Data processing method and device, computer equipment and storage medium

Abstract

The invention relates to the field of digital information, and provides a data processing method, device and equipment and a computer storage medium, the method comprises the following steps: determining target index data corresponding to index data according to associated data corresponding to preset index data in a relational database; searching index values in the relational database on the basis of the target index data, and determining the index data corresponding to the index values as the index values; storing the index numerical value and the corresponding index numerical value into a memory database; and under the condition that the index numerical value meets a preset condition, transmitting the index to a preset operation processing unit, and obtaining an operation result of the operation processing unit. The invention further relates to the field of intelligent finance, and data stored in the relational database and the memory database can be financial data.

Description

Technical Field

[0001] This application relates to the field of digital information, and particularly to a data processing method, apparatus, computer device, and storage medium. Background Art

[0002] Relational databases and in-memory databases are two different types of databases, each with its own characteristics and applicable scenarios. For example, although the read and write speed of relational databases is not as fast as that of in-memory databases, they perform well in processing complex queries and transactions and are suitable for storing large-scale data and handling complex transactions; in-memory databases store data in memory and have extremely fast read and write speeds, and are suitable for scenarios that require high-concurrency access. In order to transfer data between relational databases and in-memory databases, it is usually necessary for users to manually set index data. For example, financial data usually includes end-of-day regular data and intraday change data, and users need to set them separately for these two types. This method is inefficient and has a certain learning cost. How to automatically determine the index data for data transfer between relational databases and in-memory databases to improve data processing efficiency has become an urgent problem to be solved. Summary of the Invention

[0003] The main purpose of this application is to provide a data processing method, apparatus, device, and computer storage medium, aiming to improve the efficiency of data transfer between relational databases and in-memory databases.

[0004] In a first aspect, this application provides a data processing method, and the data processing method includes the following steps:

[0005] Determine the target index data corresponding to the metric data according to the associated data corresponding to the preset metric data in the relational database;

[0006] Search for index values in the relational database based on the target index data, and determine the metric data corresponding to each index value as metric values;

[0007] Store the metric values and the corresponding index values into the in-memory database;

[0008] When the metric values meet the preset conditions, transmit the metrics to a preset arithmetic processing unit and obtain the arithmetic result of the arithmetic processing unit.

[0009] In some embodiments, the determining the target index data corresponding to the metric data according to the associated data corresponding to the preset metric data in the relational database includes:

[0010] Determine the data columns in the relational database other than the metric data as the associated data;

[0011] Construct candidate index data based on the associated data, and filter out valid index data from the candidate index data;

[0012] Evaluate the valid index data, and determine the target index data according to the evaluation result.

[0013] In some embodiments, the constructing candidate index data based on the associated data and filtering out valid index data from the candidate index data includes:

[0014] Combine each piece of the associated data to obtain the candidate index data;

[0015] Perform a lookup operation on the metric data in the relational database according to the candidate index data;

[0016] When a unique corresponding metric value can be found according to the candidate index data, determine the candidate index data as the valid index data.

[0017] In some embodiments, the evaluating the valid index data and determining the target index data according to the evaluation result includes:

[0018] Obtain the mean value of the data volume corresponding to each piece of the valid index data;

[0019] Determine the valid index data with the smallest mean value of the data volume as the target index data.

[0020] In some embodiments, the data processing method further includes:

[0021] Store the operation result into the relational database according to the index value.

[0022] In some embodiments, the storing the operation result into the relational database according to the index value includes:

[0023] Obtain the metric value corresponding to the operation result and the index value corresponding to the metric value;

[0024] Split the index value according to the data columns in the relational database to obtain the data column values corresponding to the index value;

[0025] Correspondingly store the data column values and the operation result into the relational database.

[0026] In some embodiments, the data processing method further includes:

[0027] Output the operation result of the operation processing unit to a display unit for display; or,

[0028] Output the operation result stored in the memory database to a display unit for display.

