A streaming data computing method

Abstract

The present application provides a streaming data calculation method, which includes: according to an Excel format detailed data source with specific attribute information, storing the title name corresponding to the data source in a root node, and storing the specific indicator field under each title name in a corresponding child node; reading the title name stored in the root node to obtain multiple types of keywords in the title name; according to a formula selected by a user, calculating multiple attribute values ​​under the multiple types of keywords selected by the user to obtain calculation results between multiple indicator fields; traversing the multiple types of keywords corresponding to the root node, and traversing the indicator fields corresponding to multiple child nodes in turn to generate a directory list; editing the files in the multiple types of keywords and indicator fields, and storing the edited latest directory list structure in Excel; responding to a read instruction issued by the user, obtaining the selected value of the target list, and displaying it through a visual service terminal.

Description

Technical Field

[0001] The present invention relates to the field of computer technology, and in particular to a streaming data computing method. Background Art

[0002] Real-time streaming analysis has been widely used in the field of big data in recent years. The three characteristics of real-time streaming analysis include: infinite data, unbounded data processing, and low latency. Infinite data refers to a growing, basically infinite data set; unbounded data processing refers to a continuous data processing mode that can repeatedly process the above infinite data through the processing engine, which can break through the bottleneck of the limited data processing engine; low latency means that there is no clear definition of the amount of data, the value of data will decrease with the passage of time, and timeliness will be a problem that needs to be continuously solved.

[0003] Streaming data is mainly used in financial services, network monitoring, telecommunications data management, Web applications, manufacturing, sensor detection, etc. In the data stream model, since individual data are related tuples, such as data generated by network measurements, call records, web page visits, etc., these data are continuously delivered in the form of large, fast, and time-varying data streams. However, the current data stream model cannot meet the requirements of real-time computing of streaming data. At the same time, the persistent data stream model does not have the function of visually displaying the calculation results, and cannot perform targeted real-time analysis and traceability of the data stream. Summary of the invention

[0004] The object of the present invention is to provide a streaming data calculation method, which realizes real-time calculation and visual display of streaming data through a visual service terminal.

[0005] The present invention is implemented as follows: a streaming data calculation method, the method comprising: processing text data according to a data processing strategy corresponding to a processing strategy identifier selected by a user, obtaining an Excel format detailed data source with specific attribute information, the specific attribute information comprising: a title name and an indicator field;

[0006] The title name is stored in the root node, and the specific indicator field under each title name is stored in the corresponding child node;

[0007] In response to the selection instruction issued by the user, the title name stored in the root node is read to obtain multiple types of keywords in the title name; the multiple types of keywords include: time, attribute name, data value, and area;

[0008] According to the formula selected by the user, multiple attribute values ​​under the multiple types of keywords selected by the user are calculated to obtain calculation results between the multiple attribute values; wherein attribute value 1 is a combination of statistical path 1 and statistical path 2; attribute value 2 is a combination of attribute value 1 and statistical path 3; attribute value 3 is a combination of attribute value 1 and attribute value 2; statistical path 1 is time; statistical path 2 is composed of time and region; statistical path 3 is time, attribute name, data value, region;

[0009] Traversing multiple types of keywords corresponding to the root node, and traversing the index fields corresponding to multiple child nodes in turn, to generate a directory list, wherein the child nodes include: a left child node and a right child node;

[0010] For the directory list, the files in the multiple types of keywords and indicator fields are edited, and the edited latest directory list structure is stored in Excel format;

[0011] In response to a read instruction issued by a user, the selected value of the latest target list is obtained and displayed on the visual service terminal in the form of a tree structure.

[0012] In a preferred technical solution of the present invention, the text data is processed according to the data processing strategy corresponding to the processing strategy identifier selected by the user to obtain an Excel format detailed data source with specific attribute information, including:

[0013] In response to the processing strategy identifier of the ETL tool selected by the user, the data processing strategy corresponding to the processing strategy identifier is executed on the text data to obtain the Excel format detailed data source having the title name and the indicator field.

[0014] In a preferred technical solution of the present invention, the title name is stored in the root node, and the specific indicator field under each title name is stored in the corresponding child node, including:

[0015] The title names in the root node are stored in a group of storage units with consecutive addresses in the inner layer according to the hierarchical position;

[0016] The indicator fields corresponding to the child nodes are stored in sequence from left to right in the outer layer connected with the storage unit, and the child nodes include a left child node and a right child node.

