// Get implements CurationRemarker.
func (w *LevelDBCurationRemarker) Get(c *curationKey) (t clientmodel.Timestamp, ok bool, err error) {
k := &dto.CurationKey{}
c.dump(k)
v := &dto.CurationValue{}
ok, err = w.LevelDBPersistence.Get(k, v)
if err != nil || !ok {
return clientmodel.TimestampFromUnix(0), ok, err
}
return clientmodel.TimestampFromUnix(v.GetLastCompletionTimestamp()), true, nil
}
// Get implements HighWatermarker.
func (w *LevelDBHighWatermarker) Get(f *clientmodel.Fingerprint) (t clientmodel.Timestamp, ok bool, err error) {
k := &dto.Fingerprint{}
dumpFingerprint(k, f)
v := &dto.MetricHighWatermark{}
ok, err = w.LevelDBPersistence.Get(k, v)
if err != nil {
return t, ok, err
}
if !ok {
return clientmodel.TimestampFromUnix(0), ok, nil
}
t = clientmodel.TimestampFromUnix(v.GetTimestamp())
return t, true, nil
}
func extractCounter(out Ingester, o *ProcessOptions, f *dto.MetricFamily) error {
samples := make(model.Samples, 0, len(f.Metric))
for _, m := range f.Metric {
if m.Counter == nil {
continue
}
sample := new(model.Sample)
samples = append(samples, sample)
if m.TimestampMs != nil {
sample.Timestamp = model.TimestampFromUnix(*m.TimestampMs / 1000)
} else {
sample.Timestamp = o.Timestamp
}
sample.Metric = model.Metric{}
metric := sample.Metric
for _, p := range m.Label {
metric[model.LabelName(p.GetName())] = model.LabelValue(p.GetValue())
}
metric[model.MetricNameLabel] = model.LabelValue(f.GetName())
sample.Value = model.SampleValue(m.Counter.GetValue())
}
return out.Ingest(&Result{Samples: samples})
}
func AppendSampleAsPureSparseAppendTests(p metric.Persistence, t test.Tester) {
appendSample := func(x int) (success bool) {
v := clientmodel.SampleValue(x)
ts := clientmodel.TimestampFromUnix(int64(x))
labelName := clientmodel.LabelName(x)
labelValue := clientmodel.LabelValue(x)
l := clientmodel.Metric{labelName: labelValue}
sample := &clientmodel.Sample{
Value: v,
Timestamp: ts,
Metric: l,
}
err := p.AppendSamples(clientmodel.Samples{sample})
success = err == nil
if !success {
t.Error(err)
}
return
}
if err := quick.Check(appendSample, nil); err != nil {
t.Error(err)
}
}
// Load deserializes this SampleKey from a DTO.
func (s *SampleKey) Load(d *dto.SampleKey) {
f := &clientmodel.Fingerprint{}
loadFingerprint(f, d.GetFingerprint())
s.Fingerprint = f
s.FirstTimestamp = indexable.DecodeTime(d.Timestamp)
s.LastTimestamp = clientmodel.TimestampFromUnix(d.GetLastTimestamp())
s.SampleCount = d.GetSampleCount()
}
func AppendSampleAsSparseAppendWithReadsTests(p metric.Persistence, t test.Tester) {
appendSample := func(x int) (success bool) {
v := clientmodel.SampleValue(x)
ts := clientmodel.TimestampFromUnix(int64(x))
labelName := clientmodel.LabelName(x)
labelValue := clientmodel.LabelValue(x)
l := clientmodel.Metric{labelName: labelValue}
sample := &clientmodel.Sample{
Value: v,
Timestamp: ts,
Metric: l,
}
err := p.AppendSamples(clientmodel.Samples{sample})
if err != nil {
t.Error(err)
return
}
values, err := p.GetLabelValuesForLabelName(labelName)
if err != nil {
t.Error(err)
return
}
if len(values) != 1 {
t.Errorf("expected label values count of %d, got %d", 1, len(values))
return
}
fingerprints, err := p.GetFingerprintsForLabelMatchers(metric.LabelMatchers{{
Type: metric.Equal,
Name: labelName,
Value: labelValue,
}})
if err != nil {
t.Error(err)
return
}
if len(fingerprints) != 1 {
t.Errorf("expected fingerprint count of %d, got %d", 1, len(fingerprints))
return
}
return true
}
if err := quick.Check(appendSample, nil); err != nil {
t.Error(err)
}
}
func TestTimeEndToEnd(t *testing.T) {
tester := func(x int) bool {
random := rand.New(rand.NewSource(int64(x)))
buffer := make([]byte, 8)
incoming := clientmodel.TimestampFromUnix(random.Int63())
EncodeTimeInto(buffer, incoming)
outgoing := DecodeTime(buffer)
return incoming.Equal(outgoing) && incoming.Unix() == outgoing.Unix()
}
if err := quick.Check(tester, nil); err != nil {
t.Error(err)
}
}
func AppendSampleAsPureSingleEntityAppendTests(p metric.Persistence, t test.Tester) {
appendSample := func(x int) bool {
sample := &clientmodel.Sample{
Value: clientmodel.SampleValue(x),
Timestamp: clientmodel.TimestampFromUnix(int64(x)),
Metric: clientmodel.Metric{clientmodel.MetricNameLabel: "my_metric"},
}
err := p.AppendSamples(clientmodel.Samples{sample})
return err == nil
}
if err := quick.Check(appendSample, nil); err != nil {
t.Error(err)
}
}
// unmarshalValues decodes marshalled samples into dest and returns either dest
// or a new slice containing those values if dest has insufficient capacity.
