1 files changed, 165 insertions, 0 deletions
diff --git a/ml/ml.cc b/ml/ml.cc
new file mode 100644
index 0000000..1a7d6ae
--- /dev/null
+++ b/ml/ml.cc
@@ -0,0 +1,165 @@
+// SPDX-License-Identifier: GPL-3.0-or-later
+
+#include "Config.h"
+#include "Dimension.h"
+#include "Host.h"
+
+#include <random>
+
+using namespace ml;
+
+bool ml_capable() {
+    return true;
+}
+
+bool ml_enabled(RRDHOST *RH) {
+    if (!Cfg.EnableAnomalyDetection)
+        return false;
+
+    if (simple_pattern_matches(Cfg.SP_HostsToSkip, rrdhost_hostname(RH)))
+        return false;
+
+    return true;
+}
+
+/*
+ * Assumptions:
+ *  1) hosts outlive their sets, and sets outlive their dimensions,
+ *  2) dimensions always have a set that has a host.
+ */
+
+void ml_init(void) {
+    // Read config values
+    Cfg.readMLConfig();
+
+    if (!Cfg.EnableAnomalyDetection)
+        return;
+
+    // Generate random numbers to efficiently sample the features we need
+    // for KMeans clustering.
+    std::random_device RD;
+    std::mt19937 Gen(RD());
+
+    Cfg.RandomNums.reserve(Cfg.MaxTrainSamples);
+    for (size_t Idx = 0; Idx != Cfg.MaxTrainSamples; Idx++)
+        Cfg.RandomNums.push_back(Gen());
+}
+
+void ml_new_host(RRDHOST *RH) {
+    if (!ml_enabled(RH))
+        return;
+
+    Host *H = new Host(RH);
+    RH->ml_host = static_cast<ml_host_t>(H);
+
+    H->startAnomalyDetectionThreads();
+}
+
+void ml_delete_host(RRDHOST *RH) {
+    Host *H = static_cast<Host *>(RH->ml_host);
+    if (!H)
+        return;
+
+    H->stopAnomalyDetectionThreads();
+
+    delete H;
+    RH->ml_host = nullptr;
+}
+
+void ml_new_dimension(RRDDIM *RD) {
+    RRDSET *RS = RD->rrdset;
+
+    Host *H = static_cast<Host *>(RD->rrdset->rrdhost->ml_host);
+    if (!H)
+        return;
+
+    if (static_cast<unsigned>(RD->update_every) != H->updateEvery())
+        return;
+
+    if (simple_pattern_matches(Cfg.SP_ChartsToSkip, rrdset_name(RS)))
+        return;
+
+    Dimension *D = new Dimension(RD);
+    RD->ml_dimension = static_cast<ml_dimension_t>(D);
+    H->addDimension(D);
+}
+
+void ml_delete_dimension(RRDDIM *RD) {
+    Dimension *D = static_cast<Dimension *>(RD->ml_dimension);
+    if (!D)
+        return;
+
+    Host *H = static_cast<Host *>(RD->rrdset->rrdhost->ml_host);
+    if (!H)
+        delete D;
+    else
+        H->removeDimension(D);
+
+    RD->ml_dimension = nullptr;
+}
+
+char *ml_get_host_info(RRDHOST *RH) {
+    nlohmann::json ConfigJson;
+
+    if (RH && RH->ml_host) {
+        Host *H = static_cast<Host *>(RH->ml_host);
+        H->getConfigAsJson(ConfigJson);
+    } else {
+        ConfigJson["enabled"] = false;
+    }
+
+    return strdupz(ConfigJson.dump(2, '\t').c_str());
+}
+
+char *ml_get_host_runtime_info(RRDHOST *RH) {
+    nlohmann::json ConfigJson;
+
+    if (RH && RH->ml_host) {
+        Host *H = static_cast<Host *>(RH->ml_host);
+        H->getDetectionInfoAsJson(ConfigJson);
+    } else {
+        return nullptr;
+    }
+
+    return strdup(ConfigJson.dump(1, '\t').c_str());
+}
+
+char *ml_get_host_models(RRDHOST *RH) {
+    nlohmann::json ModelsJson;
+
+    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 nullptr;
+}
+
+bool ml_is_anomalous(RRDDIM *RD, double Value, bool Exists) {
+    Dimension *D = static_cast<Dimension *>(RD->ml_dimension);
+    if (!D)
+        return false;
+
+    return D->predict(Value, Exists);
+}
+
+bool ml_streaming_enabled() {
+    return Cfg.StreamADCharts;
+}
+
+#if defined(ENABLE_ML_TESTS)
+
+#include "gtest/gtest.h"
+
+int test_ml(int argc, char *argv[]) {
+    (void) argc;
+    (void) argv;
+
+    ::testing::InitGoogleTest(&argc, argv);
+    return RUN_ALL_TESTS();
+}
+
+#endif // ENABLE_ML_TESTS
+
+#include "ml-private.h"