[0017] In a preferred technical solution of the present invention, in response to a selection instruction issued by a user, the title name stored in the root node is read to obtain multiple types of keywords in the title name, including:

[0018] Randomly selecting at least one of the multiple keywords in the title name to generate a statistical path of the title name;

[0019] The selected keywords are internally associated with each other through addresses to obtain multiple attribute values ​​of the keywords.

[0020] In a preferred technical solution of the present invention, according to the formula selected by the user, multiple attribute values ​​under multiple types of keywords selected by the user are calculated to obtain calculation results between the multiple attribute values, including:

[0021] Establishing address associations between the multiple types of keywords and the attribute values, and after the associations, moving the addresses of the attribute values ​​according to the latest mouse positions issued by the user;

[0022] Selecting multiple attribute values ​​under the multiple types of keywords, and combining and associating addresses of the attribute values;

[0023] The attribute values ​​after multiple combinations are calculated according to the function calculation formula selected by the user to obtain the calculation result between the attribute values.

[0024] In a preferred technical solution of the present invention, traversing multiple types of keywords corresponding to the root node, and sequentially traversing the index fields corresponding to the multiple child nodes to generate a directory list includes:

[0025] According to the hierarchical tree structure, multiple types of keywords corresponding to the traversed root nodes are added to the message queue according to the hierarchy;

[0026] For each indicator field, traverse the child nodes corresponding to each indicator field one by one. If the child node is not empty, add the indicator field stored in the child node to the message queue to generate a directory list.

[0027] In a preferred technical solution of the present invention, for the directory list, the files in the multiple types of keyword and indicator fields are edited, and the edited latest directory list structure is stored in Excel format, including:

[0028] Establish a directory list according to the tree structure, and add multiple types of keywords and indicator fields stored in the target list;

[0029] The added root nodes corresponding to the multiple types of keywords and the new directory list of sub-nodes corresponding to the index fields are saved in a file in Excel format.

[0030] In a preferred technical solution of the present invention, in response to a read instruction issued by a user, the selected value of the latest directory list is obtained and displayed in a visual service terminal in the form of a tree structure, including:

[0031] For the tree structure directory list, the visualization service terminal pushes a visualization success message of the calculation result to the front-end access page;

[0032] In response to a read instruction issued by a user, the width and height selected values ​​of the latest target list are obtained and displayed on a visual service terminal with a tree structure.

[0033] In a preferred technical solution of the present invention, an electronic device includes: a processor, a storage medium and a bus, wherein the storage medium stores machine-readable instructions executable by the processor, and when the electronic device is running, the processor communicates with the storage medium through the bus, and the processor executes the machine-readable instructions to perform the steps of the streaming data computing method as described in any one of the claims.

[0034] In a preferred technical solution of the present invention, a computer-readable storage medium is provided, on which a computer program is stored, and when the computer program is executed by a processor, the steps of streaming data calculation as claimed in any one of the claims are executed.

[0035] The beneficial effects of the present invention are mainly as follows: the present application stores the title name corresponding to the data source in the root node according to the Excel format detailed data source with specific attribute information, and stores the specific indicator field under each title name in the corresponding child node; in response to the selection instruction issued by the user, reads the title name stored in the root node to obtain multiple types of keywords in the title name; calculates multiple attribute values ​​under the multiple types of keywords selected by the user according to the formula selected by the user to obtain the calculation results between multiple indicator fields; traverses the multiple types of keywords corresponding to the root node, and traverses the indicator fields corresponding to multiple child nodes in turn to generate a directory list, the child nodes include: left child nodes and right child nodes; for the directory list, edits the files in the multiple types of keywords and indicator fields, and stores the edited latest directory list structure in Excel format; in response to the read instruction issued by the user, obtains the selected value of the target list, and displays it in the form of a tree structure on the visual service terminal; specifically, reads the specific attribute information corresponding to the Excel format detailed data source, the attribute information can be financial services, network monitoring, telecommunications data management, Web The industry data of application and production manufacturing is imported into the visualization service terminal in Excel format according to the data flow report data of the industry. For the multiple types of keywords corresponding to specific attribute information and the attribute values ​​under the multiple types of keywords, the corresponding functions are called by formulas for calculation to obtain the calculation results between multiple attribute values, which are stored in Excel format and displayed in the form of page browsing in the Excel format directory list with a hierarchical tree structure. The visualization service terminal can instantly calculate streaming data, and the visualization service terminal has a clear hierarchy, is fast and intuitive. The visualization service terminal is a distributed cache Redis. In addition, the visualization service terminal can bring together valuable data of different types and can perform data calculation without predefined models. The computing architecture is scalable and can provide real-time analysis for different customers. It has a wide range of applications and is of use value.

