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authorDaniel Baumann <daniel.baumann@progress-linux.org>2023-02-06 16:11:34 +0000
committerDaniel Baumann <daniel.baumann@progress-linux.org>2023-02-06 16:11:34 +0000
commitd079b656b4719739b2247dcd9d46e9bec793095a (patch)
treed2c950c70a776bcf697c963151c5bd959f8a9f03 /ml/Chart.h
parentReleasing debian version 1.37.1-2. (diff)
downloadnetdata-d079b656b4719739b2247dcd9d46e9bec793095a.tar.xz
netdata-d079b656b4719739b2247dcd9d46e9bec793095a.zip
Merging upstream version 1.38.0.
Signed-off-by: Daniel Baumann <daniel.baumann@progress-linux.org>
Diffstat (limited to 'ml/Chart.h')
-rw-r--r--ml/Chart.h128
1 files changed, 128 insertions, 0 deletions
diff --git a/ml/Chart.h b/ml/Chart.h
new file mode 100644
index 000000000..dbd6a910f
--- /dev/null
+++ b/ml/Chart.h
@@ -0,0 +1,128 @@
+// SPDX-License-Identifier: GPL-3.0-or-later
+
+#ifndef ML_CHART_H
+#define ML_CHART_H
+
+#include "Config.h"
+#include "Dimension.h"
+
+#include "ml-private.h"
+#include "json/single_include/nlohmann/json.hpp"
+
+namespace ml
+{
+
+class Chart {
+public:
+ Chart(RRDSET *RS) :
+ RS(RS),
+ MLS()
+ { }
+
+ RRDSET *getRS() const {
+ return RS;
+ }
+
+ bool isAvailableForML() {
+ return rrdset_is_available_for_exporting_and_alarms(RS);
+ }
+
+ void addDimension(Dimension *D) {
+ std::lock_guard<Mutex> L(M);
+ Dimensions[D->getRD()] = D;
+ }
+
+ void removeDimension(Dimension *D) {
+ std::lock_guard<Mutex> L(M);
+ Dimensions.erase(D->getRD());
+ }
+
+ void getModelsAsJson(nlohmann::json &Json) {
+ std::lock_guard<Mutex> L(M);
+
+ for (auto &DP : Dimensions) {
+ Dimension *D = DP.second;
+ nlohmann::json JsonArray = nlohmann::json::array();
+ for (const KMeans &KM : D->getModels()) {
+ nlohmann::json J;
+ KM.toJson(J);
+ JsonArray.push_back(J);
+ }
+
+ Json[getMLDimensionID(D->getRD())] = JsonArray;
+ }
+ }
+
+ void updateBegin() {
+ M.lock();
+ MLS = {};
+ }
+
+ void updateDimension(Dimension *D, bool IsAnomalous) {
+ switch (D->getMLS()) {
+ case MachineLearningStatus::DisabledDueToUniqueUpdateEvery:
+ MLS.NumMachineLearningStatusDisabledUE++;
+ return;
+ case MachineLearningStatus::DisabledDueToExcludedChart:
+ MLS.NumMachineLearningStatusDisabledSP++;
+ return;
+ case MachineLearningStatus::Enabled: {
+ MLS.NumMachineLearningStatusEnabled++;
+
+ switch (D->getMT()) {
+ case MetricType::Constant:
+ MLS.NumMetricTypeConstant++;
+ MLS.NumTrainingStatusTrained++;
+ MLS.NumNormalDimensions++;
+ return;
+ case MetricType::Variable:
+ MLS.NumMetricTypeVariable++;
+ break;
+ }
+
+ switch (D->getTS()) {
+ case TrainingStatus::Untrained:
+ MLS.NumTrainingStatusUntrained++;
+ return;
+ case TrainingStatus::PendingWithoutModel:
+ MLS.NumTrainingStatusPendingWithoutModel++;
+ return;
+ case TrainingStatus::Trained:
+ MLS.NumTrainingStatusTrained++;
+
+ MLS.NumAnomalousDimensions += IsAnomalous;
+ MLS.NumNormalDimensions += !IsAnomalous;
+ return;
+ case TrainingStatus::PendingWithModel:
+ MLS.NumTrainingStatusPendingWithModel++;
+
+ MLS.NumAnomalousDimensions += IsAnomalous;
+ MLS.NumNormalDimensions += !IsAnomalous;
+ return;
+ }
+
+ return;
+ }
+ }
+ }
+
+ void updateEnd() {
+ M.unlock();
+ }
+
+ MachineLearningStats getMLS() {
+ std::lock_guard<Mutex> L(M);
+ return MLS;
+ }
+
+private:
+ RRDSET *RS;
+ MachineLearningStats MLS;
+
+ Mutex M;
+ std::unordered_map<RRDDIM *, Dimension *> Dimensions;
+};
+
+} // namespace ml
+
+#endif /* ML_CHART_H */