Data sorting method and device, equipment and storage medium
By determining the sorting priority of incremental data and merging historical and incremental data results, the real-time and resource consumption issues of data sorting are solved, and the query efficiency and accuracy of financial and medical data are improved.
Patent Information
- Application Number
- CN202510689710.8
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2025-05-26
- Publication Date
- 2025-09-16
AI Technical Summary
Existing data sorting methods have problems such as low real-time performance, high resource consumption and low efficiency, especially in the data query efficiency in the financial and medical fields.
By obtaining the data set to be sorted, determining the sorting priority of the incremental data, and sorting the incremental data according to the preset rules, the sorting results of the historical and incremental data are merged and replaced with the target sorting results.
It improves the efficiency and real-time performance of data sorting, reduces resource consumption, and improves the query efficiency and accuracy of financial and medical data.
Smart Images
Figure CN120653698A_ABST
Abstract
Description
Technical Field
[0001] The present application relates to the field of data processing technology, and in particular to a data sorting method, apparatus, device and storage medium. Background Art
[0002] With the rapid development of internet technology, internet data is rapidly growing and accumulating, leading to a continuous expansion in data size. For example, in the financial sector, the rapid growth of financial services, the rapid growth of financial-related data, and the continuous accumulation of historical data have led to a continuous expansion in data size, resulting in increasing volume and complexity of financial-related data. Specifically, in the insurance sector, the increasing accumulation of insurance contract data has led to inefficient insurance contract queries. Another example is the rapid growth and continuous accumulation of historical medical data in the healthcare sector, leading to a continuous expansion in medical data size and inefficient queries.
[0003] To improve the efficiency of data query, current methods use storage components such as cache to store and accumulate real-time sorting results, use the database's built-in sorting function to group and sort data, or cache group sorting data offline. That is, by sorting data, the efficiency and accuracy of data query can be improved. However, current data sorting methods have problems such as low real-time performance, high consumption of device memory resources, and low efficiency.
[0004] Therefore, how to reduce the resource consumption of data sorting and improve the efficiency and real-time performance of data sorting is an urgent problem to be solved. Summary of the Invention
[0005] The main purpose of this application is to provide a data sorting method, device, equipment and storage medium, aiming to improve the efficiency and real-time performance of data sorting and reduce resource consumption.
[0006] In a first aspect, the present application provides a data sorting method, the data sorting method comprising the following steps:
[0007] In response to a data sorting request, obtaining a data set to be sorted, where the data set to be sorted includes a first sorting result corresponding to the historical data set and an incremental data set;
[0008] Determining the sorting priority of each piece of incremental data in the incremental data set;
[0009] sorting each piece of incremental data in the incremental data set according to the sorting priority of each piece of incremental data in the incremental data set and a preset sorting rule to obtain a second sorting result;
[0010] The first sorting result and the second sorting result are merged to obtain a target sorting result, and the first sorting result is replaced by the target sorting result.
[0011] In a second aspect, the present application further provides a data sorting device, which includes an acquisition module, a determination module, and a generation module, wherein:
[0012] The acquisition module is configured to acquire a data set to be sorted in response to a data sorting request, wherein the data set to be sorted includes a first sorting result corresponding to the historical data set and an incremental data set;
[0013] The determining module is used to determine the sorting priority of each incremental data in the incremental data set;
[0014] The generating module is configured to sort each piece of incremental data in the incremental data set according to a sorting priority of each piece of incremental data in the incremental data set and a preset sorting rule to obtain a second sorting result;
[0015] The generating module is further configured to merge the first sorting result and the second sorting result to obtain a target sorting result, and replace the first sorting result with the target sorting result.
[0016] In a third aspect, the present application also provides a computer device, comprising a processor, a memory, and a computer program stored in the memory and executable by the processor, wherein when the computer program is executed by the processor, the steps of the data sorting method as described above are implemented.
[0017] In a fourth aspect, the present application further provides a computer-readable storage medium, on which a computer program is stored, wherein when the computer program is executed by a processor, the steps of the data sorting method as described above are implemented.
