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signoz/pkg/query-service/app/metrics/v4/query_builder_test.go

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chore: update BuilderQuery struct and add PrepareTimeseriesFilterQuery (#4165)
2023-12-12 07:24:33 +05:30
package v4
import (
"testing"
"github.com/stretchr/testify/assert"
chore: add /v4/query_range endpoint (#4361)
2024-01-16 16:56:20 +05:30
metricsV3 "go.signoz.io/signoz/pkg/query-service/app/metrics/v3"
"go.signoz.io/signoz/pkg/query-service/app/metrics/v4/helpers"
chore: update BuilderQuery struct and add PrepareTimeseriesFilterQuery (#4165)
2023-12-12 07:24:33 +05:30
v3 "go.signoz.io/signoz/pkg/query-service/model/v3"
)
func TestPrepareTimeseriesFilterQuery(t *testing.T) {
testCases := []struct {
name string
builderQuery *v3.BuilderQuery
expectedQueryContains string
}{
{
name: "test prepare time series with no filters and no group by",
builderQuery: &v3.BuilderQuery{
QueryName: "A",
StepInterval: 60,
DataSource: v3.DataSourceMetrics,
AggregateAttribute: v3.AttributeKey{
Key: "http_requests",
DataType: v3.AttributeKeyDataTypeFloat64,
Type: v3.AttributeKeyTypeUnspecified,
IsColumn: true,
IsJSON: false,
},
Temporality: v3.Delta,
Expression: "A",
Disabled: false,
// remaining struct fields are not needed here
},
expectedQueryContains: "SELECT DISTINCT fingerprint FROM signoz_metrics.time_series_v2 WHERE metric_name = 'http_requests' AND temporality = 'Delta'",
},
{
name: "test prepare time series with no filters and group by",
builderQuery: &v3.BuilderQuery{
QueryName: "A",
StepInterval: 60,
DataSource: v3.DataSourceMetrics,
AggregateAttribute: v3.AttributeKey{
Key: "http_requests",
DataType: v3.AttributeKeyDataTypeFloat64,
Type: v3.AttributeKeyTypeUnspecified,
IsColumn: true,
IsJSON: false,
},
Temporality: v3.Cumulative,
GroupBy: []v3.AttributeKey{{
Key: "service_name",
DataType: v3.AttributeKeyDataTypeString,
Type: v3.AttributeKeyTypeTag,
}},
Expression: "A",
Disabled: false,
// remaining struct fields are not needed here
},
expectedQueryContains: "SELECT DISTINCT JSONExtractString(labels, 'service_name') as service_name, fingerprint FROM signoz_metrics.time_series_v2 WHERE metric_name = 'http_requests' AND temporality = 'Cumulative'",
},
{
name: "test prepare time series with no filters and multiple group by",
builderQuery: &v3.BuilderQuery{
QueryName: "A",
StepInterval: 60,
DataSource: v3.DataSourceMetrics,
AggregateAttribute: v3.AttributeKey{
Key: "http_requests",
DataType: v3.AttributeKeyDataTypeFloat64,
Type: v3.AttributeKeyTypeUnspecified,
IsColumn: true,
IsJSON: false,
},
Temporality: v3.Cumulative,
GroupBy: []v3.AttributeKey{
{
Key: "service_name",
DataType: v3.AttributeKeyDataTypeString,
Type: v3.AttributeKeyTypeTag,
},
{
Key: "endpoint",
DataType: v3.AttributeKeyDataTypeString,
Type: v3.AttributeKeyTypeTag,
},
},
Expression: "A",
Disabled: false,
// remaining struct fields are not needed here
},
