CN113642300A - Report generation method and device, electronic equipment and computer readable medium - Google Patents
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Abstract
The invention discloses a report generation method, which comprises the following steps: receiving index configuration information input by a user on a web interface; establishing a first incidence relation between the index configuration information and a corresponding target data source; the report is generated through a preset model matched with the target data source based on the index configuration information and the target data source, the index configuration information input by a user and the corresponding target data source are established into a first incidence relation, data can be rapidly obtained from the corresponding data source, massive search is avoided, the operation amount is reduced, and the reaction time is prolonged.
Description
Technical Field
The present invention relates to the field of data processing technologies, and in particular, to a report generation method and apparatus, an electronic device, and a computer-readable medium.
Background
Business Intelligence (BI) is a complete solution for effectively integrating existing data in an enterprise, rapidly and accurately providing a report form and providing a decision basis, and helping the enterprise make an intelligent Business operation decision. In the traditional BI field, technicians generally use professional BI software to construct related reports, the construction period is long, the overall consumption of construction and adjustment is large, the feedback period of construction results is long, and one-line requirements cannot be quickly responded.
With the rapid development of financial business, the breadth and depth of business are increasing. Based on the corresponding service scenario, the content of the demand for data analysis is also increasing; meanwhile, the data analysis demand is increased, the analysis difficulty is increased, and the service side has high requirements on the construction timeliness of the landing requirements.
And, the indexes are disordered and not unified when the traditional BI builds a data analysis report; the mass data has limited supporting force, and the response is extremely slow or the response cannot be realized when ultra-multiple data rows are encountered, or the analysis dimensionality is more, the dimensionality combination is more, or the high-cardinality dimensionality is higher.
Disclosure of Invention
In order to solve the problems in the prior art, embodiments of the present invention provide a report generation method, an apparatus, an electronic device, and a computer-readable medium. The technical scheme is as follows:
in a first aspect, a report generation method is provided, where the method includes:
receiving index configuration information input by a user on a web interface;
establishing a first incidence relation between the index configuration information and a corresponding target data source;
and generating the report through a preset model matched with the target data source based on the index configuration information and the target data source.
In a preferred embodiment, the establishing a first association relationship between the index configuration information and the corresponding target data source includes:
analyzing 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 a target data source;
establishing at least one association group according to the at least one index name and the at least one index dimension, wherein the index name included in any association group is associated with the index dimension;
establishing a second association relation between any one association set and the preset model;
and establishing a first association relation between the association group and the target data source based on the second association relation.
In a preferred embodiment, the establishing at least one association group according to the at least one index name and the at least one index dimension, where any association group includes an index name associated with an index dimension, includes:
extracting an index code of each index name and extracting a dimension code of each index dimension;
and establishing at least one association group according to the corresponding relationship between the index code and the dimension code which is constructed in advance.
In a preferred embodiment, the establishing a second association relationship between any one of the associations and the preset model includes:
analyzing and obtaining a model calling parameter corresponding to the preset model based on the association;
and matching a corresponding preset model according to the model calling parameters and constructing a second incidence relation.
In a preferred embodiment, the generating the report through a preset model matched with the target data source based on the index configuration information and the target data source includes:
calling a preset model matched with the target data source;
calling target metadata to the target data source;
and generating the report through the preset model based on the index configuration information and the target metadata.
In a preferred embodiment, the target metadata includes target offline data; the invoking target metadata to the target data source comprises:
and acquiring and storing target offline data from a preset external data bin according to a preset frequency.
In a preferred embodiment, the target metadata includes target real-time data; the invoking target metadata to the target data source comprises:
and acquiring Flink in real time from the message middleware, calculating a real-time index, and sending the calculated real-time index to the message middleware, wherein the calculated real-time index is target real-time data in a preset data format.
In a second aspect, a report generating apparatus is provided, the apparatus including:
the receiving module is used for receiving index configuration information input by a user on a web interface;
the association module is used for establishing a first association relation between the index configuration information and a corresponding target data source;
and the generating module is used for generating the report based on the index configuration information and the target data source by adopting a preset model matched with the target data source.
In a third aspect, an electronic device is provided, comprising
One or more processors; and
memory associated with the one or more processors for storing program instructions which, when read and executed by the one or more processors, perform the method of any of the first aspects.