[0018] The present application provides a data sorting method, apparatus, device, and storage medium. The present application, in response to a data sorting request, obtains a data set to be sorted, the data set to be sorted including a first sorting result corresponding to a historical data set and an incremental data set; determines the sorting priority of each incremental data in the incremental data set; sorts each incremental data in the incremental data set according to the sorting priority of each incremental data in the incremental data set and a preset sorting rule to obtain a second sorting result; merges the first sorting result and the second sorting result to obtain a target sorting result, and replaces the first sorting result with the target sorting result. In the present application, when sorting the data set to be sorted, only the incremental data set needs to be sorted in real time to obtain the second sorting result, and the first sorting result corresponding to the historical data set in the data set to be sorted and the second sorting result of the incremental data set are merged, which can accurately sort the data set to be sorted, greatly improving the efficiency and real-time performance of data sorting, and reducing the resource consumption of the equipment during the data sorting process. In the financial and medical fields, the technical solution of the present application can effectively improve the sorting efficiency and accuracy of financial data and medical data. BRIEF DESCRIPTION OF THE DRAWINGS
[0019] In order to more clearly illustrate the technical solutions of the embodiments of the present application, the following is a brief introduction to the drawings required for use in the description of the embodiments. Obviously, the drawings described below are some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without any creative work.
[0020] Figure 1 A flowchart of a data sorting method provided in an embodiment of the present application;
[0021] Figure 2 for Figure 1 A schematic flow chart of the sub-steps of the data sorting method in FIG.
[0022] Figure 3 A schematic block diagram of a data sorting device provided in an embodiment of the present application;
[0023] Figure 4 for Figure 3 A schematic block diagram of a submodule of a data sorting device;
[0024] Figure 5 A schematic block diagram of the structure of a computer device provided in an embodiment of the present application.
[0025] The realization of the objectives, functional features and advantages of this application will be further explained in conjunction with embodiments and with reference to the accompanying drawings. DETAILED DESCRIPTION
[0026] The following will be combined with the drawings in the embodiments of this application to clearly and completely describe the technical solutions in the embodiments of this application. Obviously, the embodiments described are part of the embodiments of this application, not all of them. Based on the embodiments in this application, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of this application.
[0027] The flowcharts shown in the accompanying drawings are for illustrative purposes only and do not necessarily include all contents and operations / steps, nor must they be executed in the order described. For example, some operations / steps may be decomposed, combined, or partially merged, so the actual execution order may vary depending on the actual situation.
[0028] The embodiments of the present application can acquire and process relevant data based on artificial intelligence technology. Artificial Intelligence (AI) is the theory, method, technology, and application system that uses digital computers or machines controlled by digital computers to simulate, extend, and expand human intelligence, perceive the environment, acquire knowledge, and use knowledge to achieve optimal results.
[0029] Fundamental AI technologies generally include sensors, dedicated AI chips, cloud computing, distributed storage, big data processing, operating / interaction systems, and mechatronics. AI software technologies primarily encompass computer vision, robotics, biometrics, speech processing, natural language processing, and machine learning / deep learning.
[0030] With the rapid development of internet technology, internet data is rapidly growing and accumulating, leading to a continuous expansion in data size. For example, in the financial sector, the rapid growth of financial services, the rapid growth of financial-related data, and the continuous accumulation of historical data have led to a continuous expansion in data size, resulting in increasing volume and complexity of financial-related data. Specifically, in the insurance sector, the increasing accumulation of insurance contract data has led to inefficient insurance contract queries. Another example is the rapid growth and continuous accumulation of historical medical data in the healthcare sector, leading to a continuous expansion in medical data size and inefficient queries.
[0031] To improve the efficiency of data query, current methods use storage components such as cache to store and accumulate real-time sorting results, use the database's built-in sorting function to group and sort data, or cache group sorting data offline. That is, by sorting data, the efficiency and accuracy of data query can be improved. However, current data sorting methods have problems such as low real-time performance, high consumption of device memory resources, and low efficiency.
[0032] To solve the above problems, an embodiment of the present application provides a data sorting method, apparatus, device and storage medium, wherein the data sorting method includes: in response to a data sorting request, obtaining a data set to be sorted, wherein the data set to be sorted includes a first sorting result and an incremental data set corresponding to a historical data set; determining the sorting priority of each incremental data in the incremental data set; sorting each incremental data in the incremental data set according to the sorting priority of each incremental data in the incremental data set and a preset sorting rule to obtain a second sorting result; merging the first sorting result and the second sorting result to obtain a target sorting result, and replacing the first sorting result with the target sorting result.
