CN116562704A - Index calculation method, system, equipment and storage medium - Google Patents
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Abstract
The invention relates to the field of financial science and technology, and particularly provides an index calculation method, an index calculation system, index calculation equipment and a storage medium, wherein the method comprises the following steps: acquiring at least one target evaluation index corresponding to a target service scene and a data source table corresponding to the target evaluation index; configuring target evaluation indexes and preset basic indexes on all nodes of a preset tree according to preset classification labels corresponding to the target evaluation indexes and assets corresponding to the target evaluation indexes, wherein the preset tree represents the dependency relationship between the target evaluation indexes and the preset basic indexes; and calculating the value of the target evaluation index by using a recursive traversal algorithm based on a preset tree and a data source table through an index calculation engine. The invention can improve the index calculation efficiency and reduce the index calculation redundancy. Therefore, when a bank or an insurance company is in use, the relevant indexes of the financial business can be calculated efficiently, and the business processing efficiency is improved.
Description
Technical Field
The present invention relates to the technical field of financial science and technology, and in particular, to a method, a system, an apparatus, and a storage medium for calculating an index.
Background
For financial businesses often related to banks, insurance companies and the like, the index is a basis for quantifying business effects, the financial business index comprises classification indexes such as risk performance, asset liability, financial gain analysis and the like, the banks can judge whether to pay a certain business batch according to the financial business index, and the insurance companies can calculate insurance claim amounts according to the financial business index. As financial services rapidly increase, the demand for service metrics increases, and the method of computing metrics becomes more and more complex.
The current index calculation method mainly aims at customizing corresponding service index calculation scenes according to each service index, so that the calculation processes among different indexes are mutually independent, common logic calculation among different indexes is not shared, the reusability of the calculated service indexes is poor, and the calculation efficiency is low.
Disclosure of Invention
The invention provides an index calculation method, an index calculation system, index calculation equipment and a storage medium, and mainly aims to provide the index calculation method, so that the index calculation efficiency is effectively improved, and the relevant index of financial business can be efficiently calculated when a bank or an insurance company is used, and the business processing efficiency is improved.
In a first aspect, an embodiment of the present invention provides an index calculation method, including:
acquiring at least one target evaluation index corresponding to a target service scene and a data source table corresponding to the target evaluation index;
according to a preset classification label corresponding to the target evaluation index and an asset corresponding to the target evaluation index, configuring the target evaluation index and a preset basic index on each node of a preset tree, wherein the preset tree represents the dependency relationship between the target evaluation indexes and the preset basic index;
and calculating the value of the target evaluation index by using a recursive traversal algorithm based on the preset tree and the data source table through an index calculation engine.
Further, the configuring the target evaluation index and the preset basic index to each node of the preset tree according to the preset classification label corresponding to the target evaluation index and the asset corresponding to the target evaluation index includes:
acquiring a corresponding relation between the target evaluation index and the asset according to a preset classification label corresponding to the target evaluation index and a preset classification label corresponding to the asset, wherein the target evaluation index corresponds to one preset classification label, and the asset corresponds to at least one preset classification label;
acquiring a dependency relationship between the target evaluation indexes according to the correlation relationship between the assets and the corresponding relationship between the target evaluation indexes and the assets;
and configuring the target evaluation index and the preset basic index to each node of a preset tree according to the dependency relationship between the target evaluation indexes and the preset basic index.
Further, before the target evaluation index and the preset basic index are configured on each node of the preset tree according to the dependency relationship between the target evaluation indexes and the preset basic index, the method further includes:
acquiring the type of each target evaluation index according to the service calculation logic of each target evaluation index, wherein the type comprises a single index type and a complex index type;
splitting the target evaluation index of the complex index type into at least one target evaluation index of the single index type, and obtaining all the target evaluation indexes.
Further, the dependency relationship between the target evaluation index and the preset basic index is obtained by the following way:
and acquiring the dependency relationship between the target evaluation index and a preset basic index according to the business calculation logic of the target evaluation index.
Further, after the configuring the target evaluation index and the preset basic index to each node of the preset tree according to the preset classification label corresponding to the target evaluation index and the asset corresponding to the target evaluation index, the method further includes:
acquiring the dependency relationship among different dimensions of the target evaluation index;
adding dimension attribute for each node of the preset tree;
according to the dependency relationship among different dimensionalities of the target evaluation index, determining the value of the dimensionality attribute of each node of the preset tree, and taking the preset tree with the added dimensionality attribute as the preset tree again.
