@@ -446,6 +446,36 @@ describe('renderChartConfig', () => {
446446 AggregationTemporality : 2 , // Cumulative
447447 ...point ,
448448 } ) ) ;
449+ const histPointsE = [
450+ {
451+ BucketCounts : [ 1 , 1 , 1 , 1 , 1 , 1 ] ,
452+ ExplicitBounds : [ 1 , 2 , 5 , 8 , 13 ] ,
453+ TimeUnix : new Date ( now ) ,
454+ ResourceAttributes : { host : 'test-a' } ,
455+ } ,
456+ {
457+ BucketCounts : [ 2 , 2 , 2 , 2 , 2 , 2 ] ,
458+ ExplicitBounds : [ 1 , 2 , 5 , 8 , 13 ] ,
459+ TimeUnix : new Date ( now + ms ( '5s' ) ) ,
460+ ResourceAttributes : { host : 'test-b' } ,
461+ } ,
462+ {
463+ BucketCounts : [ 2 , 1 , 2 , 1 , 2 , 1 ] ,
464+ ExplicitBounds : [ 1 , 2 , 5 , 8 , 13 ] ,
465+ TimeUnix : new Date ( now + ms ( '1m' ) ) ,
466+ ResourceAttributes : { host : 'test-a' } ,
467+ } ,
468+ {
469+ BucketCounts : [ 3 , 3 , 2 , 2 , 3 , 3 ] ,
470+ ExplicitBounds : [ 1 , 2 , 5 , 8 , 13 ] ,
471+ TimeUnix : new Date ( now + ms ( '65s' ) ) ,
472+ ResourceAttributes : { host : 'test-b' } ,
473+ } ,
474+ ] . map ( point => ( {
475+ MetricName : 'test.multiple_series' ,
476+ AggregationTemporality : 2 , // Cumulative
477+ ...point ,
478+ } ) ) ;
449479
450480 await Promise . all ( [
451481 bulkInsertMetricsGauge ( [ ...gaugePointsA , ...gaugePointsB ] ) ,
@@ -462,6 +492,7 @@ describe('renderChartConfig', () => {
462492 ...histPointsB ,
463493 ...histPointsC ,
464494 ...histPointsD ,
495+ ...histPointsE ,
465496 ] ) ,
466497 ] ) ;
467498 } ) ;
@@ -655,6 +686,10 @@ describe('renderChartConfig', () => {
655686 } ) ;
656687
657688 it ( 'calculates min_rate/max_rate correctly for sum metrics' , async ( ) => {
689+ // Raw Data is
690+ // MIN_VARIANT_0: [0, 1, 8, 0, 7, 7, 15, 17, 0, 42]
691+ // MIN_VARIANT_1: [0, 2, 9, 0, 15, 25 35, 57, 0, 92]
692+ //
658693 // Based on the data inserted in the fixture, the expected stream of values
659694 // for each series after adjusting for the zero reset should be:
660695 // MIN_VARIANT_0: [0, 1, 8, 8, 15, 15, 23, 25, 25, 67]
@@ -725,20 +760,10 @@ describe('renderChartConfig', () => {
725760 Since the AggregationTemporality is 2(cumulative), we need to calculate the delta between the two points:
726761 delta: [10, 10, 10] - [0, 0, 0] = [10, 10, 10]
727762
728- Total observations: 10 + 10 + 10 = 30
729- Cumulative counts: [10, 20, 30]
730- p50 point:
731- Rank = 0.5 * 30 = 15
732- This falls in the second bucket (since 10 < 15 ≤ 20)
733-
734763 We need to interpolate between the lower and upper bounds of the second bucket:
735- Lower bound: 10
736- Upper bound: 30
737- Position in bucket: (15 - 10) / (20 - 10) = 0.5
738- Interpolated value: 10 + (30 - 10) * 0.5 = 10 + 10 = 20
739-
740- Thus the first point value would be 0 since it's at the start of the bounds.
741- The second point value would be 20 since that is the median point value delta from the first point.
764+ cum sum = [10, 20, 30]
765+ rank = 0.5 * 30 = 15 (between bounds 10 - 30)
766+ interpolate: 10 + ((15 - 10) / 30) * (30 - 10) = 13.3333
742767 */
743768 const query = await renderChartConfig (
744769 {
@@ -952,6 +977,57 @@ describe('renderChartConfig', () => {
952977 expect ( res ) . toMatchSnapshot ( ) ;
953978 } ) ;
954979
980+ it ( 'should include multiple data points in percentile computation (p50)' , async ( ) => {
981+ /*
982+ bounds: [1, 2, 5, 8, 13]
983+ host = test-a:
984+ p1 = [1, 1, 1, 1, 1, 1]
985+ p2 = [2, 1, 2, 1, 2, 1]
986+ host = test-b:
987+ p1 = [2, 2, 2, 2, 2, 2]
988+ p2 = [3, 3, 2, 2, 3, 3]
989+
990+ Compute the diff between adjacent points for each unique host (deltaSumForEach)
991+ host = test-a, diff = [1, 0, 1, 0, 1, 0]
992+ host = test-b, diff = [1, 1, 0, 0, 1, 1]
993+
994+ Sum the diffs together to obtain a combined count for the different series
995+ sum elements(d) = [2, 1, 1, 0, 2, 1]
996+
997+ Now compute the p50 value:
998+ sum(d) = 7
999+ cum sum = [2, 3, 4, 4, 6, 7]
1000+ rank = 0.5 * 7 = 3.5 (between bounds 2 - 5)
1001+ interpolate: 2 + ((3.5 - 2) / 5) * (5 - 2) = 2.9
1002+
1003+ Since all the points fall within a single granularity interval the result should be a single row
1004+ with the value 2.9.
1005+ */
1006+ const query = await renderChartConfig (
1007+ {
1008+ select : [
1009+ {
1010+ aggFn : 'quantile' ,
1011+ level : 0.5 ,
1012+ metricName : 'test.multiple_series' ,
1013+ metricType : MetricsDataType . Histogram ,
1014+ valueExpression : 'Value' ,
1015+ } ,
1016+ ] ,
1017+ from : metricSource . from ,
1018+ where : '' ,
1019+ metricTables : TEST_METRIC_TABLES ,
1020+ dateRange : [ new Date ( now ) , new Date ( now + ms ( '2m' ) ) ] ,
1021+ granularity : '5 minute' ,
1022+ timestampValueExpression : metricSource . timestampValueExpression ,
1023+ connection : connection . id ,
1024+ } ,
1025+ metadata ,
1026+ ) ;
1027+ const res = await queryData ( query ) ;
1028+ expect ( res ) . toMatchSnapshot ( ) ;
1029+ } ) ;
1030+
9551031 // HDX-1515: Handle counter reset in histogram metric in the same way that the counter reset
9561032 // is handled for sum metrics.
9571033 it . skip ( 'three_timestamps_bounded histogram with reset (p50)' , async ( ) => {
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