[0033] Among them, the data sorting method can be applied to computer devices, which can be electronic devices such as mobile phones, tablet computers, laptops, desktop computers, personal digital assistants and wearable devices.
[0034] The following describes some embodiments of the present application in detail with reference to the accompanying drawings. In the absence of conflict, the following embodiments and features therein may be combined with each other.
[0035] Please refer to Figure 1 , Figure 1 A flowchart of a data sorting method provided in an embodiment of the present application.
[0036] like Figure 1 As shown, the data sorting method includes steps S101 to S104.
[0037] Step S101 : In response to a data sorting request, a data set to be sorted is obtained, where the data set to be sorted includes a first sorting result corresponding to a historical data set and an incremental data set.
[0038] The data set to be sorted includes a first sorting result corresponding to a historical data set and an incremental data set. The historical data set is a data set that has completed data sorting, and the incremental data set is data in the data set to be sorted that has not completed sorting.
[0039] In some embodiments, upon receiving a data sorting request, a data set to be sorted is obtained according to the data sorting request, wherein the data set to be sorted includes a first sorting result corresponding to the historical data set and an incremental data set. Upon receiving the data sorting request, the data set to be sorted can be accurately obtained according to the data sorting request.
[0040] In some embodiments, a method for obtaining the dataset to be sorted based on the data sorting request may include: determining a search keyword in the data sorting request, searching for corresponding data from the data based on the search keyword, and obtaining the dataset to be sorted. If a dataset can be accurately found using the search keyword in the data sorting request, then that dataset is the dataset to be sorted.
[0041] For example, in the insurance business, a data sorting request is obtained, and the data sorting request is for a vehicle flooding event. Based on the search keyword of the data sorting request, which is the vehicle flooding event, a data set to be sorted is obtained from the database. The data set to be sorted includes a first sorting result and an incremental data set corresponding to the historical data set. The historical data set and incremental data set can be determined based on actual conditions and are not specifically limited in this embodiment of the application. For example, the historical data set can be a set of vehicle flooding events before this month, and the set of vehicle flooding events before this month has been sorted to obtain the first sorting result; and the set of vehicle flooding events this month, and the set of vehicle flooding events this month has not been sorted.
[0042] For example, in the medical field, a data sorting request is obtained, and the data sorting request is for influenza medical record data. Based on the search keyword of the data sorting request, which is influenza medical record data, a data set to be sorted is obtained from a database. The data set to be sorted includes a first sorting result and an incremental data set corresponding to a historical data set. The historical data set and the incremental data set can be determined based on actual conditions and are not specifically limited in this embodiment of the application. For example, the historical data set can be a flu medical record data set before this month, and the flu medical record data before this month has been sorted to obtain the first sorting result; and the flu medical record data of this month, and the flu medical record data of this month has not been sorted.
[0043] It should be noted that the first sorting result is obtained by sorting the historical data set according to a preset sorting rule. The preset sorting rule can be set according to actual conditions. The embodiment of the present application does not specifically limit this. For example, the preset sorting rule can be a time sorting rule. Exemplarily, the historical data set is the transaction flow data within one year from January 1, 2020 to December 31, 2020. The transaction flow data within this year is sorted according to the daily transaction flow. The daily transaction flow data has 366 transaction flow sub-data.
[0044] Step S102: Determine the sorting priority of each incremental data in the incremental data set.
[0045] The sorting priority is used to represent the sorting order of each incremental data.
[0046] In some embodiments, as Figure 2As shown, step S102 includes sub-steps S1021 and S1022.
[0047] Sub-step S1021: determining the sorting processing time of the same type of data in the historical data set and the number of sorting requests for the same type of data.
[0048] Among them, this type of data is a category of sorted data. This type of data can be set according to actual conditions. The embodiment of the present application does not make specific limitations on this. For example, this type of data can be transaction flow data, contract data, influenza medical record data, etc.
[0049] In some embodiments, the actual sorting processing time of each historical data item of the same type in the historical data set is obtained; and a weighted average processing is performed on the actual sorting processing time of multiple historical data items of the same type to obtain the sorting processing time of the same type of data. By performing a weighted average processing on the actual sorting processing time of multiple historical data items of the same type of data, the sorting processing time of the same type of data can be accurately obtained.
