func (c varbitChunk) firstTimeDelta() model.Time {
// Only the first 3 bytes are actually the timestamp, so get rid of the
// last one by bitshifting.
return model.Time(c[varbitFirstTimeDeltaOffset+2]) |
model.Time(c[varbitFirstTimeDeltaOffset+1])<<8 |
model.Time(c[varbitFirstTimeDeltaOffset])<<16
}
// UnmarshalBinary implements encoding.BinaryUnmarshaler.
func (tr *TimeRange) UnmarshalBinary(buf []byte) error {
r := bytes.NewReader(buf)
first, err := binary.ReadVarint(r)
if err != nil {
return err
}
last, err := binary.ReadVarint(r)
if err != nil {
return err
}
tr.First = model.Time(first)
tr.Last = model.Time(last)
return nil
}
func (c doubleDeltaEncodedChunk) baseTime() model.Time {
return model.Time(
binary.LittleEndian.Uint64(
c[doubleDeltaHeaderBaseTimeOffset:],
),
)
}
func benchmarkRangeValues(b *testing.B, encoding chunkEncoding) {
samples := make(model.Samples, 10000)
for i := range samples {
samples[i] = &model.Sample{
Timestamp: model.Time(2 * i),
Value: model.SampleValue(float64(i) * 0.2),
}
}
s, closer := NewTestStorage(b, encoding)
defer closer.Close()
for _, sample := range samples {
s.Append(sample)
}
s.WaitForIndexing()
fp := model.Metric{}.FastFingerprint()
_, it := s.preloadChunksForRange(fp, model.Earliest, model.Latest)
b.ResetTimer()
for i := 0; i < b.N; i++ {
for _, sample := range samples {
actual := it.RangeValues(metric.Interval{
OldestInclusive: sample.Timestamp - 20,
NewestInclusive: sample.Timestamp + 20,
})
if len(actual) < 10 {
b.Fatalf("not enough samples found")
}
}
}
}
func buildTestChunks(t *testing.T, encoding chunk.Encoding) map[model.Fingerprint][]chunk.Chunk {
fps := model.Fingerprints{
m1.FastFingerprint(),
m2.FastFingerprint(),
m3.FastFingerprint(),
}
fpToChunks := map[model.Fingerprint][]chunk.Chunk{}
for _, fp := range fps {
fpToChunks[fp] = make([]chunk.Chunk, 0, 10)
for i := 0; i < 10; i++ {
ch, err := chunk.NewForEncoding(encoding)
if err != nil {
t.Fatal(err)
}
chs, err := ch.Add(model.SamplePair{
Timestamp: model.Time(i),
Value: model.SampleValue(fp),
})
if err != nil {
t.Fatal(err)
}
fpToChunks[fp] = append(fpToChunks[fp], chs[0])
}
}
return fpToChunks
}
func TestToReader(t *testing.T) {
cntVec := prometheus.NewCounterVec(
prometheus.CounterOpts{
Name: "name",
Help: "docstring",
ConstLabels: prometheus.Labels{"constname": "constvalue"},
},
[]string{"labelname"},
)
cntVec.WithLabelValues("val1").Inc()
cntVec.WithLabelValues("val2").Inc()
reg := prometheus.NewRegistry()
reg.MustRegister(cntVec)
want := `prefix.name.constname.constvalue.labelname.val1 1 1477043
prefix.name.constname.constvalue.labelname.val2 1 1477043
`
mfs, err := reg.Gather()
if err != nil {
t.Fatalf("error: %v", err)
}
now := model.Time(1477043083)
var buf bytes.Buffer
err = writeMetrics(&buf, mfs, "prefix", now)
if err != nil {
t.Fatalf("error: %v", err)
}
if got := buf.String(); want != got {
t.Fatalf("wanted \n%s\n, got \n%s\n", want, got)
}
}
func (c varbitChunk) lastTime() model.Time {
return model.Time(
binary.BigEndian.Uint64(
c[varbitLastTimeOffset:],
),
)
}
func TestSampleDeliveryOrder(t *testing.T) {
cfg := defaultConfig
ts := 10
n := cfg.MaxSamplesPerSend * ts
// Ensure we don't drop samples in this test.
cfg.QueueCapacity = n
samples := make(model.Samples, 0, n)
for i := 0; i < n; i++ {
name := model.LabelValue(fmt.Sprintf("test_metric_%d", i%ts))
samples = append(samples, &model.Sample{
Metric: model.Metric{
model.MetricNameLabel: name,
},
Value: model.SampleValue(i),
Timestamp: model.Time(i),
})
}
c := NewTestStorageClient()
c.expectSamples(samples)
m := NewStorageQueueManager(c, &cfg)
// These should be received by the client.
for _, s := range samples {
m.Append(s)
}
go m.Run()
defer m.Stop()
c.waitForExpectedSamples(t)
}
// timestampAtIndex implements chunkIterator.
func (it *deltaEncodedChunkIterator) timestampAtIndex(idx int) model.Time {
offset := deltaHeaderBytes + idx*int(it.tBytes+it.vBytes)
switch it.tBytes {
case d1:
return it.baseT + model.Time(uint8(it.c[offset]))
case d2:
return it.baseT + model.Time(binary.LittleEndian.Uint16(it.c[offset:]))
case d4:
return it.baseT + model.Time(binary.LittleEndian.Uint32(it.c[offset:]))
case d8:
// Take absolute value for d8.
return model.Time(binary.LittleEndian.Uint64(it.c[offset:]))
default:
panic("invalid number of bytes for time delta")
}
}
// timestampAtIndex implements chunkIterator.
func (it *doubleDeltaEncodedChunkIterator) timestampAtIndex(idx int) model.Time {
if idx == 0 {
return it.baseT
}
if idx == 1 {
// If time bytes are at d8, the time is saved directly rather
// than as a difference.
if it.tBytes == d8 {
return it.baseΔT
}
return it.baseT + it.baseΔT
}
offset := doubleDeltaHeaderBytes + (idx-2)*int(it.tBytes+it.vBytes)
switch it.tBytes {
case d1:
return it.baseT +
model.Time(idx)*it.baseΔT +
model.Time(int8(it.c[offset]))
case d2:
return it.baseT +
model.Time(idx)*it.baseΔT +
model.Time(int16(binary.LittleEndian.Uint16(it.c[offset:])))
case d4:
return it.baseT +
model.Time(idx)*it.baseΔT +
model.Time(int32(binary.LittleEndian.Uint32(it.c[offset:])))
case d8:
// Take absolute value for d8.