[0029] In a second aspect, the present application further provides a data processing device, which includes:

[0030] An index determination module, configured to determine target index data corresponding to the metric data according to associated data corresponding to the preset metric data in a relational database;

[0031] A data extraction module, configured to search for index values in the relational database based on the target index data, and determine the metric data corresponding to each index value as metric values;

[0032] A data storage module, configured to store the metric values and the corresponding index values in a memory database;

[0033] A data operation module, configured to transmit the metric to a preset operation processing unit and obtain an operation result of the operation processing unit when the metric value meets a preset condition.

[0034] In a third aspect, the present application further provides a computer device, which includes a processor, a memory, and a computer program stored on the memory and executable by the processor. When the computer program is executed by the processor, the data processing method as described above is implemented.

[0035] In a fourth aspect, the present application further provides a computer-readable storage medium, on which a computer program is stored. When the computer program is executed by a processor, the data processing method as described above is implemented.

[0036] The present application provides a data processing method, device, equipment, and computer storage medium. By determining target index data corresponding to the metric data according to associated data corresponding to the preset metric data in a relational database, searching for index values in the relational database based on the target index data, and determining the metric data corresponding to each index value as metric values, storing the metric values and the corresponding index values in a memory database, and transmitting the metric to a preset operation processing unit and obtaining an operation result of the operation processing unit when the metric value meets a preset condition. Since the target index data for searching metric values is automatically determined according to the metric data, the efficiency of transmitting data from a relational database to a memory database is improved, thereby improving the data processing efficiency. Description of the Drawings

[0037] To more clearly illustrate the technical solutions of the embodiments of the present application, the following will briefly introduce the accompanying drawings required for the description of the embodiments. Obviously, the accompanying drawings in the following description are some embodiments of the present application. For those of ordinary skill in the art, without creative efforts, other accompanying drawings can also be obtained based on these drawings.

[0038] Figure 1 It is a schematic flowchart of a data processing method provided by an embodiment of the present application;

[0039] Figure 2 It is a usage scenario diagram of a data processing method provided by an embodiment of the present application;

[0040] Figure 3 It is a schematic block diagram of a data processing device provided by an embodiment of the present application;

[0041] Figure 4 It is a schematic block diagram of the structure of a computer device related to an embodiment of the present application. Detailed implementation manners

[0042] The following will clearly and completely describe the technical solutions in the embodiments of the present application with reference to the accompanying drawings in the embodiments of the present application. Obviously, the described embodiments are some, but not all, of the embodiments of the present application. Based on the embodiments in the present application, all other embodiments obtained by those of ordinary skill in the art without creative efforts belong to the scope of protection of the present application.

[0043] The flowchart shown in the accompanying drawings is only an example illustration, and does not necessarily include all contents and operations / steps, nor does it necessarily execute in the described order. For example, some operations / steps can also be decomposed, combined, or partially merged. Therefore, the actual execution order may be changed according to the actual situation.

[0044] The embodiments of the present application provide a data processing method, device, computer device, and computer-readable storage medium.

[0045] The following will elaborate on some implementation manners of the present application with reference to the accompanying drawings. Without conflict, the following embodiments and the features in the embodiments can be combined with each other.

[0046] Please refer to Figure 1 , Figure 1Schematic flowchart of a data processing method provided by an embodiment of the present application. This data processing method can be used in a terminal or a server to achieve data transmission and data processing between a relational database and an in-memory database. Among them, the terminal can be an electronic device such as a mobile phone, a tablet computer, a notebook computer, a desktop computer, a personal digital assistant, and a wearable device; the server can be an independent server, a server cluster, or a cloud server that provides basic cloud computing services such as cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communications, middleware services, domain name services, security services, Content Delivery Network (CDN), and big data and artificial intelligence platforms.

[0047] Please refer to Figure 2 , Figure 2 which is a usage scenario diagram provided by an embodiment of the present application. As Figure 2 shown, the in-memory database obtains metric values from the relational database according to the target index data, and transmits the data to the arithmetic processing unit for calculation. The arithmetic processing unit returns the calculation result to the in-memory database, and the in-memory database then stores the calculation result in the relational database; at the same time, the arithmetic processing unit outputs the calculation result to the display unit for display, or the in-memory database outputs the calculation result to the display unit for display.

