// Copyright (C) 2022 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"
	"fmt"
	"math"
	"time"

	"github.com/ClusterCockpit/cc-backend/internal/config"
	"github.com/ClusterCockpit/cc-backend/pkg/archive"
	"github.com/ClusterCockpit/cc-backend/pkg/log"
	"github.com/ClusterCockpit/cc-backend/pkg/lrucache"
	"github.com/ClusterCockpit/cc-backend/pkg/schema"
)

type MetricDataRepository interface {
	// Initialize this MetricDataRepository. One instance of
	// this interface will only ever be responsible for one cluster.
	Init(rawConfig json.RawMessage) error

	// Return the JobData for the given job, only with the requested metrics.
	LoadData(job *schema.Job, metrics []string, scopes []schema.MetricScope, ctx context.Context) (schema.JobData, error)

	// Return a map of metrics to a map of nodes to the metric statistics of the job. node scope assumed for now.
	LoadStats(job *schema.Job, metrics []string, ctx context.Context) (map[string]map[string]schema.MetricStatistics, error)

	// Return a map of hosts to a map of metrics at the requested scopes for that node.
	LoadNodeData(cluster string, metrics, nodes []string, scopes []schema.MetricScope, from, to time.Time, ctx context.Context) (map[string]map[string][]*schema.JobMetric, error)
}

var metricDataRepos map[string]MetricDataRepository = map[string]MetricDataRepository{}

var useArchive bool

func Init(disableArchive bool) error {
	useArchive = !disableArchive
	for _, cluster := range config.Keys.Clusters {
		if cluster.MetricDataRepository != nil {
			var kind struct {
				Kind string `json:"kind"`
			}
			if err := json.Unmarshal(cluster.MetricDataRepository, &kind); err != nil {
				log.Warn("Error while unmarshaling raw json MetricDataRepository")
				return err
			}

			var mdr MetricDataRepository
			switch kind.Kind {
			case "cc-metric-store":
				mdr = &CCMetricStore{}
			case "influxdb":
				mdr = &InfluxDBv2DataRepository{}
			case "prometheus":
				mdr = &PrometheusDataRepository{}
			case "test":
				mdr = &TestMetricDataRepository{}
			default:
				return fmt.Errorf("METRICDATA/METRICDATA > Unknown MetricDataRepository %v for cluster %v", kind.Kind, cluster.Name)
			}

			if err := mdr.Init(cluster.MetricDataRepository); err != nil {
				log.Errorf("Error initializing MetricDataRepository %v for cluster %v", kind.Kind, cluster.Name)
				return err
			}
			metricDataRepos[cluster.Name] = mdr
		}
	}
	return nil
}

var cache *lrucache.Cache = lrucache.New(128 * 1024 * 1024)

// Fetches the metric data for a job.
func LoadData(job *schema.Job,
	metrics []string,
	scopes []schema.MetricScope,
	ctx context.Context,
) (schema.JobData, error) {
	data := cache.Get(cacheKey(job, metrics, scopes), func() (_ interface{}, ttl time.Duration, size int) {
		var jd schema.JobData
		var err error

		if job.State == schema.JobStateRunning ||
			job.MonitoringStatus == schema.MonitoringStatusRunningOrArchiving ||
			!useArchive {

			repo, ok := metricDataRepos[job.Cluster]

			if !ok {
				return fmt.Errorf("METRICDATA/METRICDATA > no metric data repository configured for '%s'", job.Cluster), 0, 0
			}

			if scopes == nil {
				scopes = append(scopes, schema.MetricScopeNode)
			}

			if metrics == nil {
				cluster := archive.GetCluster(job.Cluster)
				for _, mc := range cluster.MetricConfig {
					metrics = append(metrics, mc.Name)
				}
			}

			jd, err = repo.LoadData(job, metrics, scopes, ctx)
			if err != nil {
				if len(jd) != 0 {
					log.Errorf("partial error: %s", err.Error())
					return err, 0, 0
				} else {
					log.Error("Error while loading job data from metric repository")
					return err, 0, 0
				}
			}
			size = jd.Size()
		} else {
			jd, err = archive.GetHandle().LoadJobData(job)
			if err != nil {
				log.Error("Error while loading job data from archive")
				return err, 0, 0
			}

			// Avoid sending unrequested data to the client:
			if metrics != nil || scopes != nil {
				if metrics == nil {
					metrics = make([]string, 0, len(jd))
					for k := range jd {
						metrics = append(metrics, k)
					}
				}

				res := schema.JobData{}
				for _, metric := range metrics {
					if perscope, ok := jd[metric]; ok {
						if len(perscope) > 1 {
							subset := make(map[schema.MetricScope]*schema.JobMetric)
							for _, scope := range scopes {
								if jm, ok := perscope[scope]; ok {
									subset[scope] = jm
								}
							}

							if len(subset) > 0 {
								perscope = subset
							}
						}

						res[metric] = perscope
					}
				}
				jd = res
			}
			size = jd.Size()
		}

		ttl = 5 * time.Hour
		if job.State == schema.JobStateRunning {
			ttl = 2 * time.Minute
		}

		prepareJobData(job, jd, scopes)

		return jd, ttl, size
	})

	if err, ok := data.(error); ok {
		log.Error("Error in returned dataset")
		return nil, err
	}

