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https://dev.mysql.com/doc/mysql-secure-deployment-guide/8.0/en/secure-deployment-post-install.html
If you do not intend to permit import or export operations, set secure_file_priv to NULL, which disables import and export operations entirely. Post-installation setup involves creating a safe directory for import and export operations, configuring ...
https://dev.mysql.com/doc/x-devapi-userguide-shell-js/en/mysql-x-expressions-ebnf-definitions.html
This section provides a visual reference guide to the grammar for the expression language used in X DevAPI.
https://dev.mysql.com/doc/x-devapi-userguide-shell-python/en/mysql-x-expressions-ebnf-definitions.html
This section provides a visual reference guide to the grammar for the expression language used in X DevAPI.
https://dev.mysql.com/doc/heatwave/en/mys-hw-lakehouse-export-query-result-outputfile.html
Exported query results are in CSV, Parquet, or JSON (As of MySQL 9.3.1) format. The number of output files and size of individual files depends on the amount of data generated by the query. The names for the output files are auto-generated and ...
https://dev.mysql.com/doc/heatwave/en/mys-hw-reload-tables.html
mysql> CALL sys.HEATWAVE_RELOAD([options]); options: { JSON_OBJECT("key","value"[,"key","value"] ...) "key","value": { ["only_user_loaded_tables",{true|false}] ["output",{"normal"|"silent"}] } } Use key-value pairs in JSON format to specify options.
https://dev.mysql.com/doc/heatwave/en/mys-hwaml-ease-of-use.html
For example: CALL sys.ML_TRAIN('heatwaveml_bench.census_train', 'revenue', NULL, @census_model); The ML_TRAIN routine leverages Oracle AutoML technology to automate training of machine learning models. For example, the following call to the ...With ...
https://dev.mysql.com/doc/heatwave/en/mys-hwaml-onnx-metadata.html
If the task is NULL, do not provide predictions_name or prediction_probabilities_name as this causes an error. To learn more about model metadata in the model catalog, see Model Metadata. ONNX Inputs Info Use the data_types_map to map the data type ...
https://dev.mysql.com/doc/heatwave/en/mys-hwaml-prepare-a-forecasting-model.html
mysql> CREATE TABLE electricity_demand ( date DATE PRIMARY KEY, demand FLOAT NOT NULL, temperature FLOAT NOT NULL ); Insert the sample data into the table. This topic describes how to prepare the data to use for a forecasting machine learning model. To prepare the data for this use case, you set up a training dataset and a testing ...
https://dev.mysql.com/doc/heatwave/en/mys-hwaml-supervised-learning.html
The dataset for this type of model must have a column whose only allowed values are 0 (normal), 1, (anomalous), and NULL (unlabeled). All rows in the dataset are used to train the unsupervised component, while the rows with a value different than ...
https://dev.mysql.com/doc/heatwave/en/mys-hwaml-topic-modeling-train.html
mysql> CALL sys.ML_TRAIN('topic_modeling_data.movies', NULL, JSON_OBJECT('task', 'topic_modeling', 'document_column', 'description'), @model); Where: topic_modeling_data.movies is the fully qualified name of the table that contains the training ...