Further, the calculating, by the index calculating engine, the value of the target evaluation index by adopting a recursive traversal algorithm based on the preset tree and the data source table, includes:
acquiring target data for calculating the correspondence of each node from the data source table according to a preset classification label and dimension attribute corresponding to each node in the preset tree;
acquiring index values corresponding to each node according to target data corresponding to each node and a preset calculation rule;
and calculating upwards layer by layer according to the index value corresponding to each node and the preset calculation rule, and obtaining the value of the target evaluation index.
Further, the layer-by-layer upward calculation includes:
and carrying out parallel computation on the nodes of the same layer of the preset tree.
In a second aspect, an embodiment of the present invention provides an index calculation system, including:
the data module is used for acquiring at least one target evaluation index corresponding to a target service scene and a data source table corresponding to the target evaluation index;
the dependency module is used for configuring the target evaluation index and a preset basic index to each node of a preset tree according to a preset classification label corresponding to the target evaluation index and an asset corresponding to the target evaluation index, wherein the preset tree represents the dependency relationship between the target evaluation indexes and the preset basic index;
the calculation module is used for calculating the value of the target evaluation index by adopting a recursive traversal algorithm based on the preset tree and the data source table through an index calculation engine.
In a third aspect, an embodiment of the present invention provides a computer device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, where the processor implements the steps of the above-mentioned index calculation method when executing the computer program.
In a fourth aspect, an embodiment of the present invention provides a computer storage medium storing a computer program which, when executed by a processor, implements the steps of the index calculation method described above.
According to the index calculation method, system, equipment and storage medium, the dependency relationship between the target evaluation indexes and the preset basic indexes are shown through the preset tree, and the specific value of each target evaluation index can be calculated by adopting a recursion traversal algorithm through the index calculation engine. Because each target evaluation index is calculated upwards one by taking the preset tree as a basic structure on the basis of the preset basic configuration index, the same calculation part of the same index is calculated once, and the calculation result of the index is directly read when the calculation is still needed next time, so that the calculation efficiency of the index is improved, and the redundancy of calculation is reduced. Therefore, when a bank or an insurance company is in use, the relevant indexes of the financial business can be calculated efficiently, and the business processing efficiency is improved.
Drawings
Fig. 1 is a schematic diagram of an application scenario of an index calculation method according to an embodiment of the present invention;
FIG. 2 is a flowchart of an index calculation method according to an embodiment of the present invention;
FIG. 3 is a flowchart of a configuration method of a preset tree according to an embodiment of the present invention;
FIG. 4 is a schematic diagram of a system for calculating an index according to an embodiment of the present invention;
fig. 5 is a schematic structural diagram of a computer device according to an embodiment of the present invention.
The achievement of the objects, functional features and advantages of the present invention will be further described with reference to the accompanying drawings, in conjunction with the embodiments.
Detailed Description
Embodiments of the present application are described in detail below, examples of which are illustrated in the accompanying drawings, wherein like or similar reference numerals refer to like or similar elements or elements having like or similar functions throughout. The embodiments described below by referring to the drawings are exemplary only for the purpose of explaining the present application and are not to be construed as limiting the present application.
In order to better understand the solution of the present application, the following description will make clear and complete descriptions of the technical solution of the embodiment of the present application with reference to the accompanying drawings in the embodiment of the present application. It will be apparent that the described embodiments are only some, but not all, of the embodiments of the present application. All other embodiments, which can be made by those skilled in the art based on the embodiments herein without making any inventive effort, are intended to be within the scope of the present application.
In the embodiment of the application, at least one refers to one or more; plural means two or more. In the description of the present application, the words "first," "second," "third," and the like are used solely for the purpose of distinguishing between descriptions and not necessarily for the purpose of indicating or implying a relative importance or order. Furthermore, the terms "first," "second," and the like, are used for descriptive purposes only and are not to be construed as indicating or implying a relative importance or implicitly indicating the number of technical features indicated. Thus, a feature defining "a first" or "a second" may explicitly or implicitly include one or more such feature. In the description of the present application, the meaning of "a plurality" is two or more, unless explicitly defined otherwise.
Reference in the specification to "one embodiment" or "some embodiments" or the like means that a particular feature, structure, or characteristic described in connection with the embodiment is included in one or more embodiments of the application. Thus, the terms "comprising," "including," "having," and variations thereof herein mean "including but not limited to," unless expressly specified otherwise.
