CN112560416B - Page chart generation method and device, electronic equipment and storage medium - Google Patents
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Abstract
The application relates to the field of development, and discloses a page chart generation method, which comprises the following steps: obtaining chart data to be generated, calculating a matching value of the chart data to be generated and a chart data acquisition model created in a database in advance, and selecting a chart data acquisition model with the matching value larger than a preset threshold value to obtain a target chart data acquisition model; based on a target chart data acquisition model, acquiring data corresponding to chart data to be generated from the database to obtain an initial chart data set; preprocessing the initial chart data set to obtain a target chart data set; performing chart configuration on the target chart data set by using a preset filter to obtain a configuration chart data set; and carrying out page interface analysis on the configuration chart data set by utilizing the pre-created text template engine to generate a corresponding page chart. Furthermore, the present application relates to blockchain techniques, and the configuration diagram dataset may be stored in a blockchain. The application can improve the efficiency of page chart generation.
Description
Technical Field
The present application relates to the field of development, and in particular, to a page chart generating method, a page chart generating device, an electronic device, and a computer readable storage medium.
Background
In the age of rapid information development, data visualization is applied to various fields, such as population census, finance, product analysis and the like, and the data visualization is usually realized based on a visual analysis tool, such as a common Excel form tool, which can also perform simple data visualization, but if the Excel tool encounters a huge data volume of a multi-organization multi-account set, the processing is complex and the response waiting time is not short. Accordingly, in recent years, commercial intelligence (Business Intelligence, BI) systems, which are systems employing modern data warehouse technology, on-line analysis processing technology, data mining and data presentation technology for data analysis to perform functions such as data reporting, data processing, etc., have become increasingly popular with users.
However, the development of BI systems currently suffers from several problems: each chart in the first and the second BI systems is independently written with codes for generating data, but in practice, the processing logic has a plurality of identical places, so redundant codes are easily generated, and the page chart generation efficiency is affected; and secondly, each chart in the BI system is independently subjected to database acquisition, and a plurality of charts exist on a page of the BI system, so that the problem of database interface performance is easily caused by excessive chart data acquisition, and the page chart generation efficiency is also influenced.
Disclosure of Invention
The application provides a page chart generation method, a page chart generation device, electronic equipment and a computer readable storage medium, and mainly aims to improve page chart generation efficiency.
In order to achieve the above object, the present application provides a page chart generating method, including:
obtaining chart data to be generated, calculating a matching value of the chart data to be generated and a chart data acquisition model created in a database in advance, and selecting a chart data acquisition model with the matching value larger than a preset threshold value to obtain a target chart data acquisition model;
acquiring data corresponding to the chart data to be generated from the database based on the target chart data acquisition model to obtain an initial chart data set;
preprocessing the initial chart data set to obtain a target chart data set;
performing chart configuration on the target chart data set by using a preset filter to obtain a configuration chart data set;
and carrying out page interface analysis on the configuration chart data set by using a pre-created text template engine to generate a corresponding page chart.
Optionally, before calculating the matching value between the chart data to be generated and the chart data acquisition model created in the database in advance, the method further includes:
acquiring all data tables of the database, and clustering the data tables of the same type to obtain one or more initial data tables;
and calculating expected values of each initial data table, and taking the initial data tables with the same expected values as a chart data acquisition model.
Optionally, said calculating an expected value for each of said initial data tables includes:
calculating the expected value of each initial data table by the following method:
wherein ,Ci Representing the expected value of the ith initial data table, E i The feature vector representing the i-th initial data table,representing the eigenvector covariance of the i-th initial data table, trace () represents the spatial filter function.
Optionally, the calculating the matching value of the chart data to be generated and the chart data acquisition model created in the database in advance includes:
acquiring the same fields of the to-be-generated chart data and the fields in the chart data acquisition model, and identifying the same fields to obtain a target field set;
summarizing the field length of each field in the chart data to be generated to obtain a first field length value, summarizing the field length of each field in the chart data acquisition model to obtain a second field length value, and summarizing the field length of each field in the target field set to obtain a third field length value;
calculating the duty ratio of the third field length value to the first field length value to obtain a first duty ratio, and calculating the duty ratio of the third field length value to the second field length value to obtain a second duty ratio;
and calculating a matching value between the chart data to be generated and the chart data acquisition model according to the first duty ratio and the second duty ratio.
