CA3169413A1 - Report generating method, device, electronic equipment, and computer-readable medium - Google Patents

Abstract

The present invention discloses a report generating method that comprises: receiving index configuration information input by a user at a web interface; establishing a first association relation of the index configuration information to a corresponding target data source; and generating the report through a preset model that is matched with the target data source on the basis of the index configuration information and the target data source. By establishing a first association relation of the index configuration information input by a user to a corresponding target data source, the present invention makes it possible to quickly obtain data from the corresponding data source, to avoid colossal amount of searches, to reduce computational amount, and to quicken response time; moreover, the report generating method according to the present application is a web browser data analysis product.

Description

REPORT GENERATING METHOD, DEVICE, ELECTRONIC EQUIPMENT, AND
COMPUTER-READABLE MEDIUM
BACKGROUND OF THE INVENTION
Technical Field [0001] The present invention relates to the field of data processing technology, and more particularly to a report generating method, and corresponding device, electronic equipment, and computer-readable medium.
Description of Related Art

[0002] Business intelligence (BI) is a set of complete solving scheme employed to effectively integrate existing data in an enterprise, to quickly and accurately provide reports and propose decision bases, and to help the enterprise make advisable business operational decisions. In the traditional BI field, it is general for technical personnel to use professional BI software to construct relevant reports, but the construction period is long, total consumptions for both construction and adjustment are relatively large, the feedback period of the construction result is relatively long, and it is impossible to quickly respond to frontline requirements.

[0003] With the rapid development of the financial business, the business has expanded itself both in extent and in depth. Based on corresponding business scenarios, the requirements on data analyses have also been incessantly increasing; at the same time, due to increase in the amount of data analyses, the difficulty of analyses is increased, and a high demand is put on the construction timeliness for requirement landing by the business part.

[0004] Moreover, data analysis reports constructed by the traditional BI are confusing and not Date Regue/Date Received 2022-07-27 unified in indexes, support for the colossal amount of data is limited in strength, and response is extremely low or it is impossible to respond in the case there are excessive rows of data, or many analysis dimensions, or many dimension combinations, or dimensions of high cardinality.
SUMMARY OF THE INVENTION

[0005] To solve problems pending in the state of the art, embodiments of the present invention provide a report generating method, and corresponding device, electronic equipment, and computer-readable medium. The technical solutions are as follows.

[0006] According to the first aspect, there is provided a report generating method that comprises:

[0007] receiving index configuration information input by a user at a web interface;

[0008] establishing a first association relation of the index configuration information to a corresponding target data source; and

[0009] generating the report through a preset model that is matched with the target data source on the basis of the index configuration information and the target data source.

[0010] In a preferred mode of execution, the step of establishing a first association relation of the index configuration information to a corresponding target data source includes:

[0011] parsing the index configuration information to obtain at least one index name, at least one index dimension, and at least one preset model, wherein each preset model corresponds to the target data source;

[0012] establishing at least one associated group according to the at least one index name and the at least one index dimension, wherein index names and index dimensions included in any associated group are associated;

[0013] establishing a second association relation of any associated group to the preset model;
and

[0014] establishing a first association relation of the associated group to the target data source Date Regue/Date Received 2022-07-27 on the basis of the second association relation.

[0015] In a preferred mode of execution, the step of establishing at least one associated group according to the at least one index name and the at least one index dimension, wherein index names and index dimensions included in any associated group are associated includes:

[0016] extracting an index code of each index name, and extracting a dimension code of each index dimension; and

[0017] establishing the at least one associated group according to a preconstructed correspondence relation between the index code and the dimension code.

[0018] In a preferred mode of execution, the step of establishing a second association relation of any associated group to the preset model includes:

[0019] parsing to obtain a model invoking parameter corresponding to the preset model on the basis of the associated group; and

[0020] matching a corresponding preset model and constructing a second association relation according to the model invoking parameter.