func unmarshalValues(buf []byte, dest metric.Values) metric.Values {
if buf[0] != formatVersion {
panic("unsupported format version")
}
n := (len(buf) - formatVersionSize) / sampleSize
if cap(dest) < n {
dest = make(metric.Values, n)
} else {
dest = dest[0:n]
}
for i := 0; i < n; i++ {
offset := formatVersionSize + i*sampleSize
dest[i].Timestamp = clientmodel.TimestampFromUnix(int64(binary.LittleEndian.Uint64(buf[offset:])))
dest[i].Value = clientmodel.SampleValue(math.Float64frombits(binary.LittleEndian.Uint64(buf[offset+8:])))
}
return dest
}
func (serv MetricsService) QueryRange(w http.ResponseWriter, r *http.Request) {
setAccessControlHeaders(w)
w.Header().Set("Content-Type", "application/json")
params := http_utils.GetQueryParams(r)
expr := params.Get("expr")
end, _ := strconv.ParseInt(params.Get("end"), 0, 64)
duration, _ := strconv.ParseInt(params.Get("range"), 0, 64)
step, _ := strconv.ParseInt(params.Get("step"), 0, 64)
exprNode, err := rules.LoadExprFromString(expr)
if err != nil {
fmt.Fprint(w, ast.ErrorToJSON(err))
return
}
if exprNode.Type() != ast.VECTOR {
fmt.Fprint(w, ast.ErrorToJSON(errors.New("Expression does not evaluate to vector type")))
return
}
if end == 0 {
end = clientmodel.Now().Unix()
}
if step < 1 {
step = 1
}
if end-duration < 0 {
duration = end
}
// Align the start to step "tick" boundary.
end -= end % step
queryStats := stats.NewTimerGroup()
evalTimer := queryStats.GetTimer(stats.TotalEvalTime).Start()
matrix, err := ast.EvalVectorRange(
exprNode.(ast.VectorNode),
clientmodel.TimestampFromUnix(end-duration),
clientmodel.TimestampFromUnix(end),
time.Duration(step)*time.Second,
serv.Storage,
queryStats)
if err != nil {
fmt.Fprint(w, ast.ErrorToJSON(err))
return
}
evalTimer.Stop()
sortTimer := queryStats.GetTimer(stats.ResultSortTime).Start()
sort.Sort(matrix)
sortTimer.Stop()
jsonTimer := queryStats.GetTimer(stats.JsonEncodeTime).Start()
result := ast.TypedValueToJSON(matrix, "matrix")
jsonTimer.Stop()
glog.Infof("Range query: %s\nQuery stats:\n%s\n", expr, queryStats)
fmt.Fprint(w, result)
}
func testBuilder(t test.Tester) {
type atTime struct {
fingerprint string
time clientmodel.Timestamp
}
type atInterval struct {
fingerprint string
from clientmodel.Timestamp
through clientmodel.Timestamp
interval time.Duration
}
type atRange struct {
fingerprint string
from clientmodel.Timestamp
through clientmodel.Timestamp
}
type in struct {
atTimes []atTime
atIntervals []atInterval
atRanges []atRange
}
type out []struct {
fingerprint string
operations ops
}
var scenarios = []struct {
in in
out out
}{
// Ensure that the fingerprint is sorted in proper order.