[0050] In some embodiments, each type of data in the historical data set is obtained, and the actual sorting processing time of each historical data corresponding to each type of data is obtained. The actual sorting processing time of multiple historical data of each type of data is averaged to obtain the sorting processing time of the same type of data. By averaging the actual sorting processing time of multiple historical data of each type of data, the sorting processing time of the same type of data can be accurately obtained.
[0051] In some embodiments, each type of data in a historical data set is obtained, and the actual sorting processing time of each historical data corresponding to each type of data is obtained. An expected calculation is performed on the actual sorting processing time of multiple historical data of the same type of data to obtain the sorting processing time of the same type of data. By performing an expected calculation on the actual sorting processing time of multiple historical data of the same type of data, the sorting processing time of the same type of data can be accurately obtained.
[0052] In some embodiments, the actual sorting processing time of multiple historical data of the same type of data is expected to be calculated. The sorting processing time of the same type of data can be obtained by constructing a normal distribution graph based on the actual sorting processing time of the same type of data and the number of historical data, and obtaining the sorting processing time of the same type of data from the normal distribution graph. By constructing a normal distribution graph of the sorting processing time of the same type of data, the sorting processing time of the same type of data can be accurately obtained.
[0053] Sub-step S1022: determining the sorting priority of each piece of the incremental data according to the sorting processing time of the same type of data and the number of requests for sorting the same type of data.
[0054] In some embodiments, a target priority parameter for sorting each type of data is determined based on the sorting processing time for the same type of data and the number of sorting requests for the same type of data. A sorting priority is set based on the target priority parameter for sorting each type of data to obtain a sorting priority for each type of data. Based on the sorting priority for each type of data, a sorting priority is matched to each piece of incremental data. By using the sorting priority for each type of data, a sorting priority can be accurately matched to each piece of incremental data, greatly improving the efficiency and accuracy of data sorting.
[0055] In some embodiments, based on the sorting processing time of the same type of data and the number of requests for sorting the same type of data, the method for determining the target priority parameters for sorting of each type of data can be as follows: multiplying the sorting processing time of each type of data by the first preset weight coefficient to obtain the first priority parameter of each type of data; multiplying the number of requests for sorting the same type of data by the second preset weight coefficient to obtain the second priority parameter of each type of data; adding the first priority parameter and the second priority parameter of each type of data to obtain the target priority parameter. Among them, the first preset weight coefficient and the second preset weight coefficient can be set according to actual conditions, and the embodiments of the present application do not make specific restrictions on this. By taking a weighted sum of the sorting processing time and the number of requests for the same type of data, the target priority parameters for sorting of each type of data can be accurately obtained.
[0056] In some embodiments, the sorting priority is set according to the target priority parameters for sorting each type of data, and the sorting priority of each type of data can be obtained by obtaining a mapping relationship table between preset target priority parameters and sorting priorities, and querying the sorting priority that matches the target priority parameters from the mapping relationship table. Among them, the mapping relationship table is established in advance based on the target priority parameters and the sorting priority. The mapping relationship table can be established according to actual conditions, and the embodiments of the present application do not make specific restrictions on this. The sorting priority of each type of data can be accurately queried through the mapping relationship table, which greatly improves the efficiency and accuracy of data sorting.
[0057] In some embodiments, according to the sorting priority of each type of data, the method of matching the sorting priority of each piece of the incremental data can be: determining the data type of each piece of incremental data, matching the sorting priority of each piece of incremental data according to the sorting priority of each type of data, and obtaining the matching sorting priority of each piece of incremental data.
[0058] Step S103: Sort each piece of incremental data in the incremental data set according to the sorting priority of each piece of incremental data in the incremental data set and a preset sorting rule to obtain a second sorting result.
[0059] The second sorting result is a data queue obtained by sorting each piece of incremental data.
[0060] In some embodiments, each incremental data item is sorted according to its sorting priority to obtain a candidate sorting result; and the order of each incremental data item in the candidate sorting result is adjusted according to a preset sorting rule to obtain a second sorting result. The preset sorting rule can be set according to actual circumstances and is not specifically limited in the present embodiment.
[0061] It should be noted that the preset sorting rule may be a sorting rule in which the longer the sorting processing time, the higher the sorting priority, and the more requests, the higher the sorting priority.
[0062] In some embodiments, each piece of incremental data is sorted according to its sorting priority, and the method for obtaining the candidate sorting result can be: sorting the sorting order of each piece of incremental data according to its sorting priority, and sorting each piece of incremental data based on the sorting order to obtain the candidate sorting result.