[0036] In order to make the above-mentioned objects, features and advantages of the present application more obvious and easy to understand, preferred embodiments are specifically cited below and described in detail with reference to the attached drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0037] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings required for use in the embodiments are briefly introduced below. It should be understood that the following drawings only show certain embodiments of the present invention and therefore should not be regarded as limiting the scope. For ordinary technicians in this field, other related drawings can be obtained based on these drawings without creative work.

[0038] Figure 1A flow chart of a streaming data computing method provided by an embodiment of the present invention.

[0039] Figure 2 A schematic diagram of the statistical path of the title name in step S301 of a streaming data calculation method provided in one embodiment of the present application.

[0040] Figure 3 A schematic diagram of attribute values ​​in step S302 of a streaming data calculation method provided in one embodiment of the present application.

[0041] Figure 4 A schematic diagram of the structure of a streaming data computing device provided in one embodiment of the present application.

[0042] Figure 5 The present invention is a schematic diagram of the structure of an electronic device provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0043] In order to make the purpose, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. The components of the embodiments of the present invention described and shown in the drawings herein can be arranged and designed in various different configurations. Therefore, the following detailed description of the embodiments of the present invention provided in the drawings is not intended to limit the scope of the claimed invention, but merely represents selected embodiments of the present invention. Based on the embodiments in the present invention, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of the present invention.

[0044] The characteristics of streaming data at this stage are that data is continuously collected from various places, with many sources, complex formats, and huge data volumes. The value of streaming data decreases with the passage of time. Therefore, it is best to process the data as soon as possible after it is generated and respond to the calculation results in real time, rather than processing it regularly after the data is accumulated.

[0045] In the prior art, the computation based on external data stream is to first call the parsing interface to retrieve the algorithm expression from the algorithm library file, then complete the algorithm call through the algorithm expression, and finally calculate the value of the corresponding data stream, which has low computational efficiency.

[0046] In recent years, as streaming data has been widely used, the persistent data stream model cannot meet the data stream calculation of large amounts of data. Individual data stream units are related tuples, such as data generated by network measurements, call records, web page visits, etc. These data are continuously arriving in the form of large, fast, and time-varying data streams. At this stage, the data stream model cannot meet the requirements of real-time calculation of streaming data. At the same time, the persistent data stream model does not have the function of visually displaying the calculation results, and cannot perform targeted real-time analysis and traceability of the data stream.

[0047] Some embodiments of the present invention are described in detail below in conjunction with the accompanying drawings. In the absence of conflict, the following embodiments and features in the embodiments can be combined with each other.

[0048] In one possible implementation, Figure 1 Schematic diagram of the flow chart of the streaming data computing method provided by the embodiment of the present invention; Figure 1 As shown, the data calculation in the method specifically includes the following steps:

[0049] Step S10, processing the text data according to the data processing strategy corresponding to the processing strategy identifier selected by the user, and obtaining an Excel format detailed data source with specific attribute information, wherein the specific attribute information includes: title name and indicator field.

[0050] Step S20, storing the title name in the root node, and storing the specific indicator field under each title name in the corresponding child node.

[0051] Step S30, in response to the selection instruction issued by the user, the title name stored in the root node is read to obtain multiple types of keywords in the title name.

[0052] Step S40, according to the formula selected by the user, multiple attribute values ​​under the multiple types of keywords selected by the user are calculated to obtain calculation results between multiple indicator fields.

[0053] Step S50, traverse multiple types of keywords corresponding to the root node, and traverse the index fields corresponding to multiple child nodes in sequence to generate a directory list, where the child nodes include: a left child node and a right child node.

[0054] Step S60, for the directory list, edit the files in the multiple types of keywords and index fields, and store the edited latest directory list structure in Excel format.

[0055] Step S70, responding to the read instruction issued by the user, obtaining the selected value of the target list, and displaying it in the form of a tree structure on the visual service terminal.

