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Dragging type visualization method and system based on big data

A drag-and-drop, big data technology, applied in the field of big data, can solve problems such as unfavorable data analysis, complex operation, difficult analysis, etc., and achieve the effect of simplifying the production process, simplifying the building procedure, and shortening the development time

Pending Publication Date: 2021-08-20
STATE GRID SHANDONG ELECTRIC POWER +1
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

Massive data is mature based on big data technology, but the display method still relies on front-end HTML writing and JS development. The operation is relatively complicated, which is not conducive to data analysis, and it is difficult to analyze, summarize and summarize its deep laws. Massive and diverse Information assets make big data require new processing modes and display modes in order to provide effective information for information users and increase the accuracy of decision-making

Method used

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  • Dragging type visualization method and system based on big data
  • Dragging type visualization method and system based on big data

Examples

Experimental program
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Effect test

Embodiment 1

[0028] In one or more implementations, a drag-and-drop visualization method based on big data is disclosed, refer to figure 1 , including the following steps:

[0029] (1) Based on Flink technology, real-time access to the bottom table data of enterprise functions, including structured data from relational databases (rows and columns), semi-structured data (CSV, logs, XML, JSON), etc., to establish a model library in the data center ;

[0030] Flink can implement batch processing and stream processing at the same time (Flink regards batch processing (that is, processing limited static data) as a special stream processing. It is a distributed system that can accept data stream programs and run them on one or more Execute in a fault-tolerant manner on a single machine, automatically ensure that the calculation can continue in the event of a machine failure or other error, or plan to execute it again after fixing a bug or performing a version upgrade. Flink essentially uses faul...

Embodiment 2

[0048] In one or more implementations, a drag-and-drop visualization system based on big data is disclosed, refer to figure 2 ,include:

[0049] The model library module is used to obtain the data of the bottom table of enterprise functions and build a model library in the data center;

[0050] The page frame building module is used to divide the data into two types of dimensions and measures based on the data in the data center, and build the basis for the binding of charts and data; select the page layout method to realize the page frame building; select the data that needs to be analyzed The data is dragged into the corresponding row and column in the page frame according to the quantity and measurement dimension, and the chart can be automatically generated according to the data;

[0051] Based on the data in the data center, intelligently bind charts and data, and generate graphics suitable for current business data according to data conditions. The system gives layout...

Embodiment 3

[0056] In one or more embodiments, a terminal device is disclosed, including a server, the server includes a memory, a processor, and a computer program stored on the memory and operable on the processor, and the processor executes the The program realizes the drag-and-drop visualization method based on big data in the first embodiment. For the sake of brevity, details are not repeated here.

[0057] It should be understood that in this embodiment, the processor can be a central processing unit CPU, and the processor can also be other general-purpose processors, digital signal processors DSP, application specific integrated circuits ASIC, off-the-shelf programmable gate array FPGA or other programmable logic devices , discrete gate or transistor logic devices, discrete hardware components, etc. A general-purpose processor may be a microprocessor, or the processor may be any conventional processor, or the like.

[0058] The memory may include read-only memory and random acces...

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Abstract

The invention discloses a dragging type visualization method and system based on big data, and the method comprises the steps of obtaining enterprise function bottom table data, and building a model library in the data; dividing data into two types of dimensions and measurement based on data of a data-in-data table, and constructing a basis for binding of a chart and the data; selecting a page layout mode, and realizing page frame building; dragging selected data needing to be analyzed into rows and columns at corresponding positions in the page frame according to the quantity and the measurement dimension, and automatically generating a chart according to the data; and returning corresponding data according to an input query condition on the basis of a corresponding relationship among the query component, the prefabricated icon and the function bottom table data in the model library, and updating the chart according to the data. According to the invention, page building, chart making and table generation are completed through conventional operations such as dragging and the like. The page chart making efficiency can be improved, the making process is simplified, and the webpage development time is shortened.

Description

technical field [0001] The present invention relates to the technical field of big data, in particular to a drag-and-drop visualization method and system based on big data. Background technique [0002] The statements in this section merely provide background information related to the present invention and do not necessarily constitute prior art. [0003] With the improvement of computer storage capacity and the development of complex algorithms, big data technology has become a hot spot in the development of new technologies and is widely used in various fields. Massive data is mature based on big data technology, but the display method still relies on front-end HTML writing and JS development. The operation is relatively complicated, which is not conducive to data analysis, and it is difficult to analyze, summarize and summarize its deep laws. Massive and diverse Information assets make big data require new processing modes and display modes in order to provide effective...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06F16/26G06F8/38G06F16/80
CPCG06F16/26G06F8/38G06F16/80
Inventor 汪耀海王德东滕杰陈峰张正利李涛郑慧林徐新源李海波赫明哲
Owner STATE GRID SHANDONG ELECTRIC POWER
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