[0063] Step S104: merge the first sorting result and the second sorting result to obtain a target sorting result, and replace the first sorting result with the target sorting result.
[0064] By merging the first sorting result and the second sorting result, the target sorting result of the data set to be sorted can be accurately obtained. In this application, only the incremental data needs to be sorted to obtain the second sorting result, and then the first sorting result of the historical data and the second sorting result of the incremental data are merged to accurately obtain the target sorting result of the data set to be sorted, which greatly improves the efficiency and real-time performance of data sorting and can effectively reduce resource consumption.
[0065] In some embodiments, after obtaining the target sorting result of the data set to be sorted, the first sorting result is replaced with the target sorting result. By updating the first sorting result to the target sorting result, the efficiency and accuracy of the next data sorting can be effectively improved.
[0066] In some embodiments, in response to a data query request, a data query result is obtained from the target sorted result according to the query conditions in the data query request. The data query result can be accurately obtained from the target sorted result according to the data query request, greatly improving the efficiency and accuracy of the data query.
[0067] For example, in the insurance business field, a data sorting request is obtained, and the data sorting request is an event of vehicle flooding. According to the retrieval keyword of the data sorting request, which is the event of vehicle flooding, a data set to be sorted is obtained from the database, and the data set to be sorted includes a first sorting result and an incremental data set corresponding to the historical data set. The first sorting result is the event set of vehicle flooding before this month, and the incremental data set is the event set of vehicle flooding this month; the sorting priority of each vehicle flooding event set this month is determined; according to the sorting priority of each vehicle flooding event in the event set of vehicle flooding this month and the preset sorting rules, the each vehicle flooding event in the event set of vehicle flooding this month is sorted to obtain a second sorting result of the vehicle flooding events this month; the first sorting result and the second sorting result are merged to obtain a target sorting result of the vehicle flooding events.
[0068] For example, in the medical field, a data sorting request is obtained, and the data sorting request is for influenza medical record data. Based on the search keyword of the data sorting request, which is influenza medical record data, a data set to be sorted is obtained from a database. The data set to be sorted includes a first sorting result corresponding to the historical data set and an incremental data set. The first sorting result is the influenza medical record data set before this month, and the incremental data set is the influenza medical record data set for this month; the sorting priority of each influenza medical record data set for this month is determined; based on the sorting priority of each influenza medical record data set in this month's influenza medical record data set and a preset sorting rule, each influenza medical record data set in this month's influenza medical record data set is sorted to obtain a second sorting result for this month's influenza medical record data; the first sorting result and the second sorting result are merged to obtain a target sorting result for sorting the influenza medical record data set.
[0069] The data sorting method provided in the above embodiment, in response to a data sorting request, obtains a data set to be sorted, wherein the data set to be sorted includes a first sorting result corresponding to a historical data set and an incremental data set; determines the sorting priority of each incremental data in the incremental data set; sorts each incremental data in the incremental data set according to the sorting priority of each incremental data in the incremental data set and a preset sorting rule to obtain a second sorting result; merges the first sorting result and the second sorting result to obtain a target sorting result, and replaces the first sorting result with the target sorting result. In the present application, when sorting the data set to be sorted, it is only necessary to sort the incremental data set in real time to obtain the second sorting result, and merge the first sorting result corresponding to the historical data set in the data set to be sorted and the second sorting result of the incremental data set, which can accurately sort the data set to be sorted, greatly improve the efficiency and real-time performance of data sorting, and reduce the resource consumption of the equipment during the data sorting process. In the financial and medical fields, the technical solution of the present application can effectively improve the sorting efficiency and accuracy of financial data and medical data.
[0070] See also Figure 3 , Figure 3 A schematic block diagram of a data sorting device provided in an embodiment of the present application.
[0071] like Figure 3 As shown, the data sorting device 200 includes an acquisition module 210, a determination module 220 and a generation module 230, wherein:
[0072] The acquisition module 210 is configured to acquire a data set to be sorted in response to a data sorting request, wherein the data set to be sorted includes a first sorting result corresponding to the historical data set and an incremental data set;
[0073] The determining module 220 is configured to determine a sorting priority of each piece of incremental data in the incremental data set;
[0074] The generating module 230 is configured to sort each piece of incremental data in the incremental data set according to the sorting priority of each piece of incremental data in the incremental data set and a preset sorting rule to obtain a second sorting result;
[0075] The generating module 230 is further configured to merge the first sorting result and the second sorting result to obtain a target sorting result, and replace the first sorting result with the target sorting result.