Optionally, the preprocessing operation is performed on the initial chart data set to obtain a target chart data set, including:
screening the chart category of the initial chart data set to obtain a screened chart data set;
performing chart generation and sequencing on the screening chart data set to obtain a sequencing chart data set;
performing chart data filling on the sequencing chart data set to obtain a filled chart data set;
performing chart data grouping on the filling chart data set to obtain a grouping chart data set;
and carrying out chart data blank on the group chart data set to obtain a target chart data set.
Optionally, the performing graph configuration on the target graph data set by using a preset filter to obtain a configured graph data set includes:
converting the enumerated data in the target chart dataset by using a chart screener in the screener to obtain a conversion chart dataset;
performing chart level association on the conversion chart data set by using a global filter in the filter to obtain an association chart data set;
and performing chart classification configuration on the associated chart data set by utilizing an automatic filter in the filter to obtain a configuration chart data set.
The page interface analysis is carried out on the configuration chart data set by utilizing a pre-created text template engine to generate a corresponding page chart, which comprises the following steps:
and carrying out text format analysis on the configuration chart data set by using the text template engine to obtain a text chart set, and transmitting the text chart set to a page interface to obtain a corresponding page chart.
In order to solve the above problems, the present application also provides a page chart generating apparatus, including:
the selecting module is used for acquiring chart data to be generated, calculating a matching value of the chart data to be generated and a chart data acquisition model which is created in a database in advance, and selecting the chart data acquisition model with the matching value larger than a preset threshold value to obtain a target chart data acquisition model;
the acquisition module is used for acquiring data corresponding to the chart data to be generated from the database based on the target chart data acquisition model to obtain an initial chart data set;
the preprocessing module is used for preprocessing the initial chart data set to obtain a target chart data set;
the configuration module is used for carrying out chart configuration on the target chart data set by utilizing a preset filter to obtain a configuration chart data set;
and the generation module is used for carrying out page interface analysis on the configuration chart data set by utilizing the pre-created text template engine to generate a corresponding page chart.
In order to solve the above-mentioned problems, the present application also provides an electronic apparatus including:
at least one processor; the method comprises the steps of,
a memory communicatively coupled to the at least one processor; wherein,
the memory stores a computer program executable by the at least one processor to implement the page table generation method described above.
In order to solve the above-described problems, the present application also provides a computer-readable storage medium having stored therein at least one computer program that is executed by a processor in an electronic device to implement the page table generating method described above.
Firstly, obtaining chart data to be generated, calculating a matching value of the chart data to be generated and a chart data acquisition model created in a database in advance, selecting the chart data acquisition model with the matching value larger than a preset threshold value, acquiring data corresponding to the chart data to be generated from the database based on the selected chart data acquisition model to obtain an initial chart data set, and preprocessing the initial chart data set to obtain a target chart data set, so that the problem of data throughput of the database caused by excessive chart data acquisition can be avoided, the interface performance of the database is improved, and the chart generation efficiency is improved; secondly, the embodiment of the application utilizes the preset filter to carry out chart configuration on the target chart data set to obtain the configured chart data set, thereby avoiding excessive data code redundancy phenomenon and improving chart generation efficiency; further, the embodiment of the application utilizes the pre-created text template engine to analyze the page interface of the configuration chart data set to generate a corresponding page chart. Therefore, the page chart generation method, the page chart generation device, the electronic equipment and the storage medium can improve the page chart generation efficiency.
Drawings
FIG. 1 is a flowchart illustrating a page diagram generating method according to an embodiment of the present application;
FIG. 2 is a detailed flowchart illustrating one of the steps of the page table generating method shown in FIG. 1 according to the first embodiment of the present application;
FIG. 3 is a schematic block diagram of a page diagram generating apparatus according to an embodiment of the present application;
fig. 4 is a schematic diagram of an internal structure of an electronic device for implementing a page chart generating method according to an embodiment of the present application;
the achievement of the objects, functional features and advantages of the present application will be further described with reference to the accompanying drawings, in conjunction with the embodiments.
Detailed Description
It should be understood that the specific embodiments described herein are for purposes of illustration only and are not intended to limit the scope of the application.
The embodiment of the application provides a page chart generation method. The execution subject of the page diagram generating method includes, but is not limited to, at least one of a server, a terminal, and the like, which can be configured to execute the method provided by the embodiment of the application. In other words, the page diagram generating method may be performed by software or hardware installed in a terminal device or a server device, and the software may be a blockchain platform. The service end includes but is not limited to: a single server, a server cluster, a cloud server or a cloud server cluster, and the like.
