diff options
Diffstat (limited to 'ml/ad_charts.cc')
-rw-r--r-- | ml/ad_charts.cc | 167 |
1 files changed, 98 insertions, 69 deletions
diff --git a/ml/ad_charts.cc b/ml/ad_charts.cc index a32ff6c650..086cd5aa02 100644 --- a/ml/ad_charts.cc +++ b/ml/ad_charts.cc @@ -6,7 +6,7 @@ void ml_update_dimensions_chart(ml_host_t *host, const ml_machine_learning_stats /* * Machine learning status */ - { + if (Cfg.enable_statistics_charts) { if (!host->machine_learning_status_rs) { char id_buf[1024]; char name_buf[1024]; @@ -48,7 +48,7 @@ void ml_update_dimensions_chart(ml_host_t *host, const ml_machine_learning_stats /* * Metric type */ - { + if (Cfg.enable_statistics_charts) { if (!host->metric_type_rs) { char id_buf[1024]; char name_buf[1024]; @@ -90,7 +90,7 @@ void ml_update_dimensions_chart(ml_host_t *host, const ml_machine_learning_stats /* * Training status */ - { + if (Cfg.enable_statistics_charts) { if (!host->training_status_rs) { char id_buf[1024]; char name_buf[1024]; @@ -179,7 +179,6 @@ void ml_update_dimensions_chart(ml_host_t *host, const ml_machine_learning_stats rrdset_done(host->dimensions_rs); } - } void ml_update_host_and_detection_rate_charts(ml_host_t *host, collected_number AnomalyRate) { @@ -301,20 +300,20 @@ void ml_update_host_and_detection_rate_charts(ml_host_t *host, collected_number } } -void ml_update_training_statistics_chart(ml_host_t *host, const ml_training_stats_t &ts) { +void ml_update_training_statistics_chart(ml_training_thread_t *training_thread, const ml_training_stats_t &ts) { /* * queue stats */ { - if (!host->queue_stats_rs) { + if (!training_thread->queue_stats_rs) { char id_buf[1024]; char name_buf[1024]; - snprintfz(id_buf, 1024, "queue_stats_on_%s", localhost->machine_guid); - snprintfz(name_buf, 1024, "queue_stats_on_%s", rrdhost_hostname(localhost)); + snprintfz(id_buf, 1024, "training_queue_%zu_stats", training_thread->id); + snprintfz(name_buf, 1024, "training_queue_%zu_stats", training_thread->id); - host->queue_stats_rs = rrdset_create( - host->rh, + training_thread->queue_stats_rs = rrdset_create( + localhost, "netdata", // type id_buf, // id name_buf, // name @@ -328,35 +327,35 @@ void ml_update_training_statistics_chart(ml_host_t *host, const ml_training_stat localhost->rrd_update_every, // update_every RRDSET_TYPE_LINE// chart_type ); - rrdset_flag_set(host->queue_stats_rs, RRDSET_FLAG_ANOMALY_DETECTION); + rrdset_flag_set(training_thread->queue_stats_rs, RRDSET_FLAG_ANOMALY_DETECTION); - host->queue_stats_queue_size_rd = - rrddim_add(host->queue_stats_rs, "queue_size", NULL, 1, 1, RRD_ALGORITHM_ABSOLUTE); - host->queue_stats_popped_items_rd = - rrddim_add(host->queue_stats_rs, "popped_items", NULL, 1, 1, RRD_ALGORITHM_ABSOLUTE); + training_thread->queue_stats_queue_size_rd = + rrddim_add(training_thread->queue_stats_rs, "queue_size", NULL, 1, 1, RRD_ALGORITHM_ABSOLUTE); + training_thread->queue_stats_popped_items_rd = + rrddim_add(training_thread->queue_stats_rs, "popped_items", NULL, 1, 1, RRD_ALGORITHM_ABSOLUTE); } - rrddim_set_by_pointer(host->queue_stats_rs, - host->queue_stats_queue_size_rd, ts.queue_size); - rrddim_set_by_pointer(host->queue_stats_rs, - host->queue_stats_popped_items_rd, ts.num_popped_items); + rrddim_set_by_pointer(training_thread->queue_stats_rs, + training_thread->queue_stats_queue_size_rd, ts.queue_size); + rrddim_set_by_pointer(training_thread->queue_stats_rs, + training_thread->queue_stats_popped_items_rd, ts.num_popped_items); - rrdset_done(host->queue_stats_rs); + rrdset_done(training_thread->queue_stats_rs); } /* * training stats */ { - if (!host->training_time_stats_rs) { + if (!training_thread->training_time_stats_rs) { char id_buf[1024]; char name_buf[1024]; - snprintfz(id_buf, 1024, "training_time_stats_on_%s", localhost->machine_guid); - snprintfz(name_buf, 