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-rw-r--r--ml/ml.cc17
1 files changed, 11 insertions, 6 deletions
diff --git a/ml/ml.cc b/ml/ml.cc
index 0bba2060..5f8f5033 100644
--- a/ml/ml.cc
+++ b/ml/ml.cc
@@ -621,7 +621,7 @@ bind_fail:
return rc;
}
-int ml_dimension_load_models(RRDDIM *rd) {
+int ml_dimension_load_models(RRDDIM *rd, sqlite3_stmt **active_stmt) {
ml_dimension_t *dim = (ml_dimension_t *) rd->ml_dimension;
if (!dim)
return 0;
@@ -635,7 +635,7 @@ int ml_dimension_load_models(RRDDIM *rd) {
std::vector<ml_kmeans_t> V;
- static __thread sqlite3_stmt *res = NULL;
+ sqlite3_stmt *res = active_stmt ? *active_stmt : NULL;
int rc = 0;
int param = 0;
@@ -645,18 +645,20 @@ int ml_dimension_load_models(RRDDIM *rd) {
}
if (unlikely(!res)) {
- rc = prepare_statement(db, db_models_load, &res);
+ rc = sqlite3_prepare_v2(db, db_models_load, -1, &res, NULL);
if (unlikely(rc != SQLITE_OK)) {
error_report("Failed to prepare statement to load models, rc = %d", rc);
return 1;
}
+ if (active_stmt)
+ *active_stmt = res;
}
rc = sqlite3_bind_blob(res, ++param, &dim->rd->metric_uuid, sizeof(dim->rd->metric_uuid), SQLITE_STATIC);
if (unlikely(rc != SQLITE_OK))
goto bind_fail;
- rc = sqlite3_bind_int(res, ++param, now_realtime_usec() - (Cfg.num_models_to_use * Cfg.max_train_samples));
+ rc = sqlite3_bind_int64(res, ++param, now_realtime_sec() - (Cfg.num_models_to_use * Cfg.max_train_samples));
if (unlikely(rc != SQLITE_OK))
goto bind_fail;
@@ -702,9 +704,12 @@ int ml_dimension_load_models(RRDDIM *rd) {
if (unlikely(rc != SQLITE_DONE))
error_report("Failed to load models, rc = %d", rc);
- rc = sqlite3_reset(res);
+ if (active_stmt)
+ rc = sqlite3_reset(res);
+ else
+ rc = sqlite3_finalize(res);
if (unlikely(rc != SQLITE_OK))
- error_report("Failed to reset statement when loading models, rc = %d", rc);
+ error_report("Failed to %s statement when loading models, rc = %d", active_stmt ? "reset" : "finalize", rc);
return 0;