Adding upstream version 1.39.0.upstream/1.39.0

Signed-off-by: Daniel Baumann <daniel.baumann@progress-linux.org>

1 files changed, 0 insertions, 387 deletions

diff --git a/ml/Host.cc b/ml/Host.cc
deleted file mode 100644
index a5f276a8..00000000
--- a/ml/Host.cc
+++ /dev/null
@@ -1,387 +0,0 @@
-// SPDX-License-Identifier: GPL-3.0-or-later
-
-#include "Config.h"
-#include "Host.h"
-#include "Queue.h"
-#include "ADCharts.h"
-
-#include "json/single_include/nlohmann/json.hpp"
-
-using namespace ml;
-
-void Host::addChart(Chart *C) {
-    std::lock_guard<Mutex> L(M);
-    Charts[C->getRS()] = C;
-}
-
-void Host::removeChart(Chart *C) {
-    std::lock_guard<Mutex> L(M);
-    Charts.erase(C->getRS());
-}
-
-void Host::getConfigAsJson(nlohmann::json &Json) const {
-    Json["version"] = 1;
-
-    Json["enabled"] = Cfg.EnableAnomalyDetection;
-
-    Json["min-train-samples"] = Cfg.MinTrainSamples;
-    Json["max-train-samples"] = Cfg.MaxTrainSamples;
-    Json["train-every"] = Cfg.TrainEvery;
-
-    Json["diff-n"] = Cfg.DiffN;
-    Json["smooth-n"] = Cfg.SmoothN;
-    Json["lag-n"] = Cfg.LagN;
-
-    Json["random-sampling-ratio"] = Cfg.RandomSamplingRatio;
-    Json["max-kmeans-iters"] = Cfg.MaxKMeansIters;
-
-    Json["dimension-anomaly-score-threshold"] = Cfg.DimensionAnomalyScoreThreshold;
-
-    Json["host-anomaly-rate-threshold"] = Cfg.HostAnomalyRateThreshold;
-    Json["anomaly-detection-grouping-method"] = group_method2string(Cfg.AnomalyDetectionGroupingMethod);
-    Json["anomaly-detection-query-duration"] = Cfg.AnomalyDetectionQueryDuration;
-
-    Json["hosts-to-skip"] = Cfg.HostsToSkip;
-    Json["charts-to-skip"] = Cfg.ChartsToSkip;
-}
-
-void Host::getModelsAsJson(nlohmann::json &Json) {
-    std::lock_guard<Mutex> L(M);
-
-    for (auto &CP : Charts) {
-        Chart *C = CP.second;
-        C->getModelsAsJson(Json);
-    }
-}
-
-#define WORKER_JOB_DETECTION_PREP 0
-#define WORKER_JOB_DETECTION_DIM_CHART 1
-#define WORKER_JOB_DETECTION_HOST_CHART 2
-#define WORKER_JOB_DETECTION_STATS 3
-#define WORKER_JOB_DETECTION_RESOURCES 4
-
-void Host::detectOnce() {
-    worker_is_busy(WORKER_JOB_DETECTION_PREP);
-
-    MLS = {};
-    MachineLearningStats MLSCopy = {};
-    TrainingStats TSCopy = {};
-
-    {
-        std::lock_guard<Mutex> L(M);
-
-        /*
-         * prediction/detection stats
-        */
-        for (auto &CP : Charts) {
-            Chart *C = CP.second;
-
-            if (!C->isAvailableForML())
-                continue;
-
-            MachineLearningStats ChartMLS = C->getMLS();
-
-            MLS.NumMachineLearningStatusEnabled += ChartMLS.NumMachineLearningStatusEnabled;
-            MLS.NumMachineLearningStatusDisabledUE += ChartMLS.NumMachineLearningStatusDisabledUE;
-            MLS.NumMachineLearningStatusDisabledSP += ChartMLS.NumMachineLearningStatusDisabledSP;
-
-            MLS.NumMetricTypeConstant += ChartMLS.NumMetricTypeConstant;
-            MLS.NumMetricTypeVariable += ChartMLS.NumMetricTypeVariable;
-
-            MLS.NumTrainingStatusUntrained += ChartMLS.NumTrainingStatusUntrained;
-            MLS.NumTrainingStatusPendingWithoutModel += ChartMLS.NumTrainingStatusPendingWithoutModel;
-            MLS.NumTrainingStatusTrained += ChartMLS.NumTrainingStatusTrained;
