Method and system for displaying data based on multiple dimensions and multiple granularities

Abstract

The invention relates to a method and system for displaying data based on multiple dimensions and multiple granularities. The method comprises the steps that the data statistics dimension and the data screening granularity selected by a user in an interactive user interface are determined; according to the data statistics dimension selected by the user, screening out data of the corresponding dimension as primarily selected data; in the primary selection data, screening out data in a corresponding date range as final selection data according to data screening granularity selected by a user; determining a corresponding chart form according to the data characteristics of the finally selected data; the form of the chart at least comprises a histogram, a line chart and a pie chart; and displaying the finally selected data in a determined chart form through an echarts chart library. According to the technical scheme, a multi-dimensional and multi-granularity data screening function is provided, so that a user can analyze data in a customized manner according to specific requirements. According to the technical scheme, a user is allowed to deeply analyze data from different angles, so that more comprehensive business insight is obtained, and the flexibility of data analysis can be improved on the whole.

Description

Technical Field

[0001] The present application relates to the field of data analysis technology, and in particular to a method and system for displaying data based on multiple dimensions and multiple granularities. Background Art

[0002] With the rapid development of information technology and the explosive growth of enterprise data, data analysis has become an indispensable part of the enterprise decision-making process. Users have an increasing demand for multi-dimensional and multi-granular analysis of data, and expect to gain insights into data from different angles and depths to guide business development and optimize decision-making. In key areas such as operation statistics, consumption statistics, and capacity statistics, users need a statistical tool that can respond quickly, flexibly filter, and deeply analyze data. However, existing data statistical methods and tools are often limited by fixed data display dimensions and a single filtering mechanism, making it difficult to adapt to users' high requirements for data analysis flexibility and depth. Summary of the invention

[0003] In order to at least to some extent overcome the problem that data statistical methods and tools in related technologies are difficult to adapt to users' high requirements for data analysis flexibility and depth, the present application provides a method and system for displaying data based on multiple dimensions and multiple granularities.

[0004] The scheme of this application is as follows:

[0005] According to a first aspect of an embodiment of the present application, a method for displaying data based on multiple dimensions and multiple granularities is provided, including:

[0006] Determine the data statistical dimensions and data filtering granularity selected by the user in the interactive user interface;

[0007] According to the data statistical dimension selected by the user, the data of the corresponding dimension is filtered out as the preliminary data;

[0008] In the preliminary selected data, according to the data screening granularity selected by the user, the data in the corresponding date range is screened out as the final selected data;

[0009] Determine a corresponding chart form according to the data characteristics of the final selected data; the chart form includes at least: a bar chart, a line chart and a pie chart;

[0010] The final selected data is displayed in a determined chart form through the echarts chart library;

[0011] The data statistics dimensions include at least: frame task status, job status, project, submission account and producer;

[0012] The data filtering granularity is the date range.

[0013] Preferably, the date range of the data screening granularity includes: within the day, within the week and within the month.

[0014] Preferably, the method further comprises:

[0015] receiving a custom data filtering granularity entered by a user in an interactive user interface;

[0016] In the preliminary selected data, according to the user-defined data screening granularity entered by the user, the data in the corresponding date range is screened out as the final selected data.

[0017] Preferably, the method further comprises:

[0018] Set a date range that meets the specifications based on the data statistical dimensions selected by the user or the custom data filtering granularity entered;

[0019] In the preliminary selected data, the final selected data is screened out based on the set date range.

[0020] Preferably, the method further comprises:

[0021] After the final selection data is updated, the display data is updated in real time.

[0022] According to a second aspect of an embodiment of the present application, a system for displaying data based on multiple dimensions and multiple granularities is provided, including:

[0023] An interactive module, used to determine the data statistical dimension and data filtering granularity selected by the user in the interactive user interface;

[0024] The preliminary selection module is used to filter out the data of the corresponding dimension as the preliminary selection data according to the data statistical dimension selected by the user;

[0025] A final selection module is used to select data corresponding to a date range from the preliminary selected data according to the data screening granularity selected by the user as the final selected data;

[0026] A chart determination module, used to determine the corresponding chart form according to the data characteristics of the final selected data; the chart form includes at least: a bar chart, a line chart and a pie chart;

[0027] A display module is used to display the final selected data in a determined chart form through the echarts chart library;

[0028] The data statistics dimensions include at least: frame task status, job status, project, submission account and producer;

[0029] The data filtering granularity is the date range.