In a fourth aspect, a computer-readable medium is provided, on which a computer program is stored, wherein the program, when executed by a processor, implements the method according to any of the first aspects.
The technical scheme provided by the embodiment of the invention has the following beneficial effects:
the embodiment of the invention provides a report generation method, a report generation device, electronic equipment and a computer readable medium, wherein a first incidence relation is established between index configuration information input by a user and a corresponding target data source, so that data can be rapidly acquired from the corresponding data source, massive search is avoided, the operation amount is reduced, and the reaction time is improved; more importantly, the method is used for interfacing different data sources and providing services to the outside through a uniform outlet, and the requirement for rapidly providing heterogeneous source index uniform services can be effectively met.
Drawings
In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the drawings needed to be used in the description of the embodiments will be briefly introduced below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and it is obvious for those skilled in the art to obtain other drawings based on these drawings without creative efforts.
FIG. 1 is a flowchart of a report generation method according to an embodiment of the present invention;
fig. 2 is a schematic structural diagram of a report generating apparatus according to an embodiment of the present invention;
fig. 3 is a schematic structural diagram of a computer system according to an embodiment of the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
As described in the background art, the BI data analysis requirements, throughput, and difficulty increase synchronously in response to the development of services, and a long processing time is often required to meet the requirements. Some analysis engines (such as real-time computing engines like Druid, Kylin, Presto/Impala, and elastic search) on the market today have some disadvantages, and cannot meet all the above requirements at the same time. The drive adopts a pre-calculation technology, but cannot achieve accurate deduplication, and the count distinting has certain errors, and has one dimension and time correlation, and has limitation on service. Kylin adopts a pre-calculation technology, but the real-time performance is not high, and a large-scale index system is met, so that huge resources are required to be occupied, and the pre-calculation time is long. The real-time computing engines such as Presto/Impala and the like have long real-time computing response time, especially the response time of complex indexes is very long, and the requirement of response within a second level cannot be met. The elastic search cannot accurately remove the duplicate, has the same accuracy error as the Druid, and has poor support of high-radix dimension combination (high bucket number).
In order to meet the timeliness requirement of a business party, the embodiment provides a report generation method, a report generation device, electronic equipment and a computer readable medium, and the problem of timeliness in the BI field can be effectively solved.
The technical solution of the present application will be further described with reference to specific examples.
Example one
As shown in fig. 1, the present embodiment provides a report generating method, which is used for a BI field to provide a decision basis in cooperation with a business party. The method comprises the following steps:
and S1, receiving index configuration information input by the user on the web interface.
Specifically, the report generation method provided by this embodiment is built based on a web browser, and a user can directly access a visual design page through a common web browser, and input the required index content on the index visual interactor page, that is, input the index content configuration information.
For example, in the embodiment, the visualization interactor is configured by configuring the index to perform human-computer interaction, the index content designed by the user is received, the visual interface obtained by what you see is used for providing user operation, and the design of the index and the cache configuration of the related index are performed. Further, the cache configuration content herein includes the index definition under various dimension combinations and the corresponding cache method.
It can be understood that, in the BI field, in order to match with the service requirements, the indexes are various and non-uniform, which directly results in the inconvenience of index use and even inconsistency of index results. The indexes in this embodiment are divided according to different index dimensions.
Illustratively, the index dimension is divided as follows: the basic attributes comprise information such as name, code, type, public dimension, father dimension, state and the like; the service attribute comprises information such as service caliber, caliber adjusting frequency and the like; the technical attributes comprise information such as corresponding table names, technical apertures, dimension corresponding fields, dimension value corresponding fields, parent dimension fields and the like; the service attribute comprises information such as cache source and cache storage information.
Illustratively, on the basis of the index dimension division, the index division is as follows: the basic attribute includes information such as name, code, type, status, etc. The service attribute comprises information such as service caliber, caliber adjusting frequency, sensitivity grade and the like. The technical attributes comprise information such as corresponding table names, technical calibers, index corresponding fields and the like. The service attribute comprises information such as cache source, cache mode, cache storage information and the like. What is also critical is: the above is based on a result mapping generated under different dimension combinations, for example, an index of a certain statistical total value, and when the dimension association is the year dimension and the month dimension, respectively, the actual technical attribute and the service attribute may be two completely different sets of information.
