Adopt cc-lib hierarchical JobData/Statistics structs

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>

internal/api/api_test.go

@@ -196,7 +196,7 @@ func cleanup() {
 func TestRestApi(t *testing.T) {
 	restapi := setup(t)
 	t.Cleanup(cleanup)
-	testData := schema.JobData{
+	testData := schema.JobData{Metrics: map[string]schema.ScopedMetrics{
 		"load_one": map[schema.MetricScope]*schema.JobMetric{
 			schema.MetricScopeNode: {
 				Unit:     schema.Unit{Base: "load"},
@@ -210,7 +210,7 @@ func TestRestApi(t *testing.T) {
 				},
 			},
 		},
-	}
+	}}
 
 	metricstore.TestLoadDataCallback = func(job *schema.Job, metrics []string, scopes []schema.MetricScope, ctx context.Context, resolution int) (schema.JobData, error) {
 		return testData, nil
@@ -497,7 +497,7 @@ func TestStopJobWithReusedJobId(t *testing.T) {
 	restapi := setup(t)
 	t.Cleanup(cleanup)
 
-	testData := schema.JobData{
+	testData := schema.JobData{Metrics: map[string]schema.ScopedMetrics{
 		"load_one": map[schema.MetricScope]*schema.JobMetric{
 			schema.MetricScopeNode: {
 				Unit:     schema.Unit{Base: "load"},
@@ -511,7 +511,7 @@ func TestStopJobWithReusedJobId(t *testing.T) {
 				},
 			},
 		},
-	}
+	}}
 
 	metricstore.TestLoadDataCallback = func(job *schema.Job, metrics []string, scopes []schema.MetricScope, ctx context.Context, resolution int) (schema.JobData, error) {
 		return testData, nil

internal/api/job.go

@@ -412,7 +412,7 @@ func (api *RestAPI) getJobByID(rw http.ResponseWriter, r *http.Request) {
 	}
 
 	res := []*JobMetricWithName{}
-	for name, md := range data {
+	for name, md := range data.Metrics {
 		for scope, metric := range md {
 			res = append(res, &JobMetricWithName{
 				Name:   name,

internal/api/nats_test.go

@@ -531,7 +531,7 @@ func TestNatsHandleStopJob(t *testing.T) {
 		},
 	}
 
-	testData := schema.JobData{
+	testData := schema.JobData{Metrics: map[string]schema.ScopedMetrics{
 		"load_one": map[schema.MetricScope]*schema.JobMetric{
 			schema.MetricScopeNode: {
 				Unit:     schema.Unit{Base: "load"},
@@ -545,7 +545,7 @@ func TestNatsHandleStopJob(t *testing.T) {
 				},
 			},
 		},
-	}
+	}}
 
 	metricstore.TestLoadDataCallback = func(job *schema.Job, metrics []string, scopes []schema.MetricScope, ctx context.Context, resolution int) (schema.JobData, error) {
 		return testData, nil

internal/archiver/archiver.go

@@ -65,11 +65,11 @@ func ArchiveJob(job *schema.Job, ctx context.Context) (*schema.Job, error) {
 		return nil, err
 	}
 
-	job.Statistics = make(map[string]schema.JobStatistics)
+	job.Statistics = schema.JobStatisticsSet{Metrics: make(map[string]schema.JobStatistics)}
 
-	for metric, data := range jobData {
+	for metric, data := range jobData.Metrics {
 		avg, min, max := 0.0, math.MaxFloat32, -math.MaxFloat32
-		nodeData, ok := data["node"]
+		nodeData, ok := data[schema.MetricScopeNode]
 		if !ok {
 			// This should never happen ?
 			continue
@@ -82,7 +82,7 @@ func ArchiveJob(job *schema.Job, ctx context.Context) (*schema.Job, error) {
 		}
 
 		// Round AVG Result to 2 Digits
-		job.Statistics[metric] = schema.JobStatistics{
+		job.Statistics.Metrics[metric] = schema.JobStatistics{
 			Unit: schema.Unit{
 				Prefix: archive.GetMetricConfig(job.Cluster, metric).Unit.Prefix,
 				Base:   archive.GetMetricConfig(job.Cluster, metric).Unit.Base,
@@ -93,5 +93,43 @@ func ArchiveJob(job *schema.Job, ctx context.Context) (*schema.Job, error) {
 		}
 	}
 
