mirror of
https://github.com/SigNoz/signoz.git
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fd032291f9
<!--A few plain bullets saying what changed and why, for a reviewer skimming it - not a wall of text, not a restatement of the diff, not generated boilerplate.--> #### Description Heatmap support here is only for metrics (except exponential histograms) via all three query types: builder, clickhouse and promql. Logs and traces can be plugged in into this later. <!--Reference issues using `Closes #issue-number` to enable automatic closure on merge. --> #### Issues closed by this PR Closes https://github.com/SigNoz/pulse-pod/issues/311
714 lines
48 KiB
Go
714 lines
48 KiB
Go
package metricsstatementbuilder
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import (
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"context"
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"fmt"
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"strings"
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"testing"
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"time"
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"github.com/SigNoz/signoz/pkg/flagger"
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"github.com/SigNoz/signoz/pkg/instrumentation/instrumentationtest"
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"github.com/SigNoz/signoz/pkg/telemetryschema/metricstelemetryschema"
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"github.com/SigNoz/signoz/pkg/types/metrictypes"
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qbtypes "github.com/SigNoz/signoz/pkg/types/querybuildertypes/querybuildertypesv5"
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"github.com/SigNoz/signoz/pkg/types/telemetrytypes"
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"github.com/SigNoz/signoz/pkg/types/telemetrytypes/telemetrytypestest"
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"github.com/SigNoz/signoz/pkg/valuer"
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"github.com/stretchr/testify/assert"
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"github.com/stretchr/testify/require"
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)
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func TestStatementBuilder(t *testing.T) {
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cases := []struct {
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name string
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requestType qbtypes.RequestType
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query qbtypes.QueryBuilderQuery[qbtypes.MetricAggregation]
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expected qbtypes.Statement
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expectedErr error
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}{
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{
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name: "test_cumulative_rate_sum",
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requestType: qbtypes.RequestTypeTimeSeries,
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query: qbtypes.QueryBuilderQuery[qbtypes.MetricAggregation]{
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Signal: telemetrytypes.SignalMetrics,
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StepInterval: qbtypes.Step{Duration: 30 * time.Second},
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Aggregations: []qbtypes.MetricAggregation{
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{
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MetricName: "signoz_calls_total",
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Type: metrictypes.SumType,
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Temporality: metrictypes.Cumulative,
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TimeAggregation: metrictypes.TimeAggregationRate,
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SpaceAggregation: metrictypes.SpaceAggregationSum,
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},
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},
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Filter: &qbtypes.Filter{
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Expression: "service.name = 'cartservice'",
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},
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Limit: 10,
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GroupBy: []qbtypes.GroupByKey{
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{
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TelemetryFieldKey: telemetrytypes.TelemetryFieldKey{
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Name: "service.name",
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},
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},
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},
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},
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expected: qbtypes.Statement{
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Query: "WITH __temporal_aggregation_cte AS (SELECT ts, `__GROUP_BY_KEY_0_service.name`, multiIf(row_number() OVER rate_window = 1, nan, (per_series_value - lagInFrame(per_series_value, 1) OVER rate_window) < 0, per_series_value / (ts - lagInFrame(ts, 1) OVER rate_window), (per_series_value - lagInFrame(per_series_value, 1) OVER rate_window) / (ts - lagInFrame(ts, 1) OVER rate_window)) AS per_series_value FROM (SELECT fingerprint, toStartOfInterval(toDateTime(intDiv(unix_milli, 1000)), toIntervalSecond(30)) AS ts, `__GROUP_BY_KEY_0_service.name`, max(value) AS per_series_value FROM signoz_metrics.distributed_samples_v4 AS points INNER JOIN (SELECT fingerprint, JSONExtractString(labels, 'service.name') AS `__GROUP_BY_KEY_0_service.name` FROM signoz_metrics.time_series_v4_6hrs WHERE metric_name IN (?) AND unix_milli >= ? AND unix_milli <= ? AND LOWER(temporality) LIKE LOWER(?) AND JSONExtractString(labels, 'service.name') = ? GROUP BY fingerprint, `__GROUP_BY_KEY_0_service.name`) AS filtered_time_series ON points.fingerprint = filtered_time_series.fingerprint WHERE metric_name IN (?) AND unix_milli >= ? AND unix_milli < ? GROUP BY fingerprint, ts, `__GROUP_BY_KEY_0_service.name` ORDER BY fingerprint, ts) WINDOW rate_window AS (PARTITION BY fingerprint ORDER BY fingerprint, ts)), __spatial_aggregation_cte AS (SELECT ts, `__GROUP_BY_KEY_0_service.name`, sum(per_series_value) AS value FROM __temporal_aggregation_cte WHERE isNaN(per_series_value) = ? GROUP BY ts, `__GROUP_BY_KEY_0_service.name`) SELECT * FROM __spatial_aggregation_cte ORDER BY `__GROUP_BY_KEY_0_service.name`, ts",
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Args: []any{"signoz_calls_total", uint64(1747936800000), uint64(1747983420000), "cumulative", "cartservice", "signoz_calls_total", uint64(1747947360000), uint64(1747983420000), 0},
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},
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expectedErr: nil,
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},
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{
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name: "test_cumulative_rate_sum_with_mat_column",
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requestType: qbtypes.RequestTypeTimeSeries,
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query: qbtypes.QueryBuilderQuery[qbtypes.MetricAggregation]{
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Signal: telemetrytypes.SignalMetrics,
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StepInterval: qbtypes.Step{Duration: 30 * time.Second},
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Aggregations: []qbtypes.MetricAggregation{
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{
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MetricName: "signoz_calls_total",