In the prior art, there may be a dependency relationship between different indexes, and some service indexes have different statistical dimensions but consistent calculation rules, for example, in the calculation process of the index a, the index C is calculated first, and in the calculation process of the index B, the index C is calculated first, the conventional method customizes the corresponding service index calculation scene for each service index, and the reusability between each service index is poor, i.e., in the conventional method, the index C is calculated twice independently, which causes redundancy in calculation, and the calculation efficiency is low. And the independent calculation of each index also generates a large number of database connections, for example, a certain table in the database is often required in the calculation process, so that the table is often accessed, and thus the table needs to be continuously read, so that a large number of database connections are generated, and further the calculation efficiency is low.
Fig. 1 is a schematic view of an application scenario of an index calculation method according to an embodiment of the present invention, as shown in fig. 1, when a specific value of an index needs to be calculated, a target evaluation index related to a target service scenario is input to a client, after the client receives the target evaluation index, the client sends the target evaluation index to a server, after the server receives the target evaluation index, the server executes the index calculation method, and finally obtains the value of the target evaluation index.
It should be noted that the server may be implemented by an independent server or a server cluster formed by a plurality of servers. The client may be, but is not limited to, a smart phone, a tablet computer, a notebook computer, a desktop computer, etc. The client and the server may be connected by bluetooth, USB (UniversalSerial Bus ) or other communication connection, which is not limited in this embodiment of the present invention.
Fig. 2 is a flowchart of an index calculation method according to an embodiment of the present invention, as shown in fig. 2, where the method includes:
s210, at least one target evaluation index corresponding to a target service scene and a data source table corresponding to the target evaluation index are obtained;
when the index of the target service scene needs to be calculated, at least one target evaluation index corresponding to the target service scene is firstly obtained, wherein the target service scene is an actual specific service scene, such as a stock investment scene, a fund investment scene, a certain company operating condition and the like, and can be determined specifically according to the actual situation, and the embodiment of the invention is not limited specifically.
At least one target evaluation index corresponding to the target service scene is obtained, a plurality of target evaluation indexes are used for evaluating the target service scene from different dimensions and angles in order to evaluate the target service scene, and the actual condition of the target service scene can be quantified through the target evaluation indexes. Generally, target evaluation indexes corresponding to different target service scenes are different, but in some special cases, the target evaluation indexes corresponding to different target service scenes are the same, and can be determined specifically according to actual application scenes, and the embodiment of the invention is not limited specifically.
For example, for a stock investment scene, particularly, the market of each stock needs to be analyzed and judged, common target evaluation indexes corresponding to the stock investment scene include a macd index, a kdj index, a ball index and the like, wherein the macd index represents a different moving average line, the kdj index represents a random index, individual stocks are analyzed mainly according to three values of k, d and j and changes among the k, d and j, the ball index represents a brin line index, individual stocks are analyzed mainly according to changes of upper, middle and lower three tracks of the brin line index, and the stock investment scene can be evaluated through the three target evaluation indexes. For example, in the case of a fund investment scenario, it is generally evaluated whether a fund is worth buying or not, and can be judged from the net value of the fund, the stability of the fund, the maximum withdrawal rate of the fund, the return rate of the fund, the historical performance of the manager of the fund, etc., so that the target evaluation index for the fund investment scenario can be the net value of the fund, the stability of the fund, the maximum withdrawal of the fund, the return rate of the fund, etc.
After at least one target evaluation index of a target application scene is acquired, a data source table corresponding to the target evaluation index is also required to be acquired, and the specific acquisition method may be to acquire all relevant data sources in the calculation process of the target evaluation index, and may relate to a plurality of business data tables of a plurality of relevant systems, and the specific relevant systems may be upstream systems or systems of other departments in an enterprise, such as financial departments of banks, market departments of insurance companies and the like, acquire relevant data information from databases of the departments, merge all acquired data information, merge data information representing the same meaning, and perform induction arrangement on the data information according to different topics, for example, all data information about a certain topic is merged into one table, and when relevant data about the topic is required to be searched, the relevant data about the topic is directly searched from the one table.
In the embodiment of the invention, the data source tables are merged, so that the number of times of reading the data tables can be reduced, database connection is reduced, and the calculation efficiency is further improved.