+	// Compute the same node-scope statistics for each array-valued metric group
+	// instance (e.g. per-filesystem) and attach it as a group in the statistics
+	// set so it round-trips into the job-meta "statistics" JSON.
+	for _, group := range jobData.Groups {
+		for _, inst := range group.Instances {
+			instStats := make(map[string]schema.JobStatistics)
+			for metric, data := range inst.Metrics {
+				avg, min, max := 0.0, math.MaxFloat32, -math.MaxFloat32
+				nodeData, ok := data[schema.MetricScopeNode]
+				if !ok {
+					// This should never happen ?
+					continue
+				}
+
+				for _, series := range nodeData.Series {
+					avg += series.Statistics.Avg
+					min = math.Min(min, series.Statistics.Min)
+					max = math.Max(max, series.Statistics.Max)
+				}
+
+				// Prefer the unit from a MetricConfig if one exists, otherwise
+				// fall back to the unit already present on the JobMetric.
+				unit := nodeData.Unit
+				if mc := archive.GetMetricConfig(job.Cluster, metric); mc != nil {
+					unit = schema.Unit{Prefix: mc.Unit.Prefix, Base: mc.Unit.Base}
+				}
+
+				instStats[metric] = schema.JobStatistics{
+					Unit: unit,
+					Avg:  (math.Round((avg/float64(job.NumNodes))*100) / 100),
+					Min:  min,
+					Max:  max,
+				}
+			}
+			job.Statistics.AddGroupInstance(group.Key, inst.Name, inst.Type, instStats)
+		}
+	}
+
 	return job, archive.GetHandle().ImportJob(job, &jobData)
 }

internal/graph/schema.resolvers.go

@@ -522,7 +522,7 @@ func (r *queryResolver) JobMetrics(ctx context.Context, id string, metrics []str
 	}
 
 	res := []*model.JobMetricWithName{}
-	for name, md := range data {
+	for name, md := range data.Metrics {
 		for scope, metric := range md {
 			res = append(res, &model.JobMetricWithName{
 				Name:   name,
@@ -575,7 +575,7 @@ func (r *queryResolver) ScopedJobStats(ctx context.Context, id string, metrics [
 	}
 
 	res := make([]*model.NamedStatsWithScope, 0)
-	for name, scoped := range data {
+	for name, scoped := range data.Metrics {
 		for scope, stats := range scoped {
 
 			mdlStats := make([]*model.ScopedStats, 0)
@@ -926,7 +926,7 @@ func (r *queryResolver) NodeMetricsList(ctx context.Context, cluster string, sub
 			cclog.Warnf("error in nodeMetrics resolver: %s", err)
 		}
 
-		for metric, scopedMetrics := range data[hostname] {
+		for metric, scopedMetrics := range data[hostname].Metrics {
 			for scope, scopedMetric := range scopedMetrics {
 				host.Metrics = append(host.Metrics, &model.JobMetricWithName{
 					Name:   metric,

internal/graph/util.go

@@ -61,7 +61,7 @@ func (r *queryResolver) rooflineHeatmap(
 			return nil, err
 		}
 
-		flops_, membw_ := jobdata["flops_any"], jobdata["mem_bw"]
+		flops_, membw_ := jobdata.Metrics["flops_any"], jobdata.Metrics["mem_bw"]
 		if flops_ == nil && membw_ == nil {
 			cclog.Warnf("rooflineHeatmap(): 'flops_any' or 'mem_bw' missing for job %d", *job.ID)
 			continue

internal/importer/initDB.go

@@ -290,7 +290,7 @@ func SanityChecks(job *schema.Job) error {
 //
 // TODO: Either implement the metric normalization or remove this dead code.
 func checkJobData(d *schema.JobData) error {
-	for _, scopes := range *d {
+	for _, scopes := range d.Metrics {
 		// var newUnit schema.Unit
 		// TODO Add node scope if missing
 		for _, metric := range scopes {

