![]() ![]() No other database service provides this capability. This means developers and DBAs no longer need to manually estimate the optimal size of their cluster. Auto provisioning predicts the number of HeatWave nodes required for running a workload by adaptive sampling of table data on which analytics is required.MySQL Autopilot provides numerous capabilities for HeatWave and OLTP. MySQL Autopilot is available at no additional charge for MySQL HeatWave customers. It uses advanced techniques to automate HeatWave, further improving performance and scalability and making it easier to use-saving developers and DBAs significant time. MySQL Autopilot automates many of the most important and often challenging aspects of achieving high query performance at scale-including provisioning, data loading, query execution, and failure handling. MySQL Autopilot: machine learning–powered automation Various analytics processing primitives use the hardware instructions of the underlying virtual machines (VMs). The overlap of computation with communication is optimized for the network bandwidth available. The sizes of the partitions have been optimized to fit the cache of the underlying shapes. Query processing in HeatWave has been optimized for commodity servers in the cloud. HeatWave has an intelligent query scheduler that overlaps computation with network communication tasks to achieve very high scalability across thousands of cores. Each node within a cluster and each core within a node can process partitioned data in parallel. This provides excellent internodal scalability. HeatWave massively partitions data across a cluster of nodes, which can be operated in parallel. Architected for massive scale and performance It implements state-of-the-art algorithms for distributed query processing that provide very high performance. ![]() HeatWave is an in-memory, massively parallel, hybrid columnar query-processing engine. ![]()
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