expectedQueryContains: "SELECT DISTINCT JSONExtractString(labels, 'service_name') as service_name, JSONExtractString(labels, 'endpoint') as endpoint, fingerprint FROM signoz_metrics.time_series_v2 WHERE metric_name = 'http_requests' AND temporality = 'Cumulative'",
},
{
name: "test prepare time series with filters and multiple group by",
builderQuery: &v3.BuilderQuery{
QueryName: "A",
StepInterval: 60,
DataSource: v3.DataSourceMetrics,
AggregateAttribute: v3.AttributeKey{
Key: "http_requests",
DataType: v3.AttributeKeyDataTypeFloat64,
Type: v3.AttributeKeyTypeUnspecified,
IsColumn: true,
IsJSON: false,
},
Temporality: v3.Cumulative,
Filters: &v3.FilterSet{
Operator: "AND",
Items: []v3.FilterItem{
{
Key: v3.AttributeKey{
Key: "service_name",
Type: v3.AttributeKeyTypeTag,
DataType: v3.AttributeKeyDataTypeString,
},
Operator: v3.FilterOperatorNotEqual,
Value: "payment_service",
},
{
Key: v3.AttributeKey{
Key: "endpoint",
Type: v3.AttributeKeyTypeTag,
DataType: v3.AttributeKeyDataTypeString,
},
Operator: v3.FilterOperatorIn,
Value: []interface{}{"/paycallback", "/payme", "/paypal"},
},
},
},
GroupBy: []v3.AttributeKey{{
Key: "service_name",
DataType: v3.AttributeKeyDataTypeString,
Type: v3.AttributeKeyTypeTag,
}},
Expression: "A",
Disabled: false,
// remaining struct fields are not needed here
},
expectedQueryContains: "SELECT DISTINCT JSONExtractString(labels, 'service_name') as service_name, fingerprint FROM signoz_metrics.time_series_v2 WHERE metric_name = 'http_requests' AND temporality = 'Cumulative' AND JSONExtractString(labels, 'service_name') != 'payment_service' AND JSONExtractString(labels, 'endpoint') IN ['/paycallback','/payme','/paypal']",
},
}
for _, testCase := range testCases {
t.Run(testCase.name, func(t *testing.T) {
chore: add /v4/query_range endpoint (#4361)
2024-01-16 16:56:20 +05:30
query, err := helpers.PrepareTimeseriesFilterQuery(testCase.builderQuery)
assert.Nil(t, err)
assert.Contains(t, query, testCase.expectedQueryContains)
})
}
}
func TestPrepareMetricQueryCumulativeRate(t *testing.T) {
testCases := []struct {
name string
builderQuery *v3.BuilderQuery
expectedQueryContains string
}{
{
name: "test time aggregation = rate, space aggregation = sum, temporality = cumulative",
builderQuery: &v3.BuilderQuery{
QueryName: "A",
StepInterval: 60,
DataSource: v3.DataSourceMetrics,
AggregateAttribute: v3.AttributeKey{
Key: "signoz_calls_total",
},
Temporality: v3.Cumulative,
Filters: &v3.FilterSet{
Operator: "AND",
Items: []v3.FilterItem{
{
Key: v3.AttributeKey{
Key: "service_name",
Type: v3.AttributeKeyTypeTag,
DataType: v3.AttributeKeyDataTypeString,
},
Operator: v3.FilterOperatorContains,
Value: "frontend",
},
},
},
GroupBy: []v3.AttributeKey{{
Key: "service_name",
DataType: v3.AttributeKeyDataTypeString,
Type: v3.AttributeKeyTypeTag,
}},
Expression: "A",
Disabled: false,
TimeAggregation: v3.TimeAggregationRate,
SpaceAggregation: v3.SpaceAggregationSum,
},
