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https://github.com/ClusterCockpit/cc-backend
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Merge pull request #251 from ClusterCockpit/hotfix
Accelerator ID Display Bugs and Footprint
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commit
ddd3fad1c6
@ -205,7 +205,7 @@ func (ccms *CCMetricStore) LoadData(
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jobData[metric][scope] = jobMetric
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}
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for _, res := range row {
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for ndx, res := range row {
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if res.Error != nil {
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/* Build list for "partial errors", if any */
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errors = append(errors, fmt.Sprintf("failed to fetch '%s' from host '%s': %s", query.Metric, query.Hostname, *res.Error))
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@ -215,7 +215,7 @@ func (ccms *CCMetricStore) LoadData(
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id := (*string)(nil)
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if query.Type != nil {
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id = new(string)
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*id = query.TypeIds[0]
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*id = query.TypeIds[ndx]
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}
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if res.Avg.IsNaN() || res.Min.IsNaN() || res.Max.IsNaN() {
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@ -312,6 +312,11 @@ func (ccms *CCMetricStore) buildQueries(
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// Accelerator -> Accelerator (Use "accelerator" scope if requested scope is lower than node)
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if nativeScope == schema.MetricScopeAccelerator && scope.LT(schema.MetricScopeNode) {
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if scope != schema.MetricScopeAccelerator {
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// Skip all other catched cases
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continue
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}
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queries = append(queries, ApiQuery{
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Metric: remoteName,
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Hostname: host.Hostname,
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@ -23,20 +23,8 @@
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: metricConfig.alert,
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};
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if (job.exclusive === 1) {
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// Exclusive: Use as defined
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return defaultThresholds;
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} else {
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// Shared: Handle specifically
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if (metricConfig.name === "cpu_load") {
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// Special: Avg Aggregation BUT scaled based on #hwthreads
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return {
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peak: job.numHWThreads,
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normal: job.numHWThreads,
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caution: defaultThresholds.caution,
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alert: defaultThresholds.alert,
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};
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} else if (metricConfig.aggregation === "avg") {
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// Job_Exclusivity does not matter, only aggregation
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if (metricConfig.aggregation === "avg") {
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return defaultThresholds;
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} else if (metricConfig.aggregation === "sum") {
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const jobFraction =
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@ -52,9 +40,8 @@
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"Missing or unkown aggregation mode (sum/avg) for metric:",
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metricConfig,
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);
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return null;
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return defaultThresholds;
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}
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} // Other job.exclusive cases?
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}
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</script>
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@ -91,29 +78,6 @@
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: ["cpu_load", "flops_any", "mem_used", "mem_bw"]; // Exclusive
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const footprintData = footprintMetrics.map((fm) => {
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// Mean: Primarily use backend sourced avgs from job.*, secondarily calculate/read from metricdata
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let mv = null;
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if (fm === "cpu_load" && job.loadAvg !== 0) {
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mv = round(job.loadAvg, 2);
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} else if (fm === "flops_any" && job.flopsAnyAvg !== 0) {
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mv = round(job.flopsAnyAvg, 2);
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} else if (fm === "mem_bw" && job.memBwAvg !== 0) {
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mv = round(job.memBwAvg, 2);
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} else {
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// Calculate from jobMetrics
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const jm = jobMetrics.find((jm) => jm.name === fm && jm.scope === "node");
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if (jm?.metric?.statisticsSeries) {
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mv = round(mean(jm.metric.statisticsSeries.mean), 2);
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} else if (jm?.metric?.series?.length > 1) {
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const avgs = jm.metric.series.map((jms) => jms.statistics.avg);
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mv = round(mean(avgs), 2);
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} else if (jm?.metric?.series) {
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mv = round(jm.metric.series[0].statistics.avg, 2);
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} else {
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mv = 0.0;
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}
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}
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// Unit
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const fmc = getContext("metrics")(job.cluster, fm);
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let unit = "";
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@ -123,6 +87,44 @@
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const fmt = findJobThresholds(job, fmc, subclusterConfig);
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if (fm === "flops_any") fmt.peak = round(fmt.peak * 0.85, 0);
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// Value: Primarily use backend sourced avgs from job.*, secondarily calculate/read from metricdata
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// Exclusivity does not matter
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let mv = 0.0;
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if (fmc.aggregation === "avg") {
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if (fm === "cpu_load" && job.loadAvg !== 0) {
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mv = round(job.loadAvg, 2);
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} else if (fm === "flops_any" && job.flopsAnyAvg !== 0) {
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mv = round(job.flopsAnyAvg, 2);
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} else if (fm === "mem_bw" && job.memBwAvg !== 0) {
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mv = round(job.memBwAvg, 2);
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} else {
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// Calculate Avg from jobMetrics
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const jm = jobMetrics.find((jm) => jm.name === fm && jm.scope === "node");
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if (jm?.metric?.statisticsSeries) {
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mv = round(mean(jm.metric.statisticsSeries.mean), 2);
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} else if (jm?.metric?.series?.length > 1) {
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const avgs = jm.metric.series.map((jms) => jms.statistics.avg);
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mv = round(mean(avgs), 2);
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} else if (jm?.metric?.series) {
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mv = round(jm.metric.series[0].statistics.avg, 2);
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}
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}
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} else if (fmc.aggregation === "sum") {
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// Calculate Sum from jobMetrics: Sum all node averages
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const jm = jobMetrics.find((jm) => jm.name === fm && jm.scope === "node");
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if (jm?.metric?.series?.length > 1) { // More than 1 node
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const avgs = jm.metric.series.map((jms) => jms.statistics.avg);
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mv = round(avgs.reduce((a, b) => a + b, 0));
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} else if (jm?.metric?.series) {
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mv = round(jm.metric.series[0].statistics.avg, 2);
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}
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} else {
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console.warn(
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"Missing or unkown aggregation mode (sum/avg) for metric:",
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metricConfig,
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);
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}
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// Define basic data
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const fmBase = {
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name: fm,
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