-            MLS.NumTrainingStatusPendingWithModel += ChartMLS.NumTrainingStatusPendingWithModel;
-
-            MLS.NumAnomalousDimensions += ChartMLS.NumAnomalousDimensions;
-            MLS.NumNormalDimensions += ChartMLS.NumNormalDimensions;
-        }
-
-        HostAnomalyRate = 0.0;
-        size_t NumActiveDimensions = MLS.NumAnomalousDimensions + MLS.NumNormalDimensions;
-        if (NumActiveDimensions)
-              HostAnomalyRate = static_cast<double>(MLS.NumAnomalousDimensions) / NumActiveDimensions;
-
-        MLSCopy = MLS;
-
-        /*
-         * training stats
-        */
-        TSCopy = TS;
-
-        TS.QueueSize = 0;
-        TS.NumPoppedItems = 0;
-
-        TS.AllottedUT = 0;
-        TS.ConsumedUT = 0;
-        TS.RemainingUT = 0;
-
-        TS.TrainingResultOk = 0;
-        TS.TrainingResultInvalidQueryTimeRange = 0;
-        TS.TrainingResultNotEnoughCollectedValues = 0;
-        TS.TrainingResultNullAcquiredDimension = 0;
-        TS.TrainingResultChartUnderReplication = 0;
-    }
-
-    // Calc the avg values
-    if (TSCopy.NumPoppedItems) {
-        TSCopy.QueueSize /= TSCopy.NumPoppedItems;
-        TSCopy.AllottedUT /= TSCopy.NumPoppedItems;
-        TSCopy.ConsumedUT /= TSCopy.NumPoppedItems;
-        TSCopy.RemainingUT /= TSCopy.NumPoppedItems;
-
-        TSCopy.TrainingResultOk /= TSCopy.NumPoppedItems;
-        TSCopy.TrainingResultInvalidQueryTimeRange /= TSCopy.NumPoppedItems;
-        TSCopy.TrainingResultNotEnoughCollectedValues /= TSCopy.NumPoppedItems;
-        TSCopy.TrainingResultNullAcquiredDimension /= TSCopy.NumPoppedItems;
-        TSCopy.TrainingResultChartUnderReplication /= TSCopy.NumPoppedItems;
-    } else {
-        TSCopy.QueueSize = 0;
-        TSCopy.AllottedUT = 0;
-        TSCopy.ConsumedUT = 0;
-        TSCopy.RemainingUT = 0;
-    }
-
-    if(!RH)
-        return;
-
-    worker_is_busy(WORKER_JOB_DETECTION_DIM_CHART);
-    updateDimensionsChart(RH, MLSCopy);
-
-    worker_is_busy(WORKER_JOB_DETECTION_HOST_CHART);
-    updateHostAndDetectionRateCharts(RH, HostAnomalyRate * 10000.0);
-
-#ifdef NETDATA_ML_RESOURCE_CHARTS
-    worker_is_busy(WORKER_JOB_DETECTION_RESOURCES);
-    struct rusage PredictionRU;
-    getrusage(RUSAGE_THREAD, &PredictionRU);
-    updateResourceUsageCharts(RH, PredictionRU, TSCopy.TrainingRU);
-#endif
-
-    worker_is_busy(WORKER_JOB_DETECTION_STATS);
-    updateTrainingStatisticsChart(RH, TSCopy);
-}
-
-class AcquiredDimension {
-public:
-    static AcquiredDimension find(RRDHOST *RH, STRING *ChartId, STRING *DimensionId) {
-        RRDDIM_ACQUIRED *AcqRD = nullptr;
-        Dimension *D = nullptr;
-
-        RRDSET *RS = rrdset_find(RH, string2str(ChartId));
-        if (RS) {
-            AcqRD = rrddim_find_and_acquire(RS, string2str(DimensionId));
-            if (AcqRD) {
-                RRDDIM *RD = rrddim_acquired_to_rrddim(AcqRD);
-                if (RD)
-                    D = reinterpret_cast<Dimension *>(RD->ml_dimension);
-            }
-        }
-
-        return AcquiredDimension(AcqRD, D);
-    }
-
-private:
-    AcquiredDimension(RRDDIM_ACQUIRED *AcqRD, Dimension *D) : AcqRD(AcqRD), D(D) {}
-
-public:
-    TrainingResult train(const TrainingRequest &TR) {
-        if (!D)
-            return TrainingResult::NullAcquiredDimension;
-
-        return D->trainModel(TR);
-    }
-