expectedQueryContains: "SELECT service_name, ts, sum(per_series_value) as value FROM (SELECT service_name, ts, If((per_series_value - lagInFrame(per_series_value, 1, 0) OVER rate_window) < 0, nan, If((ts - lagInFrame(ts, 1, toDate('1970-01-01')) OVER rate_window) >= 86400, nan, (per_series_value - lagInFrame(per_series_value, 1, 0) OVER rate_window) / (ts - lagInFrame(ts, 1, toDate('1970-01-01')) OVER rate_window))) as per_series_value FROM (SELECT fingerprint, any(service_name) as service_name, toStartOfInterval(toDateTime(intDiv(timestamp_ms, 1000)), INTERVAL 60 SECOND) as ts, max(value) as per_series_value FROM signoz_metrics.distributed_samples_v2 INNER JOIN (SELECT DISTINCT JSONExtractString(labels, 'service_name') as service_name, fingerprint FROM signoz_metrics.time_series_v2 WHERE metric_name = 'signoz_calls_total' AND temporality = 'Cumulative' AND like(JSONExtractString(labels, 'service_name'), '%frontend%')) as filtered_time_series USING fingerprint WHERE metric_name = 'signoz_calls_total' AND timestamp_ms >= 1650991920000 AND timestamp_ms <= 1651078380000 GROUP BY fingerprint, ts ORDER BY fingerprint, ts) WINDOW rate_window as (PARTITION BY fingerprint ORDER BY fingerprint, ts)) WHERE isNaN(per_series_value) = 0 GROUP BY GROUPING SETS ( (service_name, ts), (service_name) ) ORDER BY service_name ASC, ts ASC",
},
{
name: "test time aggregation = rate, space aggregation = sum, temporality = cumulative, multiple group by",
builderQuery: &v3.BuilderQuery{
QueryName: "A",
StepInterval: 60,
DataSource: v3.DataSourceMetrics,
AggregateAttribute: v3.AttributeKey{
Key: "signoz_calls_total",
},
Temporality: v3.Cumulative,
Filters: &v3.FilterSet{
Operator: "AND",
Items: []v3.FilterItem{},
},
GroupBy: []v3.AttributeKey{
{
Key: "service_name",
DataType: v3.AttributeKeyDataTypeString,
Type: v3.AttributeKeyTypeTag,
},
{
Key: "endpoint",
DataType: v3.AttributeKeyDataTypeString,
Type: v3.AttributeKeyTypeTag,
},
},
Expression: "A",
Disabled: false,
TimeAggregation: v3.TimeAggregationRate,
SpaceAggregation: v3.SpaceAggregationSum,
},
expectedQueryContains: "SELECT service_name, endpoint, ts, sum(per_series_value) as value FROM (SELECT service_name, endpoint, ts, If((per_series_value - lagInFrame(per_series_value, 1, 0) OVER rate_window) < 0, nan, If((ts - lagInFrame(ts, 1, toDate('1970-01-01')) OVER rate_window) >= 86400, nan, (per_series_value - lagInFrame(per_series_value, 1, 0) OVER rate_window) / (ts - lagInFrame(ts, 1, toDate('1970-01-01')) OVER rate_window))) as per_series_value FROM (SELECT fingerprint, any(service_name) as service_name, any(endpoint) as endpoint, toStartOfInterval(toDateTime(intDiv(timestamp_ms, 1000)), INTERVAL 60 SECOND) as ts, max(value) as per_series_value FROM signoz_metrics.distributed_samples_v2 INNER JOIN (SELECT DISTINCT JSONExtractString(labels, 'service_name') as service_name, JSONExtractString(labels, 'endpoint') as endpoint, fingerprint FROM signoz_metrics.time_series_v2 WHERE metric_name = 'signoz_calls_total' AND temporality = 'Cumulative') as filtered_time_series USING fingerprint WHERE metric_name = 'signoz_calls_total' AND timestamp_ms >= 1650991920000 AND timestamp_ms <= 1651078380000 GROUP BY fingerprint, ts ORDER BY fingerprint, ts) WINDOW rate_window as (PARTITION BY fingerprint ORDER BY fingerprint, ts)) WHERE isNaN(per_series_value) = 0 GROUP BY GROUPING SETS ( (service_name, endpoint, ts), (service_name, endpoint) ) ORDER BY service_name ASC, endpoint ASC, ts ASC",