[0048] Among them, the data stored in the relational database and the in-memory database can be financial data, such as the various performance indicators of financial products.

[0049] As Figure 1 shown, this data processing method includes steps S101 to S104.

[0050] Step S101: Determine the target index data corresponding to the metric data according to the associated data corresponding to the preset metric data in the relational database.

[0051] Exemplarily, the relational database stores data in the form of a table, and a table can include multiple data rows and data columns; while the in-memory database stores data in the form of key-value pairs, and one key corresponds to one value, thereby improving the convenience of data lookup. Therefore, when storing data from the relational database to the in-memory database, a unique key needs to be determined for each piece of data.

[0052] Exemplarily, data columns in a relational database other than the metric data to be saved can be combined into keys in an in-memory database. For example, the data columns in a relational database include "product name; product ID; time; metric name; metric ID; metric value". If the metric value is used as the preset metric data, the key corresponding to the metric data can be "product name - product ID - time - metric name - metric ID". However, this method cannot determine the most concise key for the in-memory database, resulting in an unnecessary increase in the storage cost of the in-memory database. In this regard, the data processing method provided by the embodiments of the present application can automatically determine the target index data of the metric data according to the relational database, so that the target index data can not only uniquely determine the metric data, but also minimize the data volume as much as possible.

[0053] In some embodiments, determining the target index data corresponding to the metric data according to the associated data corresponding to the preset metric data in the relational database includes:

[0054] Determine the data columns in the relational database other than the metric data as the associated data;

[0055] Construct candidate index data based on the associated data, and screen out valid index data from the candidate index data;

[0056] Evaluate the valid index data, and determine the target index data according to the evaluation result.

[0057] Exemplarily, the metric data is any one of the data columns in the relational database. The data columns in the relational database other than the metric data itself may all be target index data that can be used to uniquely determine the metric data. Therefore, the data columns in the relational database other than the metric data itself are determined as the associated data corresponding to the metric data, so as to determine the target index data that can be used to uniquely determine the metric data according to the associated data. Specifically, combine the associated data items to construct candidate index data, and determine the target index data from the candidate index data.

[0058] In some embodiments, constructing candidate index data based on the associated data, and screening out valid index data from the candidate index data includes:

[0059] Combine each of the associated data to obtain the candidate index data;

[0060] Perform a lookup operation on the metric data in the relational database according to the candidate index data;

[0061] When the unique corresponding metric value can be found according to the candidate index data, determine the candidate index data as the valid index data.

[0062] Exemplarily, the associated data is combined to obtain candidate index data, and the metric data is searched in the relational database based on the candidate index data. If the metric value can be uniquely determined without duplication in the relational database according to the candidate index data, it indicates that the candidate index data is available and valid index data; conversely, if the metric data is searched according to the candidate index data and the found metric values are duplicated, it indicates that the candidate index data is invalid index data.

[0063] Exemplarily, when determining the valid index data according to the candidate index data, the valid index data can be screened starting from the candidate index data with the fewest data columns in ascending order, and the first obtained valid index data is used as the target index data, thereby reducing the computational amount for determining the target index data.

[0064] In some embodiments, the evaluating the valid index data and determining the target index data according to the evaluation result includes:

[0065] Obtaining the mean data volume corresponding to each of the valid index data;

[0066] Determining the valid index data with the smallest mean data volume as the target index data.

[0067] Exemplarily, if multiple valid index data are obtained from the candidate index data, the one with the smallest data volume among the multiple valid index data can be determined as the target index data. Specifically, the mean data volume of the valid index values corresponding to each valid index data is calculated, so as to determine the valid index data with the smallest mean data volume as the target index data, reducing the storage space occupied by the target index data in the in-memory database.