1024, "training_time_stats_on_%s", rrdhost_hostname(localhost)); + snprintfz(id_buf, 1024, "training_queue_%zu_time_stats", training_thread->id); + snprintfz(name_buf, 1024, "training_queue_%zu_time_stats", training_thread->id); - host->training_time_stats_rs = rrdset_create( - host->rh, + training_thread->training_time_stats_rs = rrdset_create( + localhost, "netdata", // type id_buf, // id name_buf, // name @@ -370,39 +369,39 @@ void ml_update_training_statistics_chart(ml_host_t *host, const ml_training_stat localhost->rrd_update_every, // update_every RRDSET_TYPE_LINE// chart_type ); - rrdset_flag_set(host->training_time_stats_rs, RRDSET_FLAG_ANOMALY_DETECTION); - - host->training_time_stats_allotted_rd = - rrddim_add(host->training_time_stats_rs, "allotted", NULL, 1, 1000, RRD_ALGORITHM_ABSOLUTE); - host->training_time_stats_consumed_rd = - rrddim_add(host->training_time_stats_rs, "consumed", NULL, 1, 1000, RRD_ALGORITHM_ABSOLUTE); - host->training_time_stats_remaining_rd = - rrddim_add(host->training_time_stats_rs, "remaining", NULL, 1, 1000, RRD_ALGORITHM_ABSOLUTE); + rrdset_flag_set(training_thread->training_time_stats_rs, RRDSET_FLAG_ANOMALY_DETECTION); + + training_thread->training_time_stats_allotted_rd = + rrddim_add(training_thread->training_time_stats_rs, "allotted", NULL, 1, 1000, RRD_ALGORITHM_ABSOLUTE); + training_thread->training_time_stats_consumed_rd = + rrddim_add(training_thread->training_time_stats_rs, "consumed", NULL, 1, 1000, RRD_ALGORITHM_ABSOLUTE); + training_thread->training_time_stats_remaining_rd = + rrddim_add(training_thread->training_time_stats_rs, "remaining", NULL, 1, 1000, RRD_ALGORITHM_ABSOLUTE); } - rrddim_set_by_pointer(host->training_time_stats_rs, - host->training_time_stats_allotted_rd, ts.allotted_ut); - rrddim_set_by_pointer(host->training_time_stats_rs, - host->training_time_stats_consumed_rd, ts.consumed_ut); - rrddim_set_by_pointer(host->training_time_stats_rs, - host->training_time_stats_remaining_rd, ts.remaining_ut); + rrddim_set_by_pointer(training_thread->training_time_stats_rs, + training_thread->training_time_stats_allotted_rd, ts.allotted_ut); + rrddim_set_by_pointer(training_thread->training_time_stats_rs, + training_thread->training_time_stats_consumed_rd, ts.consumed_ut); + rrddim_set_by_pointer(training_thread->training_time_stats_rs, + training_thread->training_time_stats_remaining_rd, ts.remaining_ut); - rrdset_done(host->training_time_stats_rs); + rrdset_done(training_thread->training_time_stats_rs); } /* * training result stats */ { - if (!host->training_results_rs) { + if (!training_thread->training_results_rs) { char id_buf[1024]; char name_buf[1024]; - snprintfz(id_buf, 1024, "training_results_on_%s", localhost->machine_guid); - snprintfz(name_buf, 1024, "training_results_on_%s", rrdhost_hostname(localhost)); + snprintfz(id_buf, 1024, "training_queue_%zu_results", training_thread->id); + snprintfz(name_buf, 1024, "training_queue_%zu_results", training_thread->id); - host->training_results_rs = rrdset_create( - host->rh, + training_thread->training_results_rs = rrdset_create( + localhost, "netdata", // type id_buf, // id name_buf, // name @@ -416,31 +415,61 @@ void ml_update_training_statistics_chart(ml_host_t *host, const ml_training_stat localhost->rrd_update_every, // update_every RRDSET_TYPE_LINE// chart_type ); - rrdset_flag_set(host->training_results_rs, RRDSET_FLAG_ANOMALY_DETECTION); - - host->training_results_ok_rd = - rrddim_add(host->training_results_rs, "ok", NULL, 1, 1, RRD_ALGORITHM_ABSOLUTE); - host->training_results_invalid_query_time_range_rd = - rrddim_add(host->training_results_rs, "invalid-queries", NULL, 1, 1, RRD_ALGORITHM_ABSOLUTE); - host->training_results_not_enough_collected_values_rd = - rrddim_add(host->training_results_rs, "not-enough-values", NULL, 