},
}
for _, testCase := range testCases {
t.Run(testCase.name, func(t *testing.T) {
query, err := PrepareMetricQuery(1650991982000, 1651078382000, v3.QueryTypeBuilder, v3.PanelTypeGraph, testCase.builderQuery, metricsV3.Options{})
assert.Nil(t, err)
assert.Contains(t, query, testCase.expectedQueryContains)
})
}
}
func TestPrepareMetricQueryDeltaRate(t *testing.T) {
testCases := []struct {
name string
builderQuery *v3.BuilderQuery
expectedQueryContains string
}{
{
name: "test time aggregation = rate, space aggregation = sum, temporality = delta, no group by",
builderQuery: &v3.BuilderQuery{
QueryName: "A",
StepInterval: 60,
DataSource: v3.DataSourceMetrics,
AggregateAttribute: v3.AttributeKey{
Key: "signoz_calls_total",
},
Temporality: v3.Delta,
Filters: &v3.FilterSet{
Operator: "AND",
Items: []v3.FilterItem{},
},
Expression: "A",
Disabled: false,
TimeAggregation: v3.TimeAggregationRate,
SpaceAggregation: v3.SpaceAggregationSum,
},
expectedQueryContains: "SELECT toStartOfInterval(toDateTime(intDiv(timestamp_ms, 1000)), INTERVAL 60 SECOND) as ts, sum(value)/60 as value FROM signoz_metrics.distributed_samples_v2 INNER JOIN (SELECT DISTINCT fingerprint FROM signoz_metrics.time_series_v2 WHERE metric_name = 'signoz_calls_total' AND temporality = 'Delta') as filtered_time_series USING fingerprint WHERE metric_name = 'signoz_calls_total' AND timestamp_ms >= 1650991920000 AND timestamp_ms <= 1651078380000 GROUP BY ts ORDER BY ts ASC",
},
{
name: "test time aggregation = rate, space aggregation = sum, temporality = delta, group by service_name",
builderQuery: &v3.BuilderQuery{
QueryName: "A",
StepInterval: 60,
DataSource: v3.DataSourceMetrics,
AggregateAttribute: v3.AttributeKey{
Key: "signoz_calls_total",
},
Temporality: v3.Delta,
Filters: &v3.FilterSet{
Operator: "AND",
Items: []v3.FilterItem{},
},
GroupBy: []v3.AttributeKey{{
Key: "service_name",
DataType: v3.AttributeKeyDataTypeString,
Type: v3.AttributeKeyTypeTag,
}},
Expression: "A",
Disabled: false,
TimeAggregation: v3.TimeAggregationRate,
SpaceAggregation: v3.SpaceAggregationSum,
},
expectedQueryContains: "SELECT service_name, toStartOfInterval(toDateTime(intDiv(timestamp_ms, 1000)), INTERVAL 60 SECOND) as ts, sum(value)/60 as value FROM signoz_metrics.distributed_samples_v2 INNER JOIN (SELECT DISTINCT JSONExtractString(labels, 'service_name') as service_name, fingerprint FROM signoz_metrics.time_series_v2 WHERE metric_name = 'signoz_calls_total' AND temporality = 'Delta') as filtered_time_series USING fingerprint WHERE metric_name = 'signoz_calls_total' AND timestamp_ms >= 1650991920000 AND timestamp_ms <= 1651078380000 GROUP BY GROUPING SETS ( (service_name, ts), (service_name) ) ORDER BY service_name ASC, ts ASC",
},
}
for _, testCase := range testCases {
t.Run(testCase.name, func(t *testing.T) {
query, err := PrepareMetricQuery(1650991982000, 1651078382000, v3.QueryTypeBuilder, v3.PanelTypeGraph, testCase.builderQuery, metricsV3.Options{})