[0021] In a preferred mode of execution, the step of generating the report through a preset model that is matched with the target data source on the basis of the index configuration information and the target data source includes:

[0022] invoking the preset model that is matched with the target data source;

[0023] invoking target metadata from the target data source; and

[0024] generating the report through the preset model on the basis of the index configuration information and the target metadata.

[0025] In a preferred mode of execution, the target metadata includes target offline data, and the step of invoking target metadata from the target data source includes:

[0026] obtaining the target offline data from a preset external data warehouse according to a Date Regue/Date Received 2022-07-27 preset frequency and storing the same.

[0027] In a preferred mode of execution, the target metadata includes target real time data, and the step of invoking target metadata from the target data source includes:

[0028] obtaining in real time, from a message middleware, target real time data that is sent after Flink performs real-time index calculation and is of a preset data format.

[0029] According to the second aspect, there is provided a report generating device that comprises:

[0030] a receiving module, for receiving index configuration information input by a user at a web interface;

[0031] an associating module, for establishing a first association relation of the index configuration information to a corresponding target data source; and

[0032] a generating module, for employing a preset model that is matched with the target data source to generate the report on the basis of the index configuration information and the target data source.

[0033] According to the third aspect, there is provided an electronic equipment that comprises:

[0034] one or more processor(s); and

[0035] a memory, associated with the one or more processor(s) and storing a program instruction that executes the method according to any one of the first aspect when it is read and executed by the one or more processor(s).

[0036] According to the fourth aspect, there is provided a computer-readable medium storing thereon a computer program that realizes the method according to any one of the first aspect when it is executed by a processor.

[0037] The technical solutions provided by the embodiments of the present invention bring about the following advantageous effects.

Date Regue/Date Received 2022-07-27

[0038] In the report generating method, and corresponding device, electronic equipment, and computer-readable medium provided by the embodiments of the present invention, by establishing a first association relation of the index configuration information input by a user to a corresponding target data source, it is made possible to quickly obtain data from the corresponding data source, to avoid colossal amount of searches, to reduce computational amount, and to shorten response time; moreover, the report generating method according to the present application is a web browser data analysis product, as compared with the prior-art scheme in which such products are directly connected to the target database, performance optimization of the target database is not affected; what is more important, the method is accessed to different data sources, provides services to the outside through a unified outlet, and is capable of effectively satisfying the requirement on the quick provision of unified service of heterogeneous source indexes.
BRIEF DESCRIPTION OF THE DRAWINGS

[0039] To more clearly describe the technical solutions in the embodiments of the present invention, drawings required to illustrate the embodiments will be briefly introduced below. Apparently, the drawings introduced below are merely directed to some embodiments of the present invention, while persons ordinarily skilled in the art may further acquire other drawings on the basis of these drawings without spending creative effort in the process.

[0040] Fig. 1 is a flowchart illustrating the report generating method provided by an embodiment of the present invention;

[0041] Fig. 2 is a view schematically illustrating the structure of the report generating device provided by an embodiment of the present invention; and Date Regue/Date Received 2022-07-27

[0042] Fig. 3 is a view schematically illustrating the structure of a computer system provided by an embodiment of the present invention.
DETAILED DESCRIPTION OF THE INVENTION

[0043] To make more lucid and clear the objectives, technical solutions and advantages of the present invention, the technical solutions in the embodiments of the present invention will be clearly and comprehensively described below with reference to the accompanying drawings in the embodiments of the present invention. Apparently, the embodiments as described are merely partial, rather than the entire, embodiments of the present invention.
Any other embodiments makeable by persons ordinarily skilled in the art on the basis of the embodiments in the present invention without creative effort shall all fall within the protection scope of the present invention.