	return data.(schema.JobData), nil
}

// Used for the jobsFootprint GraphQL-Query. TODO: Rename/Generalize.
func LoadAverages(
	job *schema.Job,
	metrics []string,
	data [][]schema.Float,
	ctx context.Context,
) error {
	if job.State != schema.JobStateRunning && useArchive {
		return archive.LoadAveragesFromArchive(job, metrics, data) // #166 change also here?
	}

	repo, ok := metricDataRepos[job.Cluster]
	if !ok {
		return fmt.Errorf("METRICDATA/METRICDATA > no metric data repository configured for '%s'", job.Cluster)
	}

	stats, err := repo.LoadStats(job, metrics, ctx) // #166 how to handle stats for acc normalizazion?
	if err != nil {
		log.Errorf("Error while loading statistics for job %v (User %v, Project %v)", job.JobID, job.User, job.Project)
		return err
	}

	for i, m := range metrics {
		nodes, ok := stats[m]
		if !ok {
			data[i] = append(data[i], schema.NaN)
			continue
		}

		sum := 0.0
		for _, node := range nodes {
			sum += node.Avg
		}
		data[i] = append(data[i], schema.Float(sum))
	}

	return nil
}

// Used for the node/system view. Returns a map of nodes to a map of metrics.
func LoadNodeData(
	cluster string,
	metrics, nodes []string,
	scopes []schema.MetricScope,
	from, to time.Time,
	ctx context.Context,
) (map[string]map[string][]*schema.JobMetric, error) {
	repo, ok := metricDataRepos[cluster]
	if !ok {
		return nil, fmt.Errorf("METRICDATA/METRICDATA > no metric data repository configured for '%s'", cluster)
	}

	if metrics == nil {
		for _, m := range archive.GetCluster(cluster).MetricConfig {
			metrics = append(metrics, m.Name)
		}
	}

	data, err := repo.LoadNodeData(cluster, metrics, nodes, scopes, from, to, ctx)
	if err != nil {
		if len(data) != 0 {
			log.Warnf("partial error: %s", err.Error())
		} else {
			log.Error("Error while loading node data from metric repository")
			return nil, err
		}
	}

	if data == nil {
		return nil, fmt.Errorf("METRICDATA/METRICDATA > the metric data repository for '%s' does not support this query", cluster)
	}

	return data, nil
}

func cacheKey(
	job *schema.Job,
	metrics []string,
	scopes []schema.MetricScope,
) string {
	// Duration and StartTime do not need to be in the cache key as StartTime is less unique than
	// job.ID and the TTL of the cache entry makes sure it does not stay there forever.
	return fmt.Sprintf("%d(%s):[%v],[%v]",
		job.ID, job.State, metrics, scopes)
}

// For /monitoring/job/<job> and some other places, flops_any and mem_bw need
// to be available at the scope 'node'. If a job has a lot of nodes,
// statisticsSeries should be available so that a min/mean/max Graph can be
// used instead of a lot of single lines.
func prepareJobData(
	job *schema.Job,
	jobData schema.JobData,
	scopes []schema.MetricScope,
) {
	const maxSeriesSize int = 15
	for _, scopes := range jobData {
		for _, jm := range scopes {
			if jm.StatisticsSeries != nil || len(jm.Series) <= maxSeriesSize {
				continue
			}

			jm.AddStatisticsSeries()
		}
	}

	nodeScopeRequested := false
	for _, scope := range scopes {
		if scope == schema.MetricScopeNode {
			nodeScopeRequested = true
		}
	}

	if nodeScopeRequested {
		jobData.AddNodeScope("flops_any")
		jobData.AddNodeScope("mem_bw")
	}
}

// Writes a running job to the job-archive
func ArchiveJob(job *schema.Job, ctx context.Context) (*schema.JobMeta, error) {
	allMetrics := make([]string, 0)
	metricConfigs := archive.GetCluster(job.Cluster).MetricConfig
	for _, mc := range metricConfigs {
		allMetrics = append(allMetrics, mc.Name)
	}

	// TODO: Talk about this! What resolutions to store data at...
	scopes := []schema.MetricScope{schema.MetricScopeNode}
	if job.NumNodes <= 8 {
		scopes = append(scopes, schema.MetricScopeCore)
	}

	jobData, err := LoadData(job, allMetrics, scopes, ctx)
	if err != nil {
		log.Error("Error wile loading job data for archiving")
		return nil, err
	}

	jobMeta := &schema.JobMeta{
		BaseJob:    job.BaseJob,
		StartTime:  job.StartTime.Unix(),
		Statistics: make(map[string]schema.JobStatistics),
	}

	for metric, data := range jobData {
		avg, min, max := 0.0, math.MaxFloat32, -math.MaxFloat32
		nodeData, ok := data["node"]
		if !ok {
			// TODO/FIXME: Calc average for non-node metrics as well!
			continue
		}

		for _, series := range nodeData.Series {
			avg += series.Statistics.Avg
			min = math.Min(min, series.Statistics.Min)
			max = math.Max(max, series.Statistics.Max)
		}

		jobMeta.Statistics[metric] = schema.JobStatistics{
			Unit: schema.Unit{
				Prefix: archive.GetMetricConfig(job.Cluster, metric).Unit.Prefix,
				Base:   archive.GetMetricConfig(job.Cluster, metric).Unit.Base,
			},
			Avg: avg / float64(job.NumNodes),
			Min: min,
			Max: max,
		}
	}

	// If the file based archive is disabled,
	// only return the JobMeta structure as the
	// statistics in there are needed.
	if !useArchive {
		return jobMeta, nil
	}

	return jobMeta, archive.GetHandle().ImportJob(jobMeta, &jobData)
}