internal/metricdispatch/dataLoader.go

@@ -115,7 +115,7 @@ func LoadData(job *schema.Job,
 
 			jd, err = ms.LoadData(job, metrics, scopes, ctx, resolution)
 			if err != nil {
-				if len(jd) != 0 {
+				if len(jd.Metrics) != 0 {
 					cclog.Warnf("partial error loading metrics from store for job %d (user: %s, project: %s, cluster: %s-%s): %s",
 						job.JobID, job.User, job.Project, job.Cluster, job.SubCluster, err.Error())
 				} else {
@@ -138,33 +138,48 @@ func LoadData(job *schema.Job,
 
 			// Resample archived data using Largest Triangle Three Bucket algorithm to reduce data points
 			// to the requested resolution, improving transfer performance and client-side rendering.
-			for _, v := range jd {
-				for _, v_ := range v {
+			resampleScopes := func(scopeMap schema.ScopedMetrics) error {
+				for _, v_ := range scopeMap {
 					timestep := int64(0)
 					for i := 0; i < len(v_.Series); i += 1 {
 						v_.Series[i].Data, timestep, err = resampler.LargestTriangleThreeBucket(v_.Series[i].Data, int64(v_.Timestep), int64(resolution))
 						if err != nil {
-							return err, 0, 0
+							return err
 						}
 					}
 					v_.Timestep = int(timestep)
 				}
+				return nil
+			}
+			for _, v := range jd.Metrics {
+				if err := resampleScopes(v); err != nil {
+					return err, 0, 0
+				}
+			}
+			for _, group := range jd.Groups {
+				for _, inst := range group.Instances {
+					for _, v := range inst.Metrics {
+						if err := resampleScopes(v); err != nil {
+							return err, 0, 0
+						}
+					}
+				}
 			}
 
 			// Filter job data to only include requested metrics and scopes, avoiding unnecessary data transfer.
 			if metrics != nil || scopes != nil {
 				if metrics == nil {
-					metrics = make([]string, 0, len(jd))
-					for k := range jd {
+					metrics = make([]string, 0, len(jd.Metrics))
+					for k := range jd.Metrics {
 						metrics = append(metrics, k)
 					}
 				}
 
-				res := schema.JobData{}
+				res := schema.JobData{Metrics: make(map[string]schema.ScopedMetrics), Groups: jd.Groups}
 				for _, metric := range metrics {
-					if perscope, ok := jd[metric]; ok {
+					if perscope, ok := jd.Metrics[metric]; ok {
 						if len(perscope) > 1 {
-							subset := make(map[schema.MetricScope]*schema.JobMetric)
+							subset := make(schema.ScopedMetrics)
 							for _, scope := range scopes {
 								if jm, ok := perscope[scope]; ok {
 									subset[scope] = jm
@@ -176,7 +191,7 @@ func LoadData(job *schema.Job,
 							}
 						}
 
-						res[metric] = perscope
+						res.Metrics[metric] = perscope
 					}
 				}
 				jd = res
@@ -193,7 +208,7 @@ func LoadData(job *schema.Job,
 		// instead of overwhelming the UI with individual node lines. Note that newly calculated
 		// statistics use min/median/max, while archived statistics may use min/mean/max.
 		const maxSeriesSize int = 8
-		for _, scopes := range jd {
+		for _, scopes := range jd.Metrics {
 			for _, jm := range scopes {
 				if jm.StatisticsSeries != nil || len(jm.Series) < maxSeriesSize {
 					continue
@@ -223,7 +238,7 @@ func LoadData(job *schema.Job,
 
 	if err, ok := data.(error); ok {
 		cclog.Errorf("error in cached dataset for job %d: %s", job.JobID, err.Error())
-		return nil, err
+		return schema.JobData{}, err
 	}
 
 	return data.(schema.JobData), nil
@@ -290,14 +305,14 @@ func LoadScopedJobStats(
 	if err != nil {
 		cclog.Errorf("failed to access metricDataRepo for cluster %s-%s: %s",
 			job.Cluster, job.SubCluster, err.Error())
-		return nil, err
+		return schema.ScopedJobStats{}, err
 	}
 
 	scopedStats, err := ms.LoadScopedStats(job, metrics, scopes, ctx)
 	if err != nil {
 		cclog.Warnf("failed to load scoped statistics from metric store for job %d (user: %s, project: %s, cluster: %s-%s): %s",
 			job.JobID, job.User, job.Project, job.Cluster, job.SubCluster, err.Error())
-		return nil, err
+		return schema.ScopedJobStats{}, err
 	}
 