S220, configuring the target evaluation index and a preset basic index on each node of a preset tree according to a preset classification label corresponding to the target evaluation index and an asset corresponding to the target evaluation index, wherein the preset tree represents the dependency relationship between the target evaluation indexes and the preset basic index;
and then configuring the target evaluation index and the preset basic index to each node of the preset tree according to the preset classification label corresponding to the target evaluation index and the asset corresponding to the target evaluation index. The preset classification label corresponding to the target evaluation index is generally determined in advance, and the corresponding relationship between the target evaluation index and the preset classification label is also determined in advance. For example, the preset classification labels may have cost categories, profit categories, performance categories, and the like, which may be specifically determined according to actual situations, which are not specifically limited in the embodiment of the present invention.
In the embodiment of the invention, the assets corresponding to the target evaluation index can be stocks, funds, bonds and the like, and the assets corresponding to the target evaluation index refer to stocks or funds or bonds corresponding to the target evaluation index.
The target evaluation index and the preset basic index are then configured on various points of the preset tree, in the embodiment of the present invention, the preset tree is in a tree structure, the number of nodes of the preset tree can be determined according to the number of the target evaluation indexes and the number of the preset basic indexes, that is, the number of layers of the preset tree is not fixed, and the preset tree can be determined according to the actual situation, which is not particularly limited in the embodiment of the present invention. The preset basic index is an index set in advance, the basic index is calculated by simple addition, subtraction, multiplication and division operation on data, and the target evaluation index is generally obtained by performing correlation operation on the basis of the basic index.
Generally, the basic indexes are represented on the leaf nodes of the preset tree, and the basic indexes are configured on the leaf nodes of the preset tree because the basic indexes are the easiest to calculate, so that the subsequent calculation can be facilitated.
S230, calculating the value of the target evaluation index by an index calculation engine through a recursive traversal algorithm based on the preset tree and the data source table.
And finally, calculating the value of the target evaluation index by using a recursive traversal algorithm based on a preset tree and a data source table through an index calculation engine. Specifically, the index computing engine is an existing computing engine in the prior art, and common index computing engines include an offline big data architecture, a Lambda architecture, a Kappa architecture, and the like, which can be specifically determined according to actual situations, and the embodiment of the invention is not specifically limited thereto.
Inputting the preset tree and the data source table after configuration into an index calculation engine, wherein the index calculation engine adopts a recursion traversal algorithm to calculate the specific value of the preset basic index at the position of the leaf node in the preset tree table, and after the specific value is calculated, traversing upwards in sequence, calculating the specific value of the target evaluation index one by one in sequence.
The embodiment of the invention provides an index calculation method, which is characterized in that the dependency relationship between target evaluation indexes and the dependency relationship between the target evaluation indexes and preset basic indexes are shown through a preset tree, and the specific value of each target evaluation index can be calculated by adopting a recursive traversal algorithm through an index calculation engine one by one. Because each target evaluation index is calculated upwards one by taking the preset tree as a basic structure on the basis of the preset basic configuration index, the same calculation part of the same index is calculated once, and the calculation result of the index is directly read when the calculation is still needed next time, so that the calculation efficiency of the index is improved, and the redundancy of calculation is reduced. Therefore, when a bank or an insurance company is in use, the relevant indexes of the financial business can be calculated efficiently, and the business processing efficiency is improved.
In some embodiments, fig. 3 is a flowchart of a method for configuring a preset tree according to the embodiment of the present invention, as shown in fig. 3, in step S220, according to a preset classification label corresponding to the target evaluation index and an asset corresponding to the target evaluation index, configuring the target evaluation index and a preset base index to each node of the preset tree, including:
s221, obtaining a corresponding relation between the target evaluation index and the asset according to a preset classification label corresponding to the target evaluation index and a preset classification label corresponding to the asset, wherein the target evaluation index corresponds to one preset classification label, and the asset corresponds to at least one preset classification label;
s222, acquiring a dependency relationship between the target evaluation indexes according to the correlation relationship between the assets and the corresponding relationship between the target evaluation indexes and the assets;
s223, configuring the target evaluation index and the preset basic index to each node of a preset tree according to the dependency relationship between the target evaluation indexes and the preset basic index.
