mirror of
https://github.com/ClusterCockpit/cc-backend
synced 2024-12-26 05:19:05 +01:00
303 lines
9.2 KiB
Go
303 lines
9.2 KiB
Go
package graph
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import (
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"context"
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"database/sql"
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"errors"
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"fmt"
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"math"
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"time"
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"github.com/99designs/gqlgen/graphql"
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"github.com/ClusterCockpit/cc-backend/internal/config"
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"github.com/ClusterCockpit/cc-backend/internal/graph/model"
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"github.com/ClusterCockpit/cc-backend/internal/metricdata"
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"github.com/ClusterCockpit/cc-backend/internal/repository"
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"github.com/ClusterCockpit/cc-backend/pkg/schema"
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sq "github.com/Masterminds/squirrel"
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)
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// GraphQL validation should make sure that no unkown values can be specified.
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var groupBy2column = map[model.Aggregate]string{
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model.AggregateUser: "job.user",
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model.AggregateProject: "job.project",
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model.AggregateCluster: "job.cluster",
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}
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const ShortJobDuration int = 5 * 60
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// Helper function for the jobsStatistics GraphQL query placed here so that schema.resolvers.go is not too full.
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func (r *queryResolver) jobsStatistics(ctx context.Context, filter []*model.JobFilter, groupBy *model.Aggregate) ([]*model.JobsStatistics, error) {
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// In case `groupBy` is nil (not used), the model.JobsStatistics used is at the key '' (empty string)
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stats := map[string]*model.JobsStatistics{}
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// `socketsPerNode` and `coresPerSocket` can differ from cluster to cluster, so we need to explicitly loop over those.
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for _, cluster := range config.Clusters {
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for _, subcluster := range cluster.SubClusters {
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corehoursCol := fmt.Sprintf("CAST(ROUND(SUM(job.duration * job.num_nodes * %d * %d) / 3600) as int)", subcluster.SocketsPerNode, subcluster.CoresPerSocket)
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var query sq.SelectBuilder
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if groupBy == nil {
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query = sq.Select(
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"''",
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"COUNT(job.id)",
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"CAST(ROUND(SUM(job.duration) / 3600) as int)",
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corehoursCol,
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).From("job")
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} else {
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col := groupBy2column[*groupBy]
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query = sq.Select(
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col,
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"COUNT(job.id)",
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"CAST(ROUND(SUM(job.duration) / 3600) as int)",
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corehoursCol,
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).From("job").GroupBy(col)
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}
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query = query.
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Where("job.cluster = ?", cluster.Name).
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Where("job.subcluster = ?", subcluster.Name)
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query = repository.SecurityCheck(ctx, query)
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for _, f := range filter {
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query = repository.BuildWhereClause(f, query)
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}
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rows, err := query.RunWith(r.DB).Query()
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if err != nil {
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return nil, err
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}
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for rows.Next() {
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var id sql.NullString
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var jobs, walltime, corehours sql.NullInt64
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if err := rows.Scan(&id, &jobs, &walltime, &corehours); err != nil {
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return nil, err
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}
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if id.Valid {
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if s, ok := stats[id.String]; ok {
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s.TotalJobs += int(jobs.Int64)
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s.TotalWalltime += int(walltime.Int64)
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s.TotalCoreHours += int(corehours.Int64)
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} else {
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stats[id.String] = &model.JobsStatistics{
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ID: id.String,
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TotalJobs: int(jobs.Int64),
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TotalWalltime: int(walltime.Int64),
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TotalCoreHours: int(corehours.Int64),
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}
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}
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}
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}
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}
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}
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if groupBy == nil {
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query := sq.Select("COUNT(job.id)").From("job").Where("job.duration < ?", ShortJobDuration)
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query = repository.SecurityCheck(ctx, query)
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for _, f := range filter {
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query = repository.BuildWhereClause(f, query)
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}
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if err := query.RunWith(r.DB).QueryRow().Scan(&(stats[""].ShortJobs)); err != nil {
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return nil, err
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}
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} else {
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col := groupBy2column[*groupBy]
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query := sq.Select(col, "COUNT(job.id)").From("job").Where("job.duration < ?", ShortJobDuration)
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query = repository.SecurityCheck(ctx, query)
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for _, f := range filter {
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query = repository.BuildWhereClause(f, query)
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}
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rows, err := query.RunWith(r.DB).Query()
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if err != nil {
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return nil, err
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}
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for rows.Next() {
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var id sql.NullString
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var shortJobs sql.NullInt64
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if err := rows.Scan(&id, &shortJobs); err != nil {
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return nil, err
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}
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if id.Valid {
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stats[id.String].ShortJobs = int(shortJobs.Int64)
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}
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}
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}
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// Calculating the histogram data is expensive, so only do it if needed.
