logs-analyzer/signoz/pkg/query-service/app/metrics/v4/cumulative/table_test.go

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2024-09-02 22:47:30 +03:00
package cumulative
import (
"testing"
"github.com/stretchr/testify/assert"
v3 "go.signoz.io/signoz/pkg/query-service/model/v3"
)
func TestPrepareTableQuery(t *testing.T) {
testCases := []struct {
name string
builderQuery *v3.BuilderQuery
start int64
end int64
expectedQueryContains string
}{
{
name: "test time aggregation = avg, space aggregation = sum, temporality = unspecified",
builderQuery: &v3.BuilderQuery{
QueryName: "A",
StepInterval: 60,
DataSource: v3.DataSourceMetrics,
AggregateAttribute: v3.AttributeKey{
Key: "system_memory_usage",
DataType: v3.AttributeKeyDataTypeFloat64,
Type: v3.AttributeKeyTypeUnspecified,
IsColumn: true,
IsJSON: false,
},
Temporality: v3.Unspecified,
Filters: &v3.FilterSet{
Operator: "AND",
Items: []v3.FilterItem{
{
Key: v3.AttributeKey{
Key: "state",
Type: v3.AttributeKeyTypeTag,
DataType: v3.AttributeKeyDataTypeString,
},
Operator: v3.FilterOperatorNotEqual,
Value: "idle",
},
},
},
GroupBy: []v3.AttributeKey{},
Expression: "A",
Disabled: false,
TimeAggregation: v3.TimeAggregationAvg,
SpaceAggregation: v3.SpaceAggregationSum,
},
start: 1701794980000,
end: 1701796780000,
expectedQueryContains: "SELECT ts, sum(per_series_value) as value FROM (SELECT fingerprint, toStartOfInterval(toDateTime(intDiv(unix_milli, 1000)), INTERVAL 60 SECOND) as ts, avg(value) as per_series_value FROM signoz_metrics.distributed_samples_v4 INNER JOIN (SELECT DISTINCT fingerprint FROM signoz_metrics.time_series_v4 WHERE metric_name = 'system_memory_usage' AND temporality = 'Unspecified' AND unix_milli >= 1701792000000 AND unix_milli < 1701796780000 AND JSONExtractString(labels, 'state') != 'idle') as filtered_time_series USING fingerprint WHERE metric_name = 'system_memory_usage' AND unix_milli >= 1701794980000 AND unix_milli < 1701796780000 GROUP BY fingerprint, ts ORDER BY fingerprint, ts) WHERE isNaN(per_series_value) = 0 GROUP BY ts ORDER BY ts ASC",
},
{
name: "test time aggregation = rate, space aggregation = sum, temporality = cumulative",
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.FilterOperatorContains,
Value: "payment_service",
},
},
},
GroupBy: []v3.AttributeKey{{
Key: "service_name",
DataType: v3.AttributeKeyDataTypeString,
Type: v3.AttributeKeyTypeTag,
}},
Expression: "A",
Disabled: false,
TimeAggregation: v3.TimeAggregationRate,
SpaceAggregation: v3.SpaceAggregationSum,
},
start: 1701794980000,
end: 1701796780000,
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(unix_milli, 1000)), INTERVAL 60 SECOND) as ts, max(value) as per_series_value FROM signoz_metrics.distributed_samples_v4 INNER JOIN (SELECT DISTINCT JSONExtractString(labels, 'service_name') as service_name, fingerprint FROM signoz_metrics.time_series_v4 WHERE metric_name = 'http_requests' AND temporality = 'Cumulative' AND unix_milli >= 1701792000000 AND unix_milli < 1701796780000 AND like(JSONExtractString(labels, 'service_name'), '%payment_service%')) as filtered_time_series USING fingerprint WHERE metric_name = 'http_requests' AND unix_milli >= 1701794980000 AND unix_milli < 1701796780000 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 service_name, ts ORDER BY service_name ASC, ts ASC",
},
}
for _, testCase := range testCases {
t.Run(testCase.name, func(t *testing.T) {
query, err := PrepareMetricQueryCumulativeTable(
testCase.start,
testCase.end,
testCase.builderQuery.StepInterval,
testCase.builderQuery,
)
assert.Nil(t, err)
assert.Contains(t, query, testCase.expectedQueryContains)
})
}
}