When configuring the target evaluation index and the preset basic index to each node of the preset tree according to the preset classification label corresponding to the target evaluation index and the asset corresponding to the target evaluation index, the specific method may be: firstly, a preset classification label corresponding to a target evaluation index and a preset classification label corresponding to an asset are obtained, in the embodiment of the invention, the preset classification label corresponding to the target evaluation index and the preset classification label corresponding to the asset are determined in advance, and can be determined specifically according to actual conditions, and the embodiment of the invention is not particularly limited to this. In the embodiment of the invention, the target evaluation index generally corresponds to one preset classification label, and the asset generally corresponds to a plurality of preset classification labels, so that the corresponding relation between the target evaluation index and the asset can be found according to the preset classification labels. For example, if the class label corresponding to a target valuation indicator is A and the class labels corresponding to an asset are A and B, then the target valuation indicator may be considered to correspond to the asset.
Then, because the assets are mutually influenced, the dependency relationship among different target evaluation indexes can be obtained according to the mutual association relationship among the assets. For example, for a stock asset, the target evaluation index corresponding to the stock asset is a first index and a second index, and for a foundation asset, the target evaluation index corresponding to the foundation asset is a third index, and the foundation asset just includes the stock, so it can be inferred that the first index and the second index affect the third index, that is, the third index depends on the first index and the second index, and thus, the dependency relationship between different target evaluation indexes can be obtained.
After the dependency relationship among different target evaluation indexes is obtained, the target evaluation indexes and the preset basic indexes are configured on each node of the preset tree by combining the dependency relationship among the target evaluation indexes and the preset basic indexes, so that the relationship among the different target evaluation indexes, the target evaluation indexes and the preset basic indexes can be shown according to the structure of the preset tree.
As an embodiment, the dependency relationship between the target evaluation index and the preset basic index is obtained by the following manner:
and acquiring the dependency relationship between the target evaluation index and a preset basic index according to the business calculation logic of the target evaluation index.
In a specific implementation process, the dependency relationship between the target evaluation index and the preset basic index can be obtained by firstly obtaining service calculation logic of each target evaluation index, wherein the service calculation logic refers to a specific calculation process and a calculation step of the target evaluation index, and the calculation process and the calculation step of the target evaluation index are disassembled to be a calculation formula based on the preset basic index, so that the association relationship between each target evaluation index and the preset basic index can be obtained.
In some embodiments, before the configuring the target evaluation index and the preset base index on each node of the preset tree according to the dependency relationship between the target evaluation indexes and the dependency relationship between the target evaluation index and the preset base index, the method further includes:
acquiring the type of each target evaluation index according to the service calculation logic of each target evaluation index, wherein the type comprises a single index type and a complex index type;
splitting the target evaluation index of the complex index type into at least one target evaluation index of the single index type, and obtaining all the target evaluation indexes.
In the embodiment of the invention, after the dependency relationship between the target evaluation indexes is obtained according to the correlation relationship between the assets and the corresponding relationship between the target evaluation indexes and the assets, the embodiment of the invention optimizes the indexes configured by each node on the preset tree according to the type of the target evaluation indexes, specifically, firstly judges the business calculation logic of each target evaluation index, and judges the type of each target evaluation index through the business calculation logic. In the embodiment of the invention, the target evaluation index has two types, one is a single index type, the other is a complex index type, the single index type refers to an index which can be calculated through simple addition, subtraction, multiplication and division operation, and the complex index type refers to an index which can be obtained through complex operation on the basis of the single index type.
Judging the business calculation logic of each target evaluation index, judging the type of each target evaluation index, for the target evaluation index of a single index type, not processing the target evaluation index, for the target evaluation index of a complex index type, splitting the target evaluation index into a plurality of evaluation indexes of the single index type, obtaining all the target evaluation indexes of the single index type, and then configuring the target evaluation indexes and the preset basic indexes on each node of the preset tree according to the dependency relationship between different target evaluation indexes and the dependency relationship between the target evaluation indexes and the preset basic indexes.
In some embodiments, after the configuring the target evaluation index and the preset base index to each node of the preset tree according to the preset classification label corresponding to the target evaluation index and the asset corresponding to the target evaluation index, the method further includes:
acquiring the dependency relationship among different dimensions of the target evaluation index;
adding dimension attribute for each node of the preset tree;
according to the dependency relationship among different dimensionalities of the target evaluation index, determining the value of the dimensionality attribute of each node of the preset tree, and taking the preset tree with the added dimensionality attribute as the preset tree again.