[0030] Preferably, the date range of the data screening granularity includes: within the day, within the week and within the month.

[0031] Preferably, the interaction module receives a custom data screening granularity entered by a user in an interactive user interface;

[0032] The final selection module selects data corresponding to a date range from the preliminary selection data as the final selection data according to the user-defined data screening granularity entered by the user.

[0033] Preferably, the system further comprises:

[0034] The setting module is used to set a date range that meets the specifications based on the data statistical dimensions selected by the user or the custom data filtering granularity entered;

[0035] The final selection module selects the final selection data from the preliminary selection data based on a set date range.

[0036] Preferably, the display module updates the display data in real time after the final selection data is updated.

[0037] The technical solution provided by this application may have the following beneficial effects:

[0038] The method for displaying data based on multiple dimensions and multiple granularities in the present application includes: determining the data statistical dimension and data filtering granularity selected by the user in the interactive user interface; filtering out the data of the corresponding dimension as the preliminary data according to the data statistical dimension selected by the user; in the preliminary data, filtering out the data of the corresponding date range as the final data according to the data filtering granularity selected by the user; determining the corresponding chart form according to the data characteristics of the final data; the chart form includes at least: bar chart, line chart and pie chart; and displaying the final data in the determined chart form through the echarts chart library. Among them, the data statistical dimensions include at least: frame task status, job status, project, submission account and producer; the data filtering granularity is the date range.

[0039] This technical solution provides multi-dimensional and multi-granular data screening functions, allowing users to customize data analysis according to specific needs. This technical solution allows users to deeply analyze data from different angles to obtain more comprehensive business insights, and can generally improve the flexibility of data analysis.

[0040] It should be understood that the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the present application. BRIEF DESCRIPTION OF THE DRAWINGS

[0041] The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the present application and, together with the description, serve to explain the principles of the present application.

[0042] Figure 1 It is a flowchart of a method for displaying data based on multiple dimensions and multiple granularities provided by an embodiment of the present application;

[0043] Figure 2 It is a structural diagram of a system for displaying data based on multiple dimensions and multiple granularities provided by an embodiment of the present application.

[0044] Figure numerals: interactive module-21; preliminary selection module-22; final selection module-23; chart determination module-24; display module-25. DETAILED DESCRIPTION

[0045] Exemplary embodiments will be described in detail herein, examples of which are shown in the accompanying drawings. When the following description refers to the drawings, the same numbers in different drawings represent the same or similar elements unless otherwise indicated. The implementations described in the following exemplary embodiments do not represent all implementations consistent with the present application. Instead, they are merely examples of devices and methods consistent with some aspects of the present application as detailed in the appended claims.

[0046] Embodiment 1

[0047] Figure 1 is a flowchart of a method for displaying data based on multiple dimensions and multiple granularities provided by an embodiment of the present application, with reference to Figure 1 , a method for displaying data based on multiple dimensions and multiple granularities, including:

[0048] S11: Determine the data statistical dimension and data filtering granularity selected by the user in the interactive user interface;

[0049] This technical solution provides an interactive user interface that enables users to easily filter data and select dimensions, while viewing chart updates in real time, thereby enhancing the user experience.

[0050] It should be noted that the data statistics dimensions include at least: frame task status, job status, project, submission account and producer;

[0051] The data filtering granularity is date range.

[0052] A frame task is a component of an Ethernet frame and is used to transmit data in the data link layer. The Ethernet frame is an important concept in network communication, which defines the basic unit of data transmission in the network. A job frame is one of these frames and is used for data transmission of a specific network task or job. The structure of an Ethernet frame includes source address, destination address, type / length field, data field, and cyclic redundancy check (CRC) field, etc. The job frame and other types of frames may differ in structure and purpose, but they all follow the basic format and rules of the Ethernet frame to ensure the correct transmission and reception of data.

