A fpga-based memory olap query optimization method

Abstract

The invention relates to a method for memory on-line analytical processing (OLAP) query optimization based on a field programmable gate array (FPGA). The method comprises the steps of constructing a memory-memory-faced data warehouse heterogeneous storage model; performing query optimization facing a central processing unit (CPU)-FPGA heterogeneous processor based on the heterogeneous storage model: generating a grouping projection vector through subquery; performing dictionary table compression on the grouping projection vector; updating a grouping projection as a grouping projection vector based on dictionary table coding according to a projection dictionary table; performing connection operation on the grouping projection vector and a fact table foreign key, and generating a measurement vector based on measurement list aggregation computation; performing index aggregation computation based on the measurement vector; performing query optimization facing a CPU and FPGA heterogeneous computing platform based on the heterogeneous storage model: causing the FPGA and the CPU to perform shared access of an identical memory address space; when the FPGA is in PCI-E accelerator card configuration, using an FPGA acceleration connection performance and the FPGA to directly access a flash card through a PCI-E channel to perform data processing; and when the FPGA is integrated to a flash memory, accelerating data access and aggregation computation performances of the flash card through the FPGA.

Description

technical field [0001] The invention relates to an in-memory OLAP query method in the database field, in particular to an FPGA-based in-memory OLAP query optimization method. Background technique [0002] FPGA is a semi-custom circuit in the field of application-specific integrated circuit (ASIC). FPGA is a programmable device, and FPGA can be used as a full-custom or semi-custom ASIC circuit. FPGA has the characteristics of higher integration density, larger capacity, and lower power consumption. It is currently used as a hardware-level accelerator by some database manufacturers. The next-generation data center will introduce a large number of accelerator technologies to participate in the calculation of various applications, and improve the performance-to-power ratio and real-time calculation of the data center. In the development of future processors, there is also a trend of integrating FPGA into CPU's integrated heterogeneous computing architecture to improve the proce...

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