-    ~AcquiredDimension() {
-        if (AcqRD)
-            rrddim_acquired_release(AcqRD);
-    }
-
-private:
-    RRDDIM_ACQUIRED *AcqRD;
-    Dimension *D;
-};
-
-void Host::scheduleForTraining(TrainingRequest TR) {
-    TrainingQueue.push(TR);
-}
-
-#define WORKER_JOB_TRAINING_FIND 0
-#define WORKER_JOB_TRAINING_TRAIN 1
-#define WORKER_JOB_TRAINING_STATS 2
-
-void Host::train() {
-    worker_register("MLTRAIN");
-    worker_register_job_name(WORKER_JOB_TRAINING_FIND, "find");
-    worker_register_job_name(WORKER_JOB_TRAINING_TRAIN, "train");
-    worker_register_job_name(WORKER_JOB_TRAINING_STATS, "stats");
-
-    service_register(SERVICE_THREAD_TYPE_NETDATA, NULL, (force_quit_t )ml_cancel_anomaly_detection_threads, RH, true);
-
-    while (service_running(SERVICE_ML_TRAINING)) {
-        auto P = TrainingQueue.pop();
-        TrainingRequest TrainingReq = P.first;
-        size_t Size = P.second;
-
-        if (ThreadsCancelled) {
-            info("Stopping training thread because it was cancelled.");
-            break;
-        }
-
-        usec_t AllottedUT = (Cfg.TrainEvery * RH->rrd_update_every * USEC_PER_SEC) / Size;
-        if (AllottedUT > USEC_PER_SEC)
-            AllottedUT = USEC_PER_SEC;
-
-        usec_t StartUT = now_monotonic_usec();
-        TrainingResult TrainingRes;
-        {
-            worker_is_busy(WORKER_JOB_TRAINING_FIND);
-            AcquiredDimension AcqDim = AcquiredDimension::find(RH, TrainingReq.ChartId, TrainingReq.DimensionId);
-
-            worker_is_busy(WORKER_JOB_TRAINING_TRAIN);
-            TrainingRes = AcqDim.train(TrainingReq);
-
-            string_freez(TrainingReq.ChartId);
-            string_freez(TrainingReq.DimensionId);
-        }
-        usec_t ConsumedUT = now_monotonic_usec() - StartUT;
-
-        worker_is_busy(WORKER_JOB_TRAINING_STATS);
-
-        usec_t RemainingUT = 0;
-        if (ConsumedUT < AllottedUT)
-            RemainingUT = AllottedUT - ConsumedUT;
-
-        {
-            std::lock_guard<Mutex> L(M);
-
-            if (TS.AllottedUT == 0) {
-                struct rusage TRU;
-                getrusage(RUSAGE_THREAD, &TRU);
-                TS.TrainingRU = TRU;
-            }
-
-            TS.QueueSize += Size;
-            TS.NumPoppedItems += 1;
-
-            TS.AllottedUT += AllottedUT;
-            TS.ConsumedUT += ConsumedUT;
-            TS.RemainingUT += RemainingUT;
-
-            switch (TrainingRes) {
-                case TrainingResult::Ok:
-                    TS.TrainingResultOk += 1;
-                    break;
-                case TrainingResult::InvalidQueryTimeRange:
-                    TS.TrainingResultInvalidQueryTimeRange += 1;
-                    break;
-                case TrainingResult::NotEnoughCollectedValues:
-                    TS.TrainingResultNotEnoughCollectedValues += 1;
-                    break;
-                case TrainingResult::NullAcquiredDimension:
-                    TS.TrainingResultNullAcquiredDimension += 1;
-                    break;
-                case TrainingResult::ChartUnderReplication:
-                    TS.TrainingResultChartUnderReplication += 1;
-                    break;
-            }
-        }
-
-        worker_is_idle();
-        std::this_thread::sleep_for(std::chrono::microseconds{RemainingUT});