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Type: metrictypes.SumType,
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Temporality: metrictypes.Cumulative,
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TimeAggregation: metrictypes.TimeAggregationRate,
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SpaceAggregation: metrictypes.SpaceAggregationSum,
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},
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},
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Filter: &qbtypes.Filter{
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Expression: "materialized.key.name REGEXP 'cartservice' OR service.name = 'cartservice'",
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},
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Limit: 10,
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GroupBy: []qbtypes.GroupByKey{
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{
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TelemetryFieldKey: telemetrytypes.TelemetryFieldKey{
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Name: "service.name",
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},
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},
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},
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},
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expected: qbtypes.Statement{
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Query: "WITH __temporal_aggregation_cte AS (SELECT ts, `__GROUP_BY_KEY_0_service.name`, multiIf(row_number() OVER rate_window = 1, nan, (per_series_value - lagInFrame(per_series_value, 1) OVER rate_window) < 0, per_series_value / (ts - lagInFrame(ts, 1) OVER rate_window), (per_series_value - lagInFrame(per_series_value, 1) OVER rate_window) / (ts - lagInFrame(ts, 1) OVER rate_window)) AS per_series_value FROM (SELECT fingerprint, toStartOfInterval(toDateTime(intDiv(unix_milli, 1000)), toIntervalSecond(30)) AS ts, `__GROUP_BY_KEY_0_service.name`, max(value) AS per_series_value FROM signoz_metrics.distributed_samples_v4 AS points INNER JOIN (SELECT fingerprint, JSONExtractString(labels, 'service.name') AS `__GROUP_BY_KEY_0_service.name` FROM signoz_metrics.time_series_v4_6hrs WHERE metric_name IN (?) AND unix_milli >= ? AND unix_milli <= ? AND LOWER(temporality) LIKE LOWER(?) AND (match(JSONExtractString(labels, 'materialized.key.name'), ?) OR JSONExtractString(labels, 'service.name') = ?) GROUP BY fingerprint, `__GROUP_BY_KEY_0_service.name`) AS filtered_time_series ON points.fingerprint = filtered_time_series.fingerprint WHERE metric_name IN (?) AND unix_milli >= ? AND unix_milli < ? GROUP BY fingerprint, ts, `__GROUP_BY_KEY_0_service.name` ORDER BY fingerprint, ts) WINDOW rate_window AS (PARTITION BY fingerprint ORDER BY fingerprint, ts)), __spatial_aggregation_cte AS (SELECT ts, `__GROUP_BY_KEY_0_service.name`, sum(per_series_value) AS value FROM __temporal_aggregation_cte WHERE isNaN(per_series_value) = ? GROUP BY ts, `__GROUP_BY_KEY_0_service.name`) SELECT * FROM __spatial_aggregation_cte ORDER BY `__GROUP_BY_KEY_0_service.name`, ts",
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Args: []any{"signoz_calls_total", uint64(1747936800000), uint64(1747983420000), "cumulative", "cartservice", "cartservice", "signoz_calls_total", uint64(1747947360000), uint64(1747983420000), 0},
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},
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expectedErr: nil,
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},
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{
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name: "test_delta_rate_sum",
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requestType: qbtypes.RequestTypeTimeSeries,
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query: qbtypes.QueryBuilderQuery[qbtypes.MetricAggregation]{
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Signal: telemetrytypes.SignalMetrics,
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StepInterval: qbtypes.Step{Duration: 30 * time.Second},
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Aggregations: []qbtypes.MetricAggregation{
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{
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MetricName: "signoz_calls_total",
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Type: metrictypes.SumType,
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Temporality: metrictypes.Delta,
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TimeAggregation: metrictypes.TimeAggregationRate,
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SpaceAggregation: metrictypes.SpaceAggregationSum,
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},
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},
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Filter: &qbtypes.Filter{
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Expression: "service.name = 'cartservice'",
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},
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Limit: 10,
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GroupBy: []qbtypes.GroupByKey{
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{
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TelemetryFieldKey: telemetrytypes.TelemetryFieldKey{
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Name: "service.name",
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},
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},
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},
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},
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expected: qbtypes.Statement{
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Query: "WITH __spatial_aggregation_cte AS (SELECT toStartOfInterval(toDateTime(intDiv(unix_milli, 1000)), toIntervalSecond(30)) AS ts, `__GROUP_BY_KEY_0_service.name`, sum(value)/30 AS value FROM signoz_metrics.distributed_samples_v4 AS points INNER JOIN (SELECT fingerprint, JSONExtractString(labels, 'service.name') AS `__GROUP_BY_KEY_0_service.name` FROM signoz_metrics.time_series_v4_6hrs WHERE metric_name IN (?) AND unix_milli >= ? AND unix_milli <= ? AND LOWER(temporality) LIKE LOWER(?) AND JSONExtractString(labels, 'service.name') = ? GROUP BY fingerprint, `__GROUP_BY_KEY_0_service.name`) AS filtered_time_series ON points.fingerprint = filtered_time_series.fingerprint WHERE metric_name IN (?) AND unix_milli >= ? AND unix_milli < ? GROUP BY ts, `__GROUP_BY_KEY_0_service.name`) SELECT * FROM __spatial_aggregation_cte ORDER BY `__GROUP_BY_KEY_0_service.name`, ts",
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Args: []any{"signoz_calls_total", uint64(1747936800000), uint64(1747983420000), "delta", "cartservice", "signoz_calls_total", uint64(1747947390000), uint64(1747983420000)},
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},
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expectedErr: nil,
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},
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{
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name: "test_exp_histogram_percentile_delta",
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requestType: qbtypes.RequestTypeTimeSeries,
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query: qbtypes.QueryBuilderQuery[qbtypes.MetricAggregation]{
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Signal: telemetrytypes.SignalMetrics,
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StepInterval: qbtypes.Step{Duration: 30 * time.Second},
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Aggregations: []qbtypes.MetricAggregation{
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{
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MetricName: "signoz_latency",
