [0, 1),

	163 // [1, 2). v8ThreadSlices that start at 1 should be counted only in [1,2)

	164 // bucket. Filter out sample at the boundary so that they are not counted

	165 // twice.

	166 var lastSlice = slices[slices.length - 1];

	167 if (!expectation.range.intersectsRangeExclusive(lastSlice.range))
	benjhayden 2017/02/10 17:59:25 Please use curly braces here. https://github.com/c Please use curly braces here. https://github.com/catapult-project/catapult/blob/master/docs/style-guide.md#... mythria 2017/02/13 15:54:49 Thanks. Done. Show quoted text On 2017/02/10 17:59:25, benjhayden wrote: > Please use curly braces here. > https://github.com/catapult-project/catapult/blob/master/docs/style-guide.md#... Thanks. Done.
	168 slices.pop();

	169

	170 if (v8SlicesBucketOnUEMap[expectation.stageTitle] === undefined) {

	171 v8SlicesBucketOnUEMap[expectation.stageTitle] = slices;

	172 } else {

	173 var totalSlices = v8SlicesBucketOnUEMap[expectation.stageTitle].concat(

	174 slices);

	175 v8SlicesBucketOnUEMap[expectation.stageTitle] = totalSlices;

	176 }

	177 }

	178

	179 // Add histograms for each UE.

	180 for (var name in v8SlicesBucketOnUEMap) {

	181 computeRuntimeStatsBucketOnUE(histograms, v8SlicesBucketOnUEMap[name],

	182 name);
	mythria 2017/02/09 17:21:39 We just want to add one sample per each UE, basica We just want to add one sample per each UE, basically the sum of all slices for that UE. I am sorry, I did not realize that what I did earlier will add multiple samples to the histogram and hence the metrics we may track would not be the sum of all samples in each UE, but would be the average of the UEs in each bucket. benjhayden 2017/02/10 17:59:25 Just to clarify, this doesn't add one sample per U Show quoted text On 2017/02/09 at 17:21:39, mythria wrote: > We just want to add one sample per each UE, basically the sum of all slices for that UE. I am sorry, I did not realize that what I did earlier will add multiple samples to the histogram and hence the metrics we may track would not be the sum of all samples in each UE, but would be the average of the UEs in each bucket. Just to clarify, this doesn't add one sample per UserExpectation object, this code adds one sample per unique stageTitle (R/A/I/L). Both can be valid metric formulations, and it can also be valid to add one histogram sample per v8 sample. Which formulation you want is up to you, the metric designer. If you're not sure, you can try the metric this way, see how it works out, and then revisit this design decision. Histograms can compute both average and sum statistics, so the differences between the 3 formulations are basically only relevant when you consider how Histograms will be merged across story repetitions and stories. This merging currently only happens in results.html, but it will be happening in the Histogram Pipeline soon, which will affect the data on the dashboard. Once historic data is on the dashboard, you can't easily recompute it, so if you need to reformulate a metric down the road, you might lose historical continuity in the charts on the dashboard. This is all just FYI, and an apology for not knowing how to explain it very well on how-to-write-metrics.md. :-) mythria 2017/02/13 15:54:49 Thanks for the detailed explanation. Show quoted text On 2017/02/10 17:59:25, benjhayden wrote: > On 2017/02/09 at 17:21:39, mythria wrote: > > We just want to add one sample per each UE, basically the sum of all slices > for that UE. I am sorry, I did not realize that what I did earlier will add > multiple samples to the histogram and hence the metrics we may track would not > be the sum of all samples in each UE, but would be the average of the UEs in > each bucket. > > Just to clarify, this doesn't add one sample per UserExpectation object, this > code adds one sample per unique stageTitle (R/A/I/L). > Both can be valid metric formulations, and it can also be valid to add one > histogram sample per v8 sample. > Which formulation you want is up to you, the metric designer. If you're not > sure, you can try the metric this way, see how it works out, and then revisit > this design decision. > Histograms can compute both average and sum statistics, so the differences > between the 3 formulations are basically only relevant when you consider how > Histograms will be merged across story repetitions and stories. This merging > currently only happens in results.html, but it will be happening in the > Histogram Pipeline soon, which will affect the data on the dashboard. Once > historic data is on the dashboard, you can't easily recompute it, so if you need > to reformulate a metric down the road, you might lose historical continuity in > the charts on the dashboard. > > This is all just FYI, and an apology for not knowing how to explain it very well > on how-to-write-metrics.md. :-) Thanks for the detailed explanation.
	183 }

	184 // Also compute the metric that includes all of the samples. The values

	185 // in UE buckets do not add up to the total of all samples, since we

	186 // duplicate some of the samples in multiple buckets when the UEs overlap.

	187 computeRuntimeStatsBucketOnUE(histograms, v8ThreadSlices, 'Any');

	188 }

	189

	190 tr.metrics.MetricRegistry.register(runtimeStatsTotalMetric);

128 tr.metrics.MetricRegistry.register(runtimeStatsMetric);	191 tr.metrics.MetricRegistry.register(runtimeStatsMetric);

129	192

130 return {	193 return {

131 runtimeStatsMetric,	194 runtimeStatsMetric,

	195 runtimeStatsTotalMetric,

132 };	196 };

133 });	197 });

134 </script>	198 </script>

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