mirror of
https://git.mirrors.martin98.com/https://github.com/SigNoz/signoz
synced 2025-07-30 15:52:00 +08:00
347 lines
9.5 KiB
Go
347 lines
9.5 KiB
Go
package inframetrics
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import (
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"context"
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"math"
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"sort"
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"github.com/SigNoz/signoz/pkg/query-service/app/metrics/v4/helpers"
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"github.com/SigNoz/signoz/pkg/query-service/common"
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"github.com/SigNoz/signoz/pkg/query-service/interfaces"
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"github.com/SigNoz/signoz/pkg/query-service/model"
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v3 "github.com/SigNoz/signoz/pkg/query-service/model/v3"
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"github.com/SigNoz/signoz/pkg/query-service/postprocess"
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"github.com/SigNoz/signoz/pkg/valuer"
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"golang.org/x/exp/slices"
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)
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var (
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metricToUseForClusters = GetDotMetrics("k8s_node_cpu_utilization")
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clusterAttrsToEnrich = []string{GetDotMetrics("k8s_cluster_name")}
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// TODO(srikanthccv): change this to k8s_cluster_uid after showing the missing data banner
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k8sClusterUIDAttrKey = GetDotMetrics("k8s_cluster_name")
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queryNamesForClusters = map[string][]string{
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"cpu": {"A"},
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"cpu_allocatable": {"B"},
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"memory": {"C"},
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"memory_allocatable": {"D"},
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}
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clusterQueryNames = []string{"A", "B", "C", "D"}
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)
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type ClustersRepo struct {
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reader interfaces.Reader
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querierV2 interfaces.Querier
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}
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func NewClustersRepo(reader interfaces.Reader, querierV2 interfaces.Querier) *ClustersRepo {
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return &ClustersRepo{reader: reader, querierV2: querierV2}
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}
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func (n *ClustersRepo) GetClusterAttributeKeys(ctx context.Context, req v3.FilterAttributeKeyRequest) (*v3.FilterAttributeKeyResponse, error) {
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req.DataSource = v3.DataSourceMetrics
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req.AggregateAttribute = metricToUseForClusters
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if req.Limit == 0 {
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req.Limit = 50
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}
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attributeKeysResponse, err := n.reader.GetMetricAttributeKeys(ctx, &req)
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if err != nil {
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return nil, err
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}
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return attributeKeysResponse, nil
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}
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func (n *ClustersRepo) GetClusterAttributeValues(ctx context.Context, req v3.FilterAttributeValueRequest) (*v3.FilterAttributeValueResponse, error) {
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req.DataSource = v3.DataSourceMetrics
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req.AggregateAttribute = metricToUseForClusters
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if req.Limit == 0 {
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req.Limit = 50
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}
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attributeValuesResponse, err := n.reader.GetMetricAttributeValues(ctx, &req)
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if err != nil {
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return nil, err
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}
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return attributeValuesResponse, nil
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}
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func (p *ClustersRepo) getMetadataAttributes(ctx context.Context, req model.ClusterListRequest) (map[string]map[string]string, error) {
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clusterAttrs := map[string]map[string]string{}
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for _, key := range clusterAttrsToEnrich {
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hasKey := false
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for _, groupByKey := range req.GroupBy {
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if groupByKey.Key == key {
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hasKey = true
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break
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}
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}
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if !hasKey {
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req.GroupBy = append(req.GroupBy, v3.AttributeKey{Key: key})
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}
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}
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mq := v3.BuilderQuery{
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DataSource: v3.DataSourceMetrics,
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AggregateAttribute: v3.AttributeKey{
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Key: metricToUseForClusters,
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DataType: v3.AttributeKeyDataTypeFloat64,
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},
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Temporality: v3.Unspecified,
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GroupBy: req.GroupBy,
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}
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query, err := helpers.PrepareTimeseriesFilterQuery(req.Start, req.End, &mq)
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if err != nil {
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return nil, err
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}
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query = localQueryToDistributedQuery(query)
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attrsListResponse, err := p.reader.GetListResultV3(ctx, query)
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if err != nil {
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return nil, err
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}
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for _, row := range attrsListResponse {
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stringData := map[string]string{}
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for key, value := range row.Data {
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if str, ok := value.(string); ok {
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stringData[key] = str
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} else if strPtr, ok := value.(*string); ok {
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stringData[key] = *strPtr
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}
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}
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clusterUID := stringData[k8sClusterUIDAttrKey]
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if _, ok := clusterAttrs[clusterUID]; !ok {
