Hybrid data persistence method, apparatus, electronic device and computer readable medium

Abstract

Embodiments of the present disclosure disclose a hybrid data persistence method, device, electronic equipment, and computer-readable medium. A specific embodiment of the method includes: creating a communication bus; determining a data node satisfying a preset node condition among a plurality of data nodes included in the communication bus as a target data node; obtaining from each target data node in the target data node group Mixed data; create data information table, data index information table and data parameter information table; determine the data volume of each mixed data in the mixed data group, and store each mixed data in the mixed data group to the preset mixed data cache area; add the mixed data in the mixed data buffer area to the preset mixed data queue; generate data information group, data index information group and data parameter information group, and store them in the data information table, data index information table and data parameter information table middle. This embodiment can perform comprehensive data playback in the target data operating system.

Description

technical field [0001] The embodiments of the present disclosure relate to the field of computer technology, and in particular, to a hybrid data persistence method, device, electronic device, and computer-readable medium. Background technique [0002] Hybrid data persistence is a technology for persisting various data generated during the driving of autonomous vehicles. At present, when autopilot data is persisted, the usual method is: after obtaining different types of autopilot data from various hardware platforms that support data acquisition, the autopilot data is stored to complete data persistence. [0003] However, when the above method is used for hybrid data persistence, the following technical problems often exist: [0004] First, due to the fact that some hardware platforms do not support cross-platform data acquisition, the final stored mixed data is not comprehensive enough (for example, missing mixed data, wrong association of mixed data, etc.). Comprehensive...

AI Technical Summary

Problems solved by technology

[0004] First, because some hardware platforms do not support cross-platform data acquisition, the final stored mixed data is not comprehensive enough (for example, missing mixed data, wrong association of mixed data, etc.), thus, cannot Comprehensive data playback (for example, sending, displaying, etc.) in the Bantu operating system), which in turn cannot be better applied to the field of automatic driving;

[0005] Second, it does not take into account that some mixed data requires a long storage time, which makes it easy to cause database congestion during the process of storing data according to time nodes, thus reducing the efficiency of mixed data persistence

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