[0044] As noted in the Description of Related Art, corresponding to the development of businesses, BI data analysis requirements, processing amounts and difficulty are synchronously increased, and longer processing durations are usually required to satisfy the above requirements. At present, some analyzing engines (such real-time calculating engines as Druid, Kylin, Presto/Impala, etc., and ElasticSearch) currently available on the market are more or less defective, and cannot satisfy all the above requirements at the same time. Druid employs the technique of pre-calculation, but cannot perform precise duplicate removal, there is certain error in count distinct, it is necessarily required that one dimension must be relevant to time, and the business is restricted. Kylin employs the technique of pre-calculation, but it is so high in real timeliness, moreover, large resources are occupied when faced with a large-scale index system, and unduly long time is consumed in the pre-calculation. Such real-time calculating engines as Presto/Impala take relatively long response time in the real-time calculation, and the response time is even longer for complicated indexes, thereby making it impossible to satisfy the requirements for second-grade response. ElasticSearch cannot perform precise duplicate removal, there Date Regue/Date Received 2022-07-27 is precision error like Druid, and support for dimension combinations of high cardinality (high barrelage) is inferior.

[0045] To satisfy the requirement on timeliness of the business party, embodiments of the present invention provide a report generating method, and corresponding device, electronic equipment, and computer-readable medium capable of effectively solving the problem concerning timeliness in the BI field.

[0046] The technical solutions of the present application are described in greater detail below in conjunction with specific embodiments.

[0047] Embodiment 1

[0048] As shown in Fig. 1, this embodiment provides a report generating method for supplying decision bases in cooperation with a business party in the BI field. The method comprises the following steps.

[0049] Si - receiving index configuration information input by a user at a web interface.

[0050] Specifically, the report generating method provided by this embodiment is established on the basis of a web browser, the user may directly access to a visualized design webpage through an ordinary web browser, and designs and inputs required index content at an index visualized interactor page, namely to input index content configuration information.

[0051] Exemplarily, in this embodiment, a visualized interactor is configured by configuring the index to perform human-machine interaction, index contents designed by the user are received, user operations are enabled by a visualized interface in which what you see is what you get, and design of the index and relevant cache configuration of the index are carried out. Moreover, the contents of cache configuration here include the circumstance Date Regue/Date Received 2022-07-27 of index definitions under various dimension combinations and corresponding caching methods.

[0052] Understandably, in order to cooperate with business requirements in the BI field, indexes are numerous and not unified, and this directly leads to the fact that the indexes are not conveniently used and even that index results are inconsistent. Indexes in this embodiment are classified according to different index dimensions.

[0053] Exemplarily, index dimensions are classified as follows: basic attributes include such information as names, codes, types, whether being public dimensions, parent dimensions, and states, etc.; business attributes include such information as business specifications and adjustment frequencies of specifications, etc.; technical attributes include such information as corresponding table names, technical specifications, fields corresponding to dimensions, fields corresponding to dimension values, and parent dimension fields, etc.; service attributes include such information as cache sources, and cache storage information, etc.

[0054] Exemplarily, based on the above classifications of index dimensions, indexes are classified as follows: basic attributes include such information as names, codes, types, and states, etc.; business attributes include such information as business specifications, adjustment frequencies of specifications, and sensitivity levels, etc.;
technical attributes include such information as corresponding table names, technical specifications, and fields corresponding to indexes, etc.; service attributes include such information as cache sources, caching modes, and cache storage information, etc. What is additionally essential, the above contents are a result mapping generated under different dimension combinations, for instance, as regards the dimension of a certain statistic total value, when the dimension is respectively associated with a year dimension and a month dimension, the actual technical attributes and service attributes might be two groups of completely different information.

Date Regue/Date Received 2022-07-27

[0055] Accordingly, the index configuration information in this embodiment includes at least one dimension under the aforementioned different index dimensions. In this embodiment, mappings of plural groups of cache instances are generated through combined configurations of indexes and index dimensions, and contents with different features are respectively processed, so that problems based on colossal amount of data analyses, excessive amount of data analyzed, many analyzed dimensions, many combined dimensions, and dimensions with high cardinality are solved.

[0056] S2 - establishing a first association relation of the index configuration information to a corresponding target data source.

[0057] Specifically, step S2 includes the following.