 	// Round Resulting Stat Values
@@ -444,7 +459,7 @@ func LoadNodeListData(
 	// Statistics are calculated as min/median/max.
 	const maxSeriesSize int = 8
 	for _, jd := range data {
-		for _, scopes := range jd {
+		for _, scopes := range jd.Metrics {
 			for _, jm := range scopes {
 				if jm.StatisticsSeries != nil || len(jm.Series) < maxSeriesSize {
 					continue
@@ -465,19 +480,47 @@ func LoadNodeListData(
 // archived data (e.g., during resampling). This ensures the cached archive data remains
 // immutable while allowing per-request transformations.
 func deepCopy(source schema.JobData) schema.JobData {
-	result := make(schema.JobData, len(source))
+	result := schema.JobData{Metrics: make(map[string]schema.ScopedMetrics, len(source.Metrics))}
 
-	for metricName, scopeMap := range source {
-		result[metricName] = make(map[schema.MetricScope]*schema.JobMetric, len(scopeMap))
+	for metricName, scopeMap := range source.Metrics {
+		result.Metrics[metricName] = copyScopedMetrics(scopeMap)
+	}
 
-		for scope, jobMetric := range scopeMap {
-			result[metricName][scope] = copyJobMetric(jobMetric)
+	// Deep-copy array-valued metric groups (e.g. filesystems) so their series are
+	// not shared with the cached archive data during resampling.
+	if len(source.Groups) > 0 {
+		result.Groups = make([]schema.MetricGroup, len(source.Groups))
+		for gi, group := range source.Groups {
+			dstGroup := schema.MetricGroup{
+				Key:       group.Key,
+				Instances: make([]schema.MetricGroupInstance, len(group.Instances)),
+			}
+			for ii, inst := range group.Instances {
+				dstInst := schema.MetricGroupInstance{
+					Name:    inst.Name,
+					Type:    inst.Type,
+					Metrics: make(map[string]schema.ScopedMetrics, len(inst.Metrics)),
+				}
+				for metricName, scopeMap := range inst.Metrics {
+					dstInst.Metrics[metricName] = copyScopedMetrics(scopeMap)
+				}
+				dstGroup.Instances[ii] = dstInst
+			}
+			result.Groups[gi] = dstGroup
 		}
 	}
 
 	return result
 }
 
+func copyScopedMetrics(scopeMap schema.ScopedMetrics) schema.ScopedMetrics {
+	dst := make(schema.ScopedMetrics, len(scopeMap))
+	for scope, jobMetric := range scopeMap {
+		dst[scope] = copyJobMetric(jobMetric)
+	}
+	return dst
+}
+
 func copyJobMetric(src *schema.JobMetric) *schema.JobMetric {
 	dst := &schema.JobMetric{
 		Timestep: src.Timestep,

internal/metricdispatch/dataLoader_test.go

@@ -13,7 +13,7 @@ import (
 
 func TestDeepCopy(t *testing.T) {
 	nodeId := "0"
-	original := schema.JobData{
+	original := schema.JobData{Metrics: map[string]schema.ScopedMetrics{
 		"cpu_load": {
 			schema.MetricScopeNode: &schema.JobMetric{
 				Timestep: 60,
@@ -42,42 +42,42 @@ func TestDeepCopy(t *testing.T) {
 				},
 			},
 		},
-	}
+	}}
 
 	copied := deepCopy(original)
 