[0068] For example, if the valid index data determined for the metric value includes "Product Name - Time - Metric Name" and "Product ID - Time - Metric ID", although the number of data columns they contain is the same, both being 3, the target index data with a smaller mean data volume can be determined by comparing the mean data volumes of the corresponding values, and "Product Name - Time - Metric Name" is determined as the target index data, so that "Product Name - Time - Metric Name" is used as the target index data.

[0069] Step S102: Search for index values in the relational database based on the target index data, and determine the metric data corresponding to each of the index values as the metric value.

[0070] Exemplarily, the index value is the specific value of the target index data. For example, if the target index data is "product name - time - metric name", the corresponding index value may include "Daily Growth; 20241118; 7 - day annualized rate of return", so as to find the metric values corresponding to each index value according to the target index data.

[0071] Step S103: Store the metric value and the corresponding index value into the in - memory database.

[0072] Exemplarily, financial data usually includes end - of - day regular data and intraday change data. Among them, end - of - day regular data is usually batch - calculated data. For example, on a daily basis, end - of - day regular data is calculated once a day, while intraday change data is usually data that needs to be calculated in real - time and requires frequent reading and writing. Since relational databases are more complex in reading and writing compared to in - memory databases, intraday change data can be stored in the in - memory database, making it convenient to access.

[0073] Step S104: When the metric value meets the preset condition, transmit the metric to a preset operation processing unit and obtain the operation result of the operation processing unit.

[0074] Exemplarily, when the metric data meets the preset condition, for example, when the data volume of the metric data reaches the data volume threshold, the metric is transmitted to a preset operation processing unit for calculation. The operation processing unit can be a pre - set algorithm framework, which is not limited here.

[0075] Exemplarily, the metric value is transmitted from the in - memory database to the operation processing unit for calculation through kafka.

[0076] In some embodiments, the data processing method further includes:

[0077] Output the operation result of the operation processing unit to a display unit for display; or,

[0078] Output the operation result stored in the in - memory database to the display unit for display.

[0079] Exemplarily, the purpose of obtaining the operation result is to display it on the display unit. Therefore, it can be that the operation processing unit directly outputs the operation result to the display unit for display, or the operation processing unit first stores the operation result in the in - memory database, and the display unit then obtains the operation result from the in - memory database and displays it, which is not limited here.

[0080] In some embodiments, the data processing method further includes:

[0081] Store the operation result into the relational database according to the index value.

[0082] Exemplarily, to ensure the queryability of data, the operation result can be persisted into a relational database. For example, transfer the operation result saved in the in-memory database to the relational database for storage.

[0083] In some embodiments, the storing the operation result into the relational database according to the index value includes:

[0084] Obtain the metric value corresponding to the operation result and the index value corresponding to the metric value;

[0085] Split the index value according to the data columns in the relational database to obtain the data column values corresponding to the index value;

[0086] Correspondingly store the data column values and the operation result into the relational database.

[0087] Exemplarily, since the operation result is obtained based on the metric value, there is a unique corresponding index value for the metric value, and the index value is obtained by searching in the relational database according to the target index data. Therefore, for each operation result, the index value corresponding to its metric value can be split to obtain the data column values that make up the index value, so as to determine the position of the index value in the relational database according to the data column values, and store the operation result and the metric value correspondingly in the relational database to improve the queryability of data.

[0088] The data processing method provided by the above embodiment determines the target index data corresponding to the metric data according to the associated data corresponding to the preset metric data in the relational database; searches for the index value in the relational database based on the target index data, and determines the metric data corresponding to each index value as the metric value; stores the metric value and the corresponding index value into the in-memory database; when the metric value meets the preset condition, transmits the metric to the preset operation processing unit and obtains the operation result of the operation processing unit. Since the target index data for searching the metric value is automatically determined according to the metric data, the efficiency of transferring data from the relational database to the in-memory database is improved, thereby improving the data processing efficiency.

[0089] Please refer to Figure 3 , Figure 3 is a schematic diagram of a data processing device provided by an embodiment of the present application. This data processing device can be configured in a server or a terminal and is used to execute the foregoing data processing method.

