Refactor ML code and add support for multiple KMeans models (#14198)

* Add profile.plugin

Creates the specified number of charts/dimensions, and supports
backfilling with pseudo-historical data.

* Bump

* Remove wrongly merged line.

* Use the number of models specified from the config section.

* Add option to consult all ML models.

* Remove profiling option consuming all models.

* Add underscore after chart name prefix.

* prediction -> dimensions chart

* reorder funcs

* Split charts across types with correct priority

* Ignore training request when chart is under replication.

* Track global number of models consulted.

* Cleanup config.

* initial readme updates

* fix readme

* readme

* Fix function definition when ML is disabled.

* Add dummy ml_chart_update_{begin,end}

* Remove profile_plugin

* Define chart priorities under collectors/all.h

* s/curr_t/current_time/

* Use libnetdata's lock/thread wrappers.

* Fix autotools & cmake builds.

* Delete ML dimensions & charts.

* Let users of buffer preprocessing to handle memory.

* Add separate API calls to start/stop ML threads.

Co-authored-by: Andrew Maguire <andrewm4894@gmail.com>

1 files changed, 3 insertions, 3 deletions

diff --git a/ml/Config.cc b/ml/Config.cc
index eedd8c29fd..ba3a614452 100644
--- a/ml/Config.cc
+++ b/ml/Config.cc
@@ -31,7 +31,7 @@ void Config::readMLConfig(void) {
     unsigned MaxTrainSamples = config_get_number(ConfigSectionML, "maximum num samples to train", 4 * 3600);
     unsigned MinTrainSamples = config_get_number(ConfigSectionML, "minimum num samples to train", 1 * 900);
     unsigned TrainEvery = config_get_number(ConfigSectionML, "train every", 1 * 3600);
-    unsigned NumModelsToUse = config_get_number(ConfigSectionML, "number of models per dimension", 1 * 24);
+    unsigned NumModelsToUse = config_get_number(ConfigSectionML, "number of models per dimension", 1);
 
     unsigned DiffN = config_get_number(ConfigSectionML, "num samples to diff", 1);
     unsigned SmoothN = config_get_number(ConfigSectionML, "num samples to smooth", 3);
@@ -53,7 +53,7 @@ void Config::readMLConfig(void) {
     MaxTrainSamples = clamp<unsigned>(MaxTrainSamples, 1 * 3600, 24 * 3600);
     MinTrainSamples = clamp<unsigned>(MinTrainSamples, 1 * 900, 6 * 3600);
     TrainEvery = clamp<unsigned>(TrainEvery, 1 * 3600, 6 * 3600);
-    NumModelsToUse = clamp<unsigned>(TrainEvery, 1, 7 * 24);
+    NumModelsToUse = clamp<unsigned>(NumModelsToUse, 1, 7 * 24);
 
     DiffN = clamp(DiffN, 0u, 1u);
     SmoothN = clamp(SmoothN, 0u, 5u);
@@ -108,7 +108,7 @@ void Config::readMLConfig(void) {
     // Always exclude anomaly_detection charts from training.
     Cfg.ChartsToSkip = "anomaly_detection.* ";
     Cfg.ChartsToSkip += config_get(ConfigSectionML, "charts to skip from training", "netdata.*");
-    Cfg.SP_ChartsToSkip = simple_pattern_create(ChartsToSkip.c_str(), NULL, SIMPLE_PATTERN_EXACT);
+    Cfg.SP_ChartsToSkip = simple_pattern_create(Cfg.ChartsToSkip.c_str(), NULL, SIMPLE_PATTERN_EXACT);
 
     Cfg.StreamADCharts = config_get_boolean(ConfigSectionML, "stream anomaly detection charts", true);
 }