-	original["cpu_load"][schema.MetricScopeNode].Series[0].Data[0] = 999.0
-	original["cpu_load"][schema.MetricScopeNode].StatisticsSeries.Min[0] = 888.0
-	original["cpu_load"][schema.MetricScopeNode].StatisticsSeries.Percentiles[25][0] = 777.0
+	original.Metrics["cpu_load"][schema.MetricScopeNode].Series[0].Data[0] = 999.0
+	original.Metrics["cpu_load"][schema.MetricScopeNode].StatisticsSeries.Min[0] = 888.0
+	original.Metrics["cpu_load"][schema.MetricScopeNode].StatisticsSeries.Percentiles[25][0] = 777.0
 
-	if copied["cpu_load"][schema.MetricScopeNode].Series[0].Data[0] != 1.0 {
+	if copied.Metrics["cpu_load"][schema.MetricScopeNode].Series[0].Data[0] != 1.0 {
 		t.Errorf("Series data was not deeply copied: got %v, want 1.0",
-			copied["cpu_load"][schema.MetricScopeNode].Series[0].Data[0])
+			copied.Metrics["cpu_load"][schema.MetricScopeNode].Series[0].Data[0])
 	}
 
-	if copied["cpu_load"][schema.MetricScopeNode].StatisticsSeries.Min[0] != 1.0 {
+	if copied.Metrics["cpu_load"][schema.MetricScopeNode].StatisticsSeries.Min[0] != 1.0 {
 		t.Errorf("StatisticsSeries was not deeply copied: got %v, want 1.0",
-			copied["cpu_load"][schema.MetricScopeNode].StatisticsSeries.Min[0])
+			copied.Metrics["cpu_load"][schema.MetricScopeNode].StatisticsSeries.Min[0])
 	}
 
-	if copied["cpu_load"][schema.MetricScopeNode].StatisticsSeries.Percentiles[25][0] != 1.5 {
+	if copied.Metrics["cpu_load"][schema.MetricScopeNode].StatisticsSeries.Percentiles[25][0] != 1.5 {
 		t.Errorf("Percentiles was not deeply copied: got %v, want 1.5",
-			copied["cpu_load"][schema.MetricScopeNode].StatisticsSeries.Percentiles[25][0])
+			copied.Metrics["cpu_load"][schema.MetricScopeNode].StatisticsSeries.Percentiles[25][0])
 	}
 
-	if copied["cpu_load"][schema.MetricScopeNode].Timestep != 60 {
+	if copied.Metrics["cpu_load"][schema.MetricScopeNode].Timestep != 60 {
 		t.Errorf("Timestep not copied correctly: got %v, want 60",
-			copied["cpu_load"][schema.MetricScopeNode].Timestep)
+			copied.Metrics["cpu_load"][schema.MetricScopeNode].Timestep)
 	}
 
-	if copied["cpu_load"][schema.MetricScopeNode].Series[0].Hostname != "node001" {
+	if copied.Metrics["cpu_load"][schema.MetricScopeNode].Series[0].Hostname != "node001" {
 		t.Errorf("Hostname not copied correctly: got %v, want node001",
-			copied["cpu_load"][schema.MetricScopeNode].Series[0].Hostname)
+			copied.Metrics["cpu_load"][schema.MetricScopeNode].Series[0].Hostname)
 	}
 }
 
 func TestDeepCopyNilStatisticsSeries(t *testing.T) {
-	original := schema.JobData{
+	original := schema.JobData{Metrics: map[string]schema.ScopedMetrics{
 		"mem_used": {
 			schema.MetricScopeNode: &schema.JobMetric{
 				Timestep: 60,
@@ -90,18 +90,18 @@ func TestDeepCopyNilStatisticsSeries(t *testing.T) {
 				StatisticsSeries: nil,
 			},
 		},
-	}
+	}}
 
 	copied := deepCopy(original)
 