Referring to fig. 1, a flow chart of a page chart generating method according to an embodiment of the application is shown. In the embodiment of the application, the page chart generation method comprises the following steps:
s1, obtaining chart data to be generated, calculating a matching value of the chart data to be generated and a chart data acquisition model created in a database in advance, and selecting the chart data acquisition model with the matching value larger than a preset threshold value to obtain a target chart data acquisition model.
In the embodiment of the application, the database comprises a relational database, such as an Oracle database, a MySQL database and the like, and the database is used for storing data for generating the chart. The chart data to be generated is used for forming charts in a business intelligence (Business Intelligence, BI) system, wherein the BI system is a system for performing data analysis by adopting a modern data warehouse technology, an online analysis processing technology, a data mining and data presentation technology so as to realize functions of data filling, data processing and the like.
Further, before calculating the matching value between the chart data to be generated and the chart data acquisition model created in the database in advance, the embodiment of the application further comprises: acquiring all data tables of the database, and clustering the data tables of the same type to obtain one or more initial data tables; calculating expected values of each initial data table; and taking the initial data table with the same expected value as a chart data acquisition model.
The chart data acquisition model is used for inquiring data from the database, so that configuration of screening conditions required during subsequent data acquisition is avoided, and data to be acquired can be directly filled into the corresponding data acquisition model, so that the data acquisition efficiency is improved; the expected value can be understood as the importance value of each initial data table in the corresponding data table matrix.
In an alternative embodiment, the data tables are clustered by a k-means algorithm.
In an alternative embodiment, the expected value of each of the initial data tables is calculated using the following method:
wherein ,Ci Representing the expected value of the ith initial data table, E i The feature vector representing the i-th initial data table,representing the eigenvector covariance of the i-th initial data table, trace () represents the spatial filter function.
Further, the calculating the matching value of the chart data to be generated and the chart data acquisition model created in the database in advance includes: acquiring the same fields of the to-be-generated chart data and the fields in the chart data acquisition model, and identifying the same fields to obtain a target field set; summarizing the field length of each field in the chart data to be generated to obtain a first field length value, summarizing the field length of each field in the chart data acquisition model to obtain a second field length value, and summarizing the field length of each field in the target field set to obtain a third field length value; calculating the duty ratio of the third field length value to the first field length value to obtain a first duty ratio, and calculating the duty ratio of the third field length value to the second field length value to obtain a second duty ratio; and calculating a matching value between the chart data to be generated and the chart data acquisition model according to the first duty ratio and the second duty ratio.
In the embodiment of the application, the same field of the chart data to be generated and the chart data acquisition model is obtained through SQL query sentences, for example, the chart data to be generated has field numbers, the SQL query sentences are utilized to query the chart data acquisition model for the field, and if the field numbers are queried, the field numbers are identified. The field length refers to the number of characters contained in the corresponding field, for example, 7 characters are contained in the field student, and the field degree of the field student is 7.
Further, the calculating, according to the first duty ratio and the second duty ratio, a matching value between the field set and a field in the data acquisition model includes: and taking the average value of the first duty ratio and the second duty ratio as a matching value of the field set and the fields in the data acquisition model.
Further, the embodiment of the application selects the data acquisition model with the matching value larger than a preset threshold value, and optionally, the preset threshold value is 0.6.
S2, based on the target chart data acquisition model, acquiring data corresponding to the chart data to be generated from the database, and obtaining an initial chart data set.
In the embodiment of the present application, the acquiring, based on the target chart data acquisition model, data corresponding to the chart data to be generated into the database to obtain an initial chart data set includes:
and operating the SQL configuration statement of the target chart data acquisition model, and inquiring data corresponding to the chart data to be generated from the database by utilizing a preset data acquisition mechanism to obtain an initial chart data set.
In an alternative embodiment, the preset data collection mechanism is configured by SQL statements, which includes: a data master query mechanism, a data pre-query mechanism and a data independent query mechanism.
