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https://dev.mysql.com/doc/heatwave/en/mys-hw-lakehouse-error-handling.html
See MySQL 9.5 Error Message Reference for Lakehouse error messages. As of MySQL 9.2.2, a detailed summary of warnings is available when loading data to Lakehouse. This includes warnings related to the schema inference stage of loading data. The ...
https://dev.mysql.com/doc/heatwave/en/mys-hw-lakehouse-limitations-csv.html
MySQL HeatWave Lakehouse has the following limitations for CSV files. Lakehouse does not support CSV files with more than 4MB per line. As of MySQL 9.3.2, Lakehouse supports the VECTOR data type for CSV and Parquet files. Consider the following ...
https://dev.mysql.com/doc/heatwave/en/mys-hw-metadata-queries-change-propagation.html
As of MySQL 9.2.1, TRANSACTIONAL indicates that change propagation is enabled for the table. In previous versions of MySQL, RAPID_LOAD_POOL_TRANSACTIONAL indicates that change propagation is enabled for the table.
https://dev.mysql.com/doc/heatwave/en/mys-hw-secondary-load-partitions.html
As of MySQL 9.1.0, MySQL HeatWave supports partitions for DB System tables. Loading Partitions using Secxondary _Load Clause To load partitions into MySQL HeatWave, specify the SECONDARY_LOAD clause in an ALTER TABLE statement with the PARTITION ...
https://dev.mysql.com/doc/heatwave/en/mys-hw-using-views.html
This topic describes how to run queries on views using MySQL HeatWave and verify if those queries are offloaded to the MySQL HeatWave secondary engine for accelerated processing. Verify if the query is offloaded to MySQL HeatWave for processing. To ...
https://dev.mysql.com/doc/heatwave/en/mys-hwaml-anomaly-detection-logs.html
MySQL 9.2.2 introduces the ability to detect anomalies in log data. To perform anomaly detection on logs, log data is cleaned, segemented, and encoded before running anomaly detection. The input table can only have the following columns: The column ...
https://dev.mysql.com/doc/heatwave/en/mys-hwaml-classification-generate-prediction.html
To generate predictions, use the sample data from the testing_data dataset. Even though the table has labels for the Approved target column, the column is not considered when generating predictions. This allows you to compare the predictions to the ...
https://dev.mysql.com/doc/heatwave/en/mys-hwaml-classification-score.html
After generating predictions and explanations, you can score the model to assess its reliability. For a list of scoring metrics you can use with classification models, see Classification Metrics. For this use case, you use the test dataset for ...
https://dev.mysql.com/doc/heatwave/en/mys-hwaml-error-messages.html
Each error message includes an error number, SQLSTATE value, and message string, as described in Error Message Sources and Elements. Error number: ML001016; SQLSTATE: HY000 Message: Only classification, regression, and forecasting tasks are ...
https://dev.mysql.com/doc/heatwave/en/mys-hwaml-forecasting-model-types.html
This topic describes the types of forecasting models supported by AutoML. Univariate Models In a univariate model, you define one numeric column as an endogenous variable, specified as a JSON_ARRAY. For example, you forecast the rainfall for the ...