2024-04-11 23:04:30 +02:00
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// Copyright (C) NHR@FAU, University Erlangen-Nuremberg.
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2022-07-29 06:29:21 +02:00
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// All rights reserved.
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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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2022-01-24 10:06:25 +01:00
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package metricdata
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import (
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"context"
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"encoding/json"
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2022-01-31 15:16:05 +01:00
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"time"
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2022-01-24 10:06:25 +01:00
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2022-06-21 17:52:36 +02:00
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"github.com/ClusterCockpit/cc-backend/pkg/schema"
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2022-01-24 10:06:25 +01:00
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)
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2024-08-22 14:29:51 +02:00
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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) {
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panic("TODO")
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}
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// Only a mock for unit-testing.
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type TestMetricDataRepository struct{}
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2022-03-17 16:15:35 +01:00
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func (tmdr *TestMetricDataRepository) Init(_ json.RawMessage) error {
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return nil
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}
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2022-09-07 12:24:45 +02:00
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func (tmdr *TestMetricDataRepository) LoadData(
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job *schema.Job,
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metrics []string,
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scopes []schema.MetricScope,
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ctx context.Context,
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resolution int) (schema.JobData, error) {
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2024-08-22 14:29:51 +02:00
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return TestLoadDataCallback(job, metrics, scopes, ctx, resolution)
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}
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2022-09-07 12:24:45 +02:00
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func (tmdr *TestMetricDataRepository) LoadStats(
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job *schema.Job,
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metrics []string, ctx context.Context) (map[string]map[string]schema.MetricStatistics, error) {
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2022-01-24 10:06:25 +01:00
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panic("TODO")
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}
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2022-09-07 12:24:45 +02:00
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func (tmdr *TestMetricDataRepository) LoadNodeData(
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cluster string,
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metrics, nodes []string,
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scopes []schema.MetricScope,
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from, to time.Time,
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ctx context.Context) (map[string]map[string][]*schema.JobMetric, error) {
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2022-01-24 10:06:25 +01:00
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panic("TODO")
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}
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func DeepCopy(jd_temp schema.JobData) schema.JobData {
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var jd schema.JobData
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jd = make(schema.JobData, len(jd_temp))
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for k, v := range jd_temp {
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jd[k] = make(map[schema.MetricScope]*schema.JobMetric, len(jd_temp[k]))
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for k_, v_ := range v {
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jd[k][k_] = new(schema.JobMetric)
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jd[k][k_].Series = make([]schema.Series, len(v_.Series))
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for i := 0; i < len(v_.Series); i += 1 {
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jd[k][k_].Series[i].Data = make([]schema.Float, len(v_.Series[i].Data))
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copy(jd[k][k_].Series[i].Data, v_.Series[i].Data)
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jd[k][k_].Series[i].Hostname = v_.Series[i].Hostname
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jd[k][k_].Series[i].Id = v_.Series[i].Id
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jd[k][k_].Series[i].Statistics.Avg = v_.Series[i].Statistics.Avg
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jd[k][k_].Series[i].Statistics.Min = v_.Series[i].Statistics.Min
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jd[k][k_].Series[i].Statistics.Max = v_.Series[i].Statistics.Max
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}
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jd[k][k_].Timestep = v_.Timestep
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jd[k][k_].Unit.Base = v_.Unit.Base
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jd[k][k_].Unit.Prefix = v_.Unit.Prefix
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if v_.StatisticsSeries != nil {
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jd[k][k_].StatisticsSeries = new(schema.StatsSeries)
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copy(jd[k][k_].StatisticsSeries.Max, v_.StatisticsSeries.Max)
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copy(jd[k][k_].StatisticsSeries.Min, v_.StatisticsSeries.Min)
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copy(jd[k][k_].StatisticsSeries.Median, v_.StatisticsSeries.Median)
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copy(jd[k][k_].StatisticsSeries.Mean, v_.StatisticsSeries.Mean)
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for k__, v__ := range v_.StatisticsSeries.Percentiles {
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jd[k][k_].StatisticsSeries.Percentiles[k__] = v__
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}
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} else {
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jd[k][k_].StatisticsSeries = v_.StatisticsSeries
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}
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}
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}
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return jd
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}
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