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https://dev.mysql.com/doc/x-devapi-userguide-shell-python/en/index.html
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https://dev.mysql.com/doc/x-devapi-userguide-shell-python/en/working-with-document-ids.html
The document ID value is usually automatically generated by the server when the document is added, but can also be manually assigned. The assigned document ID is returned in the generatedIds property of the Result (AddResult for Connector/J) object ... This section describes what a document ID is and how to work with ...
https://dev.mysql.com/doc/x-devapi-userguide-shell-python/en/working-with-locking.html
X DevAPI supports MySQL locking through the lockShared() and lockExclusive() methods for the Collection.find() and Table.select() methods. This enables you to control row locking to ensure safe, transactional document updates on collections and to ...
https://dev.mysql.com/doc/heatwave/en/hw-automl-privileges.html
mysql> GRANT SELECT, ALTER ON database_name.* TO 'user_name'@'%'; You need the following privileges to access the database that stores the output tables of generated predictions and explanations. To use MySQL HeatWave AutoML, ask the admin user to ...
https://dev.mysql.com/doc/heatwave/en/mys-hw-advisor-auto-indexing-syntax.html
When a target schema is specified, Advisor generates recommendations for tables belonging to the target schema. Autopilot Indexing uses the following syntax: mysql> CALL sys.autopilot_index_advisor ([options]); options: { ...
https://dev.mysql.com/doc/heatwave/en/mys-hw-autopilot-index-advisor-report-table.html
When Autopilot Indexing runs, it sends detailed output to the autopilot_index_advisor_report table in the sys schema. The autopilot_index_advisor_report table is a temporary table that contains data from the last execution of Autopilot Indexing.
https://dev.mysql.com/doc/heatwave/en/mys-hw-genai-vector-search.html
When you enter a query, MySQL HeatWave GenAI performs a vector-based similarity search to retrieve similar content from the vector store and embedding tables available in the DB system. This helps the LLM to produce more relevant and accurate ...
https://dev.mysql.com/doc/heatwave/en/mys-hw-genai-vector-store.html
Using the inbuilt vector store and retrieval-augmented generation (RAG), you can load and query unstructured documents stored in Object Storage using natural language within the MySQL HeatWave ecosystem. The sections in this topic describe how to ...
https://dev.mysql.com/doc/heatwave/en/mys-hw-insert-select.html
If you set use_secondary_engine=FORCED, the operation fails and generates an offload error. This topic describes how to run a SELECT query and insert the results into a target table using the INSERT ... The target table can be an InnoDB table and ...
https://dev.mysql.com/doc/heatwave/en/mys-hw-lakehouse-load-event-based.html
As of MySQL 9.4.1, you can load data from Object Storage by using event-based incremental load. Once an event for an external file location is emitted due to a change to an object, Lakehouse automatically refreshes the data into the external table.