The data main query mechanism performs data query on the condition of date, and comprises the following steps: a time point query, which may be understood as a data query using a day as a time point, such as querying data of 18 days of 6 months of 2020, and a time period query, which may be understood as a data query using an acquisition time stamp, which is set based on a user's requirement. For example, the acquisition time stamp is { "start": "2019-01-01", "end": "2030-12-31", "diff": "23" }, where start represents the minimum start date, end represents the maximum expiration date, diff represents the difference between the desired data interval and the query entry date. The data pre-query mechanism adds query conditions to the data main query mechanism according to configured default values, such as a configuration data blacklist (which data do not need to be collected), configuration data priority (which data are queried first), and the like. The data independent query mechanism is used for querying the data which cannot be queried by the data main query mechanism so as to ensure the integrity of data acquisition.
S3, preprocessing the initial chart data set to obtain a target chart data set.
It should be appreciated that, by using the initial chart data in the initial chart data set, a corresponding chart may be generated, and since the initial chart data set includes many different types of chart data, if chart generation is directly performed according to the initial chart data set, many repeated query actions are easily brought about to affect the speed of chart generation, so that the embodiment of the application performs a preprocessing operation on the initial chart data set to increase the speed of subsequent chart generation.
In detail, the preprocessing operation is performed on the initial chart data set to obtain a target chart data set, which comprises the following steps: screening the chart category of the initial chart data set to obtain a screened chart data set; performing chart generation and sequencing on the screening chart data set to obtain a sequencing chart data set; performing chart data filling on the sequencing chart data set to obtain a filled chart data set; performing chart data grouping on the filling chart data set to obtain a grouping chart data set; and carrying out chart data blank on the group chart data set to obtain a target chart data set.
In one embodiment of the present application, the chart category filtering is performed in a key-value pair (key-value) manner, that is, the initial chart data corresponding to the same key value are divided together.
In one embodiment of the present application, the chart generating ordering is implemented by a preset ordering rule, where the preset ordering rule includes: ASC (increment, null before), DESC (decrement, null before), ASCNULL (increment, null after), desnull (decrement, null after).
In one embodiment of the present application, the graph data filling is implemented by binary coding, and is used for continuously processing discontinuous interval data. Wherein the two-level system code comprises: chart data encoding is carried out from low order to high order, namely, the first bit 0 represents filling data 1 according to the date range, and intercepting data with empty tail is represented; the second bit 0 indicates that discrete data is held and 1 indicates that padding is required for serialization.
In one embodiment of the present application, the chart data groupings are grouped according to attributes that populate the chart data set, i.e., the data that creates the same chart is grouped together.
In one embodiment of the present application, the chart data blank is implemented by an EMPTY rule, where the EMPTY rule includes [ "#removal": { "EMPTY": "true" } ], which is used to specify that the chart blank processing is required in the case that the data is blank.
And S4, performing chart configuration on the target chart data set by using a preset filter to obtain a configuration chart data set.
It should be appreciated that in the process of generating the chart of the BI system, the enumerated values of the corresponding chart data need to be converted and the corresponding chart data hierarchical relationship needs to be identified, so that the embodiment of the application uses the preset filter to perform the chart configuration on the target chart data so as to ensure the premise of chart generation. The preset filter is compiled through Java language, and comprises the following steps: graph filter, global filter and auto-filter.
In detail, referring to fig. 2, the performing graph configuration on the target graph dataset by using a preset filter to obtain a configured graph dataset includes:
s20, converting the enumerated data in the target chart dataset by using the chart filter to obtain a conversion chart dataset;
s21, performing chart level association on the conversion chart data set by using the global filter to obtain an association chart data set;
s22, carrying out chart classification configuration on the associated chart data set by utilizing the automatic filter to obtain a configuration chart data set.
In an alternative embodiment, the enumerated data conversion is implemented by a conversion rule configured in advance in the chart filter, where the conversion rule includes: { "D0009900005" { "ALL": "ALL" }, meaning that the transition of the value "ALL" to "ALL" implements name transition of enumerated values for subsequent chart presentation at the front end.
In an alternative embodiment, the chart level association is implemented by association rules configured in advance in a global filter, and the association rules include: "GLODIM" { "D0096800001" { "D0000100105" { "D0009800003" { "title": team "," rename "{" ALL ":" ALL "}," remove "{" ALL ":" }, "title": "branch", "rename" { "ALL": full area "}," nochild "{" ALL ":" }, "title": "{" ALL "}," battle "," rename "," ALL "{" ALL "}," nochild ":" { "ALL" } ", wherein title configuration specifies title of the current level, rename specify name conversion rules, nochild indicates that generation of child-level data is terminated after encountering a specified value, and remove specifies some data non-screeners.