[0076] In some embodiments, as Figure 4 As shown, the determination module 220 includes a first determination submodule 221 and a second determination submodule 222, wherein:
[0077] The first determining submodule 221 is used to determine the sorting processing time of the same type of data in the historical data set and the number of sorting requests for the same type of data;
[0078] The second determining submodule 222 is configured to determine the sorting priority of each piece of the incremental data according to the sorting processing time of the same type of data and the number of sorting requests for the same type of data.
[0079] In some embodiments, the first determining submodule 221 is further configured to:
[0080] Get the actual sorting processing time of each historical data of the same type in the historical data set;
[0081] The actual sorting processing time of multiple historical data of the same type of data is weighted averaged to obtain the sorting processing time of the same type of data.
[0082] In some embodiments, the second determining submodule 222 is further configured to:
[0083] Determine the target priority parameters for sorting of each type of data based on the sorting processing time of the same type of data and the number of sorting requests for the same type of data;
[0084] Setting the sorting priority according to the target priority parameters of the sorting of each type of data to obtain the sorting priority of each type of data;
[0085] According to the sorting priority of each type of data, the sorting priority is matched for each piece of the incremental data.
[0086] In some embodiments, the second determining submodule 222 is further configured to:
[0087] Performing a multiplication operation on the sorting processing time of each type of data and a first preset weight coefficient to obtain a first priority parameter of each type of data;
[0088] Performing a multiplication operation on the number of sorting requests for each type of data and a second preset weight coefficient to obtain a second priority parameter for each type of data;
[0089] The first priority parameter and the second priority parameter of each type of data are added to obtain the target priority parameter.
[0090] In some embodiments, the generating module 230 is further configured to:
[0091] Sort each piece of incremental data according to its sorting priority to obtain a candidate sorting result;
[0092] The order of each of the incremental data in the candidate sorting result is adjusted according to the preset sorting rule to obtain the second sorting result.
[0093] In some embodiments, the data sorting device is further configured to:
[0094] In response to a data query request, a data query result is obtained from the target sorted result according to a query condition in the data query request.
[0095] It should be noted that those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working process of the above-mentioned data sorting device can refer to the corresponding process in the aforementioned data sorting method embodiment, and will not be repeated here.
[0096] See also Figure 5 , Figure 5 A schematic block diagram of the structure of a computer device provided in an embodiment of the present application.
[0097] like Figure 5 As shown, the computer device 300 includes a processor 302 and a memory 303 connected via a system bus 301 , wherein the memory may include a storage medium and an internal memory.
[0098] The storage medium may store a computer program, wherein the computer program includes program instructions, and when the program instructions are executed, the processor may execute any data sorting method.
[0099] The processor 301 is used to provide computing and control capabilities and support the operation of the entire computer device.
[0100] The internal memory provides an environment for the operation of the computer program in the storage medium. When the computer program is executed by the processor, the processor can execute any data sorting method.
[0101] Those skilled in the art will understand that Figure 5 The structure shown in the figure is only a block diagram of a part of the structure related to the solution of the present application, and does not constitute a limitation on the computer device to which the solution of the present application is applied. The specific computer device may include more or fewer components than shown in the figure, or combine certain components, or have a different component arrangement.
[0102] It should be understood that the processor 301 may be a central processing unit (CPU), or other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field-programmable gate arrays (FPGA), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The general-purpose processor may be a microprocessor or any conventional processor.
[0103] In one embodiment, the processor 301 is configured to execute a computer program stored in a memory to implement the following steps:
[0104] In response to a data sorting request, obtaining a data set to be sorted, where the data set to be sorted includes a first sorting result corresponding to the historical data set and an incremental data set;
[0105] Determining the sorting priority of each piece of incremental data in the incremental data set;
[0106] sorting each piece of incremental data in the incremental data set according to the sorting priority of each piece of incremental data in the incremental data set and a preset sorting rule to obtain a second sorting result;
[0107] The first sorting result and the second sorting result are merged to obtain a target sorting result, and the first sorting result is replaced by the target sorting result.