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Type: metrictypes.ExpHistogramType,
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Temporality: metrictypes.Delta,
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SpaceAggregation: metrictypes.SpaceAggregationPercentile95,
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},
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},
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GroupBy: []qbtypes.GroupByKey{
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{
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TelemetryFieldKey: telemetrytypes.TelemetryFieldKey{
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Name: "service.name",
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},
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},
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},
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},
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expected: qbtypes.Statement{
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Query: "WITH __spatial_aggregation_cte AS (SELECT toStartOfInterval(toDateTime(intDiv(unix_milli, 1000)), toIntervalSecond(30)) AS ts, `__GROUP_BY_KEY_0_service.name`, quantilesDDMerge(0.01, 0.950000)(sketch)[1] AS value FROM signoz_metrics.distributed_exp_hist AS points INNER JOIN (SELECT fingerprint, JSONExtractString(labels, 'service.name') AS `__GROUP_BY_KEY_0_service.name` FROM signoz_metrics.time_series_v4_6hrs WHERE metric_name IN (?) AND unix_milli >= ? AND unix_milli <= ? AND LOWER(temporality) LIKE LOWER(?) GROUP BY fingerprint, `__GROUP_BY_KEY_0_service.name`) AS filtered_time_series ON points.fingerprint = filtered_time_series.fingerprint WHERE metric_name IN (?) AND unix_milli >= ? AND unix_milli < ? GROUP BY ts, `__GROUP_BY_KEY_0_service.name`) SELECT * FROM __spatial_aggregation_cte ORDER BY `__GROUP_BY_KEY_0_service.name`, ts",
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Args: []any{"signoz_latency", uint64(1747936800000), uint64(1747983420000), "delta", "signoz_latency", uint64(1747947390000), uint64(1747983420000)},
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},
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expectedErr: nil,
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},
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{
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// the sketch merge spans the whole step, so `rate` must not add a /step divisor
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name: "test_exp_histogram_percentile_delta_rate_time_aggregation",
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requestType: qbtypes.RequestTypeTimeSeries,
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query: qbtypes.QueryBuilderQuery[qbtypes.MetricAggregation]{
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Signal: telemetrytypes.SignalMetrics,
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StepInterval: qbtypes.Step{Duration: 30 * time.Second},
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Aggregations: []qbtypes.MetricAggregation{
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{
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MetricName: "signoz_latency",
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Type: metrictypes.ExpHistogramType,
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Temporality: metrictypes.Delta,
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TimeAggregation: metrictypes.TimeAggregationRate,
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SpaceAggregation: metrictypes.SpaceAggregationPercentile95,
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},
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},
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GroupBy: []qbtypes.GroupByKey{
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{
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TelemetryFieldKey: telemetrytypes.TelemetryFieldKey{
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Name: "service.name",
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},
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},
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},
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},
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expected: qbtypes.Statement{
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Query: "WITH __spatial_aggregation_cte AS (SELECT toStartOfInterval(toDateTime(intDiv(unix_milli, 1000)), toIntervalSecond(30)) AS ts, `__GROUP_BY_KEY_0_service.name`, quantilesDDMerge(0.01, 0.950000)(sketch)[1] AS value FROM signoz_metrics.distributed_exp_hist AS points INNER JOIN (SELECT fingerprint, JSONExtractString(labels, 'service.name') AS `__GROUP_BY_KEY_0_service.name` FROM signoz_metrics.time_series_v4_6hrs WHERE metric_name IN (?) AND unix_milli >= ? AND unix_milli <= ? AND LOWER(temporality) LIKE LOWER(?) GROUP BY fingerprint, `__GROUP_BY_KEY_0_service.name`) AS filtered_time_series ON points.fingerprint = filtered_time_series.fingerprint WHERE metric_name IN (?) AND unix_milli >= ? AND unix_milli < ? GROUP BY ts, `__GROUP_BY_KEY_0_service.name`) SELECT * FROM __spatial_aggregation_cte ORDER BY `__GROUP_BY_KEY_0_service.name`, ts",
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Args: []any{"signoz_latency", uint64(1747936800000), uint64(1747983420000), "delta", "signoz_latency", uint64(1747947390000), uint64(1747983420000)},
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},
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expectedErr: nil,
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},
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{
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name: "test_histogram_percentile1",
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requestType: qbtypes.RequestTypeTimeSeries,
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query: qbtypes.QueryBuilderQuery[qbtypes.MetricAggregation]{
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Signal: telemetrytypes.SignalMetrics,
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StepInterval: qbtypes.Step{Duration: 30 * time.Second},
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Aggregations: []qbtypes.MetricAggregation{
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{
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MetricName: "signoz_latency",
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Type: metrictypes.HistogramType,
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Temporality: metrictypes.Delta,
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TimeAggregation: metrictypes.TimeAggregationRate,
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SpaceAggregation: metrictypes.SpaceAggregationPercentile95,
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},
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},
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Filter: &qbtypes.Filter{
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Expression: "service.name = 'cartservice'",
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},
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Limit: 10,
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GroupBy: []qbtypes.GroupByKey{
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{
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TelemetryFieldKey: telemetrytypes.TelemetryFieldKey{
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Name: "service.name",
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},
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},
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},
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},
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expected: qbtypes.Statement{
