mirror of
https://github.com/ClusterCockpit/cc-backend
synced 2026-07-27 00:37:14 +02:00
cc-lib changed JobData, ScopedJobStats and Job.Statistics from flat maps to structs (a .Metrics map plus array-valued Groups) to represent filesystem (and future interconnect) metric groups. Migrate all construction, indexing and iteration to the new API across the archive backends, metricstore query path, metric dispatcher, archiver, importer, tagger, taskmanager, repository and API layers. Semantics: DecodeJobStats now projects JobData.Groups into ScopedJobStats.Groups, and the archiver derives per-filesystem node-scope statistics into Job.Statistics.Groups. deepCopy, resampling and the metric/scope filter are group-aware. The metricstore internal storage (buffers, selector tree, checkpoint/parquet) is unchanged; all conversion stays at the LoadData/archive-codec seam. Note: requires the corresponding cc-lib release; bump the cc-lib dependency version once tagged (a local go.mod replace was used during development and is intentionally not committed). Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
192 lines
6.2 KiB
Go
192 lines
6.2 KiB
Go
// Copyright (C) NHR@FAU, University Erlangen-Nuremberg.
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// All rights reserved. This file is part of cc-backend.
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// Use of this source code is governed by a MIT-style
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// license that can be found in the LICENSE file.
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package graph
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import (
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"context"
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"fmt"
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"math"
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"slices"
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"github.com/99designs/gqlgen/graphql"
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"github.com/ClusterCockpit/cc-backend/internal/graph/model"
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"github.com/ClusterCockpit/cc-backend/internal/metricdispatch"
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cclog "github.com/ClusterCockpit/cc-lib/v2/ccLogger"
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"github.com/ClusterCockpit/cc-lib/v2/schema"
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)
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const MAX_JOBS_FOR_ANALYSIS = 500
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// Helper function for the rooflineHeatmap GraphQL query placed here so that schema.resolvers.go is not too full.
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func (r *queryResolver) rooflineHeatmap(
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ctx context.Context,
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filter []*model.JobFilter,
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rows int, cols int,
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minX float64, minY float64, maxX float64, maxY float64,
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) ([][]float64, error) {
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jobs, err := r.Repo.QueryJobs(ctx, filter, &model.PageRequest{Page: 1, ItemsPerPage: MAX_JOBS_FOR_ANALYSIS + 1}, nil)
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if err != nil {
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cclog.Error("Error while querying jobs for roofline")
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return nil, err
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}
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if len(jobs) > MAX_JOBS_FOR_ANALYSIS {
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return nil, fmt.Errorf("GRAPH/UTIL > too many jobs matched (max: %d)", MAX_JOBS_FOR_ANALYSIS)
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}
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fcols, frows := float64(cols), float64(rows)
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minX, minY, maxX, maxY = math.Log10(minX), math.Log10(minY), math.Log10(maxX), math.Log10(maxY)
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tiles := make([][]float64, rows)
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for i := range tiles {
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tiles[i] = make([]float64, cols)
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}
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for _, job := range jobs {
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if job.MonitoringStatus == schema.MonitoringStatusDisabled || job.MonitoringStatus == schema.MonitoringStatusArchivingFailed {
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continue
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}
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// metricConfigs := archive.GetCluster(job.Cluster).MetricConfig
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// resolution := 0
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// for _, mc := range metricConfigs {
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// resolution = max(resolution, mc.Timestep)
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// }
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jobdata, err := metricdispatch.LoadData(job, []string{"flops_any", "mem_bw"}, []schema.MetricScope{schema.MetricScopeNode}, ctx, 0)
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if err != nil {
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cclog.Warnf("Error while loading roofline metrics for job %d", *job.ID)
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return nil, err
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}
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flops_, membw_ := jobdata.Metrics["flops_any"], jobdata.Metrics["mem_bw"]
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if flops_ == nil && membw_ == nil {
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cclog.Warnf("rooflineHeatmap(): 'flops_any' or 'mem_bw' missing for job %d", *job.ID)
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continue
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// return nil, fmt.Errorf("GRAPH/UTIL > 'flops_any' or 'mem_bw' missing for job %d", job.ID)
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}
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flops, ok1 := flops_["node"]
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membw, ok2 := membw_["node"]
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if !ok1 || !ok2 {
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cclog.Info("rooflineHeatmap() query not implemented for where flops_any or mem_bw not available at 'node' level")
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continue
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// TODO/FIXME:
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// return nil, errors.New("GRAPH/UTIL > todo: rooflineHeatmap() query not implemented for where flops_any or mem_bw not available at 'node' level")
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}
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for n := 0; n < len(flops.Series); n++ {
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flopsSeries, membwSeries := flops.Series[n], membw.Series[n]
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for i := 0; i < len(flopsSeries.Data); i++ {
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if i >= len(membwSeries.Data) {
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break
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}
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x, y := math.Log10(float64(flopsSeries.Data[i]/membwSeries.Data[i])), math.Log10(float64(flopsSeries.Data[i]))
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if math.IsNaN(x) || math.IsNaN(y) || x < minX || x >= maxX || y < minY || y > maxY {
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continue
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}
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x, y = math.Floor(((x-minX)/(maxX-minX))*fcols), math.Floor(((y-minY)/(maxY-minY))*frows)
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if x < 0 || x >= fcols || y < 0 || y >= frows {
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continue
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}
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tiles[int(y)][int(x)] += 1
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}
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}
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}
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return tiles, nil
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}
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// Helper function for the jobsFootprints GraphQL query placed here so that schema.resolvers.go is not too full.