return model.Time(binary.LittleEndian.Uint64(it.c[offset:]))
default:
panic("invalid number of bytes for time delta")
}
}
func (acc *deltaEncodedIndexAccessor) timestampAtIndex(idx int) model.Time {
offset := deltaHeaderBytes + idx*int(acc.tBytes+acc.vBytes)
switch acc.tBytes {
case d1:
return acc.baseT + model.Time(uint8(acc.c[offset]))
case d2:
return acc.baseT + model.Time(binary.LittleEndian.Uint16(acc.c[offset:]))
case d4:
return acc.baseT + model.Time(binary.LittleEndian.Uint32(acc.c[offset:]))
case d8:
// Take absolute value for d8.
return model.Time(binary.LittleEndian.Uint64(acc.c[offset:]))
default:
acc.lastErr = fmt.Errorf("invalid number of bytes for time delta: %d", acc.tBytes)
return model.Earliest
}
}
// loadChunkDescs loads the chunkDescs for a series from disk. offsetFromEnd is
// the number of chunkDescs to skip from the end of the series file. It is the
// caller's responsibility to not persist or drop anything for the same
// fingerprint concurrently.
func (p *persistence) loadChunkDescs(fp model.Fingerprint, offsetFromEnd int) ([]*chunkDesc, error) {
f, err := p.openChunkFileForReading(fp)
if os.IsNotExist(err) {
return nil, nil
}
if err != nil {
return nil, err
}
defer f.Close()
fi, err := f.Stat()
if err != nil {
return nil, err
}
if fi.Size()%int64(chunkLenWithHeader) != 0 {
// The returned error will bubble up and lead to quarantining of the whole series.
return nil, fmt.Errorf(
"size of series file for fingerprint %v is %d, which is not a multiple of the chunk length %d",
fp, fi.Size(), chunkLenWithHeader,
)
}
numChunks := int(fi.Size())/chunkLenWithHeader - offsetFromEnd
cds := make([]*chunkDesc, numChunks)
chunkTimesBuf := make([]byte, 16)
for i := 0; i < numChunks; i++ {
_, err := f.Seek(offsetForChunkIndex(i)+chunkHeaderFirstTimeOffset, os.SEEK_SET)
if err != nil {
return nil, err
}
_, err = io.ReadAtLeast(f, chunkTimesBuf, 16)
if err != nil {
return nil, err
}
cds[i] = &chunkDesc{
chunkFirstTime: model.Time(binary.LittleEndian.Uint64(chunkTimesBuf)),
chunkLastTime: model.Time(binary.LittleEndian.Uint64(chunkTimesBuf[8:])),
}
}
chunkDescOps.WithLabelValues(load).Add(float64(len(cds)))
numMemChunkDescs.Add(float64(len(cds)))
return cds, nil
}
func (c doubleDeltaEncodedChunk) baseTimeDelta() model.Time {
if len(c) < doubleDeltaHeaderBaseTimeDeltaOffset+8 {
return 0
}
return model.Time(
binary.LittleEndian.Uint64(
c[doubleDeltaHeaderBaseTimeDeltaOffset:],
),
)
}
func (it *varbitChunkIterator) readDDT() {
if it.repeats > 0 {
it.repeats--
} else {
switch it.readControlBits(3) {
case 0:
it.repeats = byte(it.readBitPattern(7))
case 1:
it.dT += model.Time(it.readSignedInt(6))
case 2:
it.dT += model.Time(it.readSignedInt(17))
case 3:
it.dT += model.Time(it.readSignedInt(23))
default:
panic("unexpected number of control bits")
}
}
it.t += it.dT
}
func TestWriteHistogram(t *testing.T) {
histVec := prometheus.NewHistogramVec(
prometheus.HistogramOpts{
Name: "name",
Help: "docstring",
ConstLabels: prometheus.Labels{"constname": "constvalue"},
Buckets: []float64{0.01, 0.02, 0.05, 0.1},
},
[]string{"labelname"},
)
histVec.WithLabelValues("val1").Observe(float64(10))
histVec.WithLabelValues("val1").Observe(float64(20))
histVec.WithLabelValues("val1").Observe(float64(30))
histVec.WithLabelValues("val2").Observe(float64(20))
histVec.WithLabelValues("val2").Observe(float64(30))
histVec.WithLabelValues("val2").Observe(float64(40))
reg := prometheus.NewRegistry()
reg.MustRegister(histVec)
mfs, err := reg.Gather()
if err != nil {
t.Fatalf("error: %v", err)
}
now := model.Time(1477043083)
var buf bytes.Buffer
err = writeMetrics(&buf, mfs, "prefix", now)
if err != nil {
t.Fatalf("error: %v", err)
}
want := `prefix.name_bucket.constname.constvalue.labelname.val1.le.0_01 0 1477043
prefix.name_bucket.constname.constvalue.labelname.val1.le.0_02 0 1477043
prefix.name_bucket.constname.constvalue.labelname.val1.le.0_05 0 1477043
prefix.name_bucket.constname.constvalue.labelname.val1.le.0_1 0 1477043
prefix.name_sum.constname.constvalue.labelname.val1 60 1477043
prefix.name_count.constname.constvalue.labelname.val1 3 1477043
prefix.name_bucket.constname.constvalue.labelname.val1.le._Inf 3 1477043
prefix.name_bucket.constname.constvalue.labelname.val2.le.0_01 0 1477043
prefix.name_bucket.constname.constvalue.labelname.val2.le.0_02 0 1477043
prefix.name_bucket.constname.constvalue.labelname.val2.le.0_05 0 1477043
prefix.name_bucket.constname.constvalue.labelname.val2.le.0_1 0 1477043
prefix.name_sum.constname.constvalue.labelname.val2 90 1477043
prefix.name_count.constname.constvalue.labelname.val2 3 1477043
prefix.name_bucket.constname.constvalue.labelname.val2.le._Inf 3 1477043
`
if got := buf.String(); want != got {
t.Fatalf("wanted \n%s\n, got \n%s\n", want, got)
}
}
func TestWriteSummary(t *testing.T) {
sumVec := prometheus.NewSummaryVec(
prometheus.SummaryOpts{
Name: "name",
Help: "docstring",
ConstLabels: prometheus.Labels{"constname": "constvalue"},
Objectives: map[float64]float64{0.5: 0.05, 0.9: 0.01, 0.99: 0.001},
},
[]string{"labelname"},
)
sumVec.WithLabelValues("val1").Observe(float64(10))
sumVec.WithLabelValues("val1").Observe(float64(20))
sumVec.WithLabelValues("val1").Observe(float64(30))
sumVec.WithLabelValues("val2").Observe(float64(20))
sumVec.WithLabelValues("val2").Observe(float64(30))
sumVec.WithLabelValues("val2").Observe(float64(40))
reg := prometheus.NewRegistry()
reg.MustRegister(sumVec)
mfs, err := reg.Gather()
if err != nil {
t.Fatalf("error: %v", err)
}
now := model.Time(1477043083)
var buf bytes.Buffer
err = writeMetrics(&buf, mfs, "prefix", now)
if err != nil {
t.Fatalf("error: %v", err)
}
want := `prefix.name.constname.constvalue.labelname.val1.quantile.0_5 20 1477043
prefix.name.constname.constvalue.labelname.val1.quantile.0_9 30 1477043
prefix.name.constname.constvalue.labelname.val1.quantile.0_99 30 1477043
