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Sampling Feature for archived and fresh data

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This commit is contained in:
Aditya Ujeniya
2024-08-22 14:29:51 +02:00
parent e74e506ffe
commit ceb3a095d8
14 changed files with 358 additions and 95 deletions
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45
internal/metricdata/utils.go
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@@ -12,7 +12,7 @@ import (
"github.com/ClusterCockpit/cc-backend/pkg/schema"
)
var TestLoadDataCallback func(job *schema.Job, metrics []string, scopes []schema.MetricScope, ctx context.Context) (schema.JobData, error) = func(job *schema.Job, metrics []string, scopes []schema.MetricScope, ctx context.Context) (schema.JobData, error) {
var TestLoadDataCallback func(job *schema.Job, metrics []string, scopes []schema.MetricScope, ctx context.Context, resolution int) (schema.JobData, error) = func(job *schema.Job, metrics []string, scopes []schema.MetricScope, ctx context.Context, resolution int) (schema.JobData, error) {
panic("TODO")
}
@@ -27,9 +27,10 @@ func (tmdr *TestMetricDataRepository) LoadData(
job *schema.Job,
metrics []string,
scopes []schema.MetricScope,
ctx context.Context) (schema.JobData, error) {
ctx context.Context,
resolution int) (schema.JobData, error) {
return TestLoadDataCallback(job, metrics, scopes, ctx)
return TestLoadDataCallback(job, metrics, scopes, ctx, resolution)
}
func (tmdr *TestMetricDataRepository) LoadStats(
@@ -48,3 +49,41 @@ func (tmdr *TestMetricDataRepository) LoadNodeData(
panic("TODO")
}
func DeepCopy(jd_temp schema.JobData) schema.JobData {
var jd schema.JobData
jd = make(schema.JobData, len(jd_temp))
for k, v := range jd_temp {
jd[k] = make(map[schema.MetricScope]*schema.JobMetric, len(jd_temp[k]))
for k_, v_ := range v {
jd[k][k_] = new(schema.JobMetric)
jd[k][k_].Series = make([]schema.Series, len(v_.Series))
for i := 0; i < len(v_.Series); i += 1 {
jd[k][k_].Series[i].Data = make([]schema.Float, len(v_.Series[i].Data))
copy(jd[k][k_].Series[i].Data, v_.Series[i].Data)
jd[k][k_].Series[i].Hostname = v_.Series[i].Hostname
jd[k][k_].Series[i].Id = v_.Series[i].Id
jd[k][k_].Series[i].Statistics.Avg = v_.Series[i].Statistics.Avg
jd[k][k_].Series[i].Statistics.Min = v_.Series[i].Statistics.Min
jd[k][k_].Series[i].Statistics.Max = v_.Series[i].Statistics.Max
}
jd[k][k_].Timestep = v_.Timestep
jd[k][k_].Unit.Base = v_.Unit.Base
jd[k][k_].Unit.Prefix = v_.Unit.Prefix
if v_.StatisticsSeries != nil {
jd[k][k_].StatisticsSeries = new(schema.StatsSeries)
copy(jd[k][k_].StatisticsSeries.Max, v_.StatisticsSeries.Max)
copy(jd[k][k_].StatisticsSeries.Min, v_.StatisticsSeries.Min)
copy(jd[k][k_].StatisticsSeries.Median, v_.StatisticsSeries.Median)
copy(jd[k][k_].StatisticsSeries.Mean, v_.StatisticsSeries.Mean)
for k__, v__ := range v_.StatisticsSeries.Percentiles {
jd[k][k_].StatisticsSeries.Percentiles[k__] = v__
}
} else {
jd[k][k_].StatisticsSeries = v_.StatisticsSeries
}
}
}
return jd
}