(timeseries, datapoints int)
| 115 | } |
| 116 | |
| 117 | func generateData(timeseries, datapoints int) (floatMatrix, histogramMatrix []*SampleStream) { |
| 118 | for i := range timeseries { |
| 119 | lset := labels.FromMap(map[string]string{ |
| 120 | model.MetricNameLabel: "timeseries_" + strconv.Itoa(i), |
| 121 | "foo": "bar", |
| 122 | }) |
| 123 | now := model.Time(1677587274055).Time() |
| 124 | floats := make([]cortexpb.Sample, datapoints) |
| 125 | histograms := make([]SampleHistogramPair, datapoints) |
| 126 | |
| 127 | for x := datapoints; x > 0; x-- { |
| 128 | f := float64(x) |
| 129 | floats[x-1] = cortexpb.Sample{ |
| 130 | // Set the time back assuming a 15s interval. Since this is used for |
| 131 | // Marshal/Unmarshal testing the actual interval doesn't matter. |
| 132 | TimestampMs: util.TimeToMillis(now.Add(time.Second * -15 * time.Duration(x))), |
| 133 | Value: f, |
| 134 | } |
| 135 | histograms[x-1] = SampleHistogramPair{ |
| 136 | TimestampMs: util.TimeToMillis(now.Add(time.Second * -15 * time.Duration(x))), |
| 137 | Histogram: SampleHistogram{ |
| 138 | Count: 13.5 * f, |
| 139 | Sum: .1 * f, |
| 140 | Buckets: []*HistogramBucket{ |
| 141 | { |
| 142 | Boundaries: 1, |
| 143 | Lower: -4870.992343051145, |
| 144 | Upper: -4466.7196729968955, |
| 145 | Count: 1 * f, |
| 146 | }, |
| 147 | { |
| 148 | Boundaries: 1, |
| 149 | Lower: -861.0779292198035, |
| 150 | Upper: -789.6119426088657, |
| 151 | Count: 2 * f, |
| 152 | }, |
| 153 | { |
| 154 | Boundaries: 1, |
| 155 | Lower: -558.3399591246119, |
| 156 | Upper: -512, |
| 157 | Count: 3 * f, |
| 158 | }, |
| 159 | { |
| 160 | Boundaries: 0, |
| 161 | Lower: 2048, |
| 162 | Upper: 2233.3598364984477, |
| 163 | Count: 1.5 * f, |
| 164 | }, |
| 165 | { |
| 166 | Boundaries: 0, |
| 167 | Lower: 2896.3093757400984, |
| 168 | Upper: 3158.4477704354626, |
| 169 | Count: 2.5 * f, |
| 170 | }, |
| 171 | { |
| 172 | Boundaries: 0, |
| 173 | Lower: 4466.7196729968955, |
| 174 | Upper: 4870.992343051145, |
no test coverage detected