prefix.name_sum.constname.constvalue.labelname.val1 60 1477043
prefix.name_count.constname.constvalue.labelname.val1 3 1477043
prefix.name.constname.constvalue.labelname.val2.quantile.0_5 30 1477043
prefix.name.constname.constvalue.labelname.val2.quantile.0_9 40 1477043
prefix.name.constname.constvalue.labelname.val2.quantile.0_99 40 1477043
prefix.name_sum.constname.constvalue.labelname.val2 90 1477043
prefix.name_count.constname.constvalue.labelname.val2 3 1477043
`
if got := buf.String(); want != got {
t.Fatalf("wanted \n%s\n, got \n%s\n", want, got)
}
}
func TestAppendOutOfOrder(t *testing.T) {
s, closer := NewTestStorage(t, 1)
defer closer.Close()
m := model.Metric{
model.MetricNameLabel: "out_of_order",
}
for i, t := range []int{0, 2, 2, 1} {
s.Append(&model.Sample{
Metric: m,
Timestamp: model.Time(t),
Value: model.SampleValue(i),
})
}
fp, err := s.mapper.mapFP(m.FastFingerprint(), m)
if err != nil {
t.Fatal(err)
}
pl := s.NewPreloader()
defer pl.Close()
err = pl.PreloadRange(fp, 0, 2, 5*time.Minute)
if err != nil {
t.Fatalf("Error preloading chunks: %s", err)
}
it := s.NewIterator(fp)
want := []model.SamplePair{
{
Timestamp: 0,
Value: 0,
},
{
Timestamp: 2,
Value: 1,
},
}
got := it.RangeValues(metric.Interval{OldestInclusive: 0, NewestInclusive: 2})
if !reflect.DeepEqual(want, got) {
t.Fatalf("want %v, got %v", want, got)
}
}
func testChunk(t *testing.T, encoding chunkEncoding) {
samples := make(model.Samples, 500000)
for i := range samples {
samples[i] = &model.Sample{
Timestamp: model.Time(i),
Value: model.SampleValue(float64(i) * 0.2),
}
}
s, closer := NewTestStorage(t, encoding)
defer closer.Close()
for _, sample := range samples {
s.Append(sample)
}
s.WaitForIndexing()
for m := range s.fpToSeries.iter() {
s.fpLocker.Lock(m.fp)
defer s.fpLocker.Unlock(m.fp) // TODO remove, see below
var values []model.SamplePair
for _, cd := range m.series.chunkDescs {
if cd.isEvicted() {
continue
}
it := cd.c.newIterator()
for it.scan() {
values = append(values, it.value())
}
if it.err() != nil {
t.Error(it.err())
}
}
for i, v := range values {
if samples[i].Timestamp != v.Timestamp {
t.Errorf("%d. Got %v; want %v", i, v.Timestamp, samples[i].Timestamp)
}
if samples[i].Value != v.Value {
t.Errorf("%d. Got %v; want %v", i, v.Value, samples[i].Value)
}
}
//s.fpLocker.Unlock(m.fp)
}
log.Info("test done, closing")
}
func buildTestChunks(encoding chunkEncoding) map[model.Fingerprint][]chunk {
fps := model.Fingerprints{
m1.FastFingerprint(),
m2.FastFingerprint(),
m3.FastFingerprint(),
}
fpToChunks := map[model.Fingerprint][]chunk{}
for _, fp := range fps {
fpToChunks[fp] = make([]chunk, 0, 10)
for i := 0; i < 10; i++ {
fpToChunks[fp] = append(fpToChunks[fp], newChunkForEncoding(encoding).add(&model.SamplePair{
Timestamp: model.Time(i),
Value: model.SampleValue(fp),
})[0])
}
}
return fpToChunks
}
// TestLoop is just a smoke test for the loop method, if we can switch it on and
// off without disaster.
func TestLoop(t *testing.T) {
if testing.Short() {
t.Skip("Skipping test in short mode.")
}
samples := make(model.Samples, 1000)
for i := range samples {
samples[i] = &model.Sample{
Timestamp: model.Time(2 * i),
Value: model.SampleValue(float64(i) * 0.2),
}
}
directory := testutil.NewTemporaryDirectory("test_storage", t)
defer directory.Close()
o := &MemorySeriesStorageOptions{
MemoryChunks: 50,
MaxChunksToPersist: 1000000,
PersistenceRetentionPeriod: 24 * 7 * time.Hour,
PersistenceStoragePath: directory.Path(),
CheckpointInterval: 250 * time.Millisecond,
SyncStrategy: Adaptive,
MinShrinkRatio: 0.1,
}
storage := NewMemorySeriesStorage(o)
if err := storage.Start(); err != nil {
t.Errorf("Error starting storage: %s", err)
}
for _, s := range samples {
storage.Append(s)
}
storage.WaitForIndexing()
series, _ := storage.(*memorySeriesStorage).fpToSeries.get(model.Metric{}.FastFingerprint())
cdsBefore := len(series.chunkDescs)
time.Sleep(fpMaxWaitDuration + time.Second) // TODO(beorn7): Ugh, need to wait for maintenance to kick in.
cdsAfter := len(series.chunkDescs)
storage.Stop()
if cdsBefore <= cdsAfter {
t.Errorf(
"Number of chunk descriptors should have gone down by now. Got before %d, after %d.",
cdsBefore, cdsAfter,
)
}
}
func benchmarkAppend(b *testing.B, encoding chunkEncoding) {
samples := make(model.Samples, b.N)
for i := range samples {
samples[i] = &model.Sample{
Metric: model.Metric{
model.MetricNameLabel: model.LabelValue(fmt.Sprintf("test_metric_%d", i%10)),
"label1": model.LabelValue(fmt.Sprintf("test_metric_%d", i%10)),
"label2": model.LabelValue(fmt.Sprintf("test_metric_%d", i%10)),
},
Timestamp: model.Time(i),
Value: model.SampleValue(i),
}
}
b.ResetTimer()
s, closer := NewTestStorage(b, encoding)
defer closer.Close()
for _, sample := range samples {
s.Append(sample)
}
}
// linearRegression performs a least-square linear regression analysis on the
// provided SamplePairs. It returns the slope, and the intercept value at the
// provided time.
func linearRegression(samples []model.SamplePair, interceptTime model.Time) (slope, intercept model.SampleValue) {
var (
n model.SampleValue
sumX, sumY model.SampleValue
sumXY, sumX2 model.SampleValue
)
for _, sample := range samples {
x := model.SampleValue(
model.Time(sample.Timestamp-interceptTime).UnixNano(),
) / 1e9
n += 1.0
sumY += sample.Value
sumX += x
sumXY += x * sample.Value
sumX2 += x * x
}
covXY := sumXY - sumX*sumY/n
varX := sumX2 - sumX*sumX/n
slope = covXY / varX
intercept = sumY/n - slope*sumX/n
return slope, intercept
}
// metricForRange returns the metric for the given fingerprint if the
// corresponding time series has samples between 'from' and 'through', together
// with a pointer to the series if it is in memory already. For a series that
// does not have samples between 'from' and 'through', the returned bool is
// false. For an archived series that does contain samples between 'from' and
// 'through', it returns (metric, nil, true).
