MySQL HeatWave User Guide  /  Overview

Chapter 1 Overview

HeatWave is a massively parallel, high performance, in-memory query accelerator that accelerates MySQL performance by orders of magnitude for analytics workloads, mixed workloads, and machine learning. HeatWave can be accessed through Oracle Cloud Infrastructure (OCI), Amazon Web Services (AWS), and Oracle Database Service for Azure (ODSA).

A HeatWave Cluster consists of a MySQL DB System and HeatWave nodes. Analytics queries that meet certain prerequisites are automatically offloaded from the MySQL DB System to the HeatWave Cluster for accelerated processing. With a HeatWave Cluster, you can run online transaction processing (OLTP), online analytical processing (OLAP), and mixed workloads from the same MySQL database without requiring extract, transfer, and load (ETL), and without modifying your applications. For more information about the analytical capabilities of HeatWave, see Chapter 2, HeatWave.

The MySQL DB System includes a HeatWave plugin that is responsible for cluster management, query scheduling, and returning query results to the MySQL DB System. The HeatWave nodes store data in memory and process analytics and machine learning queries. Each HeatWave node hosts an instance of the HeatWave query processing engine (RAPID).

Enabling a HeatWave Cluster also provides access to HeatWave AutoML, which is a fully managed, highly scalable, cost-efficient, machine learning solution for data stored in MySQL. HeatWave AutoML provides a simple SQL interface for training and using predictive machine learning models, which can be used by novice and experienced ML practitioners alike. Machine learning expertise, specialized tools, and algorithms are not required. With HeatWave AutoML, you can train a model with a single call to an SQL routine. Similarly, you can generate predictions with a single CALL or SELECT statement which can be easily integrated with your applications.

With HeatWave AutoML, data and models never leave the MySQL Database Service, saving you time and effort while keeping your data and models secure. HeatWave AutoML is optimized for HeatWave shapes and scaling, and all HeatWave AutoML processing is performed on the HeatWave Cluster. HeatWave distributes ML computation among HeatWave nodes, to take advantage of the scalability and massively parallel processing capabilities of HeatWave. For more information about the machine learning capabilities of HeatWave, see Chapter 3, HeatWave AutoML.

Analytics and machine learning queries are issued from a MySQL client or application that interacts with the HeatWave Cluster by connecting to the MySQL DB System. Results are returned to the MySQL DB System and to the MySQL client or application that issued the query.

The number of HeatWave nodes required depends on data size and the amount of compression that is achieved when loading data into the HeatWave Cluster. A HeatWave Cluster in Oracle Cloud Infrastructure (OCI) or Oracle Database Service for Azure (ODSA) supports up to 64 nodes. On Amazon Web Services (AWS), a HeatWave Cluster supports up to 128 nodes.

On Oracle Cloud Infrastructure (OCI), data that is loaded into HeatWave is automatically persisted to OCI Object Storage, which allows data to be reloaded quickly when the HeatWave Cluster resumes after a pause or when the HeatWave Cluster recovers from a cluster or node failure.

HeatWave network traffic is fully encrypted.