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https://dev.mysql.com/doc/mysql-shell/9.4/en/admin-api-routing-guidelines.html
Optimizing traffic based on the specific connection attributes to ensure compatibility, performance, compliance, and so on. Routing Guidelines control MySQL Router's routing behavior, using rules defining the destinations of incoming client ...
https://dev.mysql.com/doc/mysql-shell/9.4/en/mysql-shell-utilities-debug-slowquery-diagnostics.html
About the Utility Requirements and Restrictions Running the Utility Options for Collecting Diagnostics About the Utility util.debug.collectSlowQueryDiagnostics() runs multiple iterations of diagnostic reporting on your MySQL server, enabling you to ...
https://dev.mysql.com/doc/mysql-shell/9.4/en/upgrade-mysql-clusterset.html
Please re-bootstrap the Routers to ensure the optimal configurations are set. To upgrade the server instances in an InnoDB ClusterSet, complete the following steps: Upgrade MySQL Router. Check the versions of the installed binaries: mysqlrouter ...
https://dev.mysql.com/doc/mysql-ai/9.4/en/index.html
It covers how to load data, run queries, optimize analytics workloads, and use machine learning and generative AI capabilities. For help with using MySQL, please visit the MySQL Forums, where you can discuss your issues with other MySQL users.
https://dev.mysql.com/doc/mysql-ai/9.4/en/mys-ai-aml-automl-workflow.html
AutoML analyzes the training data, trains an optimized machine learning model, and stores the model in a model catalog. A typical AutoML workflow is described below: When you run the ML_TRAIN routine, AutoML retrieves the data to use for training.
https://dev.mysql.com/doc/mysql-ai/9.4/en/mys-ai-aml-features.html
You provide the data, and AutoML analyzes the characteristics of the data and creates an optimized machine learning model that you can use to generate predictions and explanations. The AutoML feature of MySQL AI makes it easy to use machine ...
https://dev.mysql.com/doc/mysql-ai/9.4/en/mys-ai-aml-training-an-anomaly-detection-model.html
It identifies the optimal weight between the two components based on the metric. After preparing the data for an anomaly detection model, you can train the model. Requirements for Anomaly Detection Training Consider the following based on the type ...
https://dev.mysql.com/doc/mysql-ai/9.4/en/mys-ai-genai-overview.html
All the elements that are necessary to use GenAI with proprietary data are integrated and optimized to work with each other. The GenAI feature of MySQL AI lets you communicate with unstructured data using natural-language queries. It uses a ...
https://dev.mysql.com/doc/mysql-ai/9.4/en/mys-mysqlai-ml-score.html
ML_SCORE scores a model by generating predictions using the feature columns in a labeled dataset as input and comparing the predictions to ground truth values in the target column of the labeled dataset. The dataset used with ML_SCORE should have ...