{
in: in{
atTimes: []atTime{
{
fingerprint: "0000000000000001111-a-4-a",
time: clientmodel.TimestampFromUnix(100),
},
{
fingerprint: "0000000000000000000-a-4-a",
time: clientmodel.TimestampFromUnix(100),
},
},
},
out: out{
{
fingerprint: "00000000000000000000-a-4-a",
},
{
fingerprint: "00000000000000001111-a-4-a",
},
},
},
// // Ensure that the fingerprint-timestamp pairs are sorted in proper order.
{
in: in{
atTimes: []atTime{
{
fingerprint: "1111-a-4-a",
time: clientmodel.TimestampFromUnix(100),
},
{
fingerprint: "1111-a-4-a",
time: clientmodel.TimestampFromUnix(200),
},
{
fingerprint: "0-a-4-a",
time: clientmodel.TimestampFromUnix(100),
},
{
fingerprint: "0-a-4-a",
time: clientmodel.TimestampFromUnix(0),
},
},
},
out: out{
{
fingerprint: "00000000000000000000-a-4-a",
},
{
fingerprint: "00000000000000000000-a-4-a",
},
{
fingerprint: "00000000000000001111-a-4-a",
},
{
fingerprint: "00000000000000001111-a-4-a",
},
},
},
// Ensure grouping of operations
{
in: in{
atTimes: []atTime{
{
fingerprint: "1111-a-4-a",
time: clientmodel.TimestampFromUnix(100),
},
},
atRanges: []atRange{
{
fingerprint: "1111-a-4-a",
from: clientmodel.TimestampFromUnix(100),
through: clientmodel.TimestampFromUnix(1000),
},
{
fingerprint: "1111-a-4-a",
from: clientmodel.TimestampFromUnix(100),
through: clientmodel.TimestampFromUnix(9000),
},
},
},
out: out{
{
fingerprint: "00000000000000001111-a-4-a",
},
{
fingerprint: "00000000000000001111-a-4-a",
},
{
fingerprint: "00000000000000001111-a-4-a",
},
},
},
}
for i, scenario := range scenarios {
builder := &viewRequestBuilder{}
for _, atTime := range scenario.in.atTimes {
fingerprint := &clientmodel.Fingerprint{}
fingerprint.LoadFromString(atTime.fingerprint)
builder.GetMetricAtTime(fingerprint, atTime.time)
}
for _, atInterval := range scenario.in.atIntervals {
fingerprint := &clientmodel.Fingerprint{}
fingerprint.LoadFromString(atInterval.fingerprint)
builder.GetMetricAtInterval(fingerprint, atInterval.from, atInterval.through, atInterval.interval)
}
for _, atRange := range scenario.in.atRanges {
fingerprint := &clientmodel.Fingerprint{}
fingerprint.LoadFromString(atRange.fingerprint)
builder.GetMetricRange(fingerprint, atRange.from, atRange.through)
}
for j, job := range scenario.out {
got := builder.PopOp()
if got.Fingerprint().String() != job.fingerprint {
t.Errorf("%d.%d. expected fingerprint %s, got %s", i, j, job.fingerprint, got.Fingerprint())
}
}
if builder.HasOp() {
t.Error("Expected builder to have no scan jobs left.")
}
}
}
// DecodeTime deserializes a big endian byte array into a Unix time in UTC,
// omitting granularity precision less than a second.
func DecodeTime(src []byte) clientmodel.Timestamp {
return clientmodel.TimestampFromUnix(int64(binary.BigEndian.Uint64(src)))
}
func extractSummary(out Ingester, o *ProcessOptions, f *dto.MetricFamily) error {
samples := make(model.Samples, 0, len(f.Metric))
for _, m := range f.Metric {
if m.Summary == nil {
continue
}
timestamp := o.Timestamp
if m.TimestampMs != nil {
timestamp = model.TimestampFromUnix(*m.TimestampMs / 1000)
}
for _, q := range m.Summary.Quantile {
sample := new(model.Sample)
samples = append(samples, sample)
sample.Timestamp = timestamp
sample.Metric = model.Metric{}
metric := sample.Metric
for _, p := range m.Label {
metric[model.LabelName(p.GetName())] = model.LabelValue(p.GetValue())
}
// BUG(matt): Update other names to "quantile".