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// An explicit resolver can not be used because we need to know the filters.
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histogramsNeeded := false
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fields := graphql.CollectFieldsCtx(ctx, nil)
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for _, col := range fields {
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if col.Name == "histDuration" || col.Name == "histNumNodes" {
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histogramsNeeded = true
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}
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}
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res := make([]*model.JobsStatistics, 0, len(stats))
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for _, stat := range stats {
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res = append(res, stat)
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id, col := "", ""
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if groupBy != nil {
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id = stat.ID
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col = groupBy2column[*groupBy]
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}
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if histogramsNeeded {
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var err error
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value := fmt.Sprintf(`CAST(ROUND((CASE WHEN job.job_state = "running" THEN %d - job.start_time ELSE job.duration END) / 3600) as int) as value`, time.Now().Unix())
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stat.HistDuration, err = r.jobsStatisticsHistogram(ctx, value, filter, id, col)
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if err != nil {
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return nil, err
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}
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stat.HistNumNodes, err = r.jobsStatisticsHistogram(ctx, "job.num_nodes as value", filter, id, col)
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if err != nil {
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return nil, err
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}
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}
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}
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return res, nil
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}
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// `value` must be the column grouped by, but renamed to "value". `id` and `col` can optionally be used
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// to add a condition to the query of the kind "<col> = <id>".
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func (r *queryResolver) jobsStatisticsHistogram(ctx context.Context, value string, filters []*model.JobFilter, id, col string) ([]*model.HistoPoint, error) {
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query := sq.Select(value, "COUNT(job.id) AS count").From("job")
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query = repository.SecurityCheck(ctx, query)
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for _, f := range filters {
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query = repository.BuildWhereClause(f, query)
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}
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if len(id) != 0 && len(col) != 0 {
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query = query.Where(col+" = ?", id)
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}
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rows, err := query.GroupBy("value").RunWith(r.DB).Query()
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if err != nil {
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return nil, err
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}
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points := make([]*model.HistoPoint, 0)
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for rows.Next() {
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point := model.HistoPoint{}
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if err := rows.Scan(&point.Value, &point.Count); err != nil {
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return nil, err
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}
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points = append(points, &point)
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}
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return points, nil
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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 *Resolver) rooflineHeatmap(ctx context.Context, filter []*model.JobFilter, rows int, cols int, minX float64, minY float64, maxX float64, maxY float64) ([][]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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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("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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jobdata, err := metricdata.LoadData(job, []string{"flops_any", "mem_bw"}, []schema.MetricScope{schema.MetricScopeNode}, ctx)
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if err != nil {
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return nil, err
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}
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flops_, membw_ := jobdata["flops_any"], jobdata["mem_bw"]
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if flops_ == nil && membw_ == nil {
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return nil, fmt.Errorf("'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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// TODO/FIXME:
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return nil, errors.New("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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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("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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nodehours := 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 := metricdata.LoadAverages(job, metrics, avgs, ctx); err != nil {
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return nil, err
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}
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nodehours = append(nodehours, schema.Float(float64(job.Duration)/60.0*float64(job.NumNodes)))
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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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Nodehours: nodehours,
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Metrics: res,
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}, nil
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}
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