In an alternative embodiment, the chart classification configuration is implemented by classification rules configured in advance in an autofilter, the classification rules including: "# MANDIM" { "jsz" { "# CHDCODE": "jsz", "# CHILDREN" { "=0" { "name": "Add", "# CHDCODE": "jsr", "# CHILDREN": { "= 0" { "(name") ":" enter "}," <0 "{" name "} } }," = 1 "{" name ":" decrease "} } }", wherein #MANDIM is a key of the autofilter configuration, # CHDCODE represents a code value of its sub-level filter, # CHILDREN represents an enumeration of the sub-level filter, # CHILDREN is a value of the screen option, and name specifies the name of the value.
Further, to ensure reusability and privacy of the configuration graph dataset, the configuration graph dataset may also be stored in a blockchain node.
S5, carrying out page interface analysis on the configuration chart data set by utilizing a pre-created text template engine, and generating a corresponding page chart.
The embodiment of the application utilizes the pre-created text template engine to analyze the page interface of the configuration chart data set to generate a corresponding page chart. The page diagram can be in the form of pie charts, trees, bars and the like. The text template engine includes a server side template engine (Ejs template).
In detail, the performing page interface parsing on the configuration chart dataset by using the pre-created text template engine to generate a corresponding page chart includes: and carrying out text format analysis on the configuration chart data set by using the text template engine to obtain a text chart set, and transmitting the text chart set to a page interface to obtain a corresponding page chart.
The text formats comprise josn format text, xml format text and the like, and the page interface refers to a visual page configured in the BI system and is used for intuitively displaying a page chart. Optionally, the transmission of the text chart set is implemented by an heref tag.
Firstly, obtaining chart data to be generated, calculating a matching value of the chart data to be generated and a chart data acquisition model created in a database in advance, selecting the chart data acquisition model with the matching value larger than a preset threshold value, acquiring data corresponding to the chart data to be generated from the database based on the selected chart data acquisition model to obtain an initial chart data set, and preprocessing the initial chart data set to obtain a target chart data set, so that the problem of data throughput of the database caused by excessive chart data acquisition can be avoided, the interface performance of the database is improved, and the chart generation efficiency is improved; secondly, the embodiment of the application utilizes the preset filter to carry out chart configuration on the target chart data set to obtain the configured chart data set, thereby avoiding excessive data code redundancy phenomenon and improving chart generation efficiency; further, the embodiment of the application utilizes the pre-created text template engine to analyze the page interface of the configuration chart data set to generate a corresponding page chart. Therefore, the page chart generation method, the page chart generation device, the electronic equipment and the storage medium can improve the page chart generation efficiency.
As shown in fig. 3, a functional block diagram of the page diagram generating apparatus according to the present application is shown.
The page table generating apparatus 100 of the present application may be installed in an electronic device. The page diagram generating device may include a selecting module 101, an acquiring module 102, a preprocessing module 103, a configuring module 104, and a generating module 105 according to the implemented functions. The module of the present application may also be referred to as a unit, meaning a series of computer program segments capable of being executed by the processor of the electronic device and of performing fixed functions, stored in the memory of the electronic device.
In the present embodiment, the functions concerning the respective modules/units are as follows:
the selecting module 101 is configured to obtain chart data to be generated, calculate a matching value between the chart data to be generated and a chart data acquisition model created in a database in advance, and select a chart data acquisition model with the matching value greater than a preset threshold value to obtain a target chart data acquisition model;
the collection module 102 is configured to collect, based on the target chart data collection model, data corresponding to the chart data to be generated into the database, to obtain an initial chart data set;
the preprocessing module 103 is configured to perform a preprocessing operation on the initial chart dataset to obtain a target chart dataset;
the configuration module 104 is configured to perform graph configuration on the target graph dataset by using a preset filter to obtain a configuration graph dataset;
the generating module 105 is configured to perform page interface parsing on the configuration chart dataset by using a pre-created text template engine, so as to generate a corresponding page chart.
In detail, the modules in the page chart generating device 100 in the embodiment of the present application use the same technical means as the page chart generating method described in fig. 1 and 2 and can generate the same technical effects, which are not described herein.
Fig. 4 is a schematic structural diagram of an electronic device for implementing the page chart generating method according to the present application.
The electronic device 1 may comprise a processor 10, a memory 11 and a bus, and may further comprise a computer program, such as a page diagram generating program 12, stored in the memory 11 and executable on the processor 10.