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Query: "WITH __spatial_aggregation_cte AS (SELECT toStartOfInterval(toDateTime(intDiv(unix_milli, 1000)), toIntervalSecond(30)) AS ts, `__GROUP_BY_KEY_0_service.name`, `le`, sum(value)/30 AS value FROM signoz_metrics.distributed_samples_v4 AS points INNER JOIN (SELECT fingerprint, JSONExtractString(labels, 'service.name') AS `__GROUP_BY_KEY_0_service.name`, JSONExtractString(labels, 'le') AS `le` FROM signoz_metrics.time_series_v4_6hrs WHERE metric_name IN (?) AND unix_milli >= ? AND unix_milli <= ? AND LOWER(temporality) LIKE LOWER(?) AND JSONExtractString(labels, 'service.name') = ? GROUP BY fingerprint, `__GROUP_BY_KEY_0_service.name`, `le`) AS filtered_time_series ON points.fingerprint = filtered_time_series.fingerprint WHERE metric_name IN (?) AND unix_milli >= ? AND unix_milli < ? GROUP BY ts, `__GROUP_BY_KEY_0_service.name`, `le`) SELECT ts, `__GROUP_BY_KEY_0_service.name`, histogramQuantile(arrayMap(x -> toFloat64(x), groupArray(le)), groupArray(value), 0.950) AS value FROM __spatial_aggregation_cte GROUP BY `__GROUP_BY_KEY_0_service.name`, ts ORDER BY `__GROUP_BY_KEY_0_service.name`, ts",
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Args: []any{"signoz_latency", uint64(1747936800000), uint64(1747983420000), "delta", "cartservice", "signoz_latency", uint64(1747947390000), uint64(1747983420000)},
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},
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expectedErr: nil,
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},
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{
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name: "test_histogram_percentile_explicit_le",
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requestType: qbtypes.RequestTypeTimeSeries,
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query: qbtypes.QueryBuilderQuery[qbtypes.MetricAggregation]{
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Signal: telemetrytypes.SignalMetrics,
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StepInterval: qbtypes.Step{Duration: 30 * time.Second},
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Aggregations: []qbtypes.MetricAggregation{
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{
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MetricName: "signoz_latency",
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Type: metrictypes.HistogramType,
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Temporality: metrictypes.Delta,
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TimeAggregation: metrictypes.TimeAggregationRate,
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SpaceAggregation: metrictypes.SpaceAggregationPercentile95,
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},
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},
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Filter: &qbtypes.Filter{
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Expression: "service.name = 'cartservice'",
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},
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Limit: 10,
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GroupBy: []qbtypes.GroupByKey{
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{
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TelemetryFieldKey: telemetrytypes.TelemetryFieldKey{
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Name: "le",
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},
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},
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{
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TelemetryFieldKey: telemetrytypes.TelemetryFieldKey{
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Name: "service.name",
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},
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},
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},
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},
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expected: qbtypes.Statement{
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Query: "WITH __spatial_aggregation_cte AS (SELECT toStartOfInterval(toDateTime(intDiv(unix_milli, 1000)), toIntervalSecond(30)) AS ts, `__GROUP_BY_KEY_0_service.name`, `le`, sum(value)/30 AS value FROM signoz_metrics.distributed_samples_v4 AS points INNER JOIN (SELECT fingerprint, JSONExtractString(labels, 'service.name') AS `__GROUP_BY_KEY_0_service.name`, JSONExtractString(labels, 'le') AS `le` FROM signoz_metrics.time_series_v4_6hrs WHERE metric_name IN (?) AND unix_milli >= ? AND unix_milli <= ? AND LOWER(temporality) LIKE LOWER(?) AND JSONExtractString(labels, 'service.name') = ? GROUP BY fingerprint, `__GROUP_BY_KEY_0_service.name`, `le`) AS filtered_time_series ON points.fingerprint = filtered_time_series.fingerprint WHERE metric_name IN (?) AND unix_milli >= ? AND unix_milli < ? GROUP BY ts, `__GROUP_BY_KEY_0_service.name`, `le`) SELECT ts, `__GROUP_BY_KEY_0_service.name`, histogramQuantile(arrayMap(x -> toFloat64(x), groupArray(le)), groupArray(value), 0.950) AS value FROM __spatial_aggregation_cte GROUP BY `__GROUP_BY_KEY_0_service.name`, ts ORDER BY `__GROUP_BY_KEY_0_service.name`, ts",
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Args: []any{"signoz_latency", uint64(1747936800000), uint64(1747983420000), "delta", "cartservice", "signoz_latency", uint64(1747947390000), uint64(1747983420000)},
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},
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expectedErr: nil,
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},
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{
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name: "test_histogram_count_no_param",
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requestType: qbtypes.RequestTypeTimeSeries,
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query: qbtypes.QueryBuilderQuery[qbtypes.MetricAggregation]{
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Signal: telemetrytypes.SignalMetrics,
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StepInterval: qbtypes.Step{Duration: 30 * time.Second},
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Aggregations: []qbtypes.MetricAggregation{
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{
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MetricName: "signoz_latency",
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Type: metrictypes.HistogramType,
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Temporality: metrictypes.Delta,
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TimeAggregation: metrictypes.TimeAggregationRate,
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SpaceAggregation: metrictypes.SpaceAggregationCount,
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},
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},
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GroupBy: []qbtypes.GroupByKey{
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{
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TelemetryFieldKey: telemetrytypes.TelemetryFieldKey{
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Name: "service.name",
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},
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},
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},
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},
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expected: qbtypes.Statement{