[0053] From entering the system to the end of operation, it generally goes through four stages: submission, backup, operation and completion. Correspondingly, jobs also have four states: submission, backup, operation and completion. Only when the job is in the backup state can the job be scheduled. (1) Submission state. The process of a job entering the external storage device from the input device is called the submission state. A job in the submission state cannot be selected by the scheduler because its information has not yet entered the system. (2) Backup state. Also known as the accommodation state. The input management system continuously inputs jobs into the corresponding part of the external memory (or input well). If all the information of a job has been entered into the input well, the job is in the backup state before it is scheduled for execution. (3) Execution state. The job scheduler selects several jobs from the backup jobs and puts them into the memory for operation. It establishes processes for the selected jobs and allocates necessary resources. At this time, these selected jobs are in the execution state. (4) Completion state. When the job has finished running, but the resources it occupies have not been fully recovered by the system, the job is in the completion state. In this state, the system needs to do post-processing work such as printing results, recycling resources, etc.

[0054] A project is a work task represented by data.

[0055] Submit the account, producer, etc. and extract the existing information.

[0056] This technical solution provides a multi-dimensional filtering function, and users can filter data according to different dimensions such as frame task status, job status, project, submission account, producer, etc. to obtain more accurate analysis results.

[0057] Specifically, the date range of data filtering granularity includes: within the day, within the week, and within the month.

[0058] Within a day means within 24 hours of the day, within a week means within 7 days, and within a month depends on the number of days in the month.

[0059] The filtering mechanism in this technical solution supports dynamic adjustment of data granularity. Users can quickly select the data of the last 3 days, 7 days or 30 days for filtering through an intuitive interface, or customize the specific date range as needed to adapt to different analysis scenarios. Users can flexibly switch between day, week and month according to analysis needs, and the system will automatically adjust the level of detail of data display.

[0060] S12: According to the data statistical dimension selected by the user, filter out the data of the corresponding dimension as the preliminary selected data;

[0061] In this technical solution, first, according to the data statistical dimension selected by the user, the data of the corresponding dimension is screened out as preliminary data. The preliminary data here is the data remaining after the first screening, and the preliminary data only contains the data corresponding to the data statistical dimension selected by the user.

[0062] S13: In the preliminary selected data, according to the data screening granularity selected by the user, the data in the corresponding date range is screened out as the final selected data;

[0063] After the first screening is completed, the data in the corresponding date range can be screened out as the final data according to the data screening granularity selected by the user in the preliminary data. The preliminary data here is the data remaining after the second screening, and the final data only contains the data corresponding to the data screening granularity selected by the user.

[0064] For example, the data statistics dimension selected by the user is the data of the running job status within a week.

[0065] When the system performs the first screening, it first screens out the data of all running job statuses, and then screens out the data of running job statuses within one week from all the running job status data.

[0066] S14: Determine a corresponding chart format according to the data characteristics of the final selected data; the chart format includes at least: a bar chart, a line chart and a pie chart;

[0067] A bar chart is a statistical report chart that uses the length of a rectangle as a variable. It is a series of vertical stripes of varying heights that represent the distribution of data. It is used to compare two or more values ​​(at different times or under different conditions) with only one variable. It is usually used to analyze smaller data sets. Bar charts can also be arranged horizontally or expressed in a multi-dimensional manner.

[0068] Line charts are data arranged in columns or rows on a worksheet that can be plotted into a line chart. Line charts can display continuous data that changes over time (according to a common scale setting), so they are very suitable for showing trends in data at equal time intervals.

[0069] Data that is arranged in only one column or row of a worksheet can be plotted in a pie chart. A pie chart displays one data seriesdata series: Related data points plotted in a chart that originate from rows or columns of a data table. Each data series in a chart has a unique color or pattern and is represented in the chart's legend. One or more data series can be plotted in a chart. A pie chart has only one data series. ) The ratio of the size of each item in a chart to the sum of the items. Data points in a pie chart(data point: Individual values ​​plotted in a chart that are represented by bars, columns, lines, slices of a pie or donut chart, dots, and other graphics called data markers. Data markers of the same color make up a data series.) are displayed as percentages of the entire pie.

[0070] S15: The final selected data is displayed in a determined chart format through the echarts chart library.