1, 1, RRD_ALGORITHM_ABSOLUTE); - host->training_results_null_acquired_dimension_rd = - rrddim_add(host->training_results_rs, "null-acquired-dimensions", NULL, 1, 1, RRD_ALGORITHM_ABSOLUTE); - host->training_results_chart_under_replication_rd = - rrddim_add(host->training_results_rs, "chart-under-replication", NULL, 1, 1, RRD_ALGORITHM_ABSOLUTE); + rrdset_flag_set(training_thread->training_results_rs, RRDSET_FLAG_ANOMALY_DETECTION); + + training_thread->training_results_ok_rd = + rrddim_add(training_thread->training_results_rs, "ok", NULL, 1, 1, RRD_ALGORITHM_ABSOLUTE); + training_thread->training_results_invalid_query_time_range_rd = + rrddim_add(training_thread->training_results_rs, "invalid-queries", NULL, 1, 1, RRD_ALGORITHM_ABSOLUTE); + training_thread->training_results_not_enough_collected_values_rd = + rrddim_add(training_thread->training_results_rs, "not-enough-values", NULL, 1, 1, RRD_ALGORITHM_ABSOLUTE); + training_thread->training_results_null_acquired_dimension_rd = + rrddim_add(training_thread->training_results_rs, "null-acquired-dimensions", NULL, 1, 1, RRD_ALGORITHM_ABSOLUTE); + training_thread->training_results_chart_under_replication_rd = + rrddim_add(training_thread->training_results_rs, "chart-under-replication", NULL, 1, 1, RRD_ALGORITHM_ABSOLUTE); } - rrddim_set_by_pointer(host->training_results_rs, - host->training_results_ok_rd, ts.training_result_ok); - rrddim_set_by_pointer(host->training_results_rs, - host->training_results_invalid_query_time_range_rd, ts.training_result_invalid_query_time_range); - rrddim_set_by_pointer(host->training_results_rs, - host->training_results_not_enough_collected_values_rd, ts.training_result_not_enough_collected_values); - rrddim_set_by_pointer(host->training_results_rs, - host->training_results_null_acquired_dimension_rd, ts.training_result_null_acquired_dimension); - rrddim_set_by_pointer(host->training_results_rs, - host->training_results_chart_under_replication_rd, ts.training_result_chart_under_replication); - - rrdset_done(host->training_results_rs); + rrddim_set_by_pointer(training_thread->training_results_rs, + training_thread->training_results_ok_rd, ts.training_result_ok); + rrddim_set_by_pointer(training_thread->training_results_rs, + training_thread->training_results_invalid_query_time_range_rd, ts.training_result_invalid_query_time_range); + rrddim_set_by_pointer(training_thread->training_results_rs, + training_thread->training_results_not_enough_collected_values_rd, ts.training_result_not_enough_collected_values); + rrddim_set_by_pointer(training_thread->training_results_rs, + training_thread->training_results_null_acquired_dimension_rd, ts.training_result_null_acquired_dimension); + rrddim_set_by_pointer(training_thread->training_results_rs, + training_thread->training_results_chart_under_replication_rd, ts.training_result_chart_under_replication); + + rrdset_done(training_thread->training_results_rs); + } +} + +void ml_update_global_statistics_charts(uint64_t models_consulted) { + if (Cfg.enable_statistics_charts) { + static RRDSET *st = NULL; + static RRDDIM *rd = NULL; + + if (unlikely(!st)) { + st = rrdset_create_localhost( + "netdata" // type + , "ml_models_consulted" // id + , NULL // name + , NETDATA_ML_CHART_FAMILY // family + , NULL // context + , "KMeans models used for prediction" // title + , "models" // units + , NETDATA_ML_PLUGIN // plugin + , NETDATA_ML_MODULE_DETECTION // module + , NETDATA_ML_CHART_PRIO_MACHINE_LEARNING_STATUS // priority + , localhost->rrd_update_every // update_every + , RRDSET_TYPE_AREA // chart_type + ); + + rd = rrddim_add(st, "num_models_consulted", NULL, 1, 1, RRD_ALGORITHM_INCREMENTAL); + } + + rrddim_set_by_pointer(st, rd, (collected_number) models_consulted); + + rrdset_done(st); } } |