Abstract: The disclosure provides a cloud computing-based adaptive storage layering system and method. The system includes a data node management module, a metadata management module, an adaptive storage layering module, and a pre-aggregated query routing module. According to predefined rules, node capacity is expanded and shrunk, collected queried hit models and scanned file paths are aggregated and sorted, and layering loading and pre-loading are performed on files. Based on the disclosure, an efficient On-Line Analytical Processing (OLAP) query execution engine may be constructed, to deal with complex OLAP queries of various reporting system. Therefore, the execution efficiency of cloud OLAP engines can be significantly enhanced.

Abstract: The disclosure provides a read-write separation and automatic scaling-based cloud arrangement system and method. Thus, a read operation and a write operation are separated. Capacity expansion and capacity reduction are performed on a cluster. All index data is stored in corresponding object storage. A pre-computing module submits resources (memory and CPU) required by a computing task to an automatic scaling module. Resource creation is performed by invoking API corresponding to an infrastructure automated arrangement tool Terraform, to guarantee the operation of a construction task. The automatic scaling module provides two resource expansion strategies, which are based on time and the maximum number of waiting tasks. According to the disclosure, the utilization rate of cloud resources is increased, costs are lowered, and manual intervention is reduced.