[0108] In one embodiment, when determining the sorting priority of each piece of incremental data in the incremental data set, the processor 301 is configured to implement:
[0109] Determining a sorting processing time for data of the same type in the historical data set and a number of sorting requests for data of the same type;
[0110] The sorting priority of each piece of the incremental data is determined according to the sorting processing time of the same type of data and the number of sorting requests for the same type of data.
[0111] In one embodiment, when determining the sorting processing time of data of the same type in the historical data set, the processor 301 is configured to implement:
[0112] Get the actual sorting processing time of each historical data of the same type in the historical data set;
[0113] The actual sorting processing time of multiple historical data of the same type of data is weighted averaged to obtain the sorting processing time of the same type of data.
[0114] In one embodiment, when determining the sorting priority of each piece of incremental data based on the sorting processing time of the same type of data and the number of sorting requests for the same type of data, the processor 301 is configured to implement:
[0115] Determine the target priority parameters for sorting of each type of data based on the sorting processing time of the same type of data and the number of sorting requests for the same type of data;
[0116] Setting the sorting priority according to the target priority parameters of the sorting of each type of data to obtain the sorting priority of each type of data;
[0117] According to the sorting priority of each type of data, the sorting priority is matched for each piece of the incremental data.
[0118] In one embodiment, when determining the target priority parameter for sorting each type of data based on the sorting processing time of the same type of data and the number of sorting requests for the same type of data, the processor 301 is configured to implement:
[0119] Performing a multiplication operation on the sorting processing time of each type of data and a first preset weight coefficient to obtain a first priority parameter of each type of data;
[0120] Performing a multiplication operation on the number of sorting requests for each type of data and a second preset weight coefficient to obtain a second priority parameter for each type of data;
[0121] The first priority parameter and the second priority parameter of each type of data are added to obtain the target priority parameter.
[0122] In one embodiment, when the processor 301 implements the step of sorting the incremental data in the incremental data set according to the sorting priority of each incremental data in the incremental data set and the preset sorting rule to obtain the second sorting result, it is configured to implement:
[0123] Sort each piece of incremental data according to its sorting priority to obtain a candidate sorting result;
[0124] The order of each of the incremental data in the candidate sorting result is adjusted according to the preset sorting rule to obtain the second sorting result.
[0125] In one embodiment, the processor 301 is further configured to implement:
[0126] In response to a data query request, a data query result is obtained from the target sorted result according to a query condition in the data query request.
[0127] It should be noted that those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working process of the computer device described above can refer to the corresponding process in the aforementioned data sorting method embodiment, and will not be repeated here.
[0128] An embodiment of the present application also provides a computer-readable storage medium, on which a computer program is stored. The computer program includes program instructions. The method implemented when the program instructions are executed can refer to the various embodiments of the data sorting method of the present application.
[0129] The computer-readable storage medium may be an internal storage unit of the computer device described in the aforementioned embodiment, such as a hard disk or memory of the computer device. The computer-readable storage medium may be non-volatile or volatile. The computer-readable storage medium may also be an external storage device of the computer device, such as a plug-in hard disk, a smart media card (SMC), a secure digital (SD) card, a flash memory card, etc., equipped on the computer device.
[0130] Furthermore, the computer-readable storage medium may mainly include a program storage area and a data storage area, wherein the program storage area may store an operating system, an application required for at least one function, etc.; the data storage area may store data created according to the use of the blockchain node, etc.
[0131] Blockchain, as used in this article, refers to a novel application model for computer technologies such as distributed data storage, peer-to-peer transmission, consensus mechanisms, and encryption algorithms. Blockchain is essentially a decentralized database, a series of data blocks generated using cryptographic methods. Each block contains information about a batch of online transactions, used to verify the validity of this information (to prevent counterfeiting) and generate the next block. Blockchain can include the underlying blockchain platform, the platform product service layer, and the application service layer.
[0132] It should be understood that the terms used in this specification are only for the purpose of describing specific embodiments and are not intended to limit the present application. As used in this specification, the singular forms "a", "an", and "the" are intended to include the plural forms unless the context clearly indicates otherwise.
[0133] It should also be understood that the term "and / or" used in this specification refers to any combination of one or more of the associated listed items and all possible combinations, including these combinations. It should be noted that, in this article, the terms "include", "comprise" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or system that includes a series of elements includes not only those elements, but also other elements that are not explicitly listed, or also includes elements that are inherent to such process, method, article or system. In the absence of further restrictions, an element defined by the sentence "including a..." does not exclude the presence of other identical elements in the process, method, article or system that includes the element.