//
// The caller must have locked the fp.
func (s *memorySeriesStorage) metricForRange(
fp model.Fingerprint,
from, through model.Time,
) (model.Metric, *memorySeries, bool) {
series, ok := s.fpToSeries.get(fp)
if ok {
if series.lastTime.Before(from) || series.firstTime().After(through) {
return nil, nil, false
}
return series.metric, series, true
}
// From here on, we are only concerned with archived metrics.
// If the high watermark of archived series is before 'from', we are done.
watermark := model.Time(atomic.LoadInt64((*int64)(&s.archiveHighWatermark)))
if watermark < from {
return nil, nil, false
}
if from.After(model.Earliest) || through.Before(model.Latest) {
// The range lookup is relatively cheap, so let's do it first if
// we have a chance the archived metric is not in the range.
has, first, last := s.persistence.hasArchivedMetric(fp)
if !has {
s.nonExistentSeriesMatchesCount.Inc()
return nil, nil, false
}
if first.After(through) || last.Before(from) {
return nil, nil, false
}
}
metric, err := s.persistence.archivedMetric(fp)
if err != nil {
// archivedMetric has already flagged the storage as dirty in this case.
return nil, nil, false
}
return metric, nil, true
}
func TestLen(t *testing.T) {
chunks := []Chunk{}
for _, encoding := range []Encoding{Delta, DoubleDelta, Varbit} {
c, err := NewForEncoding(encoding)
if err != nil {
t.Fatal(err)
}
chunks = append(chunks, c)
}
for _, c := range chunks {
for i := 0; i <= 10; i++ {
if c.Len() != i {
t.Errorf("chunk type %s should have %d samples, had %d", c.Encoding(), i, c.Len())
}
cs, _ := c.Add(model.SamplePair{
Timestamp: model.Time(i),
Value: model.SampleValue(i),
})
c = cs[0]
}
}
}
func (acc *doubleDeltaEncodedIndexAccessor) timestampAtIndex(idx int) model.Time {
if idx == 0 {
return acc.baseT
}
if idx == 1 {
// If time bytes are at d8, the time is saved directly rather
// than as a difference.
if acc.tBytes == d8 {
return acc.baseΔT
}
return acc.baseT + acc.baseΔT
}
offset := doubleDeltaHeaderBytes + (idx-2)*int(acc.tBytes+acc.vBytes)
switch acc.tBytes {
case d1:
return acc.baseT +
model.Time(idx)*acc.baseΔT +
model.Time(int8(acc.c[offset]))
case d2:
return acc.baseT +
model.Time(idx)*acc.baseΔT +
model.Time(int16(binary.LittleEndian.Uint16(acc.c[offset:])))
case d4:
return acc.baseT +
model.Time(idx)*acc.baseΔT +
model.Time(int32(binary.LittleEndian.Uint32(acc.c[offset:])))
case d8:
// Take absolute value for d8.
return model.Time(binary.LittleEndian.Uint64(acc.c[offset:]))
default:
acc.lastErr = fmt.Errorf("invalid number of bytes for time delta: %d", acc.tBytes)
return model.Earliest
}
}
// Add implements chunk.
func (c doubleDeltaEncodedChunk) Add(s model.SamplePair) ([]Chunk, error) {
// TODO(beorn7): Since we return &c, this method might cause an unnecessary allocation.
if c.len() == 0 {
return c.addFirstSample(s), nil
}
tb := c.timeBytes()
vb := c.valueBytes()
if c.len() == 1 {
return c.addSecondSample(s, tb, vb)
}
remainingBytes := cap(c) - len(c)
sampleSize := c.sampleSize()
// Do we generally have space for another sample in this chunk? If not,
// overflow into a new one.
if remainingBytes < sampleSize {
return addToOverflowChunk(&c, s)
}
projectedTime := c.baseTime() + model.Time(c.len())*c.baseTimeDelta()
ddt := s.Timestamp - projectedTime
projectedValue := c.baseValue() + model.SampleValue(c.len())*c.baseValueDelta()
ddv := s.Value - projectedValue
ntb, nvb, nInt := tb, vb, c.isInt()
// If the new sample is incompatible with the current encoding, reencode the
// existing chunk data into new chunk(s).
if c.isInt() && !isInt64(ddv) {
// int->float.
nvb = d4
nInt = false
} else if !c.isInt() && vb == d4 && projectedValue+model.SampleValue(float32(ddv)) != s.Value {
// float32->float64.
nvb = d8
} else {
if tb < d8 {
// Maybe more bytes for timestamp.
ntb = max(tb, bytesNeededForSignedTimestampDelta(ddt))
}
if c.isInt() && vb < d8 {
// Maybe more bytes for sample value.
nvb = max(vb, bytesNeededForIntegerSampleValueDelta(ddv))
}
}
if tb != ntb || vb != nvb || c.isInt() != nInt {
if len(c)*2 < cap(c) {
return transcodeAndAdd(newDoubleDeltaEncodedChunk(ntb, nvb, nInt, cap(c)), &c, s)
}
// Chunk is already half full. Better create a new one and save the transcoding efforts.
return addToOverflowChunk(&c, s)
}
offset := len(c)
c = c[:offset+sampleSize]
switch tb {
case d1:
c[offset] = byte(ddt)
case d2:
binary.LittleEndian.PutUint16(c[offset:], uint16(ddt))
case d4:
binary.LittleEndian.PutUint32(c[offset:], uint32(ddt))
case d8:
// Store the absolute value (no delta) in case of d8.
binary.LittleEndian.PutUint64(c[offset:], uint64(s.Timestamp))
default:
return nil, fmt.Errorf("invalid number of bytes for time delta: %d", tb)
}
offset += int(tb)
if c.isInt() {
switch vb {
case d0:
// No-op. Constant delta is stored as base value.