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clusterAttrs[clusterUID] = map[string]string{}
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}
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for _, key := range req.GroupBy {
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clusterAttrs[clusterUID][key.Key] = stringData[key.Key]
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}
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}
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return clusterAttrs, nil
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}
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func (p *ClustersRepo) getTopClusterGroups(ctx context.Context, orgID valuer.UUID, req model.ClusterListRequest, q *v3.QueryRangeParamsV3) ([]map[string]string, []map[string]string, error) {
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step, timeSeriesTableName, samplesTableName := getParamsForTopClusters(req)
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queryNames := queryNamesForClusters[req.OrderBy.ColumnName]
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topClusterGroupsQueryRangeParams := &v3.QueryRangeParamsV3{
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Start: req.Start,
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End: req.End,
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Step: step,
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CompositeQuery: &v3.CompositeQuery{
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BuilderQueries: map[string]*v3.BuilderQuery{},
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QueryType: v3.QueryTypeBuilder,
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PanelType: v3.PanelTypeTable,
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},
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}
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for _, queryName := range queryNames {
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query := q.CompositeQuery.BuilderQueries[queryName].Clone()
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query.StepInterval = step
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query.MetricTableHints = &v3.MetricTableHints{
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TimeSeriesTableName: timeSeriesTableName,
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SamplesTableName: samplesTableName,
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}
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if req.Filters != nil && len(req.Filters.Items) > 0 {
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if query.Filters == nil {
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query.Filters = &v3.FilterSet{Operator: "AND", Items: []v3.FilterItem{}}
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}
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query.Filters.Items = append(query.Filters.Items, req.Filters.Items...)
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}
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topClusterGroupsQueryRangeParams.CompositeQuery.BuilderQueries[queryName] = query
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}
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queryResponse, _, err := p.querierV2.QueryRange(ctx, orgID, topClusterGroupsQueryRangeParams)
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if err != nil {
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return nil, nil, err
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}
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formattedResponse, err := postprocess.PostProcessResult(queryResponse, topClusterGroupsQueryRangeParams)
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if err != nil {
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return nil, nil, err
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}
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if len(formattedResponse) == 0 || len(formattedResponse[0].Series) == 0 {
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return nil, nil, nil
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}
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if req.OrderBy.Order == v3.DirectionDesc {
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sort.Slice(formattedResponse[0].Series, func(i, j int) bool {
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return formattedResponse[0].Series[i].Points[0].Value > formattedResponse[0].Series[j].Points[0].Value
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})
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} else {
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sort.Slice(formattedResponse[0].Series, func(i, j int) bool {
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return formattedResponse[0].Series[i].Points[0].Value < formattedResponse[0].Series[j].Points[0].Value
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})
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}
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max := math.Min(float64(req.Offset+req.Limit), float64(len(formattedResponse[0].Series)))
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paginatedTopClusterGroupsSeries := formattedResponse[0].Series[req.Offset:int(max)]
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topClusterGroups := []map[string]string{}
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for _, series := range paginatedTopClusterGroupsSeries {
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topClusterGroups = append(topClusterGroups, series.Labels)
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}
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allClusterGroups := []map[string]string{}
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for _, series := range formattedResponse[0].Series {
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allClusterGroups = append(allClusterGroups, series.Labels)
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}
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return topClusterGroups, allClusterGroups, nil
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}
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func (p *ClustersRepo) GetClusterList(ctx context.Context, orgID valuer.UUID, req model.ClusterListRequest) (model.ClusterListResponse, error) {
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resp := model.ClusterListResponse{}
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if req.Limit == 0 {
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req.Limit = 10
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}
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if req.OrderBy == nil {
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req.OrderBy = &v3.OrderBy{ColumnName: "cpu", Order: v3.DirectionDesc}
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}
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if req.GroupBy == nil {
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req.GroupBy = []v3.AttributeKey{{Key: k8sClusterUIDAttrKey}}
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resp.Type = model.ResponseTypeList
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} else {
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resp.Type = model.ResponseTypeGroupedList
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}
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step := int64(math.Max(float64(common.MinAllowedStepInterval(req.Start, req.End)), 60))
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query := NodesTableListQuery.Clone()
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query.Start = req.Start
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query.End = req.End
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query.Step = step
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for _, query := range query.CompositeQuery.BuilderQueries {
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query.StepInterval = step
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if req.Filters != nil && len(req.Filters.Items) > 0 {
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if query.Filters == nil {
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query.Filters = &v3.FilterSet{Operator: "AND", Items: []v3.FilterItem{}}
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}
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query.Filters.Items = append(query.Filters.Items, req.Filters.Items...)