assert.Nil(t, err)
assert.Contains(t, query, testCase.expectedQueryContains)
})
}
}
func TestPrepreMetricQueryCumulativeQuantile(t *testing.T) {
testCases := []struct {
name string
builderQuery *v3.BuilderQuery
expectedQueryContains string
}{
{
name: "test temporality = cumulative, quantile = 0.99",
builderQuery: &v3.BuilderQuery{
QueryName: "A",
StepInterval: 60,
DataSource: v3.DataSourceMetrics,
AggregateAttribute: v3.AttributeKey{
Key: "signoz_latency_bucket",
},
Temporality: v3.Cumulative,
Filters: &v3.FilterSet{
Operator: "AND",
Items: []v3.FilterItem{
{
Key: v3.AttributeKey{
Key: "service_name",
Type: v3.AttributeKeyTypeTag,
DataType: v3.AttributeKeyDataTypeString,
},
Operator: v3.FilterOperatorContains,
Value: "frontend",
},
},
},
GroupBy: []v3.AttributeKey{{
Key: "service_name",
DataType: v3.AttributeKeyDataTypeString,
Type: v3.AttributeKeyTypeTag,
}},
chore: support p9{9,5,0},75,50 for space aggregation (#4382)
2024-01-26 17:07:23 +05:30
Expression: "A",
Disabled: false,
SpaceAggregation: v3.SpaceAggregationPercentile99,
chore: add /v4/query_range endpoint (#4361)
2024-01-16 16:56:20 +05:30
},
expectedQueryContains: "SELECT service_name, ts, histogramQuantile(arrayMap(x -> toFloat64(x), groupArray(le)), groupArray(value), 0.990) as value FROM (SELECT service_name, le, ts, sum(per_series_value) as value FROM (SELECT service_name, le, ts, If((per_series_value - lagInFrame(per_series_value, 1, 0) OVER rate_window) < 0, nan, If((ts - lagInFrame(ts, 1, toDate('1970-01-01')) OVER rate_window) >= 86400, nan, (per_series_value - lagInFrame(per_series_value, 1, 0) OVER rate_window) / (ts - lagInFrame(ts, 1, toDate('1970-01-01')) OVER rate_window))) as per_series_value FROM (SELECT fingerprint, any(service_name) as service_name, any(le) as le, toStartOfInterval(toDateTime(intDiv(timestamp_ms, 1000)), INTERVAL 60 SECOND) as ts, max(value) as per_series_value FROM signoz_metrics.distributed_samples_v2 INNER JOIN (SELECT DISTINCT JSONExtractString(labels, 'service_name') as service_name, JSONExtractString(labels, 'le') as le, fingerprint FROM signoz_metrics.time_series_v2 WHERE metric_name = 'signoz_latency_bucket' AND temporality = 'Cumulative' AND like(JSONExtractString(labels, 'service_name'), '%frontend%')) as filtered_time_series USING fingerprint WHERE metric_name = 'signoz_latency_bucket' AND timestamp_ms >= 1650991980000 AND timestamp_ms <= 1651078380000 GROUP BY fingerprint, ts ORDER BY fingerprint, ts) WINDOW rate_window as (PARTITION BY fingerprint ORDER BY fingerprint, ts)) WHERE isNaN(per_series_value) = 0 GROUP BY GROUPING SETS ( (service_name, le, ts), (service_name, le) ) ORDER BY service_name ASC, le ASC, ts ASC) GROUP BY service_name, ts ORDER BY service_name ASC, ts ASC",
},
{
name: "test temporality = cumulative, quantile = 0.99 without group by",
builderQuery: &v3.BuilderQuery{
QueryName: "A",
StepInterval: 60,
DataSource: v3.DataSourceMetrics,
AggregateAttribute: v3.AttributeKey{
Key: "signoz_latency_bucket",
},
Temporality: v3.Cumulative,
