1 files changed, 13 insertions, 86 deletions

diff --git a/ml/ml.cc b/ml/ml.cc
index 7275d88b..1a7d6ae2 100644
--- a/ml/ml.cc
+++ b/ml/ml.cc
@@ -16,7 +16,7 @@ bool ml_enabled(RRDHOST *RH) {
     if (!Cfg.EnableAnomalyDetection)
         return false;
 
-    if (simple_pattern_matches(Cfg.SP_HostsToSkip, RH->hostname))
+    if (simple_pattern_matches(Cfg.SP_HostsToSkip, rrdhost_hostname(RH)))
         return false;
 
     return true;
@@ -76,7 +76,7 @@ void ml_new_dimension(RRDDIM *RD) {
     if (static_cast<unsigned>(RD->update_every) != H->updateEvery())
         return;
 
-    if (simple_pattern_matches(Cfg.SP_ChartsToSkip, RS->name))
+    if (simple_pattern_matches(Cfg.SP_ChartsToSkip, rrdset_name(RS)))
         return;
 
     Dimension *D = new Dimension(RD);
@@ -108,7 +108,7 @@ char *ml_get_host_info(RRDHOST *RH) {
         ConfigJson["enabled"] = false;
     }
 
-    return strdup(ConfigJson.dump(2, '\t').c_str());
+    return strdupz(ConfigJson.dump(2, '\t').c_str());
 }
 
 char *ml_get_host_runtime_info(RRDHOST *RH) {
@@ -124,97 +124,24 @@ char *ml_get_host_runtime_info(RRDHOST *RH) {
     return strdup(ConfigJson.dump(1, '\t').c_str());
 }
 
-bool ml_is_anomalous(RRDDIM *RD, double Value, bool Exists) {
-    Dimension *D = static_cast<Dimension *>(RD->ml_dimension);
-    if (!D)
-        return false;
-
-    D->addValue(Value, Exists);
-    bool Result = D->predict().second;
-    return Result;
-}
-
-char *ml_get_anomaly_events(RRDHOST *RH, const char *AnomalyDetectorName,
-                            int AnomalyDetectorVersion, time_t After, time_t Before) {
-    if (!RH || !RH->ml_host) {
-        error("No host");
-        return nullptr;
-    }
-
-    Host *H = static_cast<Host *>(RH->ml_host);
-    std::vector<std::pair<time_t, time_t>> TimeRanges;
-
-    bool Res = H->getAnomaliesInRange(TimeRanges, AnomalyDetectorName,
-                                                  AnomalyDetectorVersion,
-                                                  H->getUUID(),
-                                                  After, Before);
-    if (!Res) {
-        error("DB result is empty");
-        return nullptr;
-    }
-
-    nlohmann::json Json = TimeRanges;
-    return strdup(Json.dump(4).c_str());
-}
-
-char *ml_get_anomaly_event_info(RRDHOST *RH, const char *AnomalyDetectorName,
-                                int AnomalyDetectorVersion, time_t After, time_t Before) {
-    if (!RH || !RH->ml_host) {
-        error("No host");
-        return nullptr;
-    }
-
-    Host *H = static_cast<Host *>(RH->ml_host);
+char *ml_get_host_models(RRDHOST *RH) {
+    nlohmann::json ModelsJson;
 
-    nlohmann::json Json;
-    bool Res = H->getAnomalyInfo(Json, AnomalyDetectorName,
-                                       AnomalyDetectorVersion,
-                                       H->getUUID(),
-                                       After, Before);
-    if (!Res) {
-        error("DB result is empty");
-        return nullptr;
+    if (RH && RH->ml_host) {
+        Host *H = static_cast<Host *>(RH->ml_host);
+        H->getModelsAsJson(ModelsJson);
+        return strdup(ModelsJson.dump(2, '\t').c_str());
     }
 
-    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;
-
-    NETDATA_DOUBLE *CNs = R->v;
-    RRDR_DIMENSION_FLAGS *DimFlags = R->od;
-
-    std::vector<std::pair<NETDATA_DOUBLE, 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);
-    }
+    return nullptr;
 }
 
-void ml_dimension_update_name(RRDSET *RS, RRDDIM *RD, const char *Name) {
-    (void) RS;
-
+bool ml_is_anomalous(RRDDIM *RD, double Value, bool Exists) {
     Dimension *D = static_cast<Dimension *>(RD->ml_dimension);
     if (!D)
-        return;
+        return false;
 
-    D->setAnomalyRateRDName(Name);
+    return D->predict(Value, Exists);
 }
 
 bool ml_streaming_enabled() {