Therefore, the index configuration information in this embodiment includes at least one index according to the above different index dimensions. According to the embodiment, the mapping of a plurality of groups of cache instances is generated through the combined configuration of indexes and index dimensions, and the contents with different characteristics are respectively processed, so that the problems of large analysis data volume, more analysis dimensions, more combination dimensions and high base number dimensions based on mass data analysis are solved.
And S2, establishing a first association relation between the index configuration information and the corresponding target data source.
Specifically, step S2 includes:
s21, analyzing 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.
The preset model comprises a mass batch index caching module, an accurate duplicate removal index caching module, a mass single index caching module and other modules defined according to functional requirements.
S22, establishing at least one association group according to the at least one index name and the at least one index dimension, wherein any association group comprises index names which are associated with the index dimension.
Further, step S22 includes:
extracting an index code of each index name and extracting a dimension code of each index dimension;
and establishing at least one association group according to the corresponding relation between the index code and the dimension code which is constructed in advance.
And S23, establishing a second association relation between any association group and the preset model.
Specifically, step S23 includes:
analyzing and obtaining a model calling parameter corresponding to a preset model based on the association group;
and matching the corresponding preset model according to the model calling parameters and constructing a second incidence relation.
S24, establishing a first association relation between the association set and the target data source based on the second association relation.
And S3, generating a report through a preset model matched with the target data source based on the index configuration information and the target data source.
Specifically, step S3 includes:
s31, calling a preset model matched with the target data source;
s32, calling the target metadata to the target data source.
In a preferred embodiment, the target metadata includes at least one of target offline data and/or target real-time data.
When the target metadata is target offline data, step S32 includes: and acquiring and storing target offline data from a preset external data bin according to a preset frequency.
When the target metadata is target real-time data, step S32 includes: the method comprises the following steps:
and acquiring Flink in real time from a message middleware (such as kafka), calculating a real-time index, and sending the calculated real-time index to target real-time data in a preset data format. Such as the data format of table name + field name + instance data.
When data is written, a table main key is obtained according to metadata information of a data model, data is updated or inserted according to the main key, and repeated and invalid data is prevented from being input; on the other hand, due to the timeliness of the message, when the data is updated, the latest data is reserved and put in a storage mode according to the accurate time in the data message, and the old data is directly discarded.
And S33, generating a report based on the index configuration information and the target metadata.
After generating the report, the method further comprises: and outputting the generated report forms to a user through the unified port to provide index service.
To further describe the report generation method, the embodiment is exemplarily described below with reference to a specific application scenario.
The report generation method is based on a common web browser to manage and maintain indexes and is executed based on a model information manager, an index configuration visual interaction device, an index analysis manager, an index cache acceleration module set, an index service module and other functional modules which are deployed on a server.
Specifically, the model information manager is used for managing the model metadata and providing the functions of querying and storing the model metadata information. The model metadata includes the name, code, status, maintenance information of the model, and related information of all fields in the model, such as field name, field type, field length, etc. Based on the method, a user can inquire all field information under the model by specifying the unique identifier of the model; and querying information such as field name, field type, field length and the like of a certain field of the specified model by specifying the unique identification of the field.
The index configuration visualization interaction device is used for man-machine interaction, and is specifically used for receiving index configuration information input by a user on a web interface so as to realize a visual interface obtained by what you see is for the user to configure.
The index analysis manager obtains index configuration information configured by a user in the index configuration visual interaction device, analyzes the index configuration information, and analyzes 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. And establishing at least one association group according to at least one index name and at least one index dimension, wherein the index name included in any association group is associated with the index dimension. And establishing a second incidence relation between any one of the incidence groups and the preset model, and establishing a first incidence relation between the incidence groups and the target data source based on the second incidence relation.
The index cache acceleration module set comprises a set of index cache acceleration modules, each module has different technical characteristics and provides different service capabilities, and the index cache acceleration module set at least comprises modules for supporting three scenes, including a mass batch index cache type acceleration module, an accurate duplicate removal index cache type acceleration module and a mass single index cache type acceleration module. And then, the transverse expansion can be carried out according to the requirement.
