HeatWave Release Notes
Abstract
This document describes how to use MySQL HeatWave. It covers how to load data from the DB System and Object Storage, accelerate query processing, optimize workloads, and use the machine learning and generative AI features of MySQL HeatWave.
For information about creating and managing a MySQL HeatWave Cluster on Oracle Cloud Infrastructure (OCI), see MySQL HeatWave on OCI Service Guide.
For information about creating and managing a MySQL HeatWave Cluster on Amazon Web Services (AWS), see MySQL HeatWave on AWS Service Guide.
For information about creating and managing a MySQL HeatWave Cluster on Oracle Database Service for Azure (ODSA), see MySQL HeatWave for Azure Service Guide.
For MySQL Server documentation, refer to the MySQL Reference Manual.
For information about the latest MySQL HeatWave features and updates, refer to the MySQL HeatWave Release Notes.
For legal information, see the Legal Notices.
For help with using MySQL, please visit the MySQL Forums, where you can discuss your issues with other MySQL users.
Licensing information. This product may include third-party software, used under license. See MySQL HeatWave License Information User Manual for licensing information, including licensing information relating to third-party software that may be included in this release.
Document generated on: 2025-08-15 (revision: 83318)
Table of Contents
- 1 Overview
- 2 Get Started
- 3 Quickstarts
- 4 Load and Manage Data
- 4.1 Load Data into DB System
- 4.2 Load Data from DB System into MySQL HeatWave Cluster
- 4.3 Load Data from Object Storage into MySQL HeatWave Cluster
- 4.3.1 About MySQL HeatWave Lakehouse
- 4.3.2 Additional MySQL HeatWave Lakehouse Requirements
- 4.3.3 MySQL HeatWave Lakehouse Privileges
- 4.3.4 Supported File Formats and Data Types
- 4.3.5 Access Object Storage
- 4.3.6 Lakehouse External Table Syntax
- 4.3.7 About Lakehouse Auto Parallel Load
- 4.3.8 Load Structured Data Using Lakehouse Auto Parallel Load
- 4.3.9 Load Structured Data Manually
- 4.3.10 Load Unstructured Data
- 4.3.11 Update Tables
- 4.4 Unload Data from MySQL HeatWave Cluster
- 4.5 Retrieve MySQL HeatWave Metadata
- 4.6 Export Query Results to Object Storage
- 4.6.1 About Exporting Query Results
- 4.6.2 Requirements to Export Query Results
- 4.6.3 Export Query Results to CSV Files
- 4.6.4 Export Query Results to Parquet Files
- 4.6.5 Export Query Results to ND-JSON Files
- 4.6.6 Redacted PAR URLs in Exported Log Files
- 4.6.7 File Name Format for Exported Query Result Files
- 4.7 Recover DB System Data
- 4.8 Monitor Data Loading
- 5 Accelerate Query Processing
- 5.1 About MySQL HeatWave
- 5.2 Supported SQL Modes
- 5.3 Supported Functions and Operators
- 5.3.1 Aggregate Functions
- 5.3.2 Arithmetic Operators
- 5.3.3 Cast Functions and Operators
- 5.3.4 Comparison Functions and Operators
- 5.3.5 Control Flow Functions and Operators
- 5.3.6 Data Masking and De-Identification Functions
- 5.3.7 Encryption and Compression Functions
- 5.3.8 JSON Functions
- 5.3.9 Logical Operators
- 5.3.10 Mathematical Functions
- 5.3.11 String Functions and Operators
- 5.3.12 Temporal Functions
- 5.3.13 Vector Functions
- 5.3.14 Window Functions
- 5.4 Run Queries
- 5.4.1 Requirements for Running Queries
- 5.4.2 SELECT Statement Clauses for MySQL HeatWave
- 5.4.3 Explain Query and Check Execution Time
- 5.4.4 CREATE TABLE ... SELECT Statements
- 5.4.5 Create MySQL HeatWave Temporary Tables
- 5.4.6 INSERT ... SELECT Statements
- 5.4.7 Query Views
- 5.4.8 View Query Runtimes and Estimates
- 5.4.9 Diagnose Query Offload
- 5.4.10 Auto Scheduling
- 5.4.11 Auto Query Plan Improvement
- 5.4.12 Dynamic Query Offload
- 5.5 Modify Tables
- 5.6 Analyze Tables
- 5.7 Run Tasks Asynchronously
- 5.8 Optimize Workloads for OLAP
- 5.9 Optimize Workloads for OLTP
- 5.10 MySQL HeatWave Monitoring
- 6 Train and Use Machine Learning Models
- 6.1 About MySQL HeatWave AutoML
- 6.2 Additional MySQL HeatWave AutoML Requirements
- 6.3 MySQL HeatWave AutoML Privileges
- 6.4 Supported Data Types for MySQL HeatWave AutoML
- 6.5 Create a Machine Learning Model
- 6.6 Learn About MySQL HeatWave AutoML with Oracle Cloud Infrastructure Generative AI
- 6.7 Machine Learning Use Cases
- 6.8 Use MySQL HeatWave AutoML with Lakehouse
- 6.9 Manage Machine Learning Models
- 6.10 Track Progress for MySQL HeatWave AutoML Routines
- 6.11 Monitor the Status of MySQL HeatWave AutoML
- 7 Perform AI-Powered Search and Content Generation
- 7.1 About MySQL HeatWave GenAI
- 7.2 Additional MySQL HeatWave GenAI Requirements
- 7.3 MySQL HeatWave GenAI Roles and Privileges
- 7.4 Supported LLMs, Embedding Models, and Languages
- 7.5 Authenticate OCI Generative AI Service
- 7.6 Generate Text-Based Content
- 7.7 Set Up a Vector Store
- 7.8 Generate Vector Embeddings
- 7.9 Perform Vector Search with RAG
- 7.10 Start a Conversational Chat
- 8 Performance and Usage
- 9 System and Status Variables
- 10 Routines
- 10.1 MySQL HeatWave Routines
- 10.2 MySQL HeatWave AutoML Routines
- 10.2.1 ML_TRAIN
- 10.2.2 ML_EXPLAIN
- 10.2.3 ML_MODEL_EXPORT
- 10.2.4 ML_MODEL_IMPORT
- 10.2.5 ML_PREDICT_ROW
- 10.2.6 ML_PREDICT_TABLE
- 10.2.7 ML_EXPLAIN_ROW
- 10.2.8 ML_EXPLAIN_TABLE
- 10.2.9 ML_SCORE
- 10.2.10 ML_MODEL_LOAD
- 10.2.11 ML_MODEL_UNLOAD
- 10.2.12 ML_MODEL_ACTIVE
- 10.2.13 NL2ML
- 10.2.14 Model Types
- 10.2.15 Optimization and Scoring Metrics
- 10.3 MySQL HeatWave GenAI Routines
- 11 Troubleshoot