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Query: "WITH __spatial_aggregation_cte AS (SELECT toStartOfInterval(toDateTime(intDiv(unix_milli, 1000)), toIntervalSecond(30)) AS ts, `__GROUP_BY_KEY_0_service.name`, `le`, sum(value) AS value FROM signoz_metrics.distributed_samples_v4 AS points INNER JOIN (SELECT fingerprint, JSONExtractString(labels, 'service.name') AS `__GROUP_BY_KEY_0_service.name`, JSONExtractString(labels, 'le') AS `le` FROM signoz_metrics.time_series_v4_6hrs WHERE metric_name IN (?) AND unix_milli >= ? AND unix_milli <= ? AND LOWER(temporality) LIKE LOWER(?) GROUP BY fingerprint, `__GROUP_BY_KEY_0_service.name`, `le`) AS filtered_time_series ON points.fingerprint = filtered_time_series.fingerprint WHERE metric_name IN (?) AND unix_milli >= ? AND unix_milli < ? GROUP BY ts, `__GROUP_BY_KEY_0_service.name`, `le`) SELECT * FROM __spatial_aggregation_cte ORDER BY `__GROUP_BY_KEY_0_service.name`, ts, toFloat64(le)",
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Args: []any{"signoz_latency", uint64(1747936800000), uint64(1747983420000), "delta", "signoz_latency", uint64(1747947390000), uint64(1747983420000)},
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},
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expectedErr: nil,
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},
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{
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name: "test_histogram_heatmap_counting_aggregations",
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requestType: qbtypes.RequestTypeHeatmap,
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query: qbtypes.QueryBuilderQuery[qbtypes.MetricAggregation]{
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Signal: telemetrytypes.SignalMetrics,
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StepInterval: qbtypes.Step{Duration: 60 * time.Second},
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Aggregations: []qbtypes.MetricAggregation{
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{
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MetricName: "signoz_latency.bucket",
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Type: metrictypes.HistogramType,
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Temporality: metrictypes.Delta,
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|
TimeAggregation: metrictypes.TimeAggregationIncrease,
|
|
SpaceAggregation: metrictypes.SpaceAggregationCount,
|
|
},
|
|
},
|
|
GroupBy: []qbtypes.GroupByKey{
|
|
{
|
|
TelemetryFieldKey: telemetrytypes.TelemetryFieldKey{
|
|
Name: "service.name",
|
|
},
|
|
},
|
|
},
|
|
},
|
|
expected: qbtypes.Statement{
|
|
Query: "WITH __spatial_aggregation_cte AS (SELECT toStartOfInterval(toDateTime(intDiv(unix_milli, 1000)), toIntervalSecond(60)) AS ts, `__GROUP_BY_KEY_0_service.name`, `le`, sum(value) AS value FROM signoz_metrics.distributed_samples_v4 AS points INNER JOIN (SELECT fingerprint, JSONExtractString(labels, 'service.name') AS `__GROUP_BY_KEY_0_service.name`, JSONExtractString(labels, 'le') AS `le` FROM signoz_metrics.time_series_v4_6hrs WHERE metric_name IN (?) AND unix_milli >= ? AND unix_milli <= ? AND LOWER(temporality) LIKE LOWER(?) GROUP BY fingerprint, `__GROUP_BY_KEY_0_service.name`, `le`) AS filtered_time_series ON points.fingerprint = filtered_time_series.fingerprint WHERE metric_name IN (?) AND unix_milli >= ? AND unix_milli < ? GROUP BY ts, `__GROUP_BY_KEY_0_service.name`, `le`) SELECT ts, `__GROUP_BY_KEY_0_service.name`, lagInFrame(toFloat64(le), 1, toFloat64('-Inf')) OVER __heatmap_window AS __bucket_min, toFloat64(le) AS __bucket_max, greatest(value - lagInFrame(value, 1, 0) OVER __heatmap_window, 0) AS __result_0 FROM __spatial_aggregation_cte WINDOW __heatmap_window AS (PARTITION BY `__GROUP_BY_KEY_0_service.name`, ts ORDER BY toFloat64(le)) ORDER BY `__GROUP_BY_KEY_0_service.name`, ts, toFloat64(le)",
|
|
Args: []any{"signoz_latency.bucket", uint64(1747936800000), uint64(1747983420000), "delta", "signoz_latency.bucket", uint64(1747947360000), uint64(1747983420000)},
|
|
},
|
|
expectedErr: nil,
|
|
},
|
|
{
|
|
// a heatmap counts observations per `le`, so a histogram's aggregations
|
|
// are rewritten to increase/count whatever was asked for — this builds
|
|
// the same statement as test_histogram_heatmap_counting_aggregations
|
|
name: "test_histogram_heatmap_overrules_requested_aggregations",
|
|
requestType: qbtypes.RequestTypeHeatmap,
|
|
query: qbtypes.QueryBuilderQuery[qbtypes.MetricAggregation]{
|
|
Signal: telemetrytypes.SignalMetrics,
|
|
StepInterval: qbtypes.Step{Duration: 60 * time.Second},
|
|
Aggregations: []qbtypes.MetricAggregation{
|
|
{
|
|
MetricName: "signoz_latency.bucket",
|
|
Type: metrictypes.HistogramType,
|
|
Temporality: metrictypes.Delta,
|
|
TimeAggregation: metrictypes.TimeAggregationRate,
|
|
SpaceAggregation: metrictypes.SpaceAggregationPercentile95,
|
|
},
|
|
},
|
|
GroupBy: []qbtypes.GroupByKey{
|
|
{
|
|
TelemetryFieldKey: telemetrytypes.TelemetryFieldKey{
|
|
Name: "service.name",
|
|
},
|
|
},
|
|
},
|
|
},
|
|
expected: qbtypes.Statement{
|
|
Query: "WITH __spatial_aggregation_cte AS (SELECT toStartOfInterval(toDateTime(intDiv(unix_milli, 1000)), toIntervalSecond(60)) AS ts, `__GROUP_BY_KEY_0_service.name`, `le`, sum(value) AS value FROM signoz_metrics.distributed_samples_v4 AS points INNER JOIN (SELECT fingerprint, JSONExtractString(labels, 'service.name') AS `__GROUP_BY_KEY_0_service.name`, JSONExtractString(labels, 'le') AS `le` FROM signoz_metrics.time_series_v4_6hrs WHERE metric_name IN (?) AND unix_milli >= ? AND unix_milli <= ? AND LOWER(temporality) LIKE LOWER(?) GROUP BY fingerprint, `__GROUP_BY_KEY_0_service.name`, `le`) AS filtered_time_series ON points.fingerprint = filtered_time_series.fingerprint WHERE metric_name IN (?) AND unix_milli >= ? AND unix_milli < ? GROUP BY ts, `__GROUP_BY_KEY_0_service.name`, `le`) SELECT ts, `__GROUP_BY_KEY_0_service.name`, lagInFrame(toFloat64(le), 1, toFloat64('-Inf')) OVER __heatmap_window AS __bucket_min, toFloat64(le) AS __bucket_max, greatest(value - lagInFrame(value, 1, 0) OVER __heatmap_window, 0) AS __result_0 FROM __spatial_aggregation_cte WINDOW __heatmap_window AS (PARTITION BY `__GROUP_BY_KEY_0_service.name`, ts ORDER BY toFloat64(le)) ORDER BY `__GROUP_BY_KEY_0_service.name`, ts, toFloat64(le)",
|
|
Args: []any{"signoz_latency.bucket", uint64(1747936800000), uint64(1747983420000), "delta", "signoz_latency.bucket", uint64(1747947360000), uint64(1747983420000)},
|
|
},
|
|
expectedErr: nil,
|
|
},
|
|
{
|
|
name: "test_gauge_heatmap_log",
|
|
requestType: qbtypes.RequestTypeHeatmap,
|
|
query: qbtypes.QueryBuilderQuery[qbtypes.MetricAggregation]{
|
|
Signal: telemetrytypes.SignalMetrics,
|
|
StepInterval: qbtypes.Step{Duration: 60 * time.Second},
|
|
Aggregations: []qbtypes.MetricAggregation{
|
|
{
|
|
MetricName: "system.memory.usage",
|
|
Type: metrictypes.GaugeType,
|
|
Temporality: metrictypes.Unspecified,
|
|
TimeAggregation: metrictypes.TimeAggregationAvg,
|
|
SpaceAggregation: metrictypes.SpaceAggregationSum,
|
|
HeatmapBucketing: &qbtypes.HeatmapBucketing{
|
|
Kind: qbtypes.BucketsKindLog,
|
|
LogScale: qbtypes.MaxLogScale,
|
|
NumBuckets: qbtypes.DefaultNumBuckets,
|
|
},
|
|
},
|
|
},
|
|
GroupBy: []qbtypes.GroupByKey{
|
|
{
|
|
TelemetryFieldKey: telemetrytypes.TelemetryFieldKey{
|
|
Name: "host.name",
|
|
},
|
|
},
|
|
},
|
|
},
|
|
expected: qbtypes.Statement{
|
|
Query: "WITH __temporal_aggregation_cte AS (SELECT fingerprint, toStartOfInterval(toDateTime(intDiv(unix_milli, 1000)), toIntervalSecond(60)) AS ts, `__GROUP_BY_KEY_0_host.name`, avg(value) AS per_series_value FROM signoz_metrics.distributed_samples_v4 AS points INNER JOIN (SELECT fingerprint, JSONExtractString(labels, 'host.name') AS `__GROUP_BY_KEY_0_host.name` FROM signoz_metrics.time_series_v4_6hrs WHERE metric_name IN (?) AND unix_milli >= ? AND unix_milli <= ? AND LOWER(temporality) LIKE LOWER(?) GROUP BY fingerprint, `__GROUP_BY_KEY_0_host.name`) AS filtered_time_series ON points.fingerprint = filtered_time_series.fingerprint WHERE metric_name IN (?) AND unix_milli >= ? AND unix_milli < ? GROUP BY fingerprint, ts, `__GROUP_BY_KEY_0_host.name` ORDER BY fingerprint, ts), __spatial_aggregation_cte AS (SELECT ts, `__GROUP_BY_KEY_0_host.name`, sum(per_series_value) AS value FROM __temporal_aggregation_cte WHERE isNaN(per_series_value) = ? GROUP BY ts, `__GROUP_BY_KEY_0_host.name`) SELECT ts, `__GROUP_BY_KEY_0_host.name`, multiIf(value <= 0, toFloat64('-Inf'), value <= 2.3283064365386963e-10, toFloat64(0), value > 1.8446744073709552e+19, toFloat64(1.8446744073709552e+19), pow(2, (ceil(log2(value) * 16) - 1) / 16)) AS __bucket_min, multiIf(value <= 0, toFloat64(0), value <= 2.3283064365386963e-10, 2.3283064365386963e-10, value > 1.8446744073709552e+19, toFloat64('+Inf'), pow(2, ceil(log2(value) * 16) / 16)) AS __bucket_max, toFloat64(1) AS __result_0 FROM __spatial_aggregation_cte ORDER BY `__GROUP_BY_KEY_0_host.name`, ts, __bucket_max",