[0058] S21 - parsing the index configuration information to obtain at least one index name, at least one index dimension, and at least one preset model, wherein each preset model corresponds to the target data source.

[0059] The preset model includes a massive amount batch index caching module, a precise duplicate-removal index caching module, a massive amount singular index caching module, and other modules self-defined according to functional requirements.

[0060] S22 - establishing at least one associated group according to the at least one index name and the at least one index dimension, wherein index names and index dimensions included in any associated group are associated.

[0061] Moreover, step S22 includes:

[0062] extracting an index code of each index name, and extracting a dimension code of each index dimension; and Date Regue/Date Received 2022-07-27

[0063] establishing at least one associated group according to a preconstructed correspondence relation between the index code and the dimension code.

[0064] S23 - establishing a second association relation of any associated group to the preset model.

[0065] Specifically, step S23 includes:

[0066] parsing to obtain a model invoking parameter corresponding to the preset model on the basis of the associated group; and

[0067] matching a corresponding preset model and constructing a second association relation according to the model invoking parameter.

[0068] S24 - establishing a first association relation of the associated group to the target data source on the basis of the second association relation.

[0069] S3 - generating the report through a preset model that is matched with the target data source on the basis of the index configuration information and the target data source.

[0070] Specifically, step S3 includes the following.

[0071] S31 - invoking the preset model that is matched with the target data source.

[0072] S32 - invoking target metadata from the target data source.

[0073] In a preferred mode of execution, the target metadata includes at least one of target offline data and/or target real time data.

[0074] When the target metadata is target offline data, step S32 includes:
obtaining the target offline data from a preset external data warehouse according to a preset frequency and Date Regue/Date Received 2022-07-27 storing the same.

[0075] When the target metadata is target real time data, step S32 includes:

[0076] obtaining in real time, from a message middleware, target real time data that is sent after Flink performs real-time index calculation and is of a preset data format. The data format is for example table name + field names + instance data.

[0077] When data is written in, a primary key of the table is obtained according to metadata information of a data model, and data is "updated" or "inserted" according to the primary key, to avoid the recording of repetitive and invalid data; on the other hand, due to the timeliness of the message, when data is updated, the "latest" data is retained and disposed in the database while "old" data is directly discarded according to precise times in the data message.

[0078] S33 - generating the report on the basis of the index configuration information and the target metadata.

[0079] After the report has been generated, the method further comprises:
outputting the generated report through a unified port to users to provide index service.

[0080] To further describe the report generating method, the following exemplary description is made in this embodiment in conjunction with a specific application scenario.

[0081] The report generating method manages and maintains indexes on the basis of an ordinary web browser, and execution is made on the basis of such functional modules as a model information administrator, an index configuration visualized interactor, an index parsing administrator, an index cache acceleration module set, and an index servicing module that are deployed on a server.

Date Regue/Date Received 2022-07-27

[0082] Specifically, the model information administrator is employed to administer model metadata, and to provide functions of enquiring and storing model metadata information.
The model metadata includes name, code, state, and maintenance information of the model, and relevant information of all fields in the model, such as field names, field types, and field lengths, etc. On the basis thereof, the user can enquire all field information under the model by designating a unique identification of the model; by designating a unique identification of a certain field of the model, such information as the field name, field type, and field length of the field is enquired.

[0083] The index configuration visualized interactor is employed for human-machine interaction, and is specifically employed to receive index configuration information input by a user at a web interface to realize a visualized interface in which what you see is what you get for configuration by the user.

[0084] The index parsing administrator obtains the index configuration information configured by the user at the index configuration visualized interactor, and parses the same to obtain at least one index name, at least one index dimension, and at least one preset model, wherein each preset model corresponds to the target data source. At least one associated group is established according to at least one index name and at least one index dimension, and index names and index dimensions included in any associated group are associated.
A second association relation of any associated group to the preset model is established, and a first association relation of the associated group to the target data source is established on the basis of the second association relation.