-	if copied["mem_used"][schema.MetricScopeNode].StatisticsSeries != nil {
+	if copied.Metrics["mem_used"][schema.MetricScopeNode].StatisticsSeries != nil {
 		t.Errorf("StatisticsSeries should be nil, got %v",
-			copied["mem_used"][schema.MetricScopeNode].StatisticsSeries)
+			copied.Metrics["mem_used"][schema.MetricScopeNode].StatisticsSeries)
 	}
 }
 
 func TestDeepCopyEmptyPercentiles(t *testing.T) {
-	original := schema.JobData{
+	original := schema.JobData{Metrics: map[string]schema.ScopedMetrics{
 		"cpu_load": {
 			schema.MetricScopeNode: &schema.JobMetric{
 				Timestep: 60,
@@ -115,11 +115,11 @@ func TestDeepCopyEmptyPercentiles(t *testing.T) {
 				},
 			},
 		},
-	}
+	}}
 
 	copied := deepCopy(original)
 
-	if copied["cpu_load"][schema.MetricScopeNode].StatisticsSeries.Percentiles != nil {
+	if copied.Metrics["cpu_load"][schema.MetricScopeNode].StatisticsSeries.Percentiles != nil {
 		t.Errorf("Percentiles should be nil when source is nil/empty")
 	}
 }

internal/metricstoreclient/cc-metric-store.go

@@ -235,7 +235,7 @@ func (ccms *CCMetricStore) LoadData(
 	queries, assignedScope, err := ccms.buildQueries(job, metrics, scopes, resolution)
 	if err != nil {
 		cclog.Errorf("Error while building queries for jobId %d, Metrics %v, Scopes %v: %s", job.JobID, metrics, scopes, err.Error())
-		return nil, err
+		return schema.JobData{}, err
 	}
 
 	// Verify assignment is correct - log any inconsistencies for debugging
@@ -256,11 +256,11 @@ func (ccms *CCMetricStore) LoadData(
 	resBody, err := ccms.doRequest(ctx, &req)
 	if err != nil {
 		cclog.Errorf("Error while performing request for job %d: %s", job.JobID, err.Error())
-		return nil, err
+		return schema.JobData{}, err
 	}
 
 	var errors []string
-	jobData := make(schema.JobData)
+	jobData := schema.JobData{Metrics: make(map[string]schema.ScopedMetrics)}
 
 	// Add safety check for potential index out of range errors
 	if len(resBody.Results) != len(req.Queries) || len(assignedScope) != len(req.Queries) {
@@ -285,8 +285,8 @@ func (ccms *CCMetricStore) LoadData(
 			continue
 		}
 
-		if _, ok := jobData[metric]; !ok {
-			jobData[metric] = make(map[schema.MetricScope]*schema.JobMetric)
+		if _, ok := jobData.Metrics[metric]; !ok {
+			jobData.Metrics[metric] = make(schema.ScopedMetrics)
 		}
 
 		res := mc.Timestep
@@ -294,14 +294,14 @@ func (ccms *CCMetricStore) LoadData(
 			res = row[0].Resolution
 		}
 
-		jobMetric, ok := jobData[metric][scope]
+		jobMetric, ok := jobData.Metrics[metric][scope]
 		if !ok {
 			jobMetric = &schema.JobMetric{
 				Unit:     mc.Unit,
 				Timestep: res,
 				Series:   make([]schema.Series, 0),
 			}
-			jobData[metric][scope] = jobMetric
+			jobData.Metrics[metric][scope] = jobMetric
 		}
 
 		for ndx, res := range row {
@@ -329,9 +329,9 @@ func (ccms *CCMetricStore) LoadData(
 
 		// So that one can later check len(jobData):
 		if len(jobMetric.Series) == 0 {
-			delete(jobData[metric], scope)
-			if len(jobData[metric]) == 0 {
-				delete(jobData, metric)
+			delete(jobData.Metrics[metric], scope)
+			if len(jobData.Metrics[metric]) == 0 {
+				delete(jobData.Metrics, metric)
 			}
 		}
 	}
@@ -426,7 +426,7 @@ func (ccms *CCMetricStore) LoadScopedStats(
 	queries, assignedScope, err := ccms.buildQueries(job, metrics, scopes, 0)
 	if err != nil {
 		cclog.Errorf("Error while building queries for jobId %d, Metrics %v, Scopes %v: %s", job.JobID, metrics, scopes, err.Error())
-		return nil, err
+		return schema.ScopedJobStats{}, err
 	}
 
