Graph calculation method and system based on dynamic code generation

Abstract

The invention provides a graph calculation method and system based on dynamic code generation, and the method comprises the steps of constructing an intermediate graph structure containing a graph operation primitive according to a graph building request, enabling the intermediate graph structure to be associated with a graph name, and then storing the associated intermediate graph structure into an intermediate graph buffer; according to the graph algorithm request, generating a graph algorithm structure composed of the external code byte codes, and sending the graph algorithm structure to a graph algorithm buffer; retrieving the intermediate graph buffer and the graph algorithm buffer according to the execution request to obtain a triple composed of the intermediate graph structure to be executed, the graph algorithm structure to be executed and the parameter list, and retrieving the triple in the local code buffer to obtain an execution object in the local code buffer so as to obtain a result through execution. According to the present invention, the generated codes are injected into a local code space, so that the overhead of data exchange is eliminated; the intermediate graph structure capable of being secondarily compiled is constructed, so that access codes of the graph data can be compiled and optimized; meanwhile, the intermediate graph structure cache and the graph algorithm cache are added, so that the preprocessing expenditure of the graph calculation is avoided.

Description

technical field [0001] The invention relates to the field of graph calculation and analysis in computer technology, and in particular to a graph calculation method and system based on dynamic code generation. Background technique [0002] Graph computing is an important technology for analyzing and mining associations in data. Due to the nonlinear characteristics of the graph structure, the development of graph algorithms is difficult, and at the same time, the performance is poor, and the code is not easy to optimize. In order to support efficient graph computing requirements, corresponding computing frameworks emerged as the times require. The graph computing framework encapsulates the graph into a unified data structure and provides basic operators to assist in the development of graph algorithms. [0003] The current graph computing framework is mainly divided into two categories: (1) Provide a fixed graph operator library and use an interpreted language to combine ope...

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Problems solved by technology

[0006] 2. The overhead of external code calls is introduced: when the graph algorithm obtains the required attributes and other data, the generated graph calculation code needs to be accessed through the external code interface, which not only introduces the overhead of external calls, but also makes the related external codes need to Exported symbols cannot be optimized inline;

[0007] 3. The graph structure cannot be reused, and the preprocessing cost of the algorithm is high: the graph algorithm needs to build the dependent graph structure data at runtime, and the same graph structure cannot be directly reused between different algorithms

At the same time, due to the introduction of complex code generation logic, the difficulty of developing graph algorithms has increased

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