[0056] During the specific implementation of step S10, the ETL (Extract-Transform-Load) data warehouse technology is used. The user selects the processing strategy identifier in the ETL tool, generates a data processing strategy for processing text data, and obtains a detailed data source in Excel format with a title name and indicator fields; the processing strategy identifier includes: input and output, data cleaning, sorting, deduplication, association merging, and grouping statistics.

[0057] During the specific implementation of step S20, a configuration file is established, and a storage unit corresponding to the title name of the Excel format detailed data source is created through the configuration file. The title name is stored in the corresponding root node, and the indicator field is stored in the corresponding child node. The text data in the title name and the indicator field are entered in Excel format specifications.

[0058] When step S30 is implemented, the title name stored in the root node is read according to the configuration file logic to obtain multiple types of keywords in the title name, including: time, attribute name, data value, and area, and the multiple types of keywords are used as new data sources.

[0059] In the specific implementation of step S40, a formula editor is used, and the user selects a calculation formula. Multiple attribute values ​​corresponding to the multiple types of keywords selected by the user are calculated according to the calculation formula selected by the user to obtain the calculation result of the attribute value.

[0060] When step S50 is implemented, the depth, height and width of the root node corresponding to various keywords are traversed, the coordinate value of the current root node is calculated, and the indicator fields corresponding to multiple child nodes are traversed in sequence. Multiple child nodes are nodes of the same layer and are stored in order from left to right to generate a target list.

[0061] For example: if the current child node and the previous child node belong to the same layer node and belong to the same parent node, then calculate the coordinate value of the current node; if the current child node and the previous child node belong to the same layer node, but do not belong to the same parent node as the previous child node, then calculate the parent node coordinate values ​​of the current child node and the previous child node respectively, and save them in the center position of the parent node; if the current child node and the previous child node do not belong to the same layer node, then calculate the coordinate value of the current child node and store it in the center position of the previous parent node.

[0062] In the specific implementation of step S60, multiple types of keywords and indicator sub-segments stored in the directory list are selected according to the tree structure, and the multiple types of keywords and indicator sub-segments are added, modified, and edited to obtain a new directory list, which is stored in Excel format.

[0063] During the specific implementation of step S70, after receiving the reading instruction from the user, the visualization service terminal obtains the width and height of the latest target list and displays it through the visualization service terminal.

[0064] In a feasible implementation scheme, in the above step S10, the text data is processed according to the data processing strategy corresponding to the processing strategy identifier selected by the user to obtain an Excel format detailed data source with specific attribute information, including:

[0065] Step 101, in response to the processing strategy identifier of the ETL tool selected by the user, execute the data processing strategy corresponding to the processing strategy identifier on the text data to obtain a detailed data source in Excel format with a title name and indicator fields.

[0066] During the specific implementation of step 101, the user uses the ETL tool to select input, sorting, deduplication, grouping statistics, association merging, and output under the processing strategy identifier in sequence. The ETL tool automatically performs data processing strategies on the acquired source data, and after processing, a detailed data source in Excel format with a specific title name and indicator fields is obtained.

[0067] In a feasible implementation scheme, in the above step S20, the title name is stored in the root node, and the specific indicator field under each title name is stored in the corresponding child node, including:

[0068] Step 201, storing the title names in the root node in a group of storage units with consecutive addresses in the inner layer according to the hierarchical position.

[0069] Step 202, the indicator fields corresponding to the child nodes are stored in sequence from left to right in the outer layer connected by storage units, and the child nodes include a left child node and a right child node.

[0070] During the specific implementation of step 201, according to the organizational framework of the tree structure, the root nodes are stored in storage units with consecutive addresses in a chain storage or sequential storage manner.

[0071] When step 202 is specifically implemented, according to the organizational structure of the tree structure, the left child node and the right child node in the child node are stored in the outer layer of the storage unit in sequence from left to right through chain storage or sequential storage.

[0072] For example: Chain storage method: the root node consists of a data area and two addresses, the title name corresponding to the root node is stored in the data area, and the two addresses are used to store the left child node and the right child node respectively; Sequential storage method: the title name corresponding to the root node is stored in the storage unit in the form of an array, where the root node is stored in the first position, the left child node is stored in the second position, and the right child node is stored in the third position.

[0073] In one possible implementation, Figure 2 A schematic diagram of the statistical path of the title name of the streaming data calculation method provided in an embodiment of the present invention.

