Skip ML initialization when it's been disabled in netdata.conf (#14920)

* Apply ML changes again.

The ML changes in 003df5f2 wheere reverted with
556bdad9 because we were partially initializing
ML even when it was explicitly disabled in
netdata.conf, causing the agent to crash on
startup.

* Do not start/stop ML threads when ML is disabled.

* Restore default config settings.

1 files changed, 29 insertions, 13 deletions

diff --git a/ml/ml-private.h b/ml/ml-private.h
index 173b82e265..d014c71d26 100644
--- a/ml/ml-private.h
+++ b/ml/ml-private.h
@@ -33,14 +33,15 @@ typedef struct {
 /*
  * KMeans
  */
-typedef struct {
-    size_t num_clusters;
-    size_t max_iterations;
 
+typedef struct {
     std::vector<DSample> cluster_centers;
 
     calculated_number_t min_dist;
     calculated_number_t max_dist;
+
+    uint32_t after;
+    uint32_t before;
 } ml_kmeans_t;
 
 typedef struct machine_learning_stats_t {
@@ -123,6 +124,7 @@ enum ml_training_result {
 
 typedef struct {
     // Chart/dimension we want to train
+    STRING *host_id;
     STRING *chart_id;
     STRING *dimension_id;
 
@@ -168,6 +170,7 @@ typedef struct {
 /*
  * Queue
 */
+
 typedef struct {
     std::queue<ml_training_request_t> internal;
     netdata_mutex_t mutex;
@@ -175,7 +178,6 @@ typedef struct {
     std::atomic<bool> exit;
 } ml_queue_t;
 
-
 typedef struct {
     RRDDIM *rd;
 
@@ -207,19 +209,12 @@ typedef struct {
     RRDHOST *rh;
 
     ml_machine_learning_stats_t mls;
-    ml_training_stats_t ts;
 
     calculated_number_t host_anomaly_rate;
 
-    std::atomic<bool> threads_running;
-    std::atomic<bool> threads_cancelled;
-    std::atomic<bool> threads_joined;
-
-    ml_queue_t *training_queue;
-
     netdata_mutex_t mutex;
 
-    netdata_thread_t training_thread;
+    ml_queue_t *training_queue;
 
     /*
      * bookkeeping for anomaly detection charts
@@ -249,6 +244,19 @@ typedef struct {
     RRDSET *detector_events_rs;
     RRDDIM *detector_events_above_threshold_rd;
     RRDDIM *detector_events_new_anomaly_event_rd;
+} ml_host_t;
+
+typedef struct {
+    size_t id;
+    netdata_thread_t nd_thread;
+    netdata_mutex_t nd_mutex;
+
+    ml_queue_t *training_queue;
+    ml_training_stats_t training_stats;
+
+    calculated_number_t *training_cns;
+    calculated_number_t *scratch_training_cns;
+    std::vector<DSample> training_samples;
 
     RRDSET *queue_stats_rs;
     RRDDIM *queue_stats_queue_size_rd;
@@ -265,7 +273,7 @@ typedef struct {
     RRDDIM *training_results_not_enough_collected_values_rd;
     RRDDIM *training_results_null_acquired_dimension_rd;
     RRDDIM *training_results_chart_under_replication_rd;
-} ml_host_t;
+} ml_training_thread_t;
 
 typedef struct {
     bool enable_anomaly_detection;
@@ -302,6 +310,14 @@ typedef struct {
     std::vector<uint32_t> random_nums;
 
     netdata_thread_t detection_thread;
+    std::atomic<bool> detection_stop;
+
+    size_t num_training_threads;
+
+    std::vector<ml_training_thread_t> training_threads;
+    std::atomic<bool> training_stop;
+
+    bool enable_statistics_charts;
 } ml_config_t;
 
 void ml_config_load(ml_config_t *cfg);