case d1:
c[offset] = byte(int8(ddv))
case d2:
binary.LittleEndian.PutUint16(c[offset:], uint16(int16(ddv)))
case d4:
binary.LittleEndian.PutUint32(c[offset:], uint32(int32(ddv)))
// d8 must not happen. Those samples are encoded as float64.
default:
return nil, fmt.Errorf("invalid number of bytes for integer delta: %d", vb)
}
} else {
switch vb {
case d4:
binary.LittleEndian.PutUint32(c[offset:], math.Float32bits(float32(ddv)))
case d8:
// Store the absolute value (no delta) in case of d8.
binary.LittleEndian.PutUint64(c[offset:], math.Float64bits(float64(s.Value)))
default:
return nil, fmt.Errorf("invalid number of bytes for floating point delta: %d", vb)
}
}
return []Chunk{&c}, nil
}
func testCheckpointAndLoadSeriesMapAndHeads(t *testing.T, encoding chunk.Encoding) {
p, closer := newTestPersistence(t, encoding)
defer closer.Close()
fpLocker := newFingerprintLocker(10)
sm := newSeriesMap()
s1, _ := newMemorySeries(m1, nil, time.Time{})
s2, _ := newMemorySeries(m2, nil, time.Time{})
s3, _ := newMemorySeries(m3, nil, time.Time{})
s4, _ := newMemorySeries(m4, nil, time.Time{})
s5, _ := newMemorySeries(m5, nil, time.Time{})
s1.add(model.SamplePair{Timestamp: 1, Value: 3.14})
s3.add(model.SamplePair{Timestamp: 2, Value: 2.7})
s3.headChunkClosed = true
s3.persistWatermark = 1
for i := 0; i < 10000; i++ {
s4.add(model.SamplePair{
Timestamp: model.Time(i),
Value: model.SampleValue(i) / 2,
})
s5.add(model.SamplePair{
Timestamp: model.Time(i),
Value: model.SampleValue(i * i),
})
}
s5.persistWatermark = 3
chunkCountS4 := len(s4.chunkDescs)
chunkCountS5 := len(s5.chunkDescs)
sm.put(m1.FastFingerprint(), s1)
sm.put(m2.FastFingerprint(), s2)
sm.put(m3.FastFingerprint(), s3)
sm.put(m4.FastFingerprint(), s4)
sm.put(m5.FastFingerprint(), s5)
if err := p.checkpointSeriesMapAndHeads(sm, fpLocker); err != nil {
t.Fatal(err)
}
loadedSM, _, err := p.loadSeriesMapAndHeads()
if err != nil {
t.Fatal(err)
}
if loadedSM.length() != 4 {
t.Errorf("want 4 series in map, got %d", loadedSM.length())
}
if loadedS1, ok := loadedSM.get(m1.FastFingerprint()); ok {
if !reflect.DeepEqual(loadedS1.metric, m1) {
t.Errorf("want metric %v, got %v", m1, loadedS1.metric)
}
if !reflect.DeepEqual(loadedS1.head().C, s1.head().C) {
t.Error("head chunks differ")
}
if loadedS1.chunkDescsOffset != 0 {
t.Errorf("want chunkDescsOffset 0, got %d", loadedS1.chunkDescsOffset)
}
if loadedS1.headChunkClosed {
t.Error("headChunkClosed is true")
}
if loadedS1.head().ChunkFirstTime != 1 {
t.Errorf("want ChunkFirstTime in head chunk to be 1, got %d", loadedS1.head().ChunkFirstTime)
}
if loadedS1.head().ChunkLastTime != model.Earliest {
t.Error("want ChunkLastTime in head chunk to be unset")
}
} else {
t.Errorf("couldn't find %v in loaded map", m1)
}
if loadedS3, ok := loadedSM.get(m3.FastFingerprint()); ok {
if !reflect.DeepEqual(loadedS3.metric, m3) {
t.Errorf("want metric %v, got %v", m3, loadedS3.metric)
}
if loadedS3.head().C != nil {
t.Error("head chunk not evicted")
}
if loadedS3.chunkDescsOffset != 0 {
t.Errorf("want chunkDescsOffset 0, got %d", loadedS3.chunkDescsOffset)
}
if !loadedS3.headChunkClosed {
t.Error("headChunkClosed is false")
}
if loadedS3.head().ChunkFirstTime != 2 {
t.Errorf("want ChunkFirstTime in head chunk to be 2, got %d", loadedS3.head().ChunkFirstTime)
}
if loadedS3.head().ChunkLastTime != 2 {
t.Errorf("want ChunkLastTime in head chunk to be 2, got %d", loadedS3.head().ChunkLastTime)
}
} else {
t.Errorf("couldn't find %v in loaded map", m3)
}
if loadedS4, ok := loadedSM.get(m4.FastFingerprint()); ok {
if !reflect.DeepEqual(loadedS4.metric, m4) {
t.Errorf("want metric %v, got %v", m4, loadedS4.metric)
}
if got, want := len(loadedS4.chunkDescs), chunkCountS4; got != want {
t.Errorf("got %d chunkDescs, want %d", got, want)
}
if got, want := loadedS4.persistWatermark, 0; got != want {
t.Errorf("got persistWatermark %d, want %d", got, want)
}
if loadedS4.chunkDescs[2].IsEvicted() {
t.Error("3rd chunk evicted")
}
if loadedS4.chunkDescs[3].IsEvicted() {
t.Error("4th chunk evicted")
}
if loadedS4.chunkDescsOffset != 0 {
t.Errorf("want chunkDescsOffset 0, got %d", loadedS4.chunkDescsOffset)
}
if loadedS4.headChunkClosed {
t.Error("headChunkClosed is true")
}
for i, cd := range loadedS4.chunkDescs {
if cd.ChunkFirstTime != cd.C.FirstTime() {
t.Errorf(
"chunk.Desc[%d]: ChunkFirstTime not consistent with chunk, want %d, got %d",
i, cd.C.FirstTime(), cd.ChunkFirstTime,
)
}
if i == len(loadedS4.chunkDescs)-1 {
// Head chunk.