The memory 11 includes at least one type of readable storage medium, including flash memory, a mobile hard disk, a multimedia card, a card memory (e.g., SD or DX memory, etc.), a magnetic memory, a magnetic disk, an optical disk, etc. The memory 11 may in some embodiments be an internal storage unit of the electronic device 1, such as a removable hard disk of the electronic device 1. The memory 11 may in other embodiments also be an external storage device of the electronic device 1, such as a plug-in mobile hard disk, a Smart Media Card (SMC), a Secure Digital (SD) Card, a Flash memory Card (Flash Card) or the like, which are provided on the electronic device 1. Further, the memory 11 may also include both an internal storage unit and an external storage device of the electronic device 1. The memory 11 may be used not only for storing application software installed in the electronic device 1 and various types of data, such as a page diagram generated code, but also for temporarily storing data that has been output or is to be output.
The processor 10 may be comprised of integrated circuits in some embodiments, for example, a single packaged integrated circuit, or may be comprised of multiple integrated circuits packaged with the same or different functions, including one or more central processing units (Central Processing unit, CPU), microprocessors, digital processing chips, graphics processors, combinations of various control chips, and the like. The processor 10 is a Control Unit (Control Unit) of the electronic device, connects respective components of the entire electronic device using various interfaces and lines, and executes various functions of the electronic device 1 and processes data by running or executing programs or modules (e.g., performing page diagram generation, etc.) stored in the memory 11, and calling data stored in the memory 11.
The bus may be a peripheral component interconnect standard (peripheral component interconnect, PCI) bus or an extended industry standard architecture (extended industry standard architecture, EISA) bus, among others. The bus may be classified as an address bus, a data bus, a control bus, etc. The bus is arranged to enable a connection communication between the memory 11 and at least one processor 10 etc.
Fig. 4 shows only an electronic device with components, it being understood by a person skilled in the art that the structure shown in fig. 4 does not constitute a limitation of the electronic device 1, and may comprise fewer or more components than shown, or may combine certain components, or may be arranged in different components.
For example, although not shown, the electronic device 1 may further include a power source (such as a battery) for supplying power to each component, and preferably, the power source may be logically connected to the at least one processor 10 through a power management device, so that functions of charge management, discharge management, power consumption management, and the like are implemented through the power management device. The power supply may also include one or more of any of a direct current or alternating current power supply, recharging device, power failure detection circuit, power converter or inverter, power status indicator, etc. The electronic device 1 may further include various sensors, bluetooth modules, wi-Fi modules, etc., which will not be described herein.
Further, the electronic device 1 may also comprise a network interface, optionally the network interface may comprise a wired interface and/or a wireless interface (e.g. WI-FI interface, bluetooth interface, etc.), typically used for establishing a communication connection between the electronic device 1 and other electronic devices.
The electronic device 1 may optionally further comprise a user interface, which may be a Display, an input unit, such as a Keyboard (Keyboard), or a standard wired interface, a wireless interface. Alternatively, in some embodiments, the display may be an LED display, a liquid crystal display, a touch-sensitive liquid crystal display, an OLED (Organic Light-Emitting Diode) touch, or the like. The display may also be referred to as a display screen or display unit, as appropriate, for displaying information processed in the electronic device 1 and for displaying a visual user interface.
It should be understood that the embodiments described are for illustrative purposes only and are not limited to this configuration in the scope of the patent application.
The page diagram generation 12 stored by the memory 11 in the electronic device 1 is a combination of a plurality of computer programs, which when run in the processor 10, can implement:
obtaining chart data to be generated, calculating a matching value of the chart data to be generated and a chart data acquisition model created in a database in advance, and selecting a chart data acquisition model with the matching value larger than a preset threshold value to obtain a target chart data acquisition model;
acquiring data corresponding to the chart data to be generated from the database based on the target chart data acquisition model to obtain an initial chart data set;
preprocessing the initial chart data set to obtain a target chart data set;
performing chart configuration on the target chart data set by using a preset filter to obtain a configuration chart data set;
and carrying out page interface analysis on the configuration chart data set by using a pre-created text template engine to generate a corresponding page chart.
In particular, the specific implementation method of the processor 10 on the computer program may refer to the description of the relevant steps in the corresponding embodiment of fig. 1, which is not repeated herein.