Filters: &v3.FilterSet{
Operator: "AND",
Items: []v3.FilterItem{
{
Key: v3.AttributeKey{
Key: "service_name",
Type: v3.AttributeKeyTypeTag,
DataType: v3.AttributeKeyDataTypeString,
},
Operator: v3.FilterOperatorContains,
Value: "frontend",
},
},
},
chore: support p9{9,5,0},75,50 for space aggregation (#4382)
2024-01-26 17:07:23 +05:30
Expression: "A",
Disabled: false,
SpaceAggregation: v3.SpaceAggregationPercentile99,
chore: add /v4/query_range endpoint (#4361)
2024-01-16 16:56:20 +05:30
},
expectedQueryContains: "SELECT ts, histogramQuantile(arrayMap(x -> toFloat64(x), groupArray(le)), groupArray(value), 0.990) as value FROM (SELECT le, ts, sum(per_series_value) as value FROM (SELECT le, ts, If((per_series_value - lagInFrame(per_series_value, 1, 0) OVER rate_window) < 0, nan, If((ts - lagInFrame(ts, 1, toDate('1970-01-01')) OVER rate_window) >= 86400, nan, (per_series_value - lagInFrame(per_series_value, 1, 0) OVER rate_window) / (ts - lagInFrame(ts, 1, toDate('1970-01-01')) OVER rate_window))) as per_series_value FROM (SELECT fingerprint, any(le) as le, toStartOfInterval(toDateTime(intDiv(timestamp_ms, 1000)), INTERVAL 60 SECOND) as ts, max(value) as per_series_value FROM signoz_metrics.distributed_samples_v2 INNER JOIN (SELECT DISTINCT JSONExtractString(labels, 'le') as le, fingerprint FROM signoz_metrics.time_series_v2 WHERE metric_name = 'signoz_latency_bucket' AND temporality = 'Cumulative' AND like(JSONExtractString(labels, 'service_name'), '%frontend%')) as filtered_time_series USING fingerprint WHERE metric_name = 'signoz_latency_bucket' AND timestamp_ms >= 1650991980000 AND timestamp_ms <= 1651078380000 GROUP BY fingerprint, ts ORDER BY fingerprint, ts) WINDOW rate_window as (PARTITION BY fingerprint ORDER BY fingerprint, ts)) WHERE isNaN(per_series_value) = 0 GROUP BY GROUPING SETS ( (le, ts), (le) ) ORDER BY le ASC, ts ASC) GROUP BY ts ORDER BY ts ASC",
},
}
for _, testCase := range testCases {
t.Run(testCase.name, func(t *testing.T) {
query, err := PrepareMetricQuery(1650991982000, 1651078382000, v3.QueryTypeBuilder, v3.PanelTypeGraph, testCase.builderQuery, metricsV3.Options{})
assert.Nil(t, err)
assert.Contains(t, query, testCase.expectedQueryContains)
})
}
}
func TestPrepreMetricQueryDeltaQuantile(t *testing.T) {
testCases := []struct {
name string
builderQuery *v3.BuilderQuery
expectedQueryContains string
}{
{
name: "test temporality = delta, quantile = 0.99 group by service_name",
builderQuery: &v3.BuilderQuery{
QueryName: "A",
StepInterval: 60,
DataSource: v3.DataSourceMetrics,
AggregateAttribute: v3.AttributeKey{
Key: "signoz_latency_bucket",
},
Temporality: v3.Delta,
Filters: &v3.FilterSet{
Operator: "AND",
Items: []v3.FilterItem{
{
Key: v3.AttributeKey{
Key: "service_name",
Type: v3.AttributeKeyTypeTag,
DataType: v3.AttributeKeyDataTypeString,
},
Operator: v3.FilterOperatorContains,
Value: "frontend",
},
},
},
GroupBy: []v3.AttributeKey{{
Key: "service_name",
DataType: v3.AttributeKeyDataTypeString,
Type: v3.AttributeKeyTypeTag,
}},
chore: support p9{9,5,0},75,50 for space aggregation (#4382)