[0085] The index cache acceleration module set contains a set of index cache acceleration modules, the technical feature of each module is different from those of others, and service capability provided by each module is also different from those of others; the set incudes modules that at least support three scenarios, including the acceleration module of a massive amount batch index caching type, the acceleration module of a precise Date Regue/Date Received 2022-07-27 duplicate-removal index caching type, and the acceleration module of a massive amount singular index caching type. Scale-out is subsequently possible as required.

[0086] The acceleration module of a massive amount batch index caching type is a core and main module for storing common index cache acceleration data, most indexes can be disposed by means of this acceleration module, moreover, the indexes support reprocessing, such as summation and calculation of maximum value, etc., for supporting scenarios such as reports, etc., exemplarily, the objective is achieved by employing a PostgreSQL citus cluster, and such solving schemes as Druid can also be employed.

[0087] The acceleration module of a precise duplicate-removal index caching type is employed to store index cache acceleration data that should be precisely duplicate-removed (namely count distinct) within a dynamic range, few indexes can be disposed by means of this acceleration module if it is required so, exemplarily, the objective is achieved by employing the PostgreSQL citus cluster.

[0088] The acceleration module of a massive amount singular index type is employed to store massive amount of singular indexes, few indexes can be disposed by means of this acceleration module if it is required so, exemplarily, the objective is achieved by employing HBase.

[0089] The index servicing module provides the user end with unified index services, in this embodiment, batch index configuration information set up by users on the web browser can be received and processed in batches, and users are uniformly centralized through the index servicing module, so as to effectively solve the problem concerning heterogenous sources.

[0090] To sum it up, by establishing a first association relation of the index configuration information input by a user to a corresponding target data source, the report generating Date Regue/Date Received 2022-07-27 method provided by this embodiment makes it possible to quickly obtain data from the corresponding data source, to avoid colossal amount of searches, to reduce computational amount, and to shorten response time; moreover, the report generating method according to the present application is a web browser data analysis product, as compared with the prior-art scheme in which such products are directly connected to the target database, performance optimization of the target database is not affected.

[0091] Embodiment 2

[0092] To execute the report generating method in Embodiment 1, this embodiment provides a report generating device corresponding thereto, as shown in Fig. 2, the device comprises:

[0093] a receiving module, for receiving index configuration information input by a user at a web interface;

[0094] an associating module, for establishing a first association relation of the index configuration information to a corresponding target data source;

[0095] the associating module includes:

[0096] a parsing unit, for parsing the index configuration information to obtain at least one index name, at least one index dimension, and at least one preset model, wherein each preset model corresponds to the target data source;

[0097] a constructing unit, for establishing at least one associated group according to the at least one index name and the at least one index dimension, wherein index names and index dimensions included in any associated group are associated;

[0098] the constructing unit is further employed for extracting an index code of each index name, and extracting a dimension code of each index dimension; and establishing the at least one associated group according to a preconstructed correspondence relation between the index code and the dimension code;

[0099] a first associating unit, for establishing a second association relation of any associated group to the preset model;

[0100] the first associating unit is further employed for parsing to obtain a model invoking Date Regue/Date Received 2022-07-27 parameter corresponding to the preset model on the basis of the associated group; and matching a corresponding preset model and constructing a second association relation according to the model invoking parameter;

[0101] a second associating unit, for establishing a first association relation of the associated group to the target data source on the basis of the second association relation;

[0102] a generating module, for generating the report through a preset model that is matched with the target data source on the basis of the index configuration information and the target data source. The generating module includes:

[0103] a first invoking unit, for invoking the preset model that is matched with the target data source;

[0104] a second invoking unit, for invoking target metadata from the target data source; and

[0105] a generating unit, for generating the report through the preset model on the basis of the index configuration information and the target metadata.

[0106] The target metadata includes target offline data, and the second invoking unit is employed for obtaining the target offline data from a preset external data warehouse according to a preset frequency and storing the same.

