Method, apparatus and system for processing data

Abstract

Disclosed are a method, apparatus and system for processing data. The method comprises: a server receiving real-time data, sent by an unmanned aerial vehicle, of the unmanned aerial vehicle; the server caching the real-time data into packet data sets corresponding to unique codes comprised in the real-time data, wherein the unique codes correspond to the packet data sets on a one-to-one basis, thereal-time data generated by means of the unmanned aerial vehicle during one flight process comprises the same unique codes, and the real-time data generated by means of the unmanned aerial vehicle during different flight processes comprises different unique codes; and the server storing data comprised in the packet data sets in sub-tables, corresponding to the unique codes, in a database, whereinthe sub-tables correspond to the unique codes on a one-to-one basis. By means of the embodiments of the present invention, real-time data generated by means of an unmanned aerial vehicle during one flight process can be stored in the same sub-table, thus improving the data query efficiency to a certain extent.

Description

technical field [0001] The present invention relates to the field of computer technology, in particular to a data processing method, device and system. Background technique [0002] With the continuous advancement of science and technology, Unmanned Aerial Vehicle (UAV) has been developed rapidly and widely used. The real-time data reporting frequency of drones during flight is once per second. The data generated after a large number of drones fly for a period of time is undoubtedly a typical large-scale data set. In the prior art, the large-scale data set is usually divided into tables by time (for example, month and day), and the resulting single-table data will be greatly reduced. But this will cause certain problems. For example, when it is necessary to find the flight track of a drone, the flight track is composed of several latitude and longitude point sets within a certain period of time. For example, the flight time of a drone is from December From 11:50 p.m. on th...

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Problems solved by technology

But this will cause certain problems. For example, when it is necessary to find the flight track of a drone, the flight track is composed of several latitude and longitude point sets within a certain period of time. For example, the flight time of a drone is from December From 11:50 p.m. on the 31st to 10 a.m. on January 1st, in this case, the data set of the flight trajectory of a drone has spanned the natural year, month, and day

Taking sub-tables by month as an example, after searching the data from the database sub-table in December, it is impossible to know whether there is any follow-up trajectory data in the database sub-table in January, so we have to continue to search the database in January sub-table

This will increase the complexity of computer programs and reduce the efficiency of finding data

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