-        worker_is_busy(0);
-    }
-}
-
-void Host::detect() {
-    worker_register("MLDETECT");
-    worker_register_job_name(WORKER_JOB_DETECTION_PREP, "prep");
-    worker_register_job_name(WORKER_JOB_DETECTION_DIM_CHART, "dim chart");
-    worker_register_job_name(WORKER_JOB_DETECTION_HOST_CHART, "host chart");
-    worker_register_job_name(WORKER_JOB_DETECTION_STATS, "stats");
-    worker_register_job_name(WORKER_JOB_DETECTION_RESOURCES, "resources");
-
-    service_register(SERVICE_THREAD_TYPE_NETDATA, NULL, (force_quit_t )ml_cancel_anomaly_detection_threads, RH, true);
-
-    heartbeat_t HB;
-    heartbeat_init(&HB);
-
-    while (service_running((SERVICE_TYPE)(SERVICE_ML_PREDICTION | SERVICE_COLLECTORS))) {
-        worker_is_idle();
-        heartbeat_next(&HB, (RH ? RH->rrd_update_every : default_rrd_update_every) * USEC_PER_SEC);
-        detectOnce();
-    }
-}
-
-void Host::getDetectionInfoAsJson(nlohmann::json &Json) const {
-    Json["version"] = 1;
-    Json["anomalous-dimensions"] = MLS.NumAnomalousDimensions;
-    Json["normal-dimensions"] = MLS.NumNormalDimensions;
-    Json["total-dimensions"] = MLS.NumAnomalousDimensions + MLS.NumNormalDimensions;
-    Json["trained-dimensions"] = MLS.NumTrainingStatusTrained + MLS.NumTrainingStatusPendingWithModel;
-}
-
-void *train_main(void *Arg) {
-    Host *H = reinterpret_cast<Host *>(Arg);
-    H->train();
-    return nullptr;
-}
-
-void *detect_main(void *Arg) {
-    Host *H = reinterpret_cast<Host *>(Arg);
-    H->detect();
-    return nullptr;
-}
-
-void Host::startAnomalyDetectionThreads() {
-    if (ThreadsRunning) {
-        error("Anomaly detections threads for host %s are already-up and running.", rrdhost_hostname(RH));
-        return;
-    }
-
-    ThreadsRunning = true;
-    ThreadsCancelled = false;
-    ThreadsJoined = false;
-
-    char Tag[NETDATA_THREAD_TAG_MAX + 1];
-
-// #define ML_DISABLE_JOINING
-
-    snprintfz(Tag, NETDATA_THREAD_TAG_MAX, "MLTR[%s]", rrdhost_hostname(RH));
-    netdata_thread_create(&TrainingThread, Tag, NETDATA_THREAD_OPTION_JOINABLE, train_main, static_cast<void *>(this));
-
-    snprintfz(Tag, NETDATA_THREAD_TAG_MAX, "MLDT[%s]", rrdhost_hostname(RH));
-    netdata_thread_create(&DetectionThread, Tag, NETDATA_THREAD_OPTION_JOINABLE, detect_main, static_cast<void *>(this));
-}
-
-void Host::stopAnomalyDetectionThreads(bool join) {
-    if (!ThreadsRunning) {
-        error("Anomaly detections threads for host %s have already been stopped.", rrdhost_hostname(RH));
-        return;
-    }
-
-    if(!ThreadsCancelled) {
-        ThreadsCancelled = true;
-
-        // Signal the training queue to stop popping-items
-        TrainingQueue.signal();
-        netdata_thread_cancel(TrainingThread);
-        netdata_thread_cancel(DetectionThread);
-    }
-
-    if (join && !ThreadsJoined) {
-        ThreadsJoined = true;
-        ThreadsRunning = false;
-
-        // these fail on alpine linux and our CI hangs forever
-        // failing to compile static builds
-
-        // commenting them, until we find a solution
-
-        // to enable again:
-        // NETDATA_THREAD_OPTION_DEFAULT needs to become NETDATA_THREAD_OPTION_JOINABLE
-
-        netdata_thread_join(TrainingThread, nullptr);
-        netdata_thread_join(DetectionThread, nullptr);
-    }
-}