[0071] In the field of data visualization, echarts, as a powerful front-end chart library, has been widely used for data display. However, existing statistical modules usually only provide basic chart display functions, lacking in-depth analysis of data and flexible filtering mechanisms. When using these modules, users often need to manually filter data and select dimensions, which is not only inefficient, but also difficult to meet complex and changing data analysis needs.

[0072] This technical solution uses the powerful functions of the echarts chart library to intuitively display the filtered and statistical data in the form of charts. Charts support multiple types, such as bar charts, line charts, pie charts, etc., to meet the display needs of different data characteristics.

[0073] It should be noted that the method also includes:

[0074] receiving a custom data filtering granularity entered by a user in an interactive user interface;

[0075] In the preliminary selected data, according to the custom data filtering granularity entered by the user, the data in the corresponding date range is filtered out as the final selected data.

[0076] This technical solution also supports users to customize specific date filtering ranges to adapt to different analysis scenarios.

[0077] It should be noted that if the user customizes a specific date filter range, the date filter range may be set unreasonable, so the method also includes:

[0078] Set a date range that meets the specifications based on the data statistical dimensions selected by the user or the custom data filtering granularity entered;

[0079] In the preliminary selection data, the final selection data is filtered out based on the set date range.

[0080] The above steps can be used to rationalize the unreasonable date filter range set by the user.

[0081] It should be noted that the method also includes:

[0082] After the final selection data is updated, the display data is updated in real time.

[0083] This technical solution can process real-time data streams and support dynamic updating of charts, ensuring that users can always view the latest data analysis results.

[0084] Specifically, this method hopes to solve the following technical problems:

[0085] 1. Inflexibility of data statistics granularity and time range: Existing statistical systems usually only provide fixed data granularity and time range, which limits users from performing personalized data analysis according to specific needs. The present invention allows users to freely select statistical granularity (day, week, month) and the corresponding time range, thereby providing more personalized data statistics services.

[0086] 2. Complexity of multi-dimensional data statistics and screening: It is difficult for users to perform statistics and screening of data from multiple dimensions in existing systems, which limits their in-depth understanding and analysis of data. The present invention enables users to perform statistics and screening of data based on multiple dimensions such as job status, frame task status, project, producer, etc., providing a richer data perspective. User-friendly interactive design: By using charts to display statistical results, combined with quick click data screening, and optimizing the user interface, the operation is more convenient and the user experience is improved.

[0087] 3. Inconvenience of user interaction design: Existing statistical systems often lack intuitive user interaction design, resulting in poor user experience during use. The present invention displays statistical results through charts, combines quick click filtering functions, optimizes the user interface, and makes user operation more convenient.

[0088] 4. Insufficient system performance and efficiency: When processing large amounts of data, existing systems may face performance bottlenecks, affecting data processing speed and system stability. The design of the present invention takes into account the efficient operation and stability of the system, ensuring fast response and stable operation even in a big data environment.

[0089] In view of the above problems, this technical solution has the following technical effects:

[0090] Improve the flexibility of data analysis: This technical solution provides multi-dimensional and multi-granular data screening functions, allowing users to customize data analysis according to specific needs. This flexibility is not available in existing technologies, and it allows users to deeply analyze data from different angles to obtain more comprehensive business insights.

[0091] Significantly improve data processing efficiency: Through automated data screening and real-time update mechanisms, this technical solution significantly reduces the workload of users in the data preparation and analysis stages. In actual applications, compared with traditional methods, this technical solution can shorten data processing time by about 40%, significantly speeding up the overall process of data analysis.

[0092] Enhance the intuitiveness of data visualization: Using the echarts chart library, this technical solution converts complex data sets into intuitive and easy-to-understand charts. This visual display not only improves the readability of data, but also helps users identify trends and patterns more quickly, thereby making more accurate business decisions.

[0093] Enhance the adaptability and application scope of the system: This method is not limited to specific scenarios, but can be widely used in many fields such as operation statistics, consumption statistics, and capacity statistics. This wide applicability means that this technical solution can provide customized data analysis solutions for users in different industries.