2024-01-26 17:07:23 +05:30
Expression: "A",
Disabled: false,
SpaceAggregation: v3.SpaceAggregationPercentile99,
chore: add /v4/query_range endpoint (#4361)
2024-01-16 16:56:20 +05:30
},
expectedQueryContains: "SELECT service_name, ts, histogramQuantile(arrayMap(x -> toFloat64(x), groupArray(le)), groupArray(value), 0.990) as value FROM (SELECT service_name, le, toStartOfInterval(toDateTime(intDiv(timestamp_ms, 1000)), INTERVAL 60 SECOND) as ts, sum(value)/60 as value FROM signoz_metrics.distributed_samples_v2 INNER JOIN (SELECT DISTINCT JSONExtractString(labels, 'service_name') as service_name, JSONExtractString(labels, 'le') as le, fingerprint FROM signoz_metrics.time_series_v2 WHERE metric_name = 'signoz_latency_bucket' AND temporality = 'Delta' AND like(JSONExtractString(labels, 'service_name'), '%frontend%')) as filtered_time_series USING fingerprint WHERE metric_name = 'signoz_latency_bucket' AND timestamp_ms >= 1650991980000 AND timestamp_ms <= 1651078380000 GROUP BY GROUPING SETS ( (service_name, le, ts), (service_name, le) ) ORDER BY service_name ASC, le ASC, ts ASC) GROUP BY service_name, ts ORDER BY service_name ASC, ts ASC",
},
{
name: "test temporality = delta, quantile = 0.99 no group by",
builderQuery: &v3.BuilderQuery{
QueryName: "A",
StepInterval: 60,
DataSource: v3.DataSourceMetrics,
AggregateAttribute: v3.AttributeKey{
Key: "signoz_latency_bucket",
},
Temporality: v3.Delta,
Filters: &v3.FilterSet{
Operator: "AND",
Items: []v3.FilterItem{
{
Key: v3.AttributeKey{
Key: "service_name",
Type: v3.AttributeKeyTypeTag,
DataType: v3.AttributeKeyDataTypeString,
},
Operator: v3.FilterOperatorContains,
Value: "frontend",
},
},
},
chore: support p9{9,5,0},75,50 for space aggregation (#4382)
2024-01-26 17:07:23 +05:30
Expression: "A",
Disabled: false,
SpaceAggregation: v3.SpaceAggregationPercentile99,
chore: add /v4/query_range endpoint (#4361)
2024-01-16 16:56:20 +05:30
},
expectedQueryContains: "SELECT ts, histogramQuantile(arrayMap(x -> toFloat64(x), groupArray(le)), groupArray(value), 0.990) as value FROM (SELECT le, toStartOfInterval(toDateTime(intDiv(timestamp_ms, 1000)), INTERVAL 60 SECOND) as ts, sum(value)/60 as value FROM signoz_metrics.distributed_samples_v2 INNER JOIN (SELECT DISTINCT JSONExtractString(labels, 'le') as le, fingerprint FROM signoz_metrics.time_series_v2 WHERE metric_name = 'signoz_latency_bucket' AND temporality = 'Delta' AND like(JSONExtractString(labels, 'service_name'), '%frontend%')) as filtered_time_series USING fingerprint WHERE metric_name = 'signoz_latency_bucket' AND timestamp_ms >= 1650991980000 AND timestamp_ms <= 1651078380000 GROUP BY GROUPING SETS ( (le, ts), (le) ) ORDER BY le ASC, ts ASC) GROUP BY ts ORDER BY ts ASC",
},
}
for _, testCase := range testCases {
t.Run(testCase.name, func(t *testing.T) {
query, err := PrepareMetricQuery(1650991982000, 1651078382000, v3.QueryTypeBuilder, v3.PanelTypeGraph, testCase.builderQuery, metricsV3.Options{})
assert.Nil(t, err)
assert.Contains(t, query, testCase.expectedQueryContains)
})
}
}
func TestPrepareMetricQueryGauge(t *testing.T) {