[0107] The target metadata includes target real time data, and the second invoking unit is employed for obtaining in real time, from a message middleware, target real time data that is sent after Flink performs real-time index calculation and is of a preset data format.

[0108] As should be noted, when the report generating device provided by the aforementioned embodiment triggers a report generating business, the division into the aforementioned various functional modules is merely by way of example, while it is possible, in actual application, to base on requirements to assign the functions to different functional modules for completion, that is to say, to divide the internal structure of the device into different functional modules to complete the entire or partial functions described above.
In addition, the report generating device provided by the aforementioned embodiment Date Regue/Date Received 2022-07-27 pertains to the same conception as the report generating method provided by the method embodiment, that is to say, the device is based on the method ¨ see the corresponding method embodiment for its specific realization process, while no repetition will be made in this context.

[0109] In addition, corresponding to the aforementioned report generating method and device, this embodiment further provides an electronic equipment that comprises:

[0110] one or more processor(s); and

[0111] a memory, associated with the one or more processor(s) and storing a program instruction that executes the report generating method disclosed by the foregoing embodiment when it is read and executed by the one or more processor(s).

[0112] Fig. 3 exemplarily illustrates the framework of a computer system that can specifically include a processor 310, a video display adapter 311, a magnetic disk driver 312, an input/output interface 313, a network interface 314, and a memory 320. The processor 310, the video display adapter 311, the magnetic disk driver 312, the input/output interface 313, the network interface 314, and the memory 320 can be communicably connected with one another via a communication bus 330.

[0113] The processor 310 can be embodied as a general CPU (Central Processing Unit), a microprocessor, an ASIC (Application Specific Integrated Circuit), or one or more integrated circuit(s) for executing relevant program(s) to realize the technical solutions provided by the present application.

[0114] The memory 320 can be embodied in such a form as an ROM (Read Only Memory), an RAM (Random Access Memory), a static storage device, or a dynamic storage device.
The memory 320 can store an operating system 321 for controlling the running of an electronic equipment 300, and a basic input/output system (BIOS) for controlling lower-level operations of the electronic equipment 300. In addition, the memory 320 can also Date Regue/Date Received 2022-07-27 store a web browser 323, a data storage management system 324, and an equipment identification information processing system 325, etc. The equipment identification information processing system 325 can be an application program that specifically realizes the aforementioned various step operations in the embodiments of the present application. To sum it up, when the technical solutions provided by the present application are to be realized via software or firmware, the relevant program codes are stored in the memory 320, and invoked and executed by the processor 310.

[0115] The input/output interface 313 is employed to connect with an input/output module to realize input and output of information. The input/output module can be equipped in the device as a component part (not shown in the drawings), and can also be externally connected with the device to provide corresponding functions. The input means can include a keyboard, a mouse, a touch screen, a microphone, and various sensors etc., and the output means can include a display screen, a loudspeaker, a vibrator, an indicator light etc.

[0116] The network interface 314 is employed to connect to a communication module (not shown in the drawings) to realize intercommunication between the current device and other devices. The communication module can realize communication in a wired mode (via USB, network cable, for example) or in a wireless mode (via mobile network, WIFI, Bluetooth, etc.).

[0117] The bus 330 includes a passageway transmitting information between various component parts of the equipment (such as the processor 310, the video display adapter 311, the magnetic disk driver 312, the input/output interface 313, the network interface 314, and the memory 320).

[0118] Additionally, the electronic equipment 300 may further obtain information of specific collection conditions from a virtual resource object collection condition information Date Regue/Date Received 2022-07-27 database for judgment on conditions, and so on.

[0119] As should be noted, although merely the processor 310, the video display adapter 311, the magnetic disk driver 312, the input/output interface 313, the network interface 314, the memory 320, and the bus 330 are illustrated for the aforementioned equipment, the equipment may further include other component parts prerequisite for realizing normal running during specific implementation. In addition, as can be understood by persons skilled in the art, the aforementioned device may as well only include component parts necessary for realizing the solutions of the present application, without including the entire component parts as illustrated.