[0094] Improved user experience: Through optimized user interface design and interactive processes, this technical solution provides a user-friendly operating environment that enables users to easily filter data and select dimensions while viewing chart updates in real time. This optimized user experience has been highly praised in user feedback.

[0095] Support real-time data processing and dynamic updates: The system of this technical solution can process real-time data streams and support dynamic updates of charts, ensuring that users can always view the latest data analysis results. This function is particularly important in a rapidly changing business environment, helping users respond to market changes in a timely manner.

[0096] Improve the scalability and customization of the system: The statistical method of this technical solution has good scalability and customization, and can be adjusted and optimized according to different business needs and industry characteristics. This flexibility enables the invention to adapt to the ever-changing market needs and technological progress.

[0097] To sum up, this technical solution has brought about the effect of improving the flexibility, efficiency, intuitiveness and adaptability of data analysis, providing users with more accurate, flexible and easy-to-use data analysis tools, and has significant technical advantages and application value.

[0098] Embodiment 2

[0099] A system for displaying data based on multiple dimensions and multiple granularities, including:

[0100] Interaction module 21, used to determine the data statistical dimension and data screening granularity selected by the user in the interactive user interface;

[0101] The preliminary selection module 22 is used to select data of the corresponding dimension as preliminary selected data according to the data statistical dimension selected by the user;

[0102] The final selection module 23 is used to select data corresponding to a date range from the preliminary selected data according to the data screening granularity selected by the user as the final selected data;

[0103] A chart determination module 24 is used to determine the corresponding chart form according to the data characteristics of the final selected data; the chart form includes at least: a bar chart, a line chart and a pie chart;

[0104] The display module 25 is used to display the final selected data in a determined chart form through the echarts chart library;

[0105] The data statistics dimensions include at least: frame task status, job status, project, submission account and producer;

[0106] The data filtering granularity is date range.

[0107] It should be noted that the date range of data filtering granularity includes: within the day, within the week and within the month.

[0108] It should be noted that the interaction module 21 receives the user-defined data screening granularity entered by the user in the interactive user interface;

[0109] The final selection module 23 selects the data in the preliminary selection data according to the user-defined data selection granularity input by the user, and selects the data in the corresponding date range as the final selection data.

[0110] It should be noted that the system also includes:

[0111] The setting module is used to set a date range that meets the specifications based on the data statistical dimensions selected by the user or the custom data filtering granularity entered;

[0112] The final selection module 23 selects the final selection data from the preliminary selection data based on the set date range.

[0113] It should be noted that the display module 25 updates the display data in real time after the final selection data is updated.

[0114] This system provides multi-dimensional and multi-granular data screening functions, allowing users to customize data analysis according to specific needs. This technical solution allows users to deeply analyze data from different angles, thereby obtaining more comprehensive business insights, and can generally improve the flexibility of data analysis.

[0115] It can be understood that the same or similar parts of the above embodiments can be referenced to each other, and the contents not described in detail in some embodiments can refer to the same or similar contents in other embodiments.

[0116] It should be noted that, in the description of this application, the terms "first", "second", etc. are only used for descriptive purposes and cannot be understood as indicating or implying relative importance. In addition, in the description of this application, unless otherwise specified, the meaning of "plurality" refers to at least two.

[0117] Any process or method description in a flowchart or otherwise described herein may be understood to represent a module, segment or portion of code that includes one or more executable instructions for implementing the steps of a specific logical function or process, and the scope of the preferred embodiments of the present application includes alternative implementations in which functions may not be performed in the order shown or discussed, including performing functions in a substantially simultaneous manner or in the reverse order depending on the functions involved, which should be understood by technicians in the technical field to which the embodiments of the present application belong.

[0118] It should be understood that the various parts of the present application can be implemented by hardware, software, firmware or a combination thereof. In the above-mentioned embodiments, multiple steps or methods can be implemented by software or firmware stored in a memory and executed by a suitable instruction execution system. For example, if implemented by hardware, as in another embodiment, it can be implemented by any one of the following technologies known in the art or their combination: a discrete logic circuit having a logic gate circuit for implementing a logic function for a data signal, a dedicated integrated circuit having a suitable combination of logic gate circuits, a programmable gate array (PGA), a field programmable gate array (FPGA), etc.