In the embodiment of the invention, after the target evaluation index and the preset basic index are configured to each node on the preset tree, because a dependency relationship exists between different dimensions of the same target evaluation index, for example, when the target evaluation index is profit, the dimensions of the index can be annual profit, quaternary profit, monthly profit and the like, the annual profit can be obtained by adding the quaternary profit and the monthly profit, the quaternary profit can be obtained by adding the monthly profit, and therefore, the dependency relationship exists between the different dimensions. In order to show the dimension of the index on the preset tree, the embodiment of the invention additionally adds a dimension attribute on each node of the preset tree, wherein the dimension attribute is used for showing the dimension of the index at the node, and the preset tree is reconfigured according to the dependency relationship between the dimensions added to the dependency relationship between the target evaluation indexes.
In some embodiments, the calculating, by the index calculation engine, the value of the target evaluation index by using a recursive traversal algorithm based on the preset tree and the data source table includes:
acquiring target data for calculating the correspondence of each node from the data source table according to a preset classification label and dimension attribute corresponding to each node in the preset tree;
acquiring index values corresponding to each node according to target data corresponding to each node and a preset calculation rule;
and calculating upwards layer by layer according to the index value corresponding to each node and the preset calculation rule, and obtaining the value of the target evaluation index.
In a specific calculation process, according to a preset classification label and a dimension attribute corresponding to each node in a preset tree, target data for calculating index values at the node are taken out from a data source table. For example, if an index corresponding to a certain node in the preset tree is a fourth index, the dimension of the fourth index is obtained, and according to the classification label of the fourth index and the dimension of the fourth index, searching is performed in the data source table, and data corresponding to the fourth index and the dimension of the fourth index are found, and these data are referred to as target data.
After the target data are found, calculating according to a preset calculation rule of the fourth index at the node to obtain a specific value of the fourth index at the node, and calculating the specific value from the leaf node of the preset tree layer by layer in the calculation process until the value of each target evaluation index is calculated.
As an embodiment, the layer-by-layer upward calculation includes:
and carrying out parallel computation on the nodes of the same layer of the preset tree.
It should be noted that, for the index at the same layer of nodes in the preset tree, the parallel calculation may be performed at the same time, and for the index at the parent-child node, the index at the child node needs to be calculated first, and then the index at the parent node needs to be calculated.
In summary, in the method for calculating the index provided by the embodiment of the invention, after merging the data from the multiple systems, a data source table is obtained, and the data source table is loaded into the memory for calculation, and only the data source table needs to be read once, so that the connection of the database can be reduced; and then configuring a plurality of dimension data into a tree structure, adopting a recursive traversal algorithm by an index calculation engine to calculate from leaf nodes layer by layer to root nodes, realizing multi-dimensional target evaluation index result calculation, splitting a complex index into a plurality of single index calculations according to target evaluation index business logic, and configuring dependence among different indexes, wherein the same sequence nodes can be used for parallel calculation, the algorithms among the indexes can be shared, and realizing highly-reusable index calculation and improving the calculation efficiency of the indexes.
Fig. 4 is a schematic structural diagram of an index computing system according to an embodiment of the present invention, as shown in fig. 4, the system includes a data module 410, a dependency module 420, and a computing module 430, where:
the data module 410 is configured to obtain at least one target evaluation index corresponding to a target service scenario and a data source table corresponding to the target evaluation index;
the dependency module 420 is configured to configure the target evaluation index and a preset base index to each node of a preset tree according to a preset classification label corresponding to the target evaluation index and an asset corresponding to the target evaluation index, where the preset tree represents a dependency relationship between the target evaluation indexes and a dependency relationship between the target evaluation index and the preset base index;
the calculation module 430 is configured to calculate, by using an index calculation engine, a value of the target evaluation index by using a recursive traversal algorithm based on the preset tree and the data source table.
The embodiment is a system embodiment corresponding to the above method, and the specific implementation process is the same as that of the above method embodiment, and the details refer to the above method embodiment, and the system embodiment is not limited in particular.
Further, the dependency module comprises a tag unit, a dependency unit and a configuration unit, wherein:
the label unit is used for acquiring the corresponding relation between the target evaluation index and the asset according to the preset classification label corresponding to the target evaluation index and the preset classification label corresponding to the asset, wherein the target evaluation index corresponds to one preset classification label, and the asset corresponds to at least one preset classification label;
the dependency unit is used for acquiring the dependency relationship between the target evaluation indexes according to the correlation relationship between the assets and the corresponding relationship between the target evaluation indexes and the assets;
the configuration unit is used for configuring the target evaluation index and the preset basic index to each node of a preset tree according to the dependency relationship between the target evaluation indexes and the preset basic index.