if cd.ChunkLastTime != model.Earliest {
t.Error("want ChunkLastTime in head chunk to be unset")
}
continue
}
lastTime, err := cd.C.NewIterator().LastTimestamp()
if err != nil {
t.Fatal(err)
}
if cd.ChunkLastTime != lastTime {
t.Errorf(
"chunk.Desc[%d]: ChunkLastTime not consistent with chunk, want %d, got %d",
i, lastTime, cd.ChunkLastTime,
)
}
}
} else {
t.Errorf("couldn't find %v in loaded map", m4)
}
if loadedS5, ok := loadedSM.get(m5.FastFingerprint()); ok {
if !reflect.DeepEqual(loadedS5.metric, m5) {
t.Errorf("want metric %v, got %v", m5, loadedS5.metric)
}
if got, want := len(loadedS5.chunkDescs), chunkCountS5; got != want {
t.Errorf("got %d chunkDescs, want %d", got, want)
}
if got, want := loadedS5.persistWatermark, 3; got != want {
t.Errorf("got persistWatermark %d, want %d", got, want)
}
if !loadedS5.chunkDescs[2].IsEvicted() {
t.Error("3rd chunk not evicted")
}
if loadedS5.chunkDescs[3].IsEvicted() {
t.Error("4th chunk evicted")
}
if loadedS5.chunkDescsOffset != 0 {
t.Errorf("want chunkDescsOffset 0, got %d", loadedS5.chunkDescsOffset)
}
if loadedS5.headChunkClosed {
t.Error("headChunkClosed is true")
}
for i, cd := range loadedS5.chunkDescs {
if i < 3 {
// Evicted chunks.
if cd.ChunkFirstTime == model.Earliest {
t.Errorf("chunk.Desc[%d]: ChunkLastTime not set", i)
}
continue
}
if cd.ChunkFirstTime != cd.C.FirstTime() {
t.Errorf(
"chunk.Desc[%d]: ChunkFirstTime not consistent with chunk, want %d, got %d",
i, cd.C.FirstTime(), cd.ChunkFirstTime,
)
}
if i == len(loadedS5.chunkDescs)-1 {
// Head chunk.
if cd.ChunkLastTime != model.Earliest {
t.Error("want ChunkLastTime in head chunk to be unset")
}
continue
}
lastTime, err := cd.C.NewIterator().LastTimestamp()
if err != nil {
t.Fatal(err)
}
if cd.ChunkLastTime != lastTime {
t.Errorf(
"chunk.Desc[%d]: ChunkLastTime not consistent with chunk, want %d, got %d",
i, cd.ChunkLastTime, lastTime,
)
}
}
} else {
t.Errorf("couldn't find %v in loaded map", m5)
}
}
func benchmarkValueAtTime(b *testing.B, encoding chunkEncoding) {
samples := make(model.Samples, 10000)
for i := range samples {
samples[i] = &model.Sample{
Timestamp: model.Time(2 * i),
Value: model.SampleValue(float64(i) * 0.2),
}
}
s, closer := NewTestStorage(b, encoding)
defer closer.Close()
for _, sample := range samples {
s.Append(sample)
}
s.WaitForIndexing()
fp := model.Metric{}.FastFingerprint()
b.ResetTimer()
for i := 0; i < b.N; i++ {
it := s.NewIterator(fp)
// #1 Exactly on a sample.
for i, expected := range samples {
actual := it.ValueAtTime(expected.Timestamp)
if len(actual) != 1 {
b.Fatalf("1.%d. Expected exactly one result, got %d.", i, len(actual))
}
if expected.Timestamp != actual[0].Timestamp {
b.Errorf("1.%d. Got %v; want %v", i, actual[0].Timestamp, expected.Timestamp)
}
if expected.Value != actual[0].Value {
b.Errorf("1.%d. Got %v; want %v", i, actual[0].Value, expected.Value)
}
}
// #2 Between samples.
for i, expected1 := range samples {
if i == len(samples)-1 {
continue
}
expected2 := samples[i+1]
actual := it.ValueAtTime(expected1.Timestamp + 1)
if len(actual) != 2 {
b.Fatalf("2.%d. Expected exactly 2 results, got %d.", i, len(actual))
}
if expected1.Timestamp != actual[0].Timestamp {
b.Errorf("2.%d. Got %v; want %v", i, actual[0].Timestamp, expected1.Timestamp)
}
if expected1.Value != actual[0].Value {
b.Errorf("2.%d. Got %v; want %v", i, actual[0].Value, expected1.Value)
}
if expected2.Timestamp != actual[1].Timestamp {
b.Errorf("2.%d. Got %v; want %v", i, actual[1].Timestamp, expected1.Timestamp)
}
if expected2.Value != actual[1].Value {
b.Errorf("2.%d. Got %v; want %v", i, actual[1].Value, expected1.Value)
}
}
}
}
func testPersistLoadDropChunks(t *testing.T, encoding chunk.Encoding) {
p, closer := newTestPersistence(t, encoding)
defer closer.Close()
fpToChunks := buildTestChunks(t, encoding)
for fp, chunks := range fpToChunks {
firstTimeNotDropped, offset, numDropped, allDropped, err :=
p.dropAndPersistChunks(fp, model.Earliest, chunks)
if err != nil {
t.Fatal(err)
}
if got, want := firstTimeNotDropped, model.Time(0); got != want {
t.Errorf("Want firstTimeNotDropped %v, got %v.", got, want)
}
if got, want := offset, 0; got != want {
t.Errorf("Want offset %v, got %v.", got, want)
}
if got, want := numDropped, 0; got != want {
t.Errorf("Want numDropped %v, got %v.", got, want)
}
if allDropped {
t.Error("All dropped.")
}
}
for fp, expectedChunks := range fpToChunks {
indexes := make([]int, 0, len(expectedChunks))
for i := range expectedChunks {
indexes = append(indexes, i)
}
actualChunks, err := p.loadChunks(fp, indexes, 0)
if err != nil {
t.Fatal(err)
}
for _, i := range indexes {
if !chunksEqual(expectedChunks[i], actualChunks[i]) {
t.Errorf("%d. Chunks not equal.", i)
}
}
// Load all chunk descs.
actualChunkDescs, err := p.loadChunkDescs(fp, 0)
if len(actualChunkDescs) != 10 {
t.Errorf("Got %d chunkDescs, want %d.", len(actualChunkDescs), 10)
}
for i, cd := range actualChunkDescs {
lastTime, err := cd.LastTime()
if err != nil {
t.Fatal(err)
}
if cd.FirstTime() != model.Time(i) || lastTime != model.Time(i) {
t.Errorf(
"Want ts=%v, got firstTime=%v, lastTime=%v.",
i, cd.FirstTime(), lastTime,
)
}
}
// Load chunk descs partially.
actualChunkDescs, err = p.loadChunkDescs(fp, 5)
if err != nil {
t.Fatal(err)
}
if len(actualChunkDescs) != 5 {
t.Errorf("Got %d chunkDescs, want %d.", len(actualChunkDescs), 5)
}
for i, cd := range actualChunkDescs {
lastTime, err := cd.LastTime()
if err != nil {
t.Fatal(err)
}
if cd.FirstTime() != model.Time(i) || lastTime != model.Time(i) {
t.Errorf(
"Want ts=%v, got firstTime=%v, lastTime=%v.",
i, cd.FirstTime(), lastTime,
)
}
}
}
// Drop half of the chunks.