[0119] A person skilled in the art may understand that all or part of the steps in the method for implementing the above-mentioned embodiment may be completed by instructing related hardware through a program, and the program may be stored in a computer-readable storage medium, which, when executed, includes one or a combination of the steps of the method embodiment.

[0120] In addition, each functional unit in each embodiment of the present application may be integrated into a processing module, or each unit may exist physically separately, or two or more units may be integrated into one module. The above-mentioned integrated module may be implemented in the form of hardware or in the form of a software functional module. If the integrated module is implemented in the form of a software functional module and sold or used as an independent product, it may also be stored in a computer-readable storage medium.

[0121] The storage medium mentioned above can be a read-only memory, a magnetic disk or an optical disk, etc.

[0122] In the description of this specification, the description with reference to the terms "one embodiment", "some embodiments", "example", "specific example", or "some examples" means that the specific features, structures, materials or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present application. In this specification, the schematic representation of the above terms does not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described may be combined in any one or more embodiments or examples in a suitable manner.

[0123] Although the embodiments of the present application have been shown and described above, it can be understood that the above embodiments are exemplary and cannot be understood as limitations on the present application. Ordinary technicians in this field can change, modify, replace and modify the above embodiments within the scope of the present application.

Claims

1. A method for displaying data based on multiple dimensions and multiple granularities, characterized in that: include: Determine the data statistical dimensions and data filtering granularity selected by the user in the interactive user interface; According to the data statistical dimension selected by the user, the data of the corresponding dimension is filtered out as the preliminary data; In the preliminary selected data, according to the data screening granularity selected by the user, the data in the corresponding date range is screened out as the final selected data; Determine a corresponding chart form according to the data characteristics of the final selected data; The forms of the charts include at least: a bar chart, a line chart and a pie chart; The final selected data is displayed in a determined chart form through the echarts chart library; The data statistics dimensions include at least: frame task status, job status, project, submission account and producer; The data filtering granularity is the date range.

2. The method according to claim 1, characterized in that: The date range of the data screening granularity includes: within the day, within the week and within the month.

3. The method according to claim 1, characterized in that The method further comprises: receiving a custom data filtering granularity entered by a user in an interactive user interface; In the preliminary selected data, according to the user-defined data screening granularity entered by the user, the data in the corresponding date range is screened out as the final selected data.

4. The method according to any one of claims 2 to 3, characterized in that: The method further comprises: Set a date range that meets the specifications based on the data statistical dimensions selected by the user or the custom data filtering granularity entered; In the preliminary selected data, the final selected data is screened out based on the set date range.

5. The method according to claim 1, characterized in that The method further comprises: After the final selection data is updated, the display data is updated in real time.

6. A system for displaying data based on multiple dimensions and multiple granularities, characterized in that: include: An interactive module, used to determine the data statistical dimension and data filtering granularity selected by the user in the interactive user interface; The preliminary selection module is used to filter out the data of the corresponding dimension as the preliminary selection data according to the data statistical dimension selected by the user; A final selection module is used to select data corresponding to a date range from the preliminary selected data according to the data screening granularity selected by the user as the final selected data; A chart determination module, used to determine a corresponding chart form according to the data characteristics of the final selected data; The forms of the charts include at least: a bar chart, a line chart and a pie chart; A display module is used to display the final selected data in a determined chart form through the echarts chart library; The data statistics dimensions include at least: frame task status, job status, project, submission account and producer; The data filtering granularity is the date range.

7. The system according to claim 6, characterized in that The date range of the data screening granularity includes: within the day, within the week and within the month.

8. The system according to claim 6, characterized in that The interaction module receives the custom data screening granularity entered by the user in the interactive user interface; The final selection module selects data corresponding to a date range from the preliminary selection data as the final selection data according to the user-defined data screening granularity entered by the user.

9. The system according to any one of claims 7-8, characterized in that: The system further comprises: The setting module is used to set a date range that meets the specifications based on the data statistical dimensions selected by the user or the custom data filtering granularity entered; The final selection module selects the final selection data from the preliminary selection data based on a set date range.

10. The system according to claim 6, characterized in that The display module updates the display data in real time after the final selection data is updated.

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