Further, the index computing system further comprises a type unit and a splitting unit, wherein:
the type unit is used for acquiring the type of each target evaluation index according to the service calculation logic of each target evaluation index, wherein the type comprises a single index type and a complex index type;
the splitting unit is used for splitting the target evaluation index of the complex index type into at least one target evaluation index of the single index type, and acquiring all the target evaluation indexes.
Further, the configuration unit comprises a logic subunit, wherein:
the logic subunit is used for acquiring the dependency relationship between the target evaluation index and a preset basic index according to the business calculation logic of the target evaluation index.
Further, the index computing system comprises a dimension module, an attribute module and an add-on module, wherein:
the dimension module is used for acquiring the dependency relationship among different dimensions of the target evaluation index;
the attribute module is used for adding dimension attributes for each node of the preset tree;
the adding module is used for determining the dimension attribute value of each node of the preset tree according to the dependency relationship among different dimensions of the target evaluation index, and re-using the preset tree with the dimension attribute added as the preset tree.
Further, the computing module includes a data unit, a first computing unit, and a second computing unit, wherein:
the data unit is used for acquiring target data for calculating the correspondence of each node from the data source table according to the preset classification labels and the dimension attribute corresponding to each node in the preset tree;
the first computing unit is used for obtaining index values corresponding to each node according to target data corresponding to each node and preset computing rules;
the second calculation unit is used for calculating the target evaluation index value layer by layer according to the index value corresponding to each node and the preset calculation rule.
Further, the layer-by-layer upward calculation includes:
and carrying out parallel computation on the nodes of the same layer of the preset tree.
The various modules in the index computing system described above may be implemented in whole or in part by software, hardware, and combinations thereof. The above modules may be embedded in hardware or may be independent of a processor in the computer device, or may be stored in software in a memory in the computer device, so that the processor may call and execute operations corresponding to the above modules.
Fig. 5 is a schematic structural diagram of a computer device according to an embodiment of the present invention, where the computer device may be a server, and an internal structure diagram of the computer device may be as shown in fig. 5. The computer device includes a processor, a memory, a network interface, and a database connected by a system bus. Wherein the processor of the computer device is configured to provide computing and control capabilities. The memory of the computer device includes a computer storage medium, an internal memory. The computer storage medium stores an operating system, computer programs, and a database. The internal memory provides an environment for the operation of the operating system and computer programs in the computer storage media. The database of the computer device is used for storing data generated or obtained in the process of executing the index calculation method, such as target evaluation indexes and target service scenes. The network interface of the computer device is used for communicating with an external terminal through a network connection. The computer program is executed by a processor to implement a method of index calculation.
In one embodiment, a computer device is provided that includes a memory, a processor, and a computer program stored on the memory and executable on the processor, the processor implementing the steps of the index calculation method in the above embodiments when the computer program is executed by the processor. Alternatively, the processor, when executing the computer program, performs the functions of the modules/units in this embodiment of the index computing system.
In an embodiment, a computer storage medium is provided, on which a computer program is stored, which when being executed by a processor, implements the steps of the index calculation method in the above embodiment. Alternatively, the computer program, when executed by a processor, performs the functions of the modules/units in this embodiment of the index calculation system described above.
Those skilled in the art will appreciate that implementing all or part of the above described methods may be accomplished by way of a computer program stored on a non-transitory computer readable storage medium, which when executed, may comprise the steps of the embodiments of the methods described above. Any reference to memory, storage, database, or other medium used in the various embodiments provided herein may include non-volatile and/or volatile memory. The nonvolatile memory can include Read Only Memory (ROM), programmable ROM (PROM), electrically Programmable ROM (EPROM), electrically Erasable Programmable ROM (EEPROM), or flash memory. Volatile memory can include Random Access Memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in a variety of forms such as Static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double Data Rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous Link DRAM (SLDRAM), memory bus direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM), among others.
It will be apparent to those skilled in the art that, for convenience and brevity of description, only the above-described division of the functional units and modules is illustrated, and in practical application, the above-described functional distribution may be performed by different functional units and modules according to needs, i.e. the internal structure of the apparatus is divided into different functional units or modules to perform all or part of the above-described functions.