[0090] AsFigure 3 As shown, the data processing device includes: an index determination module 110, a data extraction module 120, a data storage module 130, and a data operation module 140.

[0091] The index determination module 110 is configured to determine target index data corresponding to the metric data according to associated data corresponding to the preset metric data in a relational database.

[0092] The data extraction module 120 is configured to search for index values in the relational database based on the target index data, and determine the metric data corresponding to each index value as metric values.

[0093] The data storage module 130 is configured to store the metric values and the corresponding index values in an in-memory database.

[0094] The data operation module 140 is configured to transmit the metric to a preset operation processing unit and obtain an operation result of the operation processing unit when the metric value meets a preset condition.

[0095] In some embodiments, in the process of the index determination module 110 implementing the determination of the target index data corresponding to the metric data according to the associated data corresponding to the preset metric data in the relational database, it is configured to implement:

[0096] Determine the data columns in the relational database other than the metric data as the associated data;

[0097] Construct candidate index data based on the associated data, and screen out valid index data from the candidate index data;

[0098] Evaluate the valid index data, and determine the target index data according to the evaluation result.

[0099] In some embodiments, in the process of the index determination module 110 implementing the construction of candidate index data based on the associated data and screening out valid index data from the candidate index data, it is configured to implement:

[0100] Combine each piece of the associated data to obtain the candidate index data;

[0101] Perform a search operation on the metric data in the relational database according to the candidate index data;

[0102] When a unique corresponding metric value can be found according to the candidate index data, determine the candidate index data as valid index data.

[0103] In some embodiments, when the index determination module 110 is used to implement the process of evaluating the valid index data and determining the target index data according to the evaluation result, it is used to implement:

[0104] Obtain the average data volume corresponding to each piece of the valid index data;

[0105] Determine the valid index data with the smallest average data volume as the target index data.

[0106] In some embodiments, when the data processing device is used to implement the data processing method, it is used to implement:

[0107] Store the operation result into the relational database according to the index value.

[0108] In some embodiments, when the data processing device is used to implement the process of storing the operation result into the relational database according to the index value, it is used to implement:

[0109] Obtain the index value corresponding to the operation result and the index value corresponding to the index value;

[0110] Split the index value according to the data columns in the relational database to obtain the data column values corresponding to the index value;

[0111] Correspondingly store the data column values and the operation result into the relational database.

[0112] In some embodiments, when the data processing device is used to implement the data processing method, it is used to implement:

[0113] Output the operation result of the operation processing unit to the display unit for display; or,

[0114] Output the operation result stored in the in-memory database to the display unit for display.

[0115] It should be noted that those skilled in the art can clearly understand that for the convenience and brevity of description, the specific working processes of the above-described device and each module and unit can refer to the corresponding processes in the foregoing method embodiments, and will not be elaborated herein.

[0116] The methods and apparatuses of the present application can be used in numerous general-purpose or special-purpose computing system environments or configurations. For example: personal computers, server computers, handheld or portable devices, tablet devices, multi-processor systems, microprocessor-based systems, set-top boxes, programmable consumer electronic devices, network PCs, minicomputers, mainframe computers, distributed computing environments including any of the above systems or devices, and so on. The present application can be described in the general context of computer-executable instructions executed by a computer, such as program modules. Generally, program modules include routines, programs, objects, components, data structures, etc. that perform specific tasks or implement specific abstract data types. The present application can also be practiced in a distributed computing environment where tasks are performed by remote processing devices connected through a communication network. In a distributed computing environment, program modules can be located in local and remote computer storage media including storage devices.

[0117] Exemplarily, the above-mentioned methods and apparatuses can be implemented in the form of a computer program, which can run on a computer device as shown in Figure 4 the following.

[0118] Please refer to Figure 4 , Figure 4 which is a schematic block diagram of the structure of a computer device provided by an embodiment of the present application. The computer device can be a server or a terminal.

