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// 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) {
AnomalyRateRS = rrdset_create(
RH,
"anomaly_detection",
"anomaly_rates",
NULL, // name
"anomaly_rates",
NULL, // ctx
"Average anomaly rate",
"anomaly rate",
"netdata",
"ml",
39189,
Cfg.DBEngineAnomalyRateEvery,
RRDSET_TYPE_LINE
);
AnomalyRateRS->flags = static_cast<RRDSET_FLAGS>(
static_cast<int>(AnomalyRateRS->flags) | RRDSET_FLAG_HIDDEN
);
}
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;
RRDSET *AnomalyRateRS;
// Protect dimension and lock maps
std::mutex Mutex;
std::unordered_map<RRDDIM *, Dimension *> DimensionsMap;
std::unordered_map<Dimension *, std::mutex> LocksMap;
};
class TrainableHost : public RrdHost {
public:
TrainableHost(RRDHOST *RH) : RrdHost(RH) {}
void train();
void updateResourceUsage() {
std::lock_guard<std::mutex> Lock(ResourceUsageMutex);
getrusage(RUSAGE_THREAD, &ResourceUsage);
}
void getResourceUsage(struct rusage *RU) {
std::lock_guard<std::mutex> Lock(ResourceUsageMutex);
memcpy(RU, &ResourceUsage, sizeof(struct rusage));
}
private:
std::pair<Dimension *, Duration<double>> findDimensionToTrain(const TimePoint &NowTP);
void trainDimension(Dimension *D, const TimePoint &NowTP);
struct rusage ResourceUsage{};
std::mutex ResourceUsageMutex;
};
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 WindowAnomalyRate{0.0};
size_t NumAnomalousDimensions{0};
size_t NumNormalDimensions{0};
size_t NumTrainedDimensions{0};
unsigned AnomalyRateTimer{0};
Database DB{Cfg.AnomalyDBPath};
};
using Host = DetectableHost;
} // namespace ml
#endif /* ML_HOST_H */
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