for fp, expectedChunks := range fpToChunks {
firstTime, offset, numDropped, allDropped, err := p.dropAndPersistChunks(fp, 5, nil)
if err != nil {
t.Fatal(err)
}
if offset != 5 {
t.Errorf("want offset 5, got %d", offset)
}
if firstTime != 5 {
t.Errorf("want first time 5, got %d", firstTime)
}
if numDropped != 5 {
t.Errorf("want 5 dropped chunks, got %v", numDropped)
}
if allDropped {
t.Error("all chunks dropped")
}
indexes := make([]int, 5)
for i := range indexes {
indexes[i] = i
}
actualChunks, err := p.loadChunks(fp, indexes, 0)
if err != nil {
t.Fatal(err)
}
for _, i := range indexes {
if !chunksEqual(expectedChunks[i+5], actualChunks[i]) {
t.Errorf("%d. Chunks not equal.", i)
}
}
}
// Drop all the chunks.
for fp := range fpToChunks {
firstTime, offset, numDropped, allDropped, err := p.dropAndPersistChunks(fp, 100, nil)
if firstTime != 0 {
t.Errorf("want first time 0, got %d", firstTime)
}
if err != nil {
t.Fatal(err)
}
if offset != 0 {
t.Errorf("want offset 0, got %d", offset)
}
if numDropped != 5 {
t.Errorf("want 5 dropped chunks, got %v", numDropped)
}
if !allDropped {
t.Error("not all chunks dropped")
}
}
// Re-add first two of the chunks.
for fp, chunks := range fpToChunks {
firstTimeNotDropped, offset, numDropped, allDropped, err :=
p.dropAndPersistChunks(fp, model.Earliest, chunks[:2])
if err != nil {
t.Fatal(err)
}
if got, want := firstTimeNotDropped, model.Time(0); got != want {
t.Errorf("Want firstTimeNotDropped %v, got %v.", got, want)
}
if got, want := offset, 0; got != want {
t.Errorf("Want offset %v, got %v.", got, want)
}
if got, want := numDropped, 0; got != want {
t.Errorf("Want numDropped %v, got %v.", got, want)
}
if allDropped {
t.Error("All dropped.")
}
}
// Drop the first of the chunks while adding two more.
for fp, chunks := range fpToChunks {
firstTime, offset, numDropped, allDropped, err := p.dropAndPersistChunks(fp, 1, chunks[2:4])
if err != nil {
t.Fatal(err)
}
if offset != 1 {
t.Errorf("want offset 1, got %d", offset)
}
if firstTime != 1 {
t.Errorf("want first time 1, got %d", firstTime)
}
if numDropped != 1 {
t.Errorf("want 1 dropped chunk, got %v", numDropped)
}
if allDropped {
t.Error("all chunks dropped")
}
wantChunks := chunks[1:4]
indexes := make([]int, len(wantChunks))
for i := range indexes {
indexes[i] = i
}
gotChunks, err := p.loadChunks(fp, indexes, 0)
if err != nil {
t.Fatal(err)
}
for i, wantChunk := range wantChunks {
if !chunksEqual(wantChunk, gotChunks[i]) {
t.Errorf("%d. Chunks not equal.", i)
}
}
}
// Drop all the chunks while adding two more.
for fp, chunks := range fpToChunks {
firstTime, offset, numDropped, allDropped, err := p.dropAndPersistChunks(fp, 4, chunks[4:6])
if err != nil {
t.Fatal(err)
}
if offset != 0 {
t.Errorf("want offset 0, got %d", offset)
}
if firstTime != 4 {
t.Errorf("want first time 4, got %d", firstTime)
}
if numDropped != 3 {
t.Errorf("want 3 dropped chunks, got %v", numDropped)
}
if allDropped {
t.Error("all chunks dropped")
}
wantChunks := chunks[4:6]
indexes := make([]int, len(wantChunks))
for i := range indexes {
indexes[i] = i
}
gotChunks, err := p.loadChunks(fp, indexes, 0)
if err != nil {
t.Fatal(err)
}
for i, wantChunk := range wantChunks {
if !chunksEqual(wantChunk, gotChunks[i]) {
t.Errorf("%d. Chunks not equal.", i)
}
}
}
// While adding two more, drop all but one of the added ones.
for fp, chunks := range fpToChunks {
firstTime, offset, numDropped, allDropped, err := p.dropAndPersistChunks(fp, 7, chunks[6:8])
if err != nil {
t.Fatal(err)
}
if offset != 0 {
t.Errorf("want offset 0, got %d", offset)
}
if firstTime != 7 {
t.Errorf("want first time 7, got %d", firstTime)
}
if numDropped != 3 {
t.Errorf("want 3 dropped chunks, got %v", numDropped)
}
if allDropped {
t.Error("all chunks dropped")
}
wantChunks := chunks[7:8]
indexes := make([]int, len(wantChunks))
for i := range indexes {
indexes[i] = i
}
gotChunks, err := p.loadChunks(fp, indexes, 0)
if err != nil {
t.Fatal(err)
}
for i, wantChunk := range wantChunks {
if !chunksEqual(wantChunk, gotChunks[i]) {
t.Errorf("%d. Chunks not equal.", i)
}
}
}
// While adding two more, drop all chunks including the added ones.
for fp, chunks := range fpToChunks {
firstTime, offset, numDropped, allDropped, err := p.dropAndPersistChunks(fp, 10, chunks[8:])
if err != nil {
t.Fatal(err)
}
if offset != 0 {
t.Errorf("want offset 0, got %d", offset)
}
if firstTime != 0 {
t.Errorf("want first time 0, got %d", firstTime)
}
if numDropped != 3 {
t.Errorf("want 3 dropped chunks, got %v", numDropped)
}
if !allDropped {
t.Error("not all chunks dropped")
}
}
// Now set minShrinkRatio to 0.25 and play with it.
p.minShrinkRatio = 0.25
// Re-add 8 chunks.
for fp, chunks := range fpToChunks {
firstTimeNotDropped, offset, numDropped, allDropped, err :=
p.dropAndPersistChunks(fp, model.Earliest, chunks[:8])
if err != nil {
t.Fatal(err)
}
if got, want := firstTimeNotDropped, model.Time(0); got != want {
t.Errorf("Want firstTimeNotDropped %v, got %v.", got, want)
}
if got, want := offset, 0; got != want {
t.Errorf("Want offset %v, got %v.", got, want)
}
if got, want := numDropped, 0; got != want {
t.Errorf("Want numDropped %v, got %v.", got, want)
}
if allDropped {
t.Error("All dropped.")