Further, the integrated modules/units of the electronic device 1 may be stored in a non-volatile computer readable storage medium if implemented in the form of software functional units and sold or used as a stand alone product. The computer readable storage medium may be volatile or nonvolatile. For example, the computer readable medium may include: any entity or device capable of carrying the computer program code, a recording medium, a U disk, a removable hard disk, a magnetic disk, an optical disk, a computer Memory, a Read-Only Memory (ROM).
The present application also provides a computer readable storage medium storing a computer program which, when executed by a processor of an electronic device, can implement:
obtaining chart data to be generated, calculating a matching value of the chart data to be generated and a chart data acquisition model created in a database in advance, and selecting a chart data acquisition model with the matching value larger than a preset threshold value to obtain a target chart data acquisition model;
acquiring data corresponding to the chart data to be generated from the database based on the target chart data acquisition model to obtain an initial chart data set;
preprocessing the initial chart data set to obtain a target chart data set;
performing chart configuration on the target chart data set by using a preset filter to obtain a configuration chart data set;
and carrying out page interface analysis on the configuration chart data set by using a pre-created text template engine to generate a corresponding page chart.
In the several embodiments provided in the present application, it should be understood that the disclosed apparatus, device and method may be implemented in other manners. For example, the above-described apparatus embodiments are merely illustrative, and for example, the division of the modules is merely a logical function division, and there may be other manners of division when actually implemented.
The modules described as separate components may or may not be physically separate, and components shown as modules may or may not be physical units, may be located in one place, or may be distributed over multiple network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of this embodiment.
In addition, each functional module in the embodiments of the present application may be integrated in one processing unit, or each unit may exist alone physically, or two or more units may be integrated in one unit. The integrated units can be realized in a form of hardware or a form of hardware and a form of software functional modules.
It will be evident to those skilled in the art that the application is not limited to the details of the foregoing illustrative embodiments, and that the present application may be embodied in other specific forms without departing from the spirit or essential characteristics thereof.
The present embodiments are, therefore, to be considered in all respects as illustrative and not restrictive, the scope of the application being indicated by the appended claims rather than by the foregoing description, and all changes which come within the meaning and range of equivalency of the claims are therefore intended to be embraced therein. Any reference signs in the claims shall not be construed as limiting the claim concerned.
The blockchain is a novel application mode of computer technologies such as distributed data storage, point-to-point transmission, consensus mechanism, encryption algorithm and the like. The Blockchain (Blockchain), which is essentially a decentralised database, is a string of data blocks that are generated by cryptographic means in association, each data block containing a batch of information of network transactions for verifying the validity of the information (anti-counterfeiting) and generating the next block. The blockchain may include a blockchain underlying platform, a platform product services layer, an application services layer, and the like.
Furthermore, it is evident that the word "comprising" does not exclude other elements or steps, and that the singular does not exclude a plurality. A plurality of units or means recited in the system claims can also be implemented by means of software or hardware by means of one unit or means. The terms second, etc. are used to denote a name, but not any particular order.
Finally, it should be noted that the above-mentioned embodiments are merely for illustrating the technical solution of the present application and not for limiting the same, and although the present application has been described in detail with reference to the preferred embodiments, it should be understood by those skilled in the art that modifications and equivalents may be made to the technical solution of the present application without departing from the spirit and scope of the technical solution of the present application.
Claims (7)
1. A method for generating a page chart, the method comprising:
obtaining chart data to be generated, calculating a matching value of the chart data to be generated and a chart data acquisition model created in a database in advance, and selecting a chart data acquisition model with the matching value larger than a preset threshold value to obtain a target chart data acquisition model;
acquiring data corresponding to the chart data to be generated from the database based on the target chart data acquisition model to obtain an initial chart data set;
preprocessing the initial chart data set to obtain a target chart data set;
performing chart configuration on the target chart data set by using a preset filter to obtain a configuration chart data set;
carrying out page interface analysis on the configuration chart data set by utilizing a pre-created text template engine to generate a corresponding page chart;
the preprocessing operation is performed on the initial chart data set to obtain a target chart data set, which comprises the following steps: screening the chart category of the initial chart data set, and dividing the initial chart data corresponding to the same key value together through a key value pair form to obtain a screened chart data set; performing chart generation and sequencing on the screening chart data set to obtain a sequencing chart data set; performing chart data filling on the sequencing chart data set, and performing continuous processing on discontinuous interval data to obtain a filled chart data set; performing chart data grouping on the filling chart data set, grouping the data generating the same chart together to obtain a grouping chart data set; carrying out chart data blank on the group chart data set, and carrying out chart blank processing under the condition that the appointed data is blank to obtain a target chart data set;
the method for configuring the target graph data set by using the preset filter to obtain a configured graph data set comprises the following steps: converting the enumerated data in the target chart dataset by using a chart screener in the screener to obtain a conversion chart dataset; performing chart level association on the conversion chart data set by using a global filter in the filter to obtain an association chart data set; performing chart classification configuration on the associated chart data set by utilizing an automatic screener in the screener to obtain a configuration chart data set;
the page interface analysis is carried out on the configuration chart data set by utilizing a pre-created text template engine to generate a corresponding page chart, which comprises the following steps: and carrying out text format analysis on the configuration chart data set by using the text template engine to obtain a text chart set, and transmitting the text chart set to a page interface to obtain a corresponding page chart.
