// Copyright (C) NHR@FAU, University Erlangen-Nuremberg. // All rights reserved. // Use of this source code is governed by a MIT-style // license that can be found in the LICENSE file. package metricdata import ( "context" "encoding/json" "time" "github.com/ClusterCockpit/cc-backend/pkg/schema" ) 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") } // Only a mock for unit-testing. type TestMetricDataRepository struct{} func (tmdr *TestMetricDataRepository) Init(_ json.RawMessage) error { return nil } func (tmdr *TestMetricDataRepository) LoadData( job *schema.Job, metrics []string, scopes []schema.MetricScope, ctx context.Context, resolution int) (schema.JobData, error) { return TestLoadDataCallback(job, metrics, scopes, ctx, resolution) } func (tmdr *TestMetricDataRepository) LoadStats( job *schema.Job, metrics []string, ctx context.Context) (map[string]map[string]schema.MetricStatistics, error) { panic("TODO") } func (tmdr *TestMetricDataRepository) LoadNodeData( cluster string, metrics, nodes []string, scopes []schema.MetricScope, from, to time.Time, ctx context.Context) (map[string]map[string][]*schema.JobMetric, error) { 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 }