The massive batch index cache type acceleration module is a core main module and is used for storing common index cache acceleration data, most indexes can be stored by using the acceleration module, the indexes support reprocessing processing, such as summing and maximum value taking, and the like, and are used for supporting scenes such as reports, illustratively, PostgreSQL cities are adopted to achieve a target, and solutions such as Druid and the like can also be used.
The accurate deduplication index caching type acceleration module is used for storing index caching acceleration data needing accurate deduplication (namely, count partition) in a dynamic range, a small number of indexes can be stored by using the acceleration module, and illustratively, a PostgreSQL (structured query language) cluster is adopted to achieve a target.
The massive single index type acceleration module comprises: the method is used for storing the massive indexes of the monomers, a small number of indexes can be stored by using the acceleration module according to the requirement, and the target is achieved by adopting HBase exemplarily.
The index service module provides uniform index service for the user side, in the embodiment, batch index configuration information set on a web browser by a user can be received and processed in batch, and the user is bound uniformly through the index service module, so that the problem of heterogeneous sources is effectively solved.
In summary, the present embodiment provides a report generation method, which can quickly obtain data from a corresponding data source by establishing a first association between index configuration information input by a user and the corresponding target data source, avoid massive search, reduce computation workload, and improve response time, and the report generation method of the present application is a web browser data analysis product, and compared with a scheme in the prior art in which such a product is directly connected to a target database, does not affect performance optimization of the target database.
Example two
In order to execute the report generating method in the first embodiment, the present embodiment provides a report generating device corresponding to the first embodiment, as shown in fig. 2, the device includes:
and the receiving module is used for receiving the index configuration information input by the user on the web interface.
And the association module is used for establishing a first association relation between the index configuration information and the corresponding target data source.
The association module comprises:
the analysis unit is used for analyzing the index configuration information to obtain at least one index name, at least one index dimension and at least one preset model, and each preset model corresponds to a target data source;
and the construction unit is used for establishing at least one association group according to the at least one index name and the at least one index dimension, and the index name included in any one association group is associated with the index dimension.
The building unit is further configured to: extracting an index code of each index name and extracting a dimension code of each index dimension; and establishing at least one association group according to the corresponding relationship between the index code and the dimension code which is constructed in advance.
The first association unit is used for establishing a second association relation between any one association set and the preset model.
The first associating unit is further configured to: analyzing and obtaining a model calling parameter corresponding to the preset model based on the association; and matching a corresponding preset model according to the model calling parameters and constructing a second incidence relation.
And the second association unit is used for establishing a first association relation between the association set and the target data source based on the second association relation.
And the generating module is used for generating the report through a preset model matched with the target data source based on the index configuration information and the target data source. The generation module comprises:
a first calling unit, configured to call a preset model matched with the target data source
The second calling unit is used for calling the target metadata to the target data source;
and the generating unit is used for generating the report through the preset model based on the index configuration information and the target metadata.
Wherein the target metadata comprises target offline data; the second calling unit is used for: and acquiring and storing target offline data from a preset external data bin according to a preset frequency.
The target metadata comprises target real-time data; the second calling unit is used for: and acquiring Flink in real time from the message middleware, calculating a real-time index, and sending the calculated real-time index to the message middleware, wherein the calculated real-time index is target real-time data in a preset data format.
It should be noted that: the report generating device provided in the foregoing embodiment is only illustrated by dividing the functional modules when triggering the report generating service, and in practical applications, the function distribution may be completed by different functional modules according to needs, that is, the internal structure of the device is divided into different functional modules, so as to complete all or part of the functions described above. In addition, the report generation device provided by the above embodiment and the embodiment of the report generation method provided by the above embodiment belong to the same concept, that is, the device is based on the method, and the specific implementation process thereof is described in detail in the method embodiment and is not described herein again.
In addition, corresponding to the report generation method and apparatus, this embodiment further provides an electronic device, including:
one or more processors; and
and a memory associated with the one or more processors for storing program instructions which, when read and executed by the one or more processors, perform the report generation method disclosed in the above embodiments.