[0134] The serial numbers of the embodiments of the present application are for descriptive purposes only and do not represent the merits of the embodiments. The above description is only a specific embodiment of the present application, but the scope of protection of the present application is not limited thereto. Any person skilled in the art can easily think of various equivalent modifications or replacements within the technical scope disclosed in the present application, and these modifications or replacements should be included in the scope of protection of the present application.
Claims
1. A data sorting method, characterized in that: include: In response to a data sorting request, obtaining a data set to be sorted, where the data set to be sorted includes a first sorting result corresponding to the historical data set and an incremental data set; Determining the sorting priority of each piece of incremental data in the incremental data set; sorting each piece of incremental data in the incremental data set according to the sorting priority of each piece of incremental data in the incremental data set and a preset sorting rule to obtain a second sorting result; The first sorting result and the second sorting result are merged to obtain a target sorting result, and the first sorting result is replaced by the target sorting result.
2. The data sorting method according to claim 1, wherein: Determining the sorting priority of each piece of incremental data in the incremental data set includes: Determining a sorting processing time for data of the same type in the historical data set and a number of sorting requests for data of the same type; The sorting priority of each piece of the incremental data is determined according to the sorting processing time of the same type of data and the number of sorting requests for the same type of data.
3. The data sorting method according to claim 2, wherein: Determining the sorting processing time of data of the same type in the historical data set includes: Get the actual sorting processing time of each historical data of the same type in the historical data set; The actual sorting processing time of multiple historical data of the same type of data is weighted averaged to obtain the sorting processing time of the same type of data.
4. The data sorting method according to claim 2, wherein: The determining the sorting priority of each piece of incremental data according to the sorting processing time of the same type of data and the number of sorting requests for the same type of data includes: Determine the target priority parameters for sorting of each type of data based on the sorting processing time of the same type of data and the number of sorting requests for the same type of data; Setting the sorting priority according to the target priority parameters of the sorting of each type of data to obtain the sorting priority of each type of data; According to the sorting priority of each type of data, the sorting priority is matched for each piece of the incremental data.
5. The data sorting method according to claim 4, wherein: Determining the target priority parameters for sorting of each type of data based on the sorting processing time of the same type of data and the number of requests for sorting the same type of data includes: Performing a multiplication operation on the sorting processing time of each type of data and a first preset weight coefficient to obtain a first priority parameter of each type of data; Performing a multiplication operation on the number of sorting requests for each type of data and a second preset weight coefficient to obtain a second priority parameter for each type of data; The first priority parameter and the second priority parameter of each type of data are added to obtain the target priority parameter.
6. The data sorting method according to claim 1, wherein: Sorting each piece of incremental data in the incremental data set according to the sorting priority of each piece of incremental data in the incremental data set and a preset sorting rule to obtain a second sorting result includes: Sort each piece of incremental data according to its sorting priority to obtain a candidate sorting result; The order of each of the incremental data in the candidate sorting result is adjusted according to the preset sorting rule to obtain the second sorting result.
7. The data sorting method according to any one of claims 1 to 6, characterized in that: The method further comprises: In response to a data query request, a data query result is obtained from the target sorted result according to a query condition in the data query request.
8. A data sorting device, characterized in that: The data sorting device includes an acquisition module, a determination module and a generation module, wherein: The acquisition module is configured to acquire a data set to be sorted in response to a data sorting request, wherein the data set to be sorted includes a first sorting result corresponding to the historical data set and an incremental data set; The determining module is used to determine the sorting priority of each incremental data in the incremental data set; The generating module is configured to sort each piece of incremental data in the incremental data set according to a sorting priority of each piece of incremental data in the incremental data set and a preset sorting rule to obtain a second sorting result; The generating module is further configured to merge the first sorting result and the second sorting result to obtain a target sorting result, and replace the first sorting result with the target sorting result.
9. A computer device, characterized in that: The computer device includes a processor, a memory, and a computer program stored in the memory and executable by the processor, wherein when the computer program is executed by the processor, the steps of the data sorting method according to any one of claims 1 to 7 are implemented.
10. A computer-readable storage medium, characterized in that The computer-readable storage medium stores a computer program, wherein when the computer program is executed by a processor, the steps of the data sorting method according to any one of claims 1 to 7 are implemented.