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https://dev.mysql.com/doc/heatwave/en/mys-hw-encoding-string-columns.html
Encoding string columns helps accelerate the processing of queries that access those columns. HeatWave supports two string column encoding types: Variable-length encoding (VARLEN) Dictionary encoding (SORTED) When tables are loaded into HeatWave, ...
https://dev.mysql.com/doc/heatwave/en/mys-hw-genai-overview.html
All the elements that are necessary to use HeatWave GenAI with proprietary data are integrated and optimized to work with each other. HeatWave GenAI is a feature of HeatWave that lets you communicate with unstructured data in HeatWave using ...
https://dev.mysql.com/doc/heatwave/en/mys-hw-lakehouse-overview.html
The source data is read from Object Storage, transformed to the memory optimized HeatWave format, stored in the HeatWave persistence storage layer in Object Storage, and then loaded to HeatWave cluster memory. The Lakehouse feature of HeatWave ...
https://dev.mysql.com/doc/heatwave/en/mys-hw-overview-heatwave-automl.html
HeatWave AutoML is optimized for HeatWave shapes and scaling, and all HeatWave AutoML processing is performed on the HeatWave Cluster. With HeatWave AutoML, data and models never leave HeatWave, saving you time and effort while keeping your data ...
https://dev.mysql.com/doc/heatwave/en/mys-hw-overview-heatwave-lakehouse.html
The source data is read from Object Storage, transformed to the memory optimized HeatWave format, stored in the HeatWave persistence storage layer in Object Storage, and then loaded to HeatWave cluster memory. The Lakehouse feature of HeatWave ...
https://dev.mysql.com/doc/heatwave/en/mys-hw-query-runtimes.html
Runtime data is useful for query optimization, troubleshooting, and estimating the cost of running a particular query or workload. To view HeatWave query runtimes and runtime estimates use HeatWave Autopilot Advisor Auto Query Time Estimation, see: ...
https://dev.mysql.com/doc/heatwave/en/mys-hw-reloading-data-best-practice.html
Tip Instead of loading data into HeatWave manually, consider using the Auto Parallel Load utility, which prepares and loads data for you using an optimized number of parallel load threads. Reloading data is recommended in the following cases: After ...
https://dev.mysql.com/doc/heatwave/en/mys-hw-window-functions.html
For optimal performance, window functions in HeatWave utilize a massively parallel, partitioning-based algorithm. For general information about window functions, see Window Functions, in the MySQL Reference Manual. HeatWave window function support ...
https://dev.mysql.com/doc/heatwave/en/mys-hwaml-automl-workflow.html
HeatWave AutoML analyzes the training data, trains an optimized machine learning model, and stores the model in a model catalog on the MySQL DB System. A typical HeatWave AutoML workflow is described below: When the ML_TRAIN routine is called, ...
https://dev.mysql.com/doc/heatwave/en/mys-hwaml-features.html
You provide the data, and HeatWave AutoML analyzes the characteristics of the data and creates an optimized machine learning model that you can use to generate predictions and explanations. HeatWave AutoML makes it easy to use machine learning, ...