[0074] In a feasible implementation scheme, in the above step S30, in response to the selection instruction issued by the user, the title name stored in the root node is read to obtain multiple types of keywords in the title name, including:

[0075] Step S301, randomly select at least one of the multiple-category keywords in the title name to generate a statistical path of the title name, the multiple-category keywords include: time, attribute name, data value, and area.

[0076] Step S302: internally associate the selected keywords with each other through addresses to obtain multiple attribute values ​​of the keywords.

[0077] During the specific implementation of step S301, according to the selection instruction issued by the user, the corresponding multiple types of keywords in the storage unit are read, and according to at least one of the randomly selected time, attribute name, data value, and area, a statistical path of the title name is generated through the corresponding address of the randomly selected time, attribute name, data value, and area.

[0078] like Figure 2 As shown, the statistical paths for randomly reading title names include:

[0079] The statistical path 1 may be time.

[0080] Statistical path 2 may be composed of time and area.

[0081] Statistical path 3 can be time, attribute name, data value, or region.

[0082] In one possible implementation, Figure 3 A schematic diagram of attribute values ​​of the streaming data calculation method provided in an embodiment of the present invention.

[0083] When step S302 is specifically implemented, according to the statistical path, the indicator fields under the title name are randomly combined by associating the indicator fields with the addresses, and a plurality of attribute values ​​are obtained after the combination.

[0084] like Figure 3 As shown, according to the random combination of statistical path 1, statistical path 2, or statistical path 3, multiple attribute values ​​of multiple types of keywords are obtained, including:

[0085] The attribute value 1 may be a combination of the statistical path 1 and the statistical path 2.

[0086] Attribute value 2 may be a combination of attribute value 1 and statistical path 3.

[0087] Attribute value 3 can be a combination of attribute value 2 and attribute value 1.

[0088] In a feasible implementation scheme, in the above step S40, multiple attribute values ​​under multiple types of keywords selected by the user are calculated according to the formula selected by the user to obtain the calculation results between the multiple attribute values, including:

[0089] Step 401, establish address associations between multiple types of keywords and attribute values, and after association, move the address of the attribute value according to the latest mouse position issued by the user.

[0090] Step 402: Select multiple attribute values ​​under multiple types of keywords, and combine and associate the addresses of the attribute values.

[0091] Step 403, calculating the multiple combined attribute values ​​according to the function calculation formula selected by the user to obtain the calculation results between the indicator fields.

[0092] During the specific implementation of step 401, the formula editor associates the data areas of multiple types of keywords and attribute values ​​through addresses, captures the position of the mouse according to the user's selection instruction, moves the address of the data area corresponding to the attribute value, and executes the drag instruction issued by the user.

[0093] During the specific implementation of step 402, the formula editor selects attribute values ​​from multiple types of keywords and randomly combines and associates multiple attribute values ​​through addresses.

[0094] In the specific implementation of step 403, the combined multiple attribute values ​​are calculated according to the calculation formula selected by the user by using the built-in operator of the formula editor to call the corresponding function to obtain the calculation results between the multiple attribute values ​​and store them in Excel format.

[0095] In a feasible implementation scheme, in the above step S50, multiple types of keywords corresponding to the root node are traversed, and the index fields corresponding to multiple child nodes are traversed in sequence to generate a directory list, including:

[0096] Step 501, adding multiple types of keywords corresponding to the traversed root node to the message queue according to the level.

[0097] Step 502, for each indicator field, traverse the child nodes corresponding to each indicator field one by one, if the child node is not empty, add the indicator field stored in the child node to the message queue, and generate a directory list.

[0098] In the specific implementation of step 501, a linked list is created using a canvas, row data of multiple types of keywords are read, and the data are added to a message queue according to the level, and displayed in a tree structure.

[0099] When step 502 is implemented, for each attribute value, the files stored in the child node corresponding to each attribute value are traversed one by one. If the child node is not empty, the files stored in the child node are added to the message queue to generate a directory list.

[0100] For example: traverse the child nodes corresponding to each attribute value, if the current child node and the previous child node belong to the same layer node and belong to the same parent node, calculate the coordinate value of the current node; if the current child node and the previous child node belong to the same layer node, but do not belong to the same parent node as the previous child node, calculate the parent node coordinate values ​​of the current child node and the previous child node respectively, and save them in the center position of the parent node; if the current child node and the previous child node do not belong to the same layer node, calculate the coordinate value of the current child node and store it in the center position of the previous parent node.