The above embodiments are only for illustrating the technical solution of the present invention, and not for limiting the same; although the invention has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: the technical scheme described in the foregoing embodiments can be modified or some technical features thereof can be replaced by equivalents; such modifications and substitutions do not depart from the spirit and scope of the technical solutions of the embodiments of the present invention, and are intended to be included in the scope of the present invention.
Claims (10)
1. An index calculation method, comprising:
acquiring at least one target evaluation index corresponding to a target service scene and a data source table corresponding to the target evaluation index;
according to a preset classification label corresponding to the target evaluation index and an asset corresponding to the target evaluation index, configuring the target evaluation index and a preset basic index on each node of a preset tree, wherein the preset tree represents the dependency relationship between the target evaluation indexes and the preset basic index;
and calculating the value of the target evaluation index by using a recursive traversal algorithm based on the preset tree and the data source table through an index calculation engine.
2. The method according to claim 1, wherein the configuring the target evaluation index and the preset base index to each node of a preset tree according to the preset classification label corresponding to the target evaluation index and the asset corresponding to the target evaluation index comprises:
acquiring a corresponding relation between the target evaluation index and the asset according to a preset classification label corresponding to the target evaluation index and a preset classification label corresponding to the asset, wherein the target evaluation index corresponds to one preset classification label, and the asset corresponds to at least one preset classification label;
acquiring a dependency relationship between the target evaluation indexes according to the correlation relationship between the assets and the corresponding relationship between the target evaluation indexes and the assets;
and configuring the target evaluation index and the preset basic index to each node of a preset tree according to the dependency relationship between the target evaluation indexes and the preset basic index.
3. The index calculation method according to claim 2, wherein before the target evaluation index and the preset base index are configured on each node of a preset tree according to the dependency relationship between the target evaluation indexes and the dependency relationship between the target evaluation index and the preset base index, the method further comprises:
acquiring the type of each target evaluation index according to the service calculation logic of each target evaluation index, wherein the type comprises a single index type and a complex index type;
splitting the target evaluation index of the complex index type into at least one target evaluation index of the single index type, and obtaining all the target evaluation indexes.
4. The index calculation method according to claim 2, wherein the dependency relationship between the target evaluation index and the preset base index is obtained by:
and acquiring the dependency relationship between the target evaluation index and a preset basic index according to the business calculation logic of the target evaluation index.
5. The index calculation method according to claim 1, further comprising, after the configuring the target evaluation index and the preset base index to each node of a preset tree according to the preset classification tag corresponding to the target evaluation index and the asset corresponding to the target evaluation index:
acquiring the dependency relationship among different dimensions of the target evaluation index;
adding dimension attribute for each node of the preset tree;
according to the dependency relationship among different dimensionalities of the target evaluation index, determining the value of the dimensionality attribute of each node of the preset tree, and taking the preset tree with the added dimensionality attribute as the preset tree again.
6. The index calculation method according to claim 1, wherein the calculating, by the index calculation engine, the value of the target evaluation index using a recursive traversal algorithm based on the preset tree and the data source table, includes:
acquiring target data for calculating the correspondence of each node from the data source table according to a preset classification label and dimension attribute corresponding to each node in the preset tree;
acquiring index values corresponding to each node according to target data corresponding to each node and a preset calculation rule;
and calculating upwards layer by layer according to the index value corresponding to each node and the preset calculation rule, and obtaining the value of the target evaluation index.
7. The index calculation method according to claim 6, wherein the layer-by-layer upward calculation includes:
and carrying out parallel computation on the nodes of the same layer of the preset tree.
8. An index computing system, comprising:
the data module is used for acquiring at least one target evaluation index corresponding to a target service scene and a data source table corresponding to the target evaluation index;
the dependency module is used for configuring the target evaluation index and a preset basic index to each node of a preset tree according to a preset classification label corresponding to the target evaluation index and an asset corresponding to the target evaluation index, wherein the preset tree represents the dependency relationship between the target evaluation indexes and the preset basic index;
the calculation module is used for calculating the value of the target evaluation index by adopting a recursive traversal algorithm based on the preset tree and the data source table through an index calculation engine.
9. Computer device comprising a memory, a processor and a computer program stored in the memory and executable on the processor, characterized in that the processor implements the steps of the index calculation method according to any one of claims 1 to 7 when the computer program is executed.
10. A computer storage medium storing a computer program, characterized in that the computer program when executed by a processor implements the steps of the index calculation method according to any one of claims 1 to 7.
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