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authorDaniel Baumann <daniel.baumann@progress-linux.org>2022-11-30 18:47:05 +0000
committerDaniel Baumann <daniel.baumann@progress-linux.org>2022-11-30 18:47:05 +0000
commit97e01009d69b8fbebfebf68f51e3d126d0ed43fc (patch)
tree02e8b836c3a9d89806f3e67d4a5fe9f52dbb0061 /ml/ml.cc
parentReleasing debian version 1.36.1-1. (diff)
downloadnetdata-97e01009d69b8fbebfebf68f51e3d126d0ed43fc.tar.xz
netdata-97e01009d69b8fbebfebf68f51e3d126d0ed43fc.zip
Merging upstream version 1.37.0.
Signed-off-by: Daniel Baumann <daniel.baumann@progress-linux.org>
Diffstat (limited to 'ml/ml.cc')
-rw-r--r--ml/ml.cc99
1 files changed, 13 insertions, 86 deletions
diff --git a/ml/ml.cc b/ml/ml.cc
index 7275d88b..1a7d6ae2 100644
--- a/ml/ml.cc
+++ b/ml/ml.cc
@@ -16,7 +16,7 @@ bool ml_enabled(RRDHOST *RH) {
if (!Cfg.EnableAnomalyDetection)
return false;
- if (simple_pattern_matches(Cfg.SP_HostsToSkip, RH->hostname))
+ if (simple_pattern_matches(Cfg.SP_HostsToSkip, rrdhost_hostname(RH)))
return false;
return true;
@@ -76,7 +76,7 @@ void ml_new_dimension(RRDDIM *RD) {
if (static_cast<unsigned>(RD->update_every) != H->updateEvery())
return;
- if (simple_pattern_matches(Cfg.SP_ChartsToSkip, RS->name))
+ if (simple_pattern_matches(Cfg.SP_ChartsToSkip, rrdset_name(RS)))
return;
Dimension *D = new Dimension(RD);
@@ -108,7 +108,7 @@ char *ml_get_host_info(RRDHOST *RH) {
ConfigJson["enabled"] = false;
}
- return strdup(ConfigJson.dump(2, '\t').c_str());
+ return strdupz(ConfigJson.dump(2, '\t').c_str());
}
char *ml_get_host_runtime_info(RRDHOST *RH) {
@@ -124,97 +124,24 @@ char *ml_get_host_runtime_info(RRDHOST *RH) {
return strdup(ConfigJson.dump(1, '\t').c_str());
}
-bool ml_is_anomalous(RRDDIM *RD, double Value, bool Exists) {
- Dimension *D = static_cast<Dimension *>(RD->ml_dimension);
- if (!D)
- return false;
-
- D->addValue(Value, Exists);
- bool Result = D->predict().second;
- return Result;
-}
-
-char *ml_get_anomaly_events(RRDHOST *RH, const char *AnomalyDetectorName,
- int AnomalyDetectorVersion, time_t After, time_t Before) {
- if (!RH || !RH->ml_host) {
- error("No host");
- return nullptr;
- }
-
- Host *H = static_cast<Host *>(RH->ml_host);
- std::vector<std::pair<time_t, time_t>> TimeRanges;
-
- bool Res = H->getAnomaliesInRange(TimeRanges, AnomalyDetectorName,
- AnomalyDetectorVersion,
- H->getUUID(),
- After, Before);
- if (!Res) {
- error("DB result is empty");
- return nullptr;
- }
-
- nlohmann::json Json = TimeRanges;
- return strdup(Json.dump(4).c_str());
-}
-
-char *ml_get_anomaly_event_info(RRDHOST *RH, const char *AnomalyDetectorName,
- int AnomalyDetectorVersion, time_t After, time_t Before) {
- if (!RH || !RH->ml_host) {
- error("No host");
- return nullptr;
- }
-
- Host *H = static_cast<Host *>(RH->ml_host);
+char *ml_get_host_models(RRDHOST *RH) {
+ nlohmann::json ModelsJson;
- nlohmann::json Json;
- bool Res = H->getAnomalyInfo(Json, AnomalyDetectorName,
- AnomalyDetectorVersion,
- H->getUUID(),
- After, Before);
- if (!Res) {
- error("DB result is empty");
- return nullptr;
+ if (RH && RH->ml_host) {
+ Host *H = static_cast<Host *>(RH->ml_host);
+ H->getModelsAsJson(ModelsJson);
+ return strdup(ModelsJson.dump(2, '\t').c_str());
}
- return strdup(Json.dump(4, '\t').c_str());
-}
-
-void ml_process_rrdr(RRDR *R, int MaxAnomalyRates) {
- if (R->rows != 1)
- return;
-
- if (MaxAnomalyRates < 1 || MaxAnomalyRates >= R->d)
- return;
-
- NETDATA_DOUBLE *CNs = R->v;
- RRDR_DIMENSION_FLAGS *DimFlags = R->od;
-
- std::vector<std::pair<NETDATA_DOUBLE, int>> V;
-
- V.reserve(R->d);
- for (int Idx = 0; Idx != R->d; Idx++)
- V.emplace_back(CNs[Idx], Idx);
-
- std::sort(V.rbegin(), V.rend());
-
- for (int Idx = MaxAnomalyRates; Idx != R->d; Idx++) {
- int UnsortedIdx = V[Idx].second;
-
- int OldFlags = static_cast<int>(DimFlags[UnsortedIdx]);
- int NewFlags = OldFlags | RRDR_DIMENSION_HIDDEN;
-
- DimFlags[UnsortedIdx] = static_cast<rrdr_dimension_flag>(NewFlags);
- }
+ return nullptr;
}
-void ml_dimension_update_name(RRDSET *RS, RRDDIM *RD, const char *Name) {
- (void) RS;
-
+bool ml_is_anomalous(RRDDIM *RD, double Value, bool Exists) {
Dimension *D = static_cast<Dimension *>(RD->ml_dimension);
if (!D)
- return;
+ return false;
- D->setAnomalyRateRDName(Name);
+ return D->predict(Value, Exists);
}
bool ml_streaming_enabled() {