Fig. 3 illustrates an architecture of a computer system, which may include, in particular, a processor 310, a video display adapter 311, a disk drive 312, an input/output interface 313, a network interface 314, and a memory 320. The processor 310, the video display adapter 311, the disk drive 312, the input/output interface 313, the network interface 314, and the memory 320 may be communicatively connected by a communication bus 330.
The processor 310 may be implemented by a general-purpose CPU (Central Processing Unit), a microprocessor, an Application Specific Integrated Circuit (ASIC), or one or more Integrated circuits, and is configured to execute related programs to implement the technical solution provided in the present Application.
The Memory 320 may be implemented in the form of a ROM (Read Only Memory), a RAM (Random Access Memory), a static storage device, a dynamic storage device, or the like. The memory 320 may store an operating system 321 for controlling the operation of the electronic device 300, a Basic Input Output System (BIOS) for controlling low-level operations of the electronic device 300. In addition, a web browser 323, a data storage management system 324, and a device identification information processing system 325, and the like may also be stored. The device identification information processing system 325 may be an application program that implements the operations of the foregoing steps in this embodiment of the present application. In summary, when the technical solution provided by the present application is implemented by software or firmware, the relevant program code is stored in the memory 320 and called to be executed by the processor 310.
The input/output interface 313 is used for connecting an input/output module to realize information input and output. The i/o module may be configured as a component in a device (not shown) or may be external to the device to provide a corresponding function. The input devices may include a keyboard, a mouse, a touch screen, a microphone, various sensors, etc., and the output devices may include a display, a speaker, a vibrator, an indicator light, etc.
The network interface 314 is used for connecting a communication module (not shown in the figure) to realize communication interaction between the device and other devices. The communication module can realize communication in a wired mode (such as USB, network cable and the like) and also can realize communication in a wireless mode (such as mobile network, WIFI, Bluetooth and the like).
In addition, the electronic device 300 may also obtain information of specific pickup conditions from a virtual resource object pickup condition information database for performing condition judgment, and the like.
It should be noted that although the above devices only show the processor 310, the video display adapter 311, the disk drive 312, the input/output interface 313, the network interface 314, the memory 320, the bus 330, etc., in a specific implementation, the devices may also include other components necessary for normal operation. Furthermore, it will be understood by those skilled in the art that the apparatus described above may also include only the components necessary to implement the solution of the present application, and not necessarily all of the components shown in the figures.
In particular, according to embodiments of the application, the processes described above with reference to the flow diagrams may be implemented as computer software programs. For example, embodiments of the present application include a computer program product comprising a computer program embodied on a computer readable medium, the computer program comprising program code for performing the method illustrated by the flow chart. In such an embodiment, the computer program may be downloaded and installed from a network via the communication means, or installed from the memory, or installed from the ROM. The computer program, when executed by a processor, performs the above-described functions defined in the methods of embodiments of the present application.
It should be noted that the computer readable medium of the embodiments of the present application may be a computer readable signal medium or a computer readable storage medium or any combination of the two. A computer readable storage medium may be, for example, but not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination of the foregoing. More specific examples of the computer readable storage medium may include, but are not limited to: an electrical connection having one or more wires, a portable computer diskette, 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 disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing. In embodiments of the application, a computer readable storage medium may be any tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device. In embodiments of the present application, however, a computer readable signal medium may include a propagated data signal with computer readable program code embodied therein, for example, in baseband or as part of a carrier wave. Such a propagated data signal may take many forms, including, but not limited to, electro-magnetic, optical, or any suitable combination thereof. A computer readable signal medium may also be any computer readable medium that is not a computer readable storage medium and that can communicate, propagate, or transport a program for use by or in connection with an instruction execution system, apparatus, or device. Program code embodied on a computer readable medium may be transmitted using any appropriate medium, including but not limited to: electrical wires, optical cables, RF (Radio Frequency), etc., or any suitable combination of the foregoing.
The computer readable medium may be embodied in the server; or may exist separately and not be assembled into the server. The computer readable medium carries one or more programs which, when executed by the server, cause the server to: when the peripheral mode of the terminal is detected to be not activated, acquiring a frame rate of an application on the terminal; when the frame rate meets the screen information condition, judging whether a user is acquiring the screen information of the terminal; and controlling the screen to enter an immediate dimming mode in response to the judgment result that the user does not acquire the screen information of the terminal.