}
}
// Drop only the first chunk should not happen, but persistence should still work.
for fp, chunks := range fpToChunks {
firstTime, offset, numDropped, allDropped, err := p.dropAndPersistChunks(fp, 1, chunks[8:9])
if err != nil {
t.Fatal(err)
}
if offset != 8 {
t.Errorf("want offset 8, got %d", offset)
}
if firstTime != 0 {
t.Errorf("want first time 0, got %d", firstTime)
}
if numDropped != 0 {
t.Errorf("want 0 dropped chunk, got %v", numDropped)
}
if allDropped {
t.Error("all chunks dropped")
}
}
// Drop only the first two chunks should not happen, either.
for fp := range fpToChunks {
firstTime, offset, numDropped, allDropped, err := p.dropAndPersistChunks(fp, 2, nil)
if err != nil {
t.Fatal(err)
}
if offset != 0 {
t.Errorf("want offset 0, got %d", offset)
}
if firstTime != 0 {
t.Errorf("want first time 0, got %d", firstTime)
}
if numDropped != 0 {
t.Errorf("want 0 dropped chunk, got %v", numDropped)
}
if allDropped {
t.Error("all chunks dropped")
}
}
// Drop the first three chunks should finally work.
for fp, chunks := range fpToChunks {
firstTime, offset, numDropped, allDropped, err := p.dropAndPersistChunks(fp, 3, chunks[9:])
if err != nil {
t.Fatal(err)
}
if offset != 6 {
t.Errorf("want offset 6, got %d", offset)
}
if firstTime != 3 {
t.Errorf("want first time 3, got %d", firstTime)
}
if numDropped != 3 {
t.Errorf("want 3 dropped chunk, got %v", numDropped)
}
if allDropped {
t.Error("all chunks dropped")
}
}
}
func testRangeValues(t *testing.T, encoding chunkEncoding) {
samples := make(model.Samples, 10000)
for i := range samples {
samples[i] = &model.Sample{
Timestamp: model.Time(2 * i),
Value: model.SampleValue(float64(i) * 0.2),
}
}
s, closer := NewTestStorage(t, encoding)
defer closer.Close()
for _, sample := range samples {
s.Append(sample)
}
s.WaitForIndexing()
fp := model.Metric{}.FastFingerprint()
it := s.NewIterator(fp)
// #1 Zero length interval at sample.
for i, expected := range samples {
actual := it.RangeValues(metric.Interval{
OldestInclusive: expected.Timestamp,
NewestInclusive: expected.Timestamp,
})
if len(actual) != 1 {
t.Fatalf("1.%d. Expected exactly one result, got %d.", i, len(actual))
}
if expected.Timestamp != actual[0].Timestamp {
t.Errorf("1.%d. Got %v; want %v.", i, actual[0].Timestamp, expected.Timestamp)
}
if expected.Value != actual[0].Value {
t.Errorf("1.%d. Got %v; want %v.", i, actual[0].Value, expected.Value)
}
}
// #2 Zero length interval off sample.
for i, expected := range samples {
actual := it.RangeValues(metric.Interval{
OldestInclusive: expected.Timestamp + 1,
NewestInclusive: expected.Timestamp + 1,
})
if len(actual) != 0 {
t.Fatalf("2.%d. Expected no result, got %d.", i, len(actual))
}
}
// #3 2sec interval around sample.
for i, expected := range samples {
actual := it.RangeValues(metric.Interval{
OldestInclusive: expected.Timestamp - 1,
NewestInclusive: expected.Timestamp + 1,
})
if len(actual) != 1 {
t.Fatalf("3.%d. Expected exactly one result, got %d.", i, len(actual))
}
if expected.Timestamp != actual[0].Timestamp {
t.Errorf("3.%d. Got %v; want %v.", i, actual[0].Timestamp, expected.Timestamp)
}
if expected.Value != actual[0].Value {
t.Errorf("3.%d. Got %v; want %v.", i, actual[0].Value, expected.Value)
}
}
// #4 2sec interval sample to sample.
for i, expected1 := range samples {
if i == len(samples)-1 {
continue
}
expected2 := samples[i+1]
actual := it.RangeValues(metric.Interval{
OldestInclusive: expected1.Timestamp,
NewestInclusive: expected1.Timestamp + 2,
})
if len(actual) != 2 {
t.Fatalf("4.%d. Expected exactly 2 results, got %d.", i, len(actual))
}
if expected1.Timestamp != actual[0].Timestamp {
t.Errorf("4.%d. Got %v for 1st result; want %v.", i, actual[0].Timestamp, expected1.Timestamp)
}
if expected1.Value != actual[0].Value {
t.Errorf("4.%d. Got %v for 1st result; want %v.", i, actual[0].Value, expected1.Value)
}
if expected2.Timestamp != actual[1].Timestamp {
t.Errorf("4.%d. Got %v for 2nd result; want %v.", i, actual[1].Timestamp, expected2.Timestamp)
}
if expected2.Value != actual[1].Value {
t.Errorf("4.%d. Got %v for 2nd result; want %v.", i, actual[1].Value, expected2.Value)
}
}
// #5 corner cases: Interval ends at first sample, interval starts
// at last sample, interval entirely before/after samples.
expected := samples[0]
actual := it.RangeValues(metric.Interval{
OldestInclusive: expected.Timestamp - 2,
NewestInclusive: expected.Timestamp,
})
if len(actual) != 1 {
t.Fatalf("5.1. Expected exactly one result, got %d.", len(actual))
}
if expected.Timestamp != actual[0].Timestamp {
t.Errorf("5.1. Got %v; want %v.", actual[0].Timestamp, expected.Timestamp)
}
if expected.Value != actual[0].Value {
t.Errorf("5.1. Got %v; want %v.", actual[0].Value, expected.Value)
}
expected = samples[len(samples)-1]
actual = it.RangeValues(metric.Interval{
OldestInclusive: expected.Timestamp,
NewestInclusive: expected.Timestamp + 2,
})
if len(actual) != 1 {
t.Fatalf("5.2. Expected exactly one result, got %d.", len(actual))
}
if expected.Timestamp != actual[0].Timestamp {
t.Errorf("5.2. Got %v; want %v.", actual[0].Timestamp, expected.Timestamp)
}
if expected.Value != actual[0].Value {
t.Errorf("5.2. Got %v; want %v.", actual[0].Value, expected.Value)
}
firstSample := samples[0]
actual = it.RangeValues(metric.Interval{
OldestInclusive: firstSample.Timestamp - 4,
NewestInclusive: firstSample.Timestamp - 2,
})
if len(actual) != 0 {
t.Fatalf("5.3. Expected no results, got %d.", len(actual))
}
lastSample := samples[len(samples)-1]
actual = it.RangeValues(metric.Interval{
OldestInclusive: lastSample.Timestamp + 2,
NewestInclusive: lastSample.Timestamp + 4,
})
if len(actual) != 0 {
t.Fatalf("5.3. Expected no results, got %d.", len(actual))
}
}