 	req := APIQueryRequest{
@@ -441,23 +441,23 @@ func (ccms *CCMetricStore) LoadScopedStats(
 	resBody, err := ccms.doRequest(ctx, &req)
 	if err != nil {
 		cclog.Errorf("Error while performing request for job %d: %s", job.JobID, err.Error())
-		return nil, err
+		return schema.ScopedJobStats{}, err
 	}
 
 	var errors []string
-	scopedJobStats := make(schema.ScopedJobStats)
+	scopedJobStats := schema.ScopedJobStats{Metrics: make(map[string]schema.ScopedMetricStats)}
 
 	for i, row := range resBody.Results {
 		query := req.Queries[i]
 		metric := query.Metric
 		scope := assignedScope[i]
 
-		if _, ok := scopedJobStats[metric]; !ok {
-			scopedJobStats[metric] = make(map[schema.MetricScope][]*schema.ScopedStats)
+		if _, ok := scopedJobStats.Metrics[metric]; !ok {
+			scopedJobStats.Metrics[metric] = make(schema.ScopedMetricStats)
 		}
 
-		if _, ok := scopedJobStats[metric][scope]; !ok {
-			scopedJobStats[metric][scope] = make([]*schema.ScopedStats, 0)
+		if _, ok := scopedJobStats.Metrics[metric][scope]; !ok {
+			scopedJobStats.Metrics[metric][scope] = make([]*schema.ScopedStats, 0)
 		}
 
 		for ndx, res := range row {
@@ -471,7 +471,7 @@ func (ccms *CCMetricStore) LoadScopedStats(
 
 			ms.SanitizeStats(&res.Avg, &res.Min, &res.Max)
 
-			scopedJobStats[metric][scope] = append(scopedJobStats[metric][scope], &schema.ScopedStats{
+			scopedJobStats.Metrics[metric][scope] = append(scopedJobStats.Metrics[metric][scope], &schema.ScopedStats{
 				Hostname: query.Hostname,
 				ID:       id,
 				Data: &schema.MetricStatistics{
@@ -482,11 +482,11 @@ func (ccms *CCMetricStore) LoadScopedStats(
 			})
 		}
 
-		// So that one can later check len(scopedJobStats[metric][scope]): Remove from map if empty
-		if len(scopedJobStats[metric][scope]) == 0 {
-			delete(scopedJobStats[metric], scope)
-			if len(scopedJobStats[metric]) == 0 {
-				delete(scopedJobStats, metric)
+		// So that one can later check len(scopedJobStats.Metrics[metric][scope]): Remove from map if empty
+		if len(scopedJobStats.Metrics[metric][scope]) == 0 {
+			delete(scopedJobStats.Metrics[metric], scope)
+			if len(scopedJobStats.Metrics[metric]) == 0 {
+				delete(scopedJobStats.Metrics, metric)
 			}
 		}
 	}
@@ -690,14 +690,14 @@ func (ccms *CCMetricStore) LoadNodeListData(
 		// Init Nested Map Data Structures If Not Found
 		hostData, ok := data[query.Hostname]
 		if !ok {
-			hostData = make(schema.JobData)
+			hostData = schema.JobData{Metrics: make(map[string]schema.ScopedMetrics)}
 			data[query.Hostname] = hostData
 		}
 
-		metricData, ok := hostData[metric]
+		metricData, ok := hostData.Metrics[metric]
 		if !ok {
-			metricData = make(map[schema.MetricScope]*schema.JobMetric)
-			data[query.Hostname][metric] = metricData
+			metricData = make(schema.ScopedMetrics)
+			data[query.Hostname].Metrics[metric] = metricData
 		}
 
 		scopeData, ok := metricData[scope]
@@ -707,7 +707,7 @@ func (ccms *CCMetricStore) LoadNodeListData(
 				Timestep: res,
 				Series:   make([]schema.Series, 0),
 			}
-			data[query.Hostname][metric][scope] = scopeData
+			data[query.Hostname].Metrics[metric][scope] = scopeData
 		}
 