Computer program code for carrying out operations for embodiments of the present application may be written in any combination of one or more programming languages, including an object oriented programming language such as Java, Smalltalk, C + +, and conventional procedural programming languages, such as the "C" programming language or similar programming languages. The program code may execute entirely on the user's computer, partly on the user's computer, as a stand-alone software package, partly on the user's computer and partly on a remote computer or entirely on the remote computer or server. In the case of a remote computer, the remote computer may be connected to the user's computer through any type of network, including a Local Area Network (LAN) or a Wide Area Network (WAN), or the connection may be made to an external computer (for example, through the Internet using an Internet service provider).
The embodiments in the present specification are described in a progressive manner, and the same and similar parts among the embodiments are referred to each other, and each embodiment focuses on the differences from the other embodiments. In particular, the system or system embodiments are substantially similar to the method embodiments and therefore are described in a relatively simple manner, and reference may be made to some of the descriptions of the method embodiments for related points. The above-described system and system embodiments are merely illustrative, wherein units described as separate components may or may not be physically separate, and components shown as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of the present embodiment. One of ordinary skill in the art can understand and implement it without inventive effort.
The method, the device and the electronic device for processing the identification information of the terminal device provided by the present application are introduced in detail, and a specific example is applied in the description to explain the principle and the implementation of the present application, and the description of the above embodiment is only used to help understand the method and the core idea of the present application; meanwhile, for a person skilled in the art, according to the idea of the present application, the specific embodiments and the application range may be changed. In summary, this summary should not be construed as a limitation on the present application.
All the above-mentioned optional technical solutions can be combined arbitrarily to form the optional embodiments of the present invention, and are not described herein again. The present invention is not limited to the above preferred embodiments, and any modifications, equivalent replacements, improvements, etc. within the spirit and principle of the present invention should be included in the protection scope of the present invention.
Claims (10)
1. A report generation method is characterized by comprising the following steps:
receiving index configuration information input by a user on a web interface;
establishing a first incidence relation between the index configuration information and a corresponding target data source;
and generating the report through a preset model matched with the target data source based on the index configuration information and the target data source.
2. The method of claim 1, wherein establishing the first association relationship between the metric configuration information and the corresponding target data source comprises:
analyzing 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 a target data source;
establishing at least one association group according to the at least one index name and the at least one index dimension, wherein the index name included in any association group is associated with the index dimension;
establishing a second association relation between any one association set and the preset model;
and establishing a first association relation between the association group and the target data source based on the second association relation.
3. The method according to claim 2, wherein the establishing at least one association group according to the at least one index name and the at least one index dimension, any of the association groups comprising an index name associated with an index dimension comprises:
extracting an index code of each index name and extracting a dimension code of each index dimension;
and establishing at least one association group according to the corresponding relationship between the index code and the dimension code which is constructed in advance.
4. The method according to claim 2, wherein the establishing a second association relationship between any one of the associations and the preset model comprises:
analyzing and obtaining a model calling parameter corresponding to the preset model based on the association;
and matching a corresponding preset model according to the model calling parameters and constructing a second incidence relation.
5. The method according to claim 4, wherein the generating the report through a preset model matched with the target data source based on the index configuration information and the target data source comprises:
calling a preset model matched with the target data source;
calling target metadata to the target data source;
and generating the report through a preset model matched with the target data source based on the index configuration information and the target metadata.
6. The method of claim 5, wherein the target metadata comprises target offline data; the invoking target metadata to the target data source comprises:
and acquiring and storing target offline data from a preset external data bin according to a preset frequency.
7. The method of claim 5, wherein the target metadata comprises target real-time data; the invoking target metadata to the target data source comprises:
and acquiring Flink in real time from the message middleware, calculating a real-time index, and sending the calculated real-time index to the message middleware, wherein the calculated real-time index is target real-time data in a preset data format.
8. A report generation apparatus, characterized in that the apparatus comprises:
the receiving module is used for receiving index configuration information input by a user on a web interface;
the association module is used for establishing a first association relation between the index configuration information and a corresponding target data source;
and the generating module is used for generating the report through a preset model matched with the target data source based on the index configuration information and the target data source.
