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authorDaniel Baumann <daniel.baumann@progress-linux.org>2022-04-14 18:12:10 +0000
committerDaniel Baumann <daniel.baumann@progress-linux.org>2022-04-14 18:12:10 +0000
commitb5321aff06d6ea8d730d62aec2ffd8e9271c1ffc (patch)
tree36c41e35994786456154f9d3bf88c324763aeea4 /ml/ml.cc
parentAdding upstream version 1.33.1. (diff)
downloadnetdata-b5321aff06d6ea8d730d62aec2ffd8e9271c1ffc.tar.xz
netdata-b5321aff06d6ea8d730d62aec2ffd8e9271c1ffc.zip
Adding upstream version 1.34.0.upstream/1.34.0
Signed-off-by: Daniel Baumann <daniel.baumann@progress-linux.org>
Diffstat (limited to 'ml/ml.cc')
-rw-r--r--ml/ml.cc81
1 files changed, 77 insertions, 4 deletions
diff --git a/ml/ml.cc b/ml/ml.cc
index cfda3d28f..b56401b07 100644
--- a/ml/ml.cc
+++ b/ml/ml.cc
@@ -4,8 +4,24 @@
#include "Dimension.h"
#include "Host.h"
+#include <random>
+
using namespace ml;
+bool ml_capable() {
+ return true;
+}
+
+bool ml_enabled(RRDHOST *RH) {
+ if (!Cfg.EnableAnomalyDetection)
+ return false;
+
+ if (simple_pattern_matches(Cfg.SP_HostsToSkip, RH->hostname))
+ return false;
+
+ return true;
+}
+
/*
* Assumptions:
* 1) hosts outlive their sets, and sets outlive their dimensions,
@@ -13,14 +29,24 @@ using namespace ml;
*/
void ml_init(void) {
+ // Read config values
Cfg.readMLConfig();
-}
-void ml_new_host(RRDHOST *RH) {
if (!Cfg.EnableAnomalyDetection)
return;
- if (simple_pattern_matches(Cfg.SP_HostsToSkip, RH->hostname))
+ // Generate random numbers to efficiently sample the features we need
+ // for KMeans clustering.
+ std::random_device RD;
+ std::mt19937 Gen(RD());
+
+ Cfg.RandomNums.reserve(Cfg.MaxTrainSamples);
+ for (size_t Idx = 0; Idx != Cfg.MaxTrainSamples; Idx++)
+ Cfg.RandomNums.push_back(Gen());
+}
+
+void ml_new_host(RRDHOST *RH) {
+ if (!ml_enabled(RH))
return;
Host *H = new Host(RH);
@@ -64,7 +90,10 @@ void ml_delete_dimension(RRDDIM *RD) {
return;
Host *H = static_cast<Host *>(RD->rrdset->rrdhost->ml_host);
- H->removeDimension(D);
+ if (!H)
+ delete D;
+ else
+ H->removeDimension(D);
RD->state->ml_dimension = nullptr;
}
@@ -150,6 +179,48 @@ char *ml_get_anomaly_event_info(RRDHOST *RH, const char *AnomalyDetectorName,
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;
+
+ calculated_number *CNs = R->v;
+ RRDR_DIMENSION_FLAGS *DimFlags = R->od;
+
+ std::vector<std::pair<calculated_number, 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);
+ }
+}
+
+void ml_dimension_update_name(RRDSET *RS, RRDDIM *RD, const char *Name) {
+ (void) RS;
+
+ Dimension *D = static_cast<Dimension *>(RD->state->ml_dimension);
+ if (!D)
+ return;
+
+ D->setAnomalyRateRDName(Name);
+}
+
+bool ml_streaming_enabled() {
+ return Cfg.StreamADCharts;
+}
+
#if defined(ENABLE_ML_TESTS)
#include "gtest/gtest.h"
@@ -163,3 +234,5 @@ int test_ml(int argc, char *argv[]) {
}
#endif // ENABLE_ML_TESTS
+
+#include "ml-private.h"