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}
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query.GroupBy = req.GroupBy
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}
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clusterAttrs, err := p.getMetadataAttributes(ctx, req)
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if err != nil {
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return resp, err
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}
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topClusterGroups, allClusterGroups, err := p.getTopClusterGroups(ctx, orgID, req, query)
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if err != nil {
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return resp, err
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}
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groupFilters := map[string][]string{}
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for _, topClusterGroup := range topClusterGroups {
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for k, v := range topClusterGroup {
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groupFilters[k] = append(groupFilters[k], v)
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}
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}
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for groupKey, groupValues := range groupFilters {
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hasGroupFilter := false
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if req.Filters != nil && len(req.Filters.Items) > 0 {
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for _, filter := range req.Filters.Items {
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if filter.Key.Key == groupKey {
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hasGroupFilter = true
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break
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}
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}
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}
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if !hasGroupFilter {
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for _, query := range query.CompositeQuery.BuilderQueries {
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query.Filters.Items = append(query.Filters.Items, v3.FilterItem{
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Key: v3.AttributeKey{Key: groupKey},
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Value: groupValues,
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Operator: v3.FilterOperatorIn,
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})
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}
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}
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}
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queryResponse, _, err := p.querierV2.QueryRange(ctx, orgID, query)
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if err != nil {
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return resp, err
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}
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formattedResponse, err := postprocess.PostProcessResult(queryResponse, query)
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if err != nil {
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return resp, err
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}
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records := []model.ClusterListRecord{}
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for _, result := range formattedResponse {
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for _, row := range result.Table.Rows {
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record := model.ClusterListRecord{
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CPUUsage: -1,
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CPUAllocatable: -1,
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MemoryUsage: -1,
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MemoryAllocatable: -1,
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}
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if clusterUID, ok := row.Data[k8sClusterUIDAttrKey].(string); ok {
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record.ClusterUID = clusterUID
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}
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if cpu, ok := row.Data["A"].(float64); ok {
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record.CPUUsage = cpu
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}
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if cpuAllocatable, ok := row.Data["B"].(float64); ok {
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record.CPUAllocatable = cpuAllocatable
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}
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if mem, ok := row.Data["C"].(float64); ok {
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record.MemoryUsage = mem
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}
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if memoryAllocatable, ok := row.Data["D"].(float64); ok {
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record.MemoryAllocatable = memoryAllocatable
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}
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record.Meta = map[string]string{}
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if _, ok := clusterAttrs[record.ClusterUID]; ok && record.ClusterUID != "" {
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record.Meta = clusterAttrs[record.ClusterUID]
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}
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for k, v := range row.Data {
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if slices.Contains(clusterQueryNames, k) {
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continue
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}
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if labelValue, ok := v.(string); ok {
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record.Meta[k] = labelValue
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}
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}
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records = append(records, record)
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}
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}
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resp.Total = len(allClusterGroups)
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resp.Records = records
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resp.SortBy(req.OrderBy)
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return resp, nil
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}
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