[0120] Particularly, according to the embodiments of the current application, the processes described above with reference to flowcharts can be realized as computer software programs. For instance, embodiments of the present application include a computer program product that includes a computer program borne on a computer-readable medium, and the computer program contains program codes for executing the methods shown in the flowcharts. In such an embodiment, the computer program can be downloaded from the network and installed through a communication device, or installed from a storage device, or installed from an ROM. When the computer program is executed by a processor, it executes the aforementioned functions defined in the methods of the embodiments of the present application.

[0121] As should be noted, the computer-readable medium recited in the embodiments of the present application can be a computer-readable signal medium or a computer-readable storage medium or a random combination of the two. The computer-readable storage medium can for example be, but is not limited to be, an electric, magnetic, optical, electromagnetic, infrared, or semiconductor system, device or component, or any combination of the above. A more specific example of the computer-readable storage medium can include, but is not limited to include, an electrically connectible, portable Date Regue/Date Received 2022-07-27 computer magnetic disk, a hard disk, a random-access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact magnetic disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device having one or more conducting wire(s), or any suitable combination of the above. In the embodiments of the present application, the computer-readable storage medium can be any tangible medium containing or storing a program usable by or in combination with an instruction executing system, device, or component. Moreover, in the embodiments of the present application, the computer-readable signal medium can include a data signal transmitted in a baseband or as part of a carrier wave, in which data signal are borne computer-readable program codes. The data signal thusly propagated can be embodied in plural forms, including, but not limited to, an electromagnetic signal, an optical signal, or any suitable combination thereof. The computer-readable signal medium can further be any other computer-readable medium than the computer-readable storage medium, and the computer-readable signal medium can transmit, propagate, or convey programs for use by or in combination with an instruction executing system, device, or component. The program codes contained in the computer-readable medium can be transmitted via any suitable medium, including, but not limited to, an electric wire, an optical fiber, radio frequency (RF) etc., or any suitable combination of the above.

[0122] The computer-readable medium can be either contained in the server, or independent of, not installed in the server. The computer-readable medium carries therewith one or more program(s), when the one or more program(s) is/are executed by the server, the server is enabled: to respond to the inactivated peripheral mode of the terminal as detected to obtain frame rate applied to the terminal; to judge whether the user is obtaining screen information of the terminal when the frame rate satisfies a screen resting condition; and to control the screen to enter an immediately darkening mode in response to a judging result that the user has not obtained the screen information.

Date Regue/Date Received 2022-07-27

[0123] One or more programming language(s) or a combination thereof can be employed to write the computer program codes for executing the operations of the embodiments of the present application, the programming language(s) include(s) such an object-oriented programming language as Java, Smalltalk, C++, and further include(s) such a conventional procedural programming language as "C" language or a similar programming language. The program codes can be entirely executed on a user computer, partly executed on a user computer, executed as an independent software package, partly executed on a user computer and partly executed on a remote computer, or entirely executed on a remote computer or a server. In the case a remote computer is involved, the remote computer can be connected to the user computer via a randomly typed network, including a local area network (LAN) or a wide area network (WAN), or can be connected to an external computer (for example, internet connection can be supplied by an internet service provider).

[0124] The various embodiments are progressively described in the Description, identical or similar sections among the various embodiments can be inferred from one another, and each embodiment stresses what is different from other embodiments.
Particularly, with respect to the system or system embodiment, since it is essentially similar to the method embodiment, its description is relatively simple, and the relevant sections thereof can be inferred from the corresponding sections of the method embodiment. The system or system embodiment as described above is merely exemplary in nature, units therein described as separate parts can be or may not be physically separate, parts displayed as units can be or may not be physical units, that is to say, they can be located in a single site, or distributed over a plurality of network units. It is possible to base on practical requirements to select partial modules or the entire modules to realize the objectives of the embodied solutions. It is understandable and implementable by persons ordinarily skilled in the art without spending creative effort in the process.

