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author | Daniel Baumann <daniel.baumann@progress-linux.org> | 2021-12-01 06:15:04 +0000 |
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committer | Daniel Baumann <daniel.baumann@progress-linux.org> | 2021-12-01 06:15:04 +0000 |
commit | e970e0b37b8bd7f246feb3f70c4136418225e434 (patch) | |
tree | 0b67c0ca45f56f2f9d9c5c2e725279ecdf52d2eb /ml/Host.h | |
parent | Adding upstream version 1.31.0. (diff) | |
download | netdata-e970e0b37b8bd7f246feb3f70c4136418225e434.tar.xz netdata-e970e0b37b8bd7f246feb3f70c4136418225e434.zip |
Adding upstream version 1.32.0.upstream/1.32.0
Signed-off-by: Daniel Baumann <daniel.baumann@progress-linux.org>
Diffstat (limited to 'ml/Host.h')
-rw-r--r-- | ml/Host.h | 104 |
1 files changed, 104 insertions, 0 deletions
diff --git a/ml/Host.h b/ml/Host.h new file mode 100644 index 000000000..86591d7ae --- /dev/null +++ b/ml/Host.h @@ -0,0 +1,104 @@ +// SPDX-License-Identifier: GPL-3.0-or-later + +#ifndef ML_HOST_H +#define ML_HOST_H + +#include "BitRateWindow.h" +#include "Config.h" +#include "Database.h" +#include "Dimension.h" + +#include "ml-private.h" + +namespace ml { + +class RrdHost { +public: + RrdHost(RRDHOST *RH) : RH(RH) {} + + RRDHOST *getRH() { return RH; } + + unsigned updateEvery() { return RH->rrd_update_every; } + + std::string getUUID() { + char S[UUID_STR_LEN]; + uuid_unparse_lower(RH->host_uuid, S); + return S; + } + + void addDimension(Dimension *D); + void removeDimension(Dimension *D); + + void getConfigAsJson(nlohmann::json &Json) const; + + virtual ~RrdHost() {}; + +protected: + RRDHOST *RH; + + // Protect dimension and lock maps + std::mutex Mutex; + + std::map<RRDDIM *, Dimension *> DimensionsMap; + std::map<Dimension *, std::mutex> LocksMap; +}; + +class TrainableHost : public RrdHost { +public: + TrainableHost(RRDHOST *RH) : RrdHost(RH) {} + + void train(); + +private: + std::pair<Dimension *, Duration<double>> findDimensionToTrain(const TimePoint &NowTP); + void trainDimension(Dimension *D, const TimePoint &NowTP); +}; + +class DetectableHost : public TrainableHost { +public: + DetectableHost(RRDHOST *RH) : TrainableHost(RH) {} + + void startAnomalyDetectionThreads(); + void stopAnomalyDetectionThreads(); + + template<typename ...ArgTypes> + bool getAnomalyInfo(ArgTypes&&... Args) { + return DB.getAnomalyInfo(Args...); + } + + template<typename ...ArgTypes> + bool getAnomaliesInRange(ArgTypes&&... Args) { + return DB.getAnomaliesInRange(Args...); + } + + void getDetectionInfoAsJson(nlohmann::json &Json) const; + +private: + void detect(); + void detectOnce(); + +private: + std::thread TrainingThread; + std::thread DetectionThread; + + BitRateWindow BRW{ + static_cast<size_t>(Cfg.ADMinWindowSize), + static_cast<size_t>(Cfg.ADMaxWindowSize), + static_cast<size_t>(Cfg.ADIdleWindowSize), + static_cast<size_t>(Cfg.ADMinWindowSize * Cfg.ADWindowRateThreshold) + }; + + CalculatedNumber AnomalyRate{0.0}; + + size_t NumAnomalousDimensions{0}; + size_t NumNormalDimensions{0}; + size_t NumTrainedDimensions{0}; + + Database DB{Cfg.AnomalyDBPath}; +}; + +using Host = DetectableHost; + +} // namespace ml + +#endif /* ML_HOST_H */ |