A chain dependence analysis method and system for a directed acyclic graph

Abstract

The invention provides a chain dependence analysis method and system for a directed acyclic graph, and the method comprises the following steps: detecting whether a previous batch task of a current batch is completed or not through a global scanner; If the previous batch of tasks are completed, instantiating all tasks of the current batch; Running all root node tasks; Judging whether all root nodetasks normally run or not; If all the root node tasks are normally operated, monitoring and operating all subsequent tasks to which respective root node tasks belong through a node scanner; And if all the root node tasks of the current batch and the subsequent tasks to which the root node tasks belong are normally operated, running the subsequent batch. Under the condition that server resources are limited, high-efficiency analysis on DAG chain dependence and real-time performance of task execution are achieved, when the current batch runs, only follow-up tasks are monitored in real time through the node scanners, scanning operation is few, and real-time efficiency is high.

Description

technical field [0001] The invention relates to the technical field of block chains, in particular to a chain dependency analysis method and system for directed acyclic graphs. Background technique [0002] There are two solutions for the chain dependency analysis of directed acyclic graphs: one is to create a waiting task view, which monitors the task running table and task dependency table in real time, and adds tasks that can enter the running queue to the view Among them, the program scans the view at a certain time interval and runs the waiting tasks; the other is that the program scans the waiting tasks in the task running table in real time, analyzes whether the pre-dependencies of all waiting tasks have been completed, and runs the waiting tasks if completed . The problem in Solution 1 is: Since the analysis of view’s dependence on tasks takes a certain amount of time, the scanning time interval cannot be too small and difficult to predict, and the real-time perform...

AI Technical Summary

Problems solved by technology

The problem in Solution 1 is: Since the analysis of view’s dependence on tasks takes a certain amount of time, the scanning time interval cannot be too small and difficult to predict, and the real-time performance is relatively poor.

The problem in Solution 2 is: the number of tasks should not be too large, otherwise each polling of waiting tasks and analyzing the dependencies of waiting tasks will take a lot of time and reduce real-time performance; high-speed scanning will occupy a lot of server resources

However, regardless of scheme 1 or scheme 2, there is a problem that the scanning programs of the two schemes will always run regardless of whether the tasks have been completed, which will cause a waste of server resources.

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