HeatWave Release Notes
MySQL 9.0.0 introduces the
ML_MODEL_ACTIVE routine. Use this
routine to check which models are loaded and active for which
users. All active users and models share the amount of memory
defined by the shape, and it might be necessary to schedule
users.
mysql> CALL sys.ML_MODEL_ACTIVE (user, model_info);
ML_MODEL_ACTIVE parameters:
user: The user to provide information for. Set tocurrentorallorNULL.NULLis equivalent tocurrent.-
model_info: The name of the JSON array session variable that contains the active user and model information. There are two JSON object literals.If
useris set tocurrentorNULL, the following information displays.-
A JSON object literal that displays:
Key: The total model size (bytes).
Value: The sum of model sizes for the current user.
-
A second JSON object literal that displays:
Key: The model handle for a loaded and active model owned by the current user.
Value: The
model_metadatafor the model.
If
useris set toall, the following information displays.-
A JSON object literal that displays:
Key: The total model size (bytes).
Value: The sum of model sizes for all users.
-
A second JSON object literal that displays:
Key: The name of a user who has loaded and active models.
Value: A list of JSON object literals of the model handle and brief model metadata for each loaded and active model.
-
-
user1checks their own models:mysql> CALL sys.ML_MODEL_ACTIVE('current', @model_info); Query OK, 0 rows affected (0.10 sec) mysql> SELECT JSON_PRETTY(@model_info); +-----------------------------------------------------------+ | JSON_PRETTY(@model_info) | +-----------------------------------------------------------+ | [ | { | "total model size(bytes)": 348954 | }, | { | "iris_export_user1": { | "task": "classification", | "notes": "", | "chunks": 1, | "format": "HWMLv2.0", | "n_rows": 120, | "status": "Ready", | "options": { | "model_explainer": "permutation_importance, shap", | "prediction_explainer": "shap" | }, | "n_columns": 4, | "pos_class": null, | "column_names": [ | "sepal length", | "sepal width", | "petal length", | "petal width" | ], | "contamination": null, | "model_quality": "high", | "training_time": 18.363686, | "algorithm_name": "ExtraTreesClassifier", | "training_score": -0.10970368035588404, | "build_timestamp": 1697524180, | "n_selected_rows": 96, | "training_params": { | "sp_arr": null, | "timezone": null, | "recommend": "ratings", | "force_use_X": false, | "recommend_k": 3, | "remove_seen": true, | "contamination": null, | "feedback_threshold": 1 | }, | "train_table_name": "mlcorpus.iris_train", | "model_explanation": { | "shap": { | "petal width": 0.3139, | "sepal width": 0.0296, | "petal length": 0.2787, | "sepal length": 0.0462 | }, | "permutation_importance": { | "petal width": 0.2301, | "sepal width": 0.0056, | "petal length": 0.2192, | "sepal length": 0.0056 | } | }, | "model_object_size": 348954, | "n_selected_columns": 4, | "target_column_name": "class", | "optimization_metric": "neg_log_loss", | "selected_column_names": [ | "petal length", | "petal width", | "sepal length", | "sepal width" | ] | } | } | ] | | +-----------------------------------------------------------+ 1 row in set (0.00 sec) -
user1checks their own models, and extracts specific information:mysql> CALL sys.ML_MODEL_ACTIVE('current', @model_info); Query OK, 0 rows affected (0.12 sec) mysql> SELECT JSON_KEYS(JSON_EXTRACT(@model_info, '$[1]')); +------------------------------------------------------------+ | JSON_KEYS(JSON_EXTRACT(@model_info, '$[1]')) | +------------------------------------------------------------+ | ["iris_export", "mlcorpus.iris_train_user1_1697524152037"] | +------------------------------------------------------------+ 1 row in set (0.00 sec) mysql> SELECT JSON_EXTRACT(@model_info, '$[0]'); +--------------------------------------+ | JSON_EXTRACT(@model_info, '$[0]') | +--------------------------------------+ | {"total model size(bytes)": 697908} | +--------------------------------------+ 1 row in set (0.01 sec) -
user1checks the models for all users:mysql> CALL sys.ML_MODEL_ACTIVE('all', @model_info); Query OK, 0 rows affected (0.11 sec) mysql> SELECT JSON_PRETTY(@model_info); +-----------------------------------------------------+ | JSON_PRETTY(@model_info) | +-----------------------------------------------------+ | [ | { | "total model size(bytes)": 1046862 | }, | { | "user2": [ | { | "iris_export_user2": { | "format": "HWMLv2.0", | "model_size(byte)": 348954 | } | } | ], | "user1": [ | { | "mlcorpus.iris_train_user1_1697524152037": { | "format": "HWMLv2.0", | "model_size(byte)": 348954 | } | }, | { | "iris_export": { | "format": "HWMLv2.0", | "model_size(byte)": 348954 | } | } | ] | } | ] | | +-----------------------------------------------------+ 1 row in set (0.00 sec)