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https://dev.mysql.com/doc/refman/8.4/en/audit-log-filter-definitions.html
The AUDIT_ABORT_EXEMPT privilege is available to permit a user account’s queries to always be executed even if an abort item would block them. Table 8.40 audit_log_policy_value Values Value Corresponding audit_log_policy Value 0 or "::none" NONE 1 ...For information about using JSON data in MySQL, see Section 13.5, “The JSON Data ...
https://dev.mysql.com/doc/refman/8.4/en/cost-model.html
To generate execution plans, the optimizer uses a cost model that is based on estimates of the cost of various operations that occur during query execution. The optimizer has a set of compiled-in default “cost constants” available to it to make ...
https://dev.mysql.com/doc/refman/8.4/en/json-utility-functions.html
This section documents utility functions that act on JSON values, or strings that can be parsed as JSON values. JSON_PRETTY() prints out a JSON value in a format that is easy to read. JSON_STORAGE_SIZE() and JSON_STORAGE_FREE() show, respectively, ...
https://dev.mysql.com/doc/mysql-ai/9.5/en/mys-mysqlai-ml-train.html
Run the ML_TRAIN routine on a training dataset to produce a trained machine learning model. Before training models, make sure to review the following: Additional AutoML Requirements Supported Data Types for AutoML Train a Model Machine Learning Use ...
https://dev.mysql.com/doc/heatwave/en/mys-hwgenai-hw-chat.html
The HEATWAVE_CHAT routine automatically calls the ML_RAG routine which loads an LLM and runs a semantic search on the available vector stores by default. If the routine cannot find a vector store, then it calls the ML_GENERATE routine and uses ...
https://dev.mysql.com/doc/heatwave/en/mys-hwgenai-ml-rag.html
The ML_RAG routine performs retrieval-augmented generation (RAG) by: Taking a natural-language query. This routine aims to provide detailed, accurate, and contextually relevant answers by augmenting a generative model with information retrieved ...
https://dev.mysql.com/doc/heatwave/en/mys-hwgenai-nl-sql.html
You can use this routine for generating and running SQL queries only for databases and tables that you have access to. schemas: specifies the databases to consider for generating and running SQL queries. tables: specifies the tables to consider for ...The routine also runs the generated SQL statement and displays the result ...
https://dev.mysql.com/doc/refman/8.4/en/audit-log-logging-configuration.html
This data is available in the slow query log for qualifying queries, and in the context of the audit log it similarly helps to detect outliers for activity analysis. This section describes how to configure audit logging characteristics, such as the ...
https://dev.mysql.com/doc/refman/8.4/en/converting-tables-to-innodb.html
The InnoDB buffer pool caches both table data and index data, speeding up lookups for queries and keeping query results in memory for reuse. autocommit=1 is suitable for InnoDB tables when running a sequence of queries for generating reports or ...
https://dev.mysql.com/doc/refman/8.4/en/fulltext-natural-language.html
By default or with the IN NATURAL LANGUAGE MODE modifier, the MATCH() function performs a natural language search for a string against a text collection. A collection is a set of one or more columns included in a FULLTEXT index. For each row in the ...