|
|
Args: []any{"system.memory.usage", uint64(1747936800000), uint64(1747983420000), "unspecified", "system.memory.usage", uint64(1747947360000), uint64(1747983420000), 0},
|
|
},
|
|
expectedErr: nil,
|
|
},
|
|
{
|
|
name: "test_gauge_heatmap_linear",
|
|
requestType: qbtypes.RequestTypeHeatmap,
|
|
query: qbtypes.QueryBuilderQuery[qbtypes.MetricAggregation]{
|
|
Signal: telemetrytypes.SignalMetrics,
|
|
StepInterval: qbtypes.Step{Duration: 60 * time.Second},
|
|
Aggregations: []qbtypes.MetricAggregation{
|
|
{
|
|
MetricName: "system.memory.usage",
|
|
Type: metrictypes.GaugeType,
|
|
Temporality: metrictypes.Unspecified,
|
|
TimeAggregation: metrictypes.TimeAggregationAvg,
|
|
SpaceAggregation: metrictypes.SpaceAggregationSum,
|
|
HeatmapBucketing: &qbtypes.HeatmapBucketing{
|
|
Kind: qbtypes.BucketsKindLinear,
|
|
MaxValue: 500,
|
|
NumBuckets: 25,
|
|
},
|
|
},
|
|
},
|
|
GroupBy: []qbtypes.GroupByKey{
|
|
{
|
|
TelemetryFieldKey: telemetrytypes.TelemetryFieldKey{
|
|
Name: "host.name",
|
|
},
|
|
},
|
|
},
|
|
},
|
|
expected: qbtypes.Statement{
|
|
Query: "WITH __temporal_aggregation_cte AS (SELECT fingerprint, toStartOfInterval(toDateTime(intDiv(unix_milli, 1000)), toIntervalSecond(60)) AS ts, `__GROUP_BY_KEY_0_host.name`, avg(value) AS per_series_value FROM signoz_metrics.distributed_samples_v4 AS points INNER JOIN (SELECT fingerprint, JSONExtractString(labels, 'host.name') AS `__GROUP_BY_KEY_0_host.name` FROM signoz_metrics.time_series_v4_6hrs WHERE metric_name IN (?) AND unix_milli >= ? AND unix_milli <= ? AND LOWER(temporality) LIKE LOWER(?) GROUP BY fingerprint, `__GROUP_BY_KEY_0_host.name`) AS filtered_time_series ON points.fingerprint = filtered_time_series.fingerprint WHERE metric_name IN (?) AND unix_milli >= ? AND unix_milli < ? GROUP BY fingerprint, ts, `__GROUP_BY_KEY_0_host.name` ORDER BY fingerprint, ts), __spatial_aggregation_cte AS (SELECT ts, `__GROUP_BY_KEY_0_host.name`, sum(per_series_value) AS value FROM __temporal_aggregation_cte WHERE isNaN(per_series_value) = ? GROUP BY ts, `__GROUP_BY_KEY_0_host.name`) SELECT ts, `__GROUP_BY_KEY_0_host.name`, multiIf(value <= 0, toFloat64('-Inf'), value > 500, toFloat64(500), (least(greatest(ceil(value * 25 / 500), 1), 25) - 1) * 500 / 25) AS __bucket_min, multiIf(value <= 0, toFloat64(0), value > 500, toFloat64('+Inf'), least(greatest(ceil(value * 25 / 500), 1), 25) * 500 / 25) AS __bucket_max, toFloat64(1) AS __result_0 FROM __spatial_aggregation_cte ORDER BY `__GROUP_BY_KEY_0_host.name`, ts, __bucket_max",
|
|
Args: []any{"system.memory.usage", uint64(1747936800000), uint64(1747983420000), "unspecified", "system.memory.usage", uint64(1747947360000), uint64(1747983420000), 0},
|
|
},
|
|
expectedErr: nil,
|
|
},
|
|
{
|
|
// cumulative keeps CanShortCircuitDelta false, so the counts reach the
|
|
// bucket differencing through the temporal CTE rather than the delta
|
|
// fast path
|
|
name: "test_histogram_heatmap_cumulative",
|
|
requestType: qbtypes.RequestTypeHeatmap,
|
|
query: qbtypes.QueryBuilderQuery[qbtypes.MetricAggregation]{
|
|
Signal: telemetrytypes.SignalMetrics,
|
|
StepInterval: qbtypes.Step{Duration: 60 * time.Second},
|
|
Aggregations: []qbtypes.MetricAggregation{
|
|
{
|
|
MetricName: "http_server_duration_bucket",
|
|
Type: metrictypes.HistogramType,
|
|
Temporality: metrictypes.Cumulative,
|
|
TimeAggregation: metrictypes.TimeAggregationRate,
|
|
SpaceAggregation: metrictypes.SpaceAggregationPercentile95,
|
|
},
|
|
},
|
|
GroupBy: []qbtypes.GroupByKey{
|
|
{
|
|
TelemetryFieldKey: telemetrytypes.TelemetryFieldKey{
|
|
Name: "service.name",
|
|
},
|
|
},
|
|
},
|
|
},
|
|
expected: qbtypes.Statement{
|
|
Query: "WITH __temporal_aggregation_cte AS (SELECT ts, `__GROUP_BY_KEY_0_service.name`, `le`, multiIf(row_number() OVER rate_window = 1, nan, (per_series_value - lagInFrame(per_series_value, 1) OVER rate_window) < 0, per_series_value, per_series_value - lagInFrame(per_series_value, 1) OVER rate_window) AS per_series_value FROM (SELECT fingerprint, toStartOfInterval(toDateTime(intDiv(unix_milli, 1000)), toIntervalSecond(60)) AS ts, `__GROUP_BY_KEY_0_service.name`, `le`, max(value) AS per_series_value FROM signoz_metrics.distributed_samples_v4 AS points INNER JOIN (SELECT fingerprint, JSONExtractString(labels, 'service.name') AS `__GROUP_BY_KEY_0_service.name`, JSONExtractString(labels, 'le') AS `le` FROM signoz_metrics.time_series_v4_6hrs WHERE metric_name IN (?) AND unix_milli >= ? AND unix_milli <= ? AND LOWER(temporality) LIKE LOWER(?) GROUP BY fingerprint, `__GROUP_BY_KEY_0_service.name`, `le`) AS filtered_time_series ON points.fingerprint = filtered_time_series.fingerprint WHERE metric_name IN (?) AND unix_milli >= ? AND unix_milli < ? GROUP BY fingerprint, ts, `__GROUP_BY_KEY_0_service.name`, `le` ORDER BY fingerprint, ts) WINDOW rate_window AS (PARTITION BY fingerprint ORDER BY fingerprint, ts)), __spatial_aggregation_cte AS (SELECT ts, `__GROUP_BY_KEY_0_service.name`, `le`, sum(per_series_value) AS value FROM __temporal_aggregation_cte WHERE isNaN(per_series_value) = ? GROUP BY ts, `__GROUP_BY_KEY_0_service.name`, `le`) SELECT ts, `__GROUP_BY_KEY_0_service.name`, lagInFrame(toFloat64(le), 1, toFloat64('-Inf')) OVER __heatmap_window AS __bucket_min, toFloat64(le) AS __bucket_max, greatest(value - lagInFrame(value, 1, 0) OVER __heatmap_window, 0) AS __result_0 FROM __spatial_aggregation_cte WINDOW __heatmap_window AS (PARTITION BY `__GROUP_BY_KEY_0_service.name`, ts ORDER BY toFloat64(le)) ORDER BY `__GROUP_BY_KEY_0_service.name`, ts, toFloat64(le)",
|
|
Args: []any{"http_server_duration_bucket", uint64(1747936800000), uint64(1747983420000), "cumulative", "http_server_duration_bucket", uint64(1747947300000), uint64(1747983420000), 0},
|
|
},
|
|
expectedErr: nil,
|
|
},
|
|
{
|
|
name: "test_sum_heatmap_cumulative",
|
|
requestType: qbtypes.RequestTypeHeatmap,
|
|
query: qbtypes.QueryBuilderQuery[qbtypes.MetricAggregation]{
|
|
Signal: telemetrytypes.SignalMetrics,
|
|
StepInterval: qbtypes.Step{Duration: 60 * time.Second},
|
|
Aggregations: []qbtypes.MetricAggregation{
|
|
{
|
|
MetricName: "signoz_calls_total",
|
|
Type: metrictypes.SumType,
|
|
Temporality: metrictypes.Cumulative,
|
|
TimeAggregation: metrictypes.TimeAggregationIncrease,
|
|
SpaceAggregation: metrictypes.SpaceAggregationSum,
|
|
HeatmapBucketing: &qbtypes.HeatmapBucketing{
|
|
Kind: qbtypes.BucketsKindLog,
|
|
LogScale: qbtypes.MaxLogScale,
|
|
NumBuckets: qbtypes.DefaultNumBuckets,
|
|
},
|
|
},
|
|
},
|
|
GroupBy: []qbtypes.GroupByKey{
|
|
{
|
|
TelemetryFieldKey: telemetrytypes.TelemetryFieldKey{
|
|
Name: "service.name",
|
|
},
|
|
},
|
|
},
|
|
},
|
|
expected: qbtypes.Statement{
|
|