metric[model.LabelName("quantile")] = model.LabelValue(fmt.Sprint(q.GetQuantile()))
metric[model.MetricNameLabel] = model.LabelValue(f.GetName())
sample.Value = model.SampleValue(q.GetValue())
}
if m.Summary.SampleSum != nil {
sum := new(model.Sample)
sum.Timestamp = timestamp
metric := model.Metric{}
for _, p := range m.Label {
metric[model.LabelName(p.GetName())] = model.LabelValue(p.GetValue())
}
metric[model.MetricNameLabel] = model.LabelValue(f.GetName() + "_sum")
sum.Metric = metric
sum.Value = model.SampleValue(m.Summary.GetSampleSum())
samples = append(samples, sum)
}
if m.Summary.SampleCount != nil {
count := new(model.Sample)
count.Timestamp = timestamp
metric := model.Metric{}
for _, p := range m.Label {
metric[model.LabelName(p.GetName())] = model.LabelValue(p.GetValue())
}
metric[model.MetricNameLabel] = model.LabelValue(f.GetName() + "_count")
count.Metric = metric
count.Value = model.SampleValue(m.Summary.GetSampleCount())
samples = append(samples, count)
}
}
return out.Ingest(&Result{Samples: samples})
}
func (w *watermarks) load(d *dto.MetricHighWatermark) {
w.High = clientmodel.TimestampFromUnix(d.GetTimestamp())
}
func StochasticTests(persistenceMaker func() (metric.Persistence, test.Closer), t test.Tester) {
stochastic := func(x int) (success bool) {
p, closer := persistenceMaker()
defer closer.Close()
defer p.Close()
seed := rand.NewSource(int64(x))
random := rand.New(seed)
numberOfMetrics := random.Intn(stochasticMaximumVariance) + 1
numberOfSharedLabels := random.Intn(stochasticMaximumVariance)
numberOfUnsharedLabels := random.Intn(stochasticMaximumVariance)
numberOfSamples := random.Intn(stochasticMaximumVariance) + 2
numberOfRangeScans := random.Intn(stochasticMaximumVariance)
metricTimestamps := map[int]map[int64]bool{}
metricEarliestSample := map[int]int64{}
metricNewestSample := map[int]int64{}
for metricIndex := 0; metricIndex < numberOfMetrics; metricIndex++ {
sample := &clientmodel.Sample{
Metric: clientmodel.Metric{},
}
v := clientmodel.LabelValue(fmt.Sprintf("metric_index_%d", metricIndex))
sample.Metric[clientmodel.MetricNameLabel] = v
for sharedLabelIndex := 0; sharedLabelIndex < numberOfSharedLabels; sharedLabelIndex++ {
l := clientmodel.LabelName(fmt.Sprintf("shared_label_%d", sharedLabelIndex))
v := clientmodel.LabelValue(fmt.Sprintf("label_%d", sharedLabelIndex))
sample.Metric[l] = v
}
for unsharedLabelIndex := 0; unsharedLabelIndex < numberOfUnsharedLabels; unsharedLabelIndex++ {
l := clientmodel.LabelName(fmt.Sprintf("metric_index_%d_private_label_%d", metricIndex, unsharedLabelIndex))
v := clientmodel.LabelValue(fmt.Sprintf("private_label_%d", unsharedLabelIndex))
sample.Metric[l] = v
}
timestamps := map[int64]bool{}
metricTimestamps[metricIndex] = timestamps
var newestSample int64 = math.MinInt64
var oldestSample int64 = math.MaxInt64
var nextTimestamp func() int64
nextTimestamp = func() int64 {
var candidate int64
candidate = random.Int63n(math.MaxInt32 - 1)
if _, has := timestamps[candidate]; has {
// WART
candidate = nextTimestamp()
}
timestamps[candidate] = true
if candidate < oldestSample {
oldestSample = candidate
}
if candidate > newestSample {
newestSample = candidate
}
return candidate
}
// BUG(matt): Invariant of the in-memory database assumes this.