[0119] As shown in Figure 4 the following, the computer device includes a processor, a memory, and a network interface connected through a system bus. Among them, the memory can include a storage medium and an internal memory.

[0120] The storage medium can store an operating system and a computer program. The computer program includes program instructions, and when the program instructions are executed, the processor can be enabled to execute any one of the data processing methods.

[0121] The processor is used to provide computing and control capabilities to support the operation of the entire computer device.

[0122] 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 be enabled to execute any one of the data processing methods.

[0123] The network interface is used for network communication, such as sending assigned tasks, etc. Those skilled in the art can understand that the structure shown in Figure 4 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 those shown in the figure, or combine some components, or have different component arrangements.

[0124] It should be understood that the processor may be a Central Processing Unit (CPU), and the processor may also be other general-purpose processors, Digital Signal Processors (DSPs), Application Specific Integrated Circuits (ASICs), Field-Programmable Gate Arrays (FPGAs) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. Among them, the general-purpose processor may be a microprocessor or the processor may also be any conventional processor, etc.

[0125] Among them, in one embodiment, the processor is used to run a computer program stored in the memory to implement the following steps:

[0126] Determine the target index data corresponding to the metric data according to the associated data corresponding to the preset metric data in the relational database;

[0127] Search for index values in the relational database based on the target index data, and determine the metric data corresponding to each index value as metric values;

[0128] Store the metric values and the corresponding index values into the in-memory database;

[0129] When the metric values meet the preset conditions, transmit the metrics to a preset arithmetic processing unit and obtain the operation result of the arithmetic processing unit.

[0130] In some embodiments, in the process of implementing the determination of the target index data corresponding to the metric data according to the associated data corresponding to the preset metric data in the relational database, the processor is used to implement:

[0131] Determine the data columns in the relational database other than the metric data as the associated data;

[0132] Construct candidate index data based on the associated data, and screen out valid index data from the candidate index data;

[0133] Evaluate the valid index data, and determine the target index data according to the evaluation results.

[0134] In some embodiments, in the process of implementing the construction of candidate index data based on the associated data and screening out valid index data from the candidate index data, the processor is configured to implement:

[0135] Combine each piece of the associated data to obtain the candidate index data;

[0136] Perform a lookup operation on the metric data in the relational database according to the candidate index data;

[0137] When a unique corresponding metric value can be found according to the candidate index data, determine the candidate index data as the valid index data.

[0138] In some embodiments, in the process of implementing the evaluation of the valid index data and determining the target index data according to the evaluation result, the processor is configured to implement:

[0139] Obtain the average data volume corresponding to each piece of the valid index data;

[0140] Determine the valid index data with the smallest average data volume as the target index data.

[0141] In some embodiments, in the process of implementing the data processing method, the processor is configured to implement:

[0142] Store the operation result into the relational database according to the index value.

[0143] In some embodiments, in the process of implementing the storage of the operation result into the relational database according to the index value, the processor is configured to implement:

[0144] Obtain the metric value corresponding to the operation result and the index value corresponding to the metric value;

[0145] Split the index value according to the data columns in the relational database to obtain the data column values corresponding to the index value;

[0146] Correspondingly store the data column values and the operation result into the relational database.

[0147] In some embodiments, in the process of implementing the data processing method, the processor is configured to implement:

[0148] Output the operation result of the operation processing unit to the display unit for display; or,

[0149] Output the operation result stored in the in-memory database to the display unit for display.

[0150] 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-described data processing can refer to the corresponding process in the foregoing embodiments of the data processing control method, and will not be elaborated herein.

[0151] The embodiment of the present application further provides a computer-readable storage medium, on which a computer program is stored. The computer program includes program instructions, and the method implemented when the program instructions are executed can refer to each embodiment of the data processing method of the present application.

[0152] Among them, the computer-readable storage medium may be an internal storage unit of the computer device described in the foregoing embodiments, such as the hard disk or memory of the computer device. 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 Card, etc. equipped on the computer device.