testCases := []struct {
name string
builderQuery *v3.BuilderQuery
expectedQueryContains string
}{
{
name: "test gauge query with no group by",
builderQuery: &v3.BuilderQuery{
QueryName: "A",
StepInterval: 60,
DataSource: v3.DataSourceMetrics,
AggregateAttribute: v3.AttributeKey{
Key: "system_cpu_usage",
},
Temporality: v3.Unspecified,
Filters: &v3.FilterSet{
Operator: "AND",
Items: []v3.FilterItem{},
},
Expression: "A",
TimeAggregation: v3.TimeAggregationAvg,
SpaceAggregation: v3.SpaceAggregationSum,
Disabled: false,
},
expectedQueryContains: "SELECT ts, sum(per_series_value) as value FROM (SELECT fingerprint, toStartOfInterval(toDateTime(intDiv(timestamp_ms, 1000)), INTERVAL 60 SECOND) as ts, avg(value) as per_series_value FROM signoz_metrics.distributed_samples_v2 INNER JOIN (SELECT DISTINCT fingerprint FROM signoz_metrics.time_series_v2 WHERE metric_name = 'system_cpu_usage' AND temporality = 'Unspecified') as filtered_time_series USING fingerprint WHERE metric_name = 'system_cpu_usage' AND timestamp_ms >= 1650991980000 AND timestamp_ms <= 1651078380000 GROUP BY fingerprint, ts ORDER BY fingerprint, ts) WHERE isNaN(per_series_value) = 0 GROUP BY ts ORDER BY ts ASC",
},
{
name: "test gauge query with group by host_name",
builderQuery: &v3.BuilderQuery{
QueryName: "A",
StepInterval: 60,
DataSource: v3.DataSourceMetrics,
AggregateAttribute: v3.AttributeKey{
Key: "system_cpu_usage",
},
Temporality: v3.Unspecified,
Filters: &v3.FilterSet{
Operator: "AND",
Items: []v3.FilterItem{},
},
GroupBy: []v3.AttributeKey{{
Key: "host_name",
DataType: v3.AttributeKeyDataTypeString,
Type: v3.AttributeKeyTypeTag,
}},
TimeAggregation: v3.TimeAggregationAvg,
SpaceAggregation: v3.SpaceAggregationSum,
Expression: "A",
Disabled: false,
},
expectedQueryContains: "SELECT host_name, ts, sum(per_series_value) as value FROM (SELECT fingerprint, any(host_name) as host_name, toStartOfInterval(toDateTime(intDiv(timestamp_ms, 1000)), INTERVAL 60 SECOND) as ts, avg(value) as per_series_value FROM signoz_metrics.distributed_samples_v2 INNER JOIN (SELECT DISTINCT JSONExtractString(labels, 'host_name') as host_name, fingerprint FROM signoz_metrics.time_series_v2 WHERE metric_name = 'system_cpu_usage' AND temporality = 'Unspecified') as filtered_time_series USING fingerprint WHERE metric_name = 'system_cpu_usage' AND timestamp_ms >= 1650991980000 AND timestamp_ms <= 1651078380000 GROUP BY fingerprint, ts ORDER BY fingerprint, ts) WHERE isNaN(per_series_value) = 0 GROUP BY GROUPING SETS ( (host_name, ts), (host_name) ) ORDER BY host_name ASC, ts ASC",
},
}
for _, testCase := range testCases {
t.Run(testCase.name, func(t *testing.T) {
query, err := PrepareMetricQuery(1650991982000, 1651078382000, v3.QueryTypeBuilder, v3.PanelTypeGraph, testCase.builderQuery, metricsV3.Options{})
chore: update BuilderQuery struct and add PrepareTimeseriesFilterQuery (#4165)
2023-12-12 07:24:33 +05:30
assert.Nil(t, err)
assert.Contains(t, query, testCase.expectedQueryContains)
})
}
}
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