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func (r *queryResolver) jobsFootprints(ctx context.Context, filter []*model.JobFilter, metrics []string) (*model.Footprints, error) {
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jobs, err := r.Repo.QueryJobs(ctx, filter, &model.PageRequest{Page: 1, ItemsPerPage: MAX_JOBS_FOR_ANALYSIS + 1}, nil)
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if err != nil {
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cclog.Error("Error while querying jobs for footprint")
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return nil, err
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}
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if len(jobs) > MAX_JOBS_FOR_ANALYSIS {
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return nil, fmt.Errorf("GRAPH/UTIL > too many jobs matched (max: %d)", MAX_JOBS_FOR_ANALYSIS)
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}
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avgs := make([][]schema.Float, len(metrics))
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for i := range avgs {
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avgs[i] = make([]schema.Float, 0, len(jobs))
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}
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timeweights := new(model.TimeWeights)
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timeweights.NodeHours = make([]schema.Float, 0, len(jobs))
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timeweights.AccHours = make([]schema.Float, 0, len(jobs))
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timeweights.CoreHours = make([]schema.Float, 0, len(jobs))
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for _, job := range jobs {
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if job.MonitoringStatus == schema.MonitoringStatusDisabled || job.MonitoringStatus == schema.MonitoringStatusArchivingFailed {
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continue
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}
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if err := metricdispatch.LoadAverages(job, metrics, avgs, ctx); err != nil {
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cclog.Error("Error while loading averages for footprint")
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return nil, err
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}
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// #166 collect arrays: Null values or no null values?
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timeweights.NodeHours = append(timeweights.NodeHours, schema.Float(float64(job.Duration)/60.0*float64(job.NumNodes)))
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if job.NumAcc > 0 {
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timeweights.AccHours = append(timeweights.AccHours, schema.Float(float64(job.Duration)/60.0*float64(job.NumAcc)))
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} else {
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timeweights.AccHours = append(timeweights.AccHours, schema.Float(1.0))
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}
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if job.NumHWThreads > 0 {
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timeweights.CoreHours = append(timeweights.CoreHours, schema.Float(float64(job.Duration)/60.0*float64(job.NumHWThreads))) // SQLite HWThreads == Cores; numCoresForJob(job)
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} else {
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timeweights.CoreHours = append(timeweights.CoreHours, schema.Float(1.0))
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}
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}
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res := make([]*model.MetricFootprints, len(avgs))
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for i, arr := range avgs {
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res[i] = &model.MetricFootprints{
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Metric: metrics[i],
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Data: arr,
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}
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}
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return &model.Footprints{
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TimeWeights: timeweights,
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Metrics: res,
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}, nil
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}
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// func numCoresForJob(job *schema.Job) (numCores int) {
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// subcluster, scerr := archive.GetSubCluster(job.Cluster, job.SubCluster)
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// if scerr != nil {
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// return 1
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// }
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// totalJobCores := 0
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// topology := subcluster.Topology
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// for _, host := range job.Resources {
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// hwthreads := host.HWThreads
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// if hwthreads == nil {
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// hwthreads = topology.Node
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// }
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// hostCores, _ := topology.GetCoresFromHWThreads(hwthreads)
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// totalJobCores += len(hostCores)
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// }
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// return totalJobCores
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// }
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func requireField(ctx context.Context, name string) bool {
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fields := graphql.CollectAllFields(ctx)
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return slices.Contains(fields, name)
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}
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