sortedTimestamps := timeslice{}
for sampleIndex := 0; sampleIndex < numberOfSamples; sampleIndex++ {
sortedTimestamps = append(sortedTimestamps, clientmodel.TimestampFromUnix(nextTimestamp()))
}
sort.Sort(sortedTimestamps)
for sampleIndex := 0; sampleIndex < numberOfSamples; sampleIndex++ {
sample.Timestamp = sortedTimestamps[sampleIndex]
sample.Value = clientmodel.SampleValue(sampleIndex)
err := p.AppendSamples(clientmodel.Samples{sample})
if err != nil {
t.Error(err)
return
}
}
metricEarliestSample[metricIndex] = oldestSample
metricNewestSample[metricIndex] = newestSample
for sharedLabelIndex := 0; sharedLabelIndex < numberOfSharedLabels; sharedLabelIndex++ {
matchers := metric.LabelMatchers{{
Type: metric.Equal,
Name: clientmodel.LabelName(fmt.Sprintf("shared_label_%d", sharedLabelIndex)),
Value: clientmodel.LabelValue(fmt.Sprintf("label_%d", sharedLabelIndex)),
}}
fingerprints, err := p.GetFingerprintsForLabelMatchers(matchers)
if err != nil {
t.Error(err)
return
}
if len(fingerprints) == 0 {
t.Errorf("expected fingerprint count of %d, got %d", 0, len(fingerprints))
return
}
}
}
for metricIndex := 0; metricIndex < numberOfMetrics; metricIndex++ {
for unsharedLabelIndex := 0; unsharedLabelIndex < numberOfUnsharedLabels; unsharedLabelIndex++ {
labelName := clientmodel.LabelName(fmt.Sprintf("metric_index_%d_private_label_%d", metricIndex, unsharedLabelIndex))
labelValue := clientmodel.LabelValue(fmt.Sprintf("private_label_%d", unsharedLabelIndex))
matchers := metric.LabelMatchers{{
Type: metric.Equal,
Name: labelName,
Value: labelValue,
}}
fingerprints, err := p.GetFingerprintsForLabelMatchers(matchers)
if err != nil {
t.Error(err)
return
}
if len(fingerprints) != 1 {
t.Errorf("expected fingerprint count of %d, got %d", 1, len(fingerprints))
return
}
}
m := clientmodel.Metric{}
m[clientmodel.MetricNameLabel] = clientmodel.LabelValue(fmt.Sprintf("metric_index_%d", metricIndex))
for i := 0; i < numberOfSharedLabels; i++ {
l := clientmodel.LabelName(fmt.Sprintf("shared_label_%d", i))
v := clientmodel.LabelValue(fmt.Sprintf("label_%d", i))
m[l] = v
}
for i := 0; i < numberOfUnsharedLabels; i++ {
l := clientmodel.LabelName(fmt.Sprintf("metric_index_%d_private_label_%d", metricIndex, i))
v := clientmodel.LabelValue(fmt.Sprintf("private_label_%d", i))
m[l] = v
}
for i := 0; i < numberOfRangeScans; i++ {
timestamps := metricTimestamps[metricIndex]
var first int64
var second int64
for {
firstCandidate := random.Int63n(int64(len(timestamps)))
secondCandidate := random.Int63n(int64(len(timestamps)))
smallest := int64(-1)
largest := int64(-1)
if firstCandidate == secondCandidate {
continue
} else if firstCandidate > secondCandidate {
largest = firstCandidate
smallest = secondCandidate
} else {
largest = secondCandidate
smallest = firstCandidate
}
j := int64(0)
for i := range timestamps {
if j == smallest {
first = i
} else if j == largest {
second = i
break
}
j++
}
break
}
begin := first
end := second
if second < first {
begin, end = second, first
}
interval := metric.Interval{
OldestInclusive: clientmodel.TimestampFromUnix(begin),
NewestInclusive: clientmodel.TimestampFromUnix(end),
}
samples := metric.Values{}
fp := &clientmodel.Fingerprint{}
fp.LoadFromMetric(m)
switch persistence := p.(type) {
case metric.View:
samples = persistence.GetRangeValues(fp, interval)
if len(samples) < 2 {
t.Fatalf("expected sample count greater than %d, got %d", 2, len(samples))
}
case *LevelDBPersistence:
var err error
samples, err = levelDBGetRangeValues(persistence, fp, interval)
if err != nil {
t.Fatal(err)
}
if len(samples) < 2 {
t.Fatalf("expected sample count greater than %d, got %d", 2, len(samples))
}
default:
t.Error("Unexpected type of metric.Persistence.")
}
}
}
return true
}
if err := quick.Check(stochastic, nil); err != nil {
t.Error(err)
}
}