[0153] It should be understood that the terms used in the specification of the present application are only for the purpose of describing specific embodiments and are not intended to limit the present application. As used in the specification of the present application and the appended claims, unless the context clearly indicates otherwise, the singular forms "a", "an" and "the" are intended to include the plural forms.

[0154] It should also be understood that the term "and / or" used in the specification of the present application and the appended claims refers to any combination and all possible combinations of one or more of the associated listed items, and includes these combinations. It should be noted that in this article, the term "comprises", "comprising" or any other variation thereof is intended to cover a non-exclusive inclusion, such that a process, method, article or system including a series of elements includes not only those elements but also other elements not expressly listed, or further includes elements inherent to such process, method, article or system. Without further limitation, an element defined by the phrase "comprising a..." does not exclude the existence of additional identical elements in the process, method, article or system including the element.

[0155] The serial numbers of the embodiments of the present application above are only for description and do not represent the superiority or inferiority of the embodiments. The above is only the specific implementation manner of the present application, but the protection scope of the present application is not limited thereto. Any person skilled in the art within the technical scope disclosed by the present application can easily think of various equivalent modifications or substitutions, and these modifications or substitutions should all be covered within the protection scope of the present application. Therefore, the protection scope of the present application shall be subject to the protection scope of the claims.

Claims

1. A data processing method, characterized in that: The method comprises: Determine the target index data corresponding to the indicator data according to the associated data corresponding to the preset indicator data in the relational database; Searching for index values ​​in the relational database based on the target index data, and determining the index data corresponding to each of the index values ​​as the index value; Storing the indicator value and the corresponding index value in a memory database; When the indicator value meets the preset condition, the indicator is transmitted to a preset operation processing unit, and the operation result of the operation processing unit is obtained.

2. The data processing method according to claim 1, characterized in that: The step of determining target index data corresponding to the indicator data according to associated data corresponding to the preset indicator data in the relational database includes: Determine the data columns other than the indicator data in the relational database as the associated data; constructing candidate index data based on the associated data, and screening out valid index data from the candidate index data; The valid index data is evaluated, and the target index data is determined according to the evaluation result.

3. The data processing method according to claim 2, characterized in that: The constructing candidate index data based on the associated data, and screening out valid index data from the candidate index data, comprises: Combining the associated data to obtain the candidate index data; Performing a search operation on the indicator data in the relational database according to the candidate index data; In the case that a unique corresponding index value can be found according to the candidate index data, the candidate index data is determined as valid index data.

4. The data processing method according to claim 2, characterized in that: The step of evaluating the valid index data and determining the target index data according to the evaluation result includes: Obtaining the mean value of the data amount corresponding to each of the valid index data; The valid index data with the smallest data amount mean is determined as the target index data.

5. The data processing method according to claim 1, characterized in that: The data processing method further includes: The operation result is stored in the relational database according to the index value.

6. The data processing method according to claim 5, characterized in that: The step of storing the operation result in the relational database according to the index value includes: Obtaining the indicator value corresponding to the calculation result and the index value corresponding to the indicator value; Splitting the index value according to the data column in the relational database to obtain the data column value corresponding to the index value; The data column values ​​and the calculation results are stored in the relational database in correspondence.

7. The data processing method according to any one of claims 1 to 6, characterized in that: The data processing method further includes: Outputting the calculation result of the calculation processing unit to the display unit for display; or, The calculation results stored in the memory database are output to the display unit for display.

8. A data processing device, characterized in that: The data processing device comprises: An index determination module, used to determine target index data corresponding to the indicator data according to the associated data corresponding to the preset indicator data in the relational database; A data extraction module, used for searching index values ​​in the relational database based on the target index data, and determining the indicator data corresponding to each of the index values ​​as the indicator value; A data storage module, used for storing the indicator value and the corresponding index value in a memory database; The data operation module is used to transmit the indicator to a preset operation processing unit and obtain the operation result of the operation processing unit when the indicator value meets the preset conditions.

9. A computer device, characterized in that: The computer device comprises 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 processing 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 processing method according to any one of claims 1 to 7 are implemented.

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