Merge pull request #12737 from prometheus/beorn7/histogram

textparse: fix infinite loop during exemplar parsing
This commit is contained in:
Bryan Boreham 2023-08-23 09:36:56 +01:00 committed by GitHub
commit d73b4acb30
No known key found for this signature in database
GPG Key ID: 4AEE18F83AFDEB23
3 changed files with 133 additions and 9 deletions

View File

@ -56,6 +56,10 @@ type ProtobufParser struct {
fieldsDone bool // true if no more fields of a Summary or (legacy) Histogram to be processed.
redoClassic bool // true after parsing a native histogram if we need to parse it again as a classic histogram.
// exemplarReturned is set to true each time an exemplar has been
// returned, and set back to false upon each Next() call.
exemplarReturned bool
// state is marked by the entry we are processing. EntryInvalid implies
// that we have to decode the next MetricFamily.
state Entry
@ -293,8 +297,12 @@ func (p *ProtobufParser) Metric(l *labels.Labels) string {
// Exemplar writes the exemplar of the current sample into the passed
// exemplar. It returns if an exemplar exists or not. In case of a native
// histogram, the legacy bucket section is still used for exemplars. To ingest
// all examplars, call the Exemplar method repeatedly until it returns false.
// all exemplars, call the Exemplar method repeatedly until it returns false.
func (p *ProtobufParser) Exemplar(ex *exemplar.Exemplar) bool {
if p.exemplarReturned && p.state == EntrySeries {
// We only ever return one exemplar per (non-native-histogram) series.
return false
}
m := p.mf.GetMetric()[p.metricPos]
var exProto *dto.Exemplar
switch p.mf.GetType() {
@ -335,6 +343,7 @@ func (p *ProtobufParser) Exemplar(ex *exemplar.Exemplar) bool {
}
p.builder.Sort()
ex.Labels = p.builder.Labels()
p.exemplarReturned = true
return true
}
@ -342,6 +351,7 @@ func (p *ProtobufParser) Exemplar(ex *exemplar.Exemplar) bool {
// text format parser). It returns (EntryInvalid, io.EOF) if no samples were
// read.
func (p *ProtobufParser) Next() (Entry, error) {
p.exemplarReturned = false
switch p.state {
case EntryInvalid:
p.metricPos = 0

View File

@ -1779,6 +1779,7 @@ func TestProtobufParse(t *testing.T) {
} else {
require.Equal(t, true, found, "i: %d", i)
require.Equal(t, exp[i].e[0], e, "i: %d", i)
require.False(t, p.Exemplar(&e), "too many exemplars returned, i: %d", i)
}
case EntryHistogram:

View File

@ -1985,13 +1985,14 @@ func TestScrapeLoopAppendNoStalenessIfTimestamp(t *testing.T) {
func TestScrapeLoopAppendExemplar(t *testing.T) {
tests := []struct {
title string
scrapeText string
contentType string
discoveryLabels []string
floats []floatSample
histograms []histogramSample
exemplars []exemplar.Exemplar
title string
scrapeClassicHistograms bool
scrapeText string
contentType string
discoveryLabels []string
floats []floatSample
histograms []histogramSample
exemplars []exemplar.Exemplar
}{
{
title: "Metric without exemplars",
@ -2145,6 +2146,115 @@ metric: <
{Labels: labels.FromStrings("dummyID", "5617"), Value: -0.00029, Ts: 1234568, HasTs: false},
},
},
{
title: "Native histogram with two exemplars scraped as classic histogram",
scrapeText: `name: "test_histogram"
help: "Test histogram with many buckets removed to keep it manageable in size."
type: HISTOGRAM
metric: <
histogram: <
sample_count: 175
sample_sum: 0.0008280461746287094
bucket: <
cumulative_count: 2
upper_bound: -0.0004899999999999998
>
bucket: <
cumulative_count: 4
upper_bound: -0.0003899999999999998
exemplar: <
label: <
name: "dummyID"
value: "59727"
>
value: -0.00039
timestamp: <
seconds: 1625851155
nanos: 146848499
>
>
>
bucket: <
cumulative_count: 16
upper_bound: -0.0002899999999999998
exemplar: <
label: <
name: "dummyID"
value: "5617"
>
value: -0.00029
>
>
schema: 3
zero_threshold: 2.938735877055719e-39
zero_count: 2
negative_span: <
offset: -162
length: 1
>
negative_span: <
offset: 23
length: 4
>
negative_delta: 1
negative_delta: 3
negative_delta: -2
negative_delta: -1
negative_delta: 1
positive_span: <
offset: -161
length: 1
>
positive_span: <
offset: 8
length: 3
>
positive_delta: 1
positive_delta: 2
positive_delta: -1
positive_delta: -1
>
timestamp_ms: 1234568
>
`,
scrapeClassicHistograms: true,
contentType: "application/vnd.google.protobuf",
floats: []floatSample{
{metric: labels.FromStrings("__name__", "test_histogram_count"), t: 1234568, f: 175},
{metric: labels.FromStrings("__name__", "test_histogram_sum"), t: 1234568, f: 0.0008280461746287094},
{metric: labels.FromStrings("__name__", "test_histogram_bucket", "le", "-0.0004899999999999998"), t: 1234568, f: 2},
{metric: labels.FromStrings("__name__", "test_histogram_bucket", "le", "-0.0003899999999999998"), t: 1234568, f: 4},
{metric: labels.FromStrings("__name__", "test_histogram_bucket", "le", "-0.0002899999999999998"), t: 1234568, f: 16},
{metric: labels.FromStrings("__name__", "test_histogram_bucket", "le", "+Inf"), t: 1234568, f: 175},
},
histograms: []histogramSample{{
t: 1234568,
h: &histogram.Histogram{
Count: 175,
ZeroCount: 2,
Sum: 0.0008280461746287094,
ZeroThreshold: 2.938735877055719e-39,
Schema: 3,
PositiveSpans: []histogram.Span{
{Offset: -161, Length: 1},
{Offset: 8, Length: 3},
},
NegativeSpans: []histogram.Span{
{Offset: -162, Length: 1},
{Offset: 23, Length: 4},
},
PositiveBuckets: []int64{1, 2, -1, -1},
NegativeBuckets: []int64{1, 3, -2, -1, 1},
},
}},
exemplars: []exemplar.Exemplar{
{Labels: labels.FromStrings("dummyID", "59727"), Value: -0.00039, Ts: 1625851155146, HasTs: true},
{Labels: labels.FromStrings("dummyID", "5617"), Value: -0.00029, Ts: 1234568, HasTs: false},
{Labels: labels.FromStrings("dummyID", "59727"), Value: -0.00039, Ts: 1625851155146, HasTs: true},
{Labels: labels.FromStrings("dummyID", "5617"), Value: -0.00029, Ts: 1234568, HasTs: false},
},
},
}
for _, test := range tests {
@ -2171,7 +2281,7 @@ metric: <
nil,
0,
0,
false,
test.scrapeClassicHistograms,
false,
false,
nil,
@ -2181,6 +2291,9 @@ metric: <
now := time.Now()
for i := range test.floats {
if test.floats[i].t != 0 {
continue
}
test.floats[i].t = timestamp.FromTime(now)
}