2. The page graph generation method of claim 1, wherein before calculating the matching value of the graph data to be generated and the graph data collection model created in the database in advance, further comprising:
acquiring all data tables of the database, and clustering the data tables of the same type to obtain one or more initial data tables;
and calculating expected values of each initial data table, and taking the initial data tables with the same expected values as a chart data acquisition model.
3. The page table generating method as claimed in claim 2, wherein said calculating the expected value of each of the initial data tables includes:
calculating the expected value of each initial data table by the following method:
wherein ,representing the expected value of the ith initial data table,/->Feature vector representing the i-th initial data table, is->Representing the eigenvector covariance of the i-th initial data table, trace () represents the spatial filter function.
4. The page graph generation method of claim 1, wherein the calculating a matching value of the graph data to be generated and a graph data collection model created in advance in a database includes:
acquiring the same fields of the to-be-generated chart data and the fields in the chart data acquisition model, and identifying the same fields to obtain a target field set;
summarizing the field length of each field in the chart data to be generated to obtain a first field length value, summarizing the field length of each field in the chart data acquisition model to obtain a second field length value, and summarizing the field length of each field in the target field set to obtain a third field length value;
calculating the duty ratio of the third field length value to the first field length value to obtain a first duty ratio, and calculating the duty ratio of the third field length value to the second field length value to obtain a second duty ratio;
and calculating a matching value between the chart data to be generated and the chart data acquisition model according to the first duty ratio and the second duty ratio.
5. A page chart generation apparatus for implementing the page chart generation method according to any one of claims 1 to 4, characterized in that the apparatus comprises:
the selecting module is used for acquiring chart data to be generated, calculating a matching value of the chart data to be generated and a chart data acquisition model which is created in a database in advance, and selecting the chart data acquisition model with the matching value larger than a preset threshold value to obtain a target chart data acquisition model;
the acquisition module is used for acquiring data corresponding to the chart data to be generated from the database based on the target chart data acquisition model to obtain an initial chart data set;
the preprocessing module is used for preprocessing the initial chart data set to obtain a target chart data set;
the configuration module is used for carrying out chart configuration on the target chart data set by utilizing a preset filter to obtain a configuration chart data set;
and the generation module is used for carrying out page interface analysis on the configuration chart data set by utilizing the pre-created text template engine to generate a corresponding page chart.
6. An electronic device, the electronic device comprising:
at least one processor; the method comprises the steps of,
a memory communicatively coupled to the at least one processor; wherein,
the memory stores a computer program executable by the at least one processor to enable the at least one processor to perform the page table generation method of any one of claims 1 to 4.
7. A computer readable storage medium storing a computer program, wherein the computer program when executed by a processor implements the page table generation method according to any one of claims 1 to 4.
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| WO2009154484A2 (en) * | 2008-06-20 | 2009-12-23 | Business Intelligence Solutions Safe B.V. | Methods, apparatus and systems for data visualization and related applications |
| WO2014096453A1 (en) * | 2012-12-21 | 2014-06-26 | What-Ifolution Bv | Method and system for visualizing and manipulating graphic charts |
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| WO2004029755A2 (en) * | 2002-09-27 | 2004-04-08 | Enviance, Inc. | Automated report building system |
| WO2009154484A2 (en) * | 2008-06-20 | 2009-12-23 | Business Intelligence Solutions Safe B.V. | Methods, apparatus and systems for data visualization and related applications |
| WO2014096453A1 (en) * | 2012-12-21 | 2014-06-26 | What-Ifolution Bv | Method and system for visualizing and manipulating graphic charts |
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