Query: "WITH __temporal_aggregation_cte AS (SELECT ts, `__GROUP_BY_KEY_0_service.name`, multiIf(row_number() OVER rate_window = 1, nan, (per_series_value - lagInFrame(per_series_value, 1) OVER rate_window) < 0, per_series_value, per_series_value - lagInFrame(per_series_value, 1) OVER rate_window) AS per_series_value FROM (SELECT fingerprint, toStartOfInterval(toDateTime(intDiv(unix_milli, 1000)), toIntervalSecond(60)) AS ts, `__GROUP_BY_KEY_0_service.name`, max(value) AS per_series_value FROM signoz_metrics.distributed_samples_v4 AS points INNER JOIN (SELECT fingerprint, JSONExtractString(labels, 'service.name') AS `__GROUP_BY_KEY_0_service.name` FROM signoz_metrics.time_series_v4_6hrs WHERE metric_name IN (?) AND unix_milli >= ? AND unix_milli <= ? AND LOWER(temporality) LIKE LOWER(?) GROUP BY fingerprint, `__GROUP_BY_KEY_0_service.name`) AS filtered_time_series ON points.fingerprint = filtered_time_series.fingerprint WHERE metric_name IN (?) AND unix_milli >= ? AND unix_milli < ? GROUP BY fingerprint, ts, `__GROUP_BY_KEY_0_service.name` ORDER BY fingerprint, ts) WINDOW rate_window AS (PARTITION BY fingerprint ORDER BY fingerprint, ts)), __spatial_aggregation_cte AS (SELECT ts, `__GROUP_BY_KEY_0_service.name`, sum(per_series_value) AS value FROM __temporal_aggregation_cte WHERE isNaN(per_series_value) = ? GROUP BY ts, `__GROUP_BY_KEY_0_service.name`) SELECT ts, `__GROUP_BY_KEY_0_service.name`, multiIf(value <= 0, toFloat64('-Inf'), value <= 2.3283064365386963e-10, toFloat64(0), value > 1.8446744073709552e+19, toFloat64(1.8446744073709552e+19), pow(2, (ceil(log2(value) * 16) - 1) / 16)) AS __bucket_min, multiIf(value <= 0, toFloat64(0), value <= 2.3283064365386963e-10, 2.3283064365386963e-10, value > 1.8446744073709552e+19, toFloat64('+Inf'), pow(2, ceil(log2(value) * 16) / 16)) AS __bucket_max, toFloat64(1) AS __result_0 FROM __spatial_aggregation_cte ORDER BY `__GROUP_BY_KEY_0_service.name`, ts, __bucket_max",
|
|
Args: []any{"signoz_calls_total", uint64(1747936800000), uint64(1747983420000), "cumulative", "signoz_calls_total", uint64(1747947300000), uint64(1747983420000), 0},
|
|
},
|
|
expectedErr: nil,
|
|
},
|
|
{
|
|
name: "test_gauge_avg_sum",
|
|
requestType: qbtypes.RequestTypeTimeSeries,
|
|
query: qbtypes.QueryBuilderQuery[qbtypes.MetricAggregation]{
|
|
Signal: telemetrytypes.SignalMetrics,
|
|
StepInterval: qbtypes.Step{Duration: 30 * time.Second},
|
|
Aggregations: []qbtypes.MetricAggregation{
|
|
{
|
|
MetricName: "system.memory.usage",
|
|
Type: metrictypes.GaugeType,
|
|
Temporality: metrictypes.Unspecified,
|
|
TimeAggregation: metrictypes.TimeAggregationAvg,
|
|
SpaceAggregation: metrictypes.SpaceAggregationSum,
|
|
},
|
|
},
|
|
Filter: &qbtypes.Filter{
|
|
Expression: "host.name = 'big-data-node-1'",
|
|
},
|
|
Limit: 10,
|
|
GroupBy: []qbtypes.GroupByKey{
|
|
{
|
|
TelemetryFieldKey: telemetrytypes.TelemetryFieldKey{
|
|
Name: "host.name",
|
|
},
|
|
},
|
|
},
|
|
},
|
|
expected: qbtypes.Statement{
|
|
Query: "WITH __temporal_aggregation_cte AS (SELECT fingerprint, toStartOfInterval(toDateTime(intDiv(unix_milli, 1000)), toIntervalSecond(30)) AS ts, `__GROUP_BY_KEY_0_host.name`, avg(value) AS per_series_value FROM signoz_metrics.distributed_samples_v4 AS points INNER JOIN (SELECT fingerprint, JSONExtractString(labels, 'host.name') AS `__GROUP_BY_KEY_0_host.name` FROM signoz_metrics.time_series_v4_6hrs WHERE metric_name IN (?) AND unix_milli >= ? AND unix_milli <= ? AND LOWER(temporality) LIKE LOWER(?) AND JSONExtractString(labels, 'host.name') = ? GROUP BY fingerprint, `__GROUP_BY_KEY_0_host.name`) AS filtered_time_series ON points.fingerprint = filtered_time_series.fingerprint WHERE metric_name IN (?) AND unix_milli >= ? AND unix_milli < ? GROUP BY fingerprint, ts, `__GROUP_BY_KEY_0_host.name` ORDER BY fingerprint, ts), __spatial_aggregation_cte AS (SELECT ts, `__GROUP_BY_KEY_0_host.name`, sum(per_series_value) AS value FROM __temporal_aggregation_cte WHERE isNaN(per_series_value) = ? GROUP BY ts, `__GROUP_BY_KEY_0_host.name`) SELECT * FROM __spatial_aggregation_cte ORDER BY `__GROUP_BY_KEY_0_host.name`, ts",
|
|
Args: []any{"system.memory.usage", uint64(1747936800000), uint64(1747983420000), "unspecified", "big-data-node-1", "system.memory.usage", uint64(1747947390000), uint64(1747983420000), 0},
|
|
},
|
|
expectedErr: nil,
|
|
},
|
|
{
|
|
name: "test_histogram_percentile2",
|
|
requestType: qbtypes.RequestTypeTimeSeries,
|
|
query: qbtypes.QueryBuilderQuery[qbtypes.MetricAggregation]{
|
|
Signal: telemetrytypes.SignalMetrics,
|
|
StepInterval: qbtypes.Step{Duration: 30 * time.Second},
|
|
Aggregations: []qbtypes.MetricAggregation{
|
|
{
|
|
MetricName: "http_server_duration_bucket",
|
|
Type: metrictypes.HistogramType,
|
|
Temporality: metrictypes.Cumulative,
|
|
TimeAggregation: metrictypes.TimeAggregationRate,
|
|
SpaceAggregation: metrictypes.SpaceAggregationPercentile95,
|
|
},
|
|
},
|
|
Limit: 10,
|
|
GroupBy: []qbtypes.GroupByKey{
|
|
{
|
|
TelemetryFieldKey: telemetrytypes.TelemetryFieldKey{
|
|
Name: "service.name",
|
|
},
|
|
},
|
|
},
|
|
},
|
|
expected: qbtypes.Statement{
|
|
Query: "WITH __temporal_aggregation_cte AS (SELECT ts, `__GROUP_BY_KEY_0_service.name`, `le`, multiIf(row_number() OVER rate_window = 1, nan, (per_series_value - lagInFrame(per_series_value, 1) OVER rate_window) < 0, per_series_value / (ts - lagInFrame(ts, 1) OVER rate_window), (per_series_value - lagInFrame(per_series_value, 1) OVER rate_window) / (ts - lagInFrame(ts, 1) OVER rate_window)) AS per_series_value FROM (SELECT fingerprint, toStartOfInterval(toDateTime(intDiv(unix_milli, 1000)), toIntervalSecond(30)) AS ts, `__GROUP_BY_KEY_0_service.name`, `le`, max(value) AS per_series_value FROM signoz_metrics.distributed_samples_v4 AS points INNER JOIN (SELECT fingerprint, JSONExtractString(labels, 'service.name') AS `__GROUP_BY_KEY_0_service.name`, JSONExtractString(labels, 'le') AS `le` FROM signoz_metrics.time_series_v4_6hrs WHERE metric_name IN (?) AND unix_milli >= ? AND unix_milli <= ? AND LOWER(temporality) LIKE LOWER(?) GROUP BY fingerprint, `__GROUP_BY_KEY_0_service.name`, `le`) AS filtered_time_series ON points.fingerprint = filtered_time_series.fingerprint WHERE metric_name IN (?) AND unix_milli >= ? AND unix_milli < ? GROUP BY fingerprint, ts, `__GROUP_BY_KEY_0_service.name`, `le` ORDER BY fingerprint, ts) WINDOW rate_window AS (PARTITION BY fingerprint ORDER BY fingerprint, ts)), __spatial_aggregation_cte AS (SELECT ts, `__GROUP_BY_KEY_0_service.name`, `le`, sum(per_series_value) AS value FROM __temporal_aggregation_cte WHERE isNaN(per_series_value) = ? GROUP BY ts, `__GROUP_BY_KEY_0_service.name`, `le`) SELECT ts, `__GROUP_BY_KEY_0_service.name`, histogramQuantile(arrayMap(x -> toFloat64(x), groupArray(le)), groupArray(value), 0.950) AS value FROM __spatial_aggregation_cte GROUP BY `__GROUP_BY_KEY_0_service.name`, ts ORDER BY `__GROUP_BY_KEY_0_service.name`, ts",
|
|
Args: []any{"http_server_duration_bucket", uint64(1747936800000), uint64(1747983420000), "cumulative", "http_server_duration_bucket", uint64(1747947360000), uint64(1747983420000), 0},
|
|
},
|
|
expectedErr: nil,
|
|
},
|
|
{
|
|
name: "test_missing_key_falls_back_to_labels",
|
|
requestType: qbtypes.RequestTypeTimeSeries,
|
|
query: qbtypes.QueryBuilderQuery[qbtypes.MetricAggregation]{
|
|
Signal: telemetrytypes.SignalMetrics,
|
|
StepInterval: qbtypes.Step{Duration: 30 * time.Second},
|
|
Aggregations: []qbtypes.MetricAggregation{
|
|
{
|
|
MetricName: "signoz_calls_total",
|
|
Type: metrictypes.SumType,
|
|
Temporality: metrictypes.Cumulative,
|
|
TimeAggregation: metrictypes.TimeAggregationRate,
|
|
SpaceAggregation: metrictypes.SpaceAggregationSum,
|
|
},
|
|
},
|
|
Filter: &qbtypes.Filter{
|
|
Expression: "k8s.statefulset.name = 'my-statefulset'",
|
|
},
|
|
GroupBy: []qbtypes.GroupByKey{
|
|
{
|
|
TelemetryFieldKey: telemetrytypes.TelemetryFieldKey{
|
|
Name: "k8s.statefulset.name",
|
|
},
|
|
},
|
|
},
|
|
},
|
|
expected: qbtypes.Statement{
|
|
