Oracle announced the availability of MySQL Autopilot, a new component of MySQL HeatWave service, the in-memory query acceleration engine for MySQL Database Service in Oracle Cloud Infrastructure (OCI). MySQL Autopilot uses advanced machine learning techniques to automate HeatWave, making it easier to use and further improving performance and scalability. Autopilot is available at no additional charge for MySQL HeatWave customers.
MySQL Autopilot automates many of the most critical and challenging aspects of achieving high query performance at scale — including provisioning, data loading, query execution and failure handling. It uses advanced techniques to sample data, collect statistics on data and queries, and build machine learning models using Oracle AutoML to model memory usage, network load and execution time.
MySQL Autopilot then uses these machine learning models to execute its core capabilities. MySQL Autopilot makes the HeatWave query optimiser increasingly intelligent as more queries are executed, resulting in continually improving system performance over time — a capability not available on Amazon Aurora, Amazon Redshift, Snowflake, or other MySQL-based database services.
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MySQL Autopilot includes the following capabilities:
- Auto-provisioning predicts the number of HeatWave nodes required for running a workload by an adaptive sampling of table data on which analytics is needed. This means that customers no longer need to estimate the optimal size of their cluster manually. No other database service provides this capability.
- The auto parallel load can optimise the load time and memory usage by predicting the optimal degree of parallelism for each table loaded into HeatWave. No other cloud vendor offers this capability.
- Auto data placement predicts the column on which tables should be partitioned in memory to help achieve the best performance for queries. It also predicts the expected gain in query performance with the new column recommendation. This minimises data movement across nodes due to suboptimal choices that can be made by operators when manually selecting the column. No other database service provides this capability.
- Auto encoding can determine the optimal representation of columns being loaded into HeatWave, considering the queries. This optimal representation provides the best query performance and minimises the size of the cluster to minimise costs.
- Auto query plan improvement learns various statistics from the execution of queries and can improve the execution plan of future questions. This enhances the performance of the system as more queries are run. No other database service provides this capability.
- Auto query time estimation can estimate the execution time of a query before executing the query. This provides a prediction of how long a question will take, enabling customers to decide if the duration of the query is too long and instead run a different query.
- Auto change propagation intelligently determines the optimal time when changes in MySQL Database should be propagated to the HeatWave Scale-out Data Management layer. This helps ensure that changes are being propagated at the right optimal cadence. No other cloud vendor offers this capability.
- Auto scheduling can determine which queries in the queue are short running and prioritise them over long-running queries intelligently to reduce overall wait time. Most other databases use the First In, First Out (FIFO) mechanism for scheduling.
- Auto error recovery provisions new nodes and reloads necessary data if one or more HeatWave nodes is unresponsive due to software or hardware failure.
“Oracle’s MySQL Database Service with HeatWave is the only MySQL database that efficiently supports both OLTP and OLAP, enabling users to run mixed workloads or real-time analytics against their MySQL database with 10 to 1,000 times better performance and less than half the cost compared to other analytical or MySQL-based databases,” said Edward Screven, Chief Corporate Architect, Oracle. “MySQL HeatWave is one of the fastest-growing cloud services on OCI and an increasing number of customers are moving their MySQL workloads to HeatWave. Today, we are announcing a number of innovations that are the result of years of research and advanced development at Oracle. The combination of these innovations delivers massive improvements in automation, performance and cost — further distancing HeatWave from other database cloud services.”
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As part of this announcement, Oracle is also introducing MySQL Scale-out Data Management, which can improve the performance of reloading data into HeatWave by up to 100 times. HeatWave now supports a cluster size of 64 nodes—up from 24 nodes—and is capable of processing up to 32 TB of data—up from 12 TB. These new enhancements further strengthen the price/performance advantages of HeatWave relative to its primary competitors.