 		for ndx, res := range row {

internal/repository/stats.go

@@ -403,7 +403,7 @@ func (r *JobRepository) JobsStats(
 //
 // Returns the requested statistic value or 0.0 if not found.
 func LoadJobStat(job *schema.Job, metric string, statType string) float64 {
-	if stats, ok := job.Statistics[metric]; ok {
+	if stats, ok := job.Statistics.Metrics[metric]; ok {
 		switch statType {
 		case "avg":
 			return stats.Avg

internal/tagger/classifyJob.go

@@ -107,7 +107,7 @@ type JobClassTagger struct {
 	// repo provides access to job database operations
 	repo JobRepository
 	// getStatistics retrieves job statistics for analysis
-	getStatistics func(job *schema.Job) (map[string]schema.JobStatistics, error)
+	getStatistics func(job *schema.Job) (schema.JobStatisticsSet, error)
 	// getMetricConfig retrieves metric configuration (limits) for a cluster
 	getMetricConfig func(cluster, subCluster string) map[string]*schema.Metric
 }
@@ -361,7 +361,7 @@ func (t *JobClassTagger) Match(job *schema.Job) {
 		// add metrics to env
 		skipRule := false
 		for _, m := range ri.metrics {
-			stats, ok := jobStats[m]
+			stats, ok := jobStats.Metrics[m]
 			if !ok {
 				cclog.Debugf("job classification: missing metric '%s' for rule %s on job %d", m, tag, job.JobID)
 				skipRule = true

internal/tagger/classifyJob_test.go

@@ -64,10 +64,10 @@ func TestClassifyJobMatch(t *testing.T) {
 		parameters: make(map[string]any),
 		tagType:    "jobClass",
 		repo:       mockRepo,
-		getStatistics: func(job *schema.Job) (map[string]schema.JobStatistics, error) {
-			return map[string]schema.JobStatistics{
+		getStatistics: func(job *schema.Job) (schema.JobStatisticsSet, error) {
+			return schema.JobStatisticsSet{Metrics: map[string]schema.JobStatistics{
 				"flops_any": {Min: 0, Max: 200, Avg: 150},
-			}, nil
+			}}, nil
 		},
 		getMetricConfig: func(cluster, subCluster string) map[string]*schema.Metric {
 			return map[string]*schema.Metric{
@@ -120,10 +120,10 @@ func TestMatch_NoMatch(t *testing.T) {
 		parameters: make(map[string]any),
 		tagType:    "jobClass",
 		repo:       mockRepo,
-		getStatistics: func(job *schema.Job) (map[string]schema.JobStatistics, error) {
-			return map[string]schema.JobStatistics{
+		getStatistics: func(job *schema.Job) (schema.JobStatisticsSet, error) {
+			return schema.JobStatisticsSet{Metrics: map[string]schema.JobStatistics{
 				"flops_any": {Min: 0, Max: 50, Avg: 20}, // Avg 20 < 100
-			}, nil
+			}}, nil
 		},
 		getMetricConfig: func(cluster, subCluster string) map[string]*schema.Metric {
 			return map[string]*schema.Metric{

internal/taskmanager/updateFootprintService.go

@@ -80,7 +80,7 @@ func RegisterFootprintWorker() {
 							continue
 						}
 
-						job.Statistics = make(map[string]schema.JobStatistics)
+						job.Statistics = schema.JobStatisticsSet{Metrics: make(map[string]schema.JobStatistics)}
 
 						for _, metric := range allMetrics {
 							avg, min, max := 0.0, 0.0, 0.0
@@ -98,7 +98,7 @@ func RegisterFootprintWorker() {
 							}
 
 							// Add values rounded to 2 digits: repo.LoadStats may return unrounded
-							job.Statistics[metric] = schema.JobStatistics{
+							job.Statistics.Metrics[metric] = schema.JobStatistics{
 								Unit: schema.Unit{
 									Prefix: archive.GetMetricConfig(job.Cluster, metric).Unit.Prefix,
 									Base:   archive.GetMetricConfig(job.Cluster, metric).Unit.Base,