Query: "WITH __temporal_aggregation_cte AS (SELECT ts, `__GROUP_BY_KEY_0_k8s.statefulset.name`, multiIf(row_number() OVER rate_window = 1, nan, (per_series_value - lagInFrame(per_series_value, 1) OVER rate_window) < 0, per_series_value / (ts - lagInFrame(ts, 1) OVER rate_window), (per_series_value - lagInFrame(per_series_value, 1) OVER rate_window) / (ts - lagInFrame(ts, 1) OVER rate_window)) AS per_series_value FROM (SELECT fingerprint, toStartOfInterval(toDateTime(intDiv(unix_milli, 1000)), toIntervalSecond(30)) AS ts, `__GROUP_BY_KEY_0_k8s.statefulset.name`, max(value) AS per_series_value FROM signoz_metrics.distributed_samples_v4 AS points INNER JOIN (SELECT fingerprint, JSONExtractString(labels, 'k8s.statefulset.name') AS `__GROUP_BY_KEY_0_k8s.statefulset.name` FROM signoz_metrics.time_series_v4_6hrs WHERE metric_name IN (?) AND unix_milli >= ? AND unix_milli <= ? AND LOWER(temporality) LIKE LOWER(?) AND JSONExtractString(labels, 'k8s.statefulset.name') = ? GROUP BY fingerprint, `__GROUP_BY_KEY_0_k8s.statefulset.name`) AS filtered_time_series ON points.fingerprint = filtered_time_series.fingerprint WHERE metric_name IN (?) AND unix_milli >= ? AND unix_milli < ? GROUP BY fingerprint, ts, `__GROUP_BY_KEY_0_k8s.statefulset.name` ORDER BY fingerprint, ts) WINDOW rate_window AS (PARTITION BY fingerprint ORDER BY fingerprint, ts)), __spatial_aggregation_cte AS (SELECT ts, `__GROUP_BY_KEY_0_k8s.statefulset.name`, sum(per_series_value) AS value FROM __temporal_aggregation_cte WHERE isNaN(per_series_value) = ? GROUP BY ts, `__GROUP_BY_KEY_0_k8s.statefulset.name`) SELECT * FROM __spatial_aggregation_cte ORDER BY `__GROUP_BY_KEY_0_k8s.statefulset.name`, ts",
|
|
Args: []any{"signoz_calls_total", uint64(1747936800000), uint64(1747983420000), "cumulative", "my-statefulset", "signoz_calls_total", uint64(1747947360000), uint64(1747983420000), 0},
|
|
Warnings: []string{"label `k8s.statefulset.name` not found in metadata; check the label name for typos"},
|
|
},
|
|
expectedErr: nil,
|
|
},
|
|
{
|
|
name: "test_bool_label_filter",
|
|
requestType: qbtypes.RequestTypeTimeSeries,
|
|
query: qbtypes.QueryBuilderQuery[qbtypes.MetricAggregation]{
|
|
Signal: telemetrytypes.SignalMetrics,
|
|
StepInterval: qbtypes.Step{Duration: 30 * time.Second},
|
|
Aggregations: []qbtypes.MetricAggregation{
|
|
{
|
|
MetricName: "signoz_calls_total",
|
|
Type: metrictypes.SumType,
|
|
Temporality: metrictypes.Cumulative,
|
|
TimeAggregation: metrictypes.TimeAggregationRate,
|
|
SpaceAggregation: metrictypes.SpaceAggregationSum,
|
|
},
|
|
},
|
|
Filter: &qbtypes.Filter{
|
|
Expression: "success = true",
|
|
},
|
|
GroupBy: []qbtypes.GroupByKey{
|
|
{
|
|
TelemetryFieldKey: telemetrytypes.TelemetryFieldKey{
|
|
Name: "service.name",
|
|
},
|
|
},
|
|
},
|
|
},
|
|
expected: qbtypes.Statement{
|
|
Query: "WITH __temporal_aggregation_cte AS (SELECT ts, `__GROUP_BY_KEY_0_service.name`, multiIf(row_number() OVER rate_window = 1, nan, (per_series_value - lagInFrame(per_series_value, 1) OVER rate_window) < 0, per_series_value / (ts - lagInFrame(ts, 1) OVER rate_window), (per_series_value - lagInFrame(per_series_value, 1) OVER rate_window) / (ts - lagInFrame(ts, 1) OVER rate_window)) AS per_series_value FROM (SELECT fingerprint, toStartOfInterval(toDateTime(intDiv(unix_milli, 1000)), toIntervalSecond(30)) AS ts, `__GROUP_BY_KEY_0_service.name`, max(value) AS per_series_value FROM signoz_metrics.distributed_samples_v4 AS points INNER JOIN (SELECT fingerprint, JSONExtractString(labels, 'service.name') AS `__GROUP_BY_KEY_0_service.name` FROM signoz_metrics.time_series_v4_6hrs WHERE metric_name IN (?) AND unix_milli >= ? AND unix_milli <= ? AND LOWER(temporality) LIKE LOWER(?) AND accurateCastOrNull(JSONExtractString(labels, 'success'), 'Bool') = ? GROUP BY fingerprint, `__GROUP_BY_KEY_0_service.name`) AS filtered_time_series ON points.fingerprint = filtered_time_series.fingerprint WHERE metric_name IN (?) AND unix_milli >= ? AND unix_milli < ? GROUP BY fingerprint, ts, `__GROUP_BY_KEY_0_service.name` ORDER BY fingerprint, ts) WINDOW rate_window AS (PARTITION BY fingerprint ORDER BY fingerprint, ts)), __spatial_aggregation_cte AS (SELECT ts, `__GROUP_BY_KEY_0_service.name`, sum(per_series_value) AS value FROM __temporal_aggregation_cte WHERE isNaN(per_series_value) = ? GROUP BY ts, `__GROUP_BY_KEY_0_service.name`) SELECT * FROM __spatial_aggregation_cte ORDER BY `__GROUP_BY_KEY_0_service.name`, ts",
|
|
Args: []any{"signoz_calls_total", uint64(1747936800000), uint64(1747983420000), "cumulative", true, "signoz_calls_total", uint64(1747947360000), uint64(1747983420000), 0},
|
|
},
|
|
expectedErr: nil,
|
|
},
|
|
}
|
|
|
|
fm := metricstelemetryschema.NewFieldMapper()
|
|
cb := metricstelemetryschema.NewConditionBuilder(fm)
|
|
mockMetadataStore := telemetrytypestest.NewMockMetadataStore()
|
|
keys, err := telemetrytypestest.LoadFieldKeysFromJSON("testdata/keys_map.json")
|
|
if err != nil {
|
|
t.Fatalf("failed to load field keys: %v", err)
|
|
}
|
|
mockMetadataStore.KeysMap = keys
|
|
// NOTE: LoadFieldKeysFromJSON doesn't set Materialized field
|
|
// for keys, so we have to set it manually here for testing
|
|
if _, ok := mockMetadataStore.KeysMap["materialized.key.name"]; ok {
|
|
if len(mockMetadataStore.KeysMap["materialized.key.name"]) > 0 {
|
|
mockMetadataStore.KeysMap["materialized.key.name"][0].Materialized = true
|
|
}
|
|
}
|
|
|
|
flagger, err := flagger.New(context.Background(), instrumentationtest.New().ToProviderSettings(), flagger.Config{}, flagger.MustNewRegistry())
|
|
if err != nil {
|
|
t.Fatalf("failed to create flagger: %v", err)
|
|
}
|
|
|
|
statementBuilder := NewMetricQueryStatementBuilder(
|
|
instrumentationtest.New().ToProviderSettings(),
|
|
mockMetadataStore,
|
|
fm,
|
|
cb,
|
|
flagger,
|
|
)
|
|
|
|
for _, c := range cases {
|
|
t.Run(c.name, func(t *testing.T) {
|
|
|
|
q, err := statementBuilder.Build(context.Background(), valuer.UUID{}, 1747947419000, 1747983448000, c.requestType, c.query, nil)
|
|
|
|
if c.expectedErr != nil {
|
|
require.Error(t, err)
|
|
require.Contains(t, err.Error(), c.expectedErr.Error())
|
|
} else {
|
|
require.NoError(t, err)
|
|
require.Equal(t, c.expected.Query, q.Query)
|
|
require.Equal(t, c.expected.Args, q.Args)
|
|
require.Equal(t, c.expected.Warnings, q.Warnings)
|
|
}
|
|
})
|
|
}
|
|
}
|
|
|
|
func TestGroupByAliasAvoidsColumnCollision(t *testing.T) {
|
|
fm := metricstelemetryschema.NewFieldMapper()
|
|
cb := metricstelemetryschema.NewConditionBuilder(fm)
|
|
mockMetadataStore := telemetrytypestest.NewMockMetadataStore()
|
|
keys, err := telemetrytypestest.LoadFieldKeysFromJSON("testdata/keys_map.json")
|
|
require.NoError(t, err)
|
|
mockMetadataStore.KeysMap = keys
|
|
|
|
fl, err := flagger.New(context.Background(), instrumentationtest.New().ToProviderSettings(), flagger.Config{}, flagger.MustNewRegistry())
|
|
require.NoError(t, err)
|
|
|
|
statementBuilder := NewMetricQueryStatementBuilder(
|
|
instrumentationtest.New().ToProviderSettings(),
|
|
mockMetadataStore,
|
|
fm,
|
|
cb,
|
|
fl,
|
|
)
|
|
|
|
for _, groupBy := range []string{"ts", "value", "fingerprint", "service.name"} {
|
|
t.Run(groupBy, func(t *testing.T) {
|
|
stmt, err := statementBuilder.Build(
|
|
context.Background(),
|
|
valuer.UUID{},
|
|
1747947419000,
|
|
1747983448000,
|
|
qbtypes.RequestTypeTimeSeries,
|
|
qbtypes.QueryBuilderQuery[qbtypes.MetricAggregation]{
|
|
Signal: telemetrytypes.SignalMetrics,
|
|
StepInterval: qbtypes.Step{Duration: 30 * time.Second},
|
|
Aggregations: []qbtypes.MetricAggregation{
|
|
{
|
|
MetricName: "signoz_calls_total",
|
|
Type: metrictypes.SumType,
|
|
Temporality: metrictypes.Cumulative,
|
|
TimeAggregation: metrictypes.TimeAggregationRate,
|
|
SpaceAggregation: metrictypes.SpaceAggregationSum,
|
|
},
|
|
},
|
|
GroupBy: []qbtypes.GroupByKey{
|
|
{TelemetryFieldKey: telemetrytypes.TelemetryFieldKey{Name: groupBy}},
|
|
},
|
|
},
|
|
nil,
|
|
)
|
|
require.NoError(t, err)
|
|
|
|
assert.Contains(t, stmt.Query, fmt.Sprintf("`__GROUP_BY_KEY_0_%s`", groupBy))
|
|
assert.NotContains(t, stmt.Query, fmt.Sprintf("`%s`", groupBy),
|
|
"the group-by column must not be selected under the label's own name")
|
|
assert.Equal(t, 1, strings.Count(stmt.Query, " AS ts,"),
|
|
"the step bucket is the only column named ts")
|
|
})
|
|
}
|
|
}
|