[0125] The terminal equipment identification information processing method, and the Date Regue/Date Received 2022-07-27 corresponding device, and electronic equipment provided by the present application have been described in detail above, and concrete examples are used in this paper to enunciate the principles and modes of execution of the present application; the descriptions of the foregoing embodiments are merely meant to help understand the methods and kernel conception of the present application; at the same time, persons ordinarily skilled in the art may make various modifications both in terms of the specific modes of execution and the ranges of application in accordance with the conception of the present application. In summary, the contents of this Description shall not be understood to restrict the present application.

[0126] All the aforementioned optional technical solutions are randomly combinable to form optional embodiments of the present invention, to which no repetition is redundantly made on a one-by-one basis. The above is merely directed to preferred embodiments of the present invention, and is not meant to restrict the present invention. Any amendment, equivalent replacement, and improvement makeable within the spirit and principle of the present invention shall all be covered by the protection scope of the present invention.

Date Regue/Date Received 2022-07-27

Claims (10)

What is claimed is:

1. A report generating method, characterized in that the method comprises:
receiving index configuration information input by a user at a web interface;
establishing a first association relation of the index configuration information to a corresponding target data source; and generating the report through a preset model that is matched with the target data source on the basis of the index configuration information and the target data source.

2. The method according to Claim 1, characterized in that the step of establishing a first association relation of the index configuration information to a corresponding target data source includes:
parsing the index configuration information to obtain at least one index name, at least one index dimension, and at least one preset model, wherein each preset model corresponds to the target data source;
establishing at least one associated group according to the at least one index name and the at least one index dimension, wherein index names and index dimensions included in any associated group are associated;
establishing a second association relation of any associated group to the preset model; and establishing a first association relation of the associated group to the target data source on the basis of the second association relation.

3. The method according to Claim 2, characterized in that the step of establishing at least one associated group according to the at least one index name and the at least one index dimension, wherein index names and index dimensions included in any associated group are associated includes:
extracting an index code of each index name, and extracting a dimension code of each index Date Regue/Date Received 2022-07-27 dimension; and establishing the at least one associated group according to a preconstructed correspondence relation between the index code and the dimension code.

4. The method according to Claim 2, characterized in that the step of establishing a second association relation of any associated group to the preset model includes:
parsing to obtain a model invoking parameter corresponding to the preset model on the basis of the associated group; and matching a corresponding preset model and constructing a second association relation according to the model invoking parameter.

5. The method according to Claim 4, characterized in that the step of generating the report through a preset model that is matched with the target data source on the basis of the index configuration information and the target data source includes:
invoking the preset model that is matched with the target data source;
invoking target metadata from the target data source; and generating the report through the preset model that is matched with the target data source on the basis of the index configuration information and the target metadata.

6. The method according to Claim 5, characterized in that the target metadata includes target offline data, and that the step of invoking target metadata from the target data source includes:
obtaining the target offline data from a preset external data warehouse according to a preset frequency and storing the same.

7. The method according to Claim 5, characterized in that the target metadata includes target real time data, and that the step of invoking target metadata from the target data source includes:
obtaining in real time, from a message middleware, target real time data that is sent after Flink performs real-time index calculation and is of a preset data format.

Date Regue/Date Received 2022-07-27

8. A report generating device, characterized in that the device comprises:
a receiving module, for receiving index configuration information input by a user at a web interface;
an associating module, for establishing a first association relation of the index configuration information to a corresponding target data source; and a generating module, for generating the report through a preset model that is matched with the target data source on the basis of the index configuration information and the target data source.

9. An electronic equipment, characterized in comprising:
one or more processor(s); and a memory, associated with the one or more processor(s) and storing a program instruction that executes the method according to any of Claims 1 to 7 when it is read and executed by the one or more processor(s).

10. A computer-readable medium, storing thereon a computer program, wherein the program realizes the method according to any of Claims 1 to 7 when it is executed by a processor.

Date Regue/Date Received 2022-07-27