9. An electronic device, comprising:
one or more processors; and
a memory associated with the one or more processors for storing program instructions that, when read and executed by the one or more processors, perform the method of any of claims 1-7.
10. A computer-readable medium, on which a computer program is stored which, when being executed by a processor, carries out the method according to any one of claims 1-7.
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| CN202110870721.8A CN113642300A (en) | 2021-07-30 | 2021-07-30 | Report generation method and device, electronic equipment and computer readable medium |
| CA3169413A CA3169413A1 (en) | 2021-07-30 | 2022-07-27 | Report generating method, device, electronic equipment, and computer-readable medium |
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| CN202110870721.8A CN113642300A (en) | 2021-07-30 | 2021-07-30 | Report generation method and device, electronic equipment and computer readable medium |
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Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN114116747A (en) * | 2021-11-25 | 2022-03-01 | 北京力控元通科技有限公司 | Production execution system data analysis method and device |
| CN114371884A (en) * | 2021-12-31 | 2022-04-19 | 南京星云数字技术有限公司 | Method, device, equipment and storage medium for processing Flink calculation task |
| CN116108819A (en) * | 2022-10-27 | 2023-05-12 | 广州市扬海数码科技有限公司 | Automatic document generation method and system for ERP management system |
Families Citing this family (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN116414853A (en) * | 2023-02-20 | 2023-07-11 | 广州快决测信息科技有限公司 | Online report generation system, method, electronic equipment and medium |
Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN109657214A (en) * | 2018-09-27 | 2019-04-19 | 深圳壹账通智能科技有限公司 | Report form generation method, device, terminal and storage medium |
| CN112131220A (en) * | 2020-09-15 | 2020-12-25 | 北京奇艺世纪科技有限公司 | Data report processing method and device |
| CN112507003A (en) * | 2021-02-03 | 2021-03-16 | 江苏海平面数据科技有限公司 | Internet of vehicles data analysis platform based on big data architecture |
| CN112949269A (en) * | 2021-04-06 | 2021-06-11 | 携程旅游信息技术（上海）有限公司 | Method, system, equipment and storage medium for generating visual data analysis report |
| CN113076358A (en) * | 2021-03-25 | 2021-07-06 | 恒安嘉新（北京）科技股份公司 | Report generation method, device, equipment and storage medium |
-
2021
- 2021-07-30 CN CN202110870721.8A patent/CN113642300A/en not_active Withdrawn
-
2022
- 2022-07-27 CA CA3169413A patent/CA3169413A1/en active Pending
Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN109657214A (en) * | 2018-09-27 | 2019-04-19 | 深圳壹账通智能科技有限公司 | Report form generation method, device, terminal and storage medium |
| CN112131220A (en) * | 2020-09-15 | 2020-12-25 | 北京奇艺世纪科技有限公司 | Data report processing method and device |
| CN112507003A (en) * | 2021-02-03 | 2021-03-16 | 江苏海平面数据科技有限公司 | Internet of vehicles data analysis platform based on big data architecture |
| CN113076358A (en) * | 2021-03-25 | 2021-07-06 | 恒安嘉新（北京）科技股份公司 | Report generation method, device, equipment and storage medium |
| CN112949269A (en) * | 2021-04-06 | 2021-06-11 | 携程旅游信息技术（上海）有限公司 | Method, system, equipment and storage medium for generating visual data analysis report |
Cited By (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN114116747A (en) * | 2021-11-25 | 2022-03-01 | 北京力控元通科技有限公司 | Production execution system data analysis method and device |
| CN114116747B (en) * | 2021-11-25 | 2023-03-24 | 北京力控元通科技有限公司 | Production execution system data analysis method and device |
| CN114371884A (en) * | 2021-12-31 | 2022-04-19 | 南京星云数字技术有限公司 | Method, device, equipment and storage medium for processing Flink calculation task |
| CN116108819A (en) * | 2022-10-27 | 2023-05-12 | 广州市扬海数码科技有限公司 | Automatic document generation method and system for ERP management system |
| CN116108819B (en) * | 2022-10-27 | 2024-03-05 | 广州市扬海数码科技有限公司 | Automatic document generation method and system for ERP management system |
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| CA3169413A1 (en) | 2023-01-30 |
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