[0101] In a feasible implementation scheme, in the above step S60, for the directory list, files in multiple types of keywords and index fields are edited, and the edited latest directory list structure is stored in Excel format, including:

[0102] Step 601, establish a directory list according to the tree structure, and perform an addition operation on multiple types of keywords and indicator fields stored in the target list.

[0103] Step 602, the root nodes corresponding to the added multiple types of keywords and the child nodes corresponding to the index fields are stored in Excel format.

[0104] In the specific implementation of step 601, a root node and a child node association relationship in a directory list is established according to a tree structure, and an addition operation is performed on files of multiple types of keywords and index fields stored in the target category.

[0105] During the specific implementation of step 602, the various types of keywords and index fields added to the directory list are reversely written into the Excel format through the search box.

[0106] In a feasible implementation scheme, in the above step S70, in response to the read instruction issued by the user, the selected value of the latest directory list is obtained and displayed in the form of a tree structure on the visual service terminal, including:

[0107] Step 701: For the tree structure directory list, the visualization service terminal pushes a visualization success message of the calculation result to the front-end access page.

[0108] Step 702, in response to the read instruction issued by the user, obtain the width value and height value of the latest target list, and display them on the visual service terminal.

[0109] During the specific implementation of step 701, after the root node and child nodes corresponding to the directory list are calculated and updated according to the tree structure export function, the visualization service terminal pushes a success notification message.

[0110] When step 702 is implemented, in response to the user's read instruction, the width value and height value corresponding to the directory list are converted into a graphic using the canvas function. The graphic is displayed through the visualization service terminal. The graphic is used to display the text of various types of keywords and indicator fields stored in the directory list.

[0111] Figure 4 A schematic diagram of a streaming data computing device provided in one embodiment of the present application, the device comprising:

[0112] The data source module 801 is used to process the text data according to the data processing strategy corresponding to the processing strategy identifier selected by the user, and obtain an Excel format detailed data source with specific attribute information, wherein the specific attribute information includes: title name and indicator field;

[0113] The storage module 802 is used to store the title name in the root node, and store the specific indicator field under each title name in the corresponding child node;

[0114] The reading module 803 is used to respond to the selection instruction issued by the user, read the title name stored in the root node, and obtain multiple types of keywords in the title name;

[0115] The calculation module 804 is used to calculate the multiple attribute values ​​under the multiple types of keywords selected by the user according to the formula selected by the user to obtain the calculation results between the multiple attribute values;

[0116] The list module 805 is used to establish a directory list module, traverse the multiple types of keywords corresponding to the root node, and traverse the index fields corresponding to multiple child nodes in turn to generate a directory list. The child nodes include: a left child node and a right child node;

[0117] The editing module 806 is used to edit the files in the multiple types of keywords and index fields for the directory list, and store the edited latest directory list structure in Excel format;

[0118] The display module 807 is used to respond to the reading instruction issued by the user, obtain the selected value of the latest target list, and display it in the form of a tree structure on the visual service terminal.

[0119] In a feasible implementation, the data source module 801 includes:

[0120] The reading unit is used to respond to the processing strategy identifier of the ETL tool selected by the user, execute the data processing strategy corresponding to the processing strategy identifier on the text data, and obtain an Excel format detailed data source with a title name and indicator fields.

[0121] In a feasible implementation, the storage module 802 includes:

[0122] The root node storage unit is used to store the title name in the root node in a group of storage units with consecutive addresses according to the hierarchical position;

[0123] The child node storage unit is used to store the indicator fields corresponding to the child nodes in order from left to right in the outer layer connected by the storage unit. The child nodes include left child nodes and right child nodes.

[0124] In a feasible implementation, the reading module 803 includes:

[0125] A title name unit is read to randomly select at least one of multiple keywords in the title name, wherein the multiple keywords include: time, attribute name, data value, and area;

[0126] The attribute value unit is used to establish internal associations between the selected multiple types of keywords through addresses to obtain multiple attribute values ​​of the multiple types of keywords.

[0127] In a feasible implementation, the calculation module 804 includes:

[0128] The attribute value address association unit is used to establish the address association between multiple types of keywords and attribute values, and after association, move the address of the attribute value according to the latest mouse position issued by the user;

[0129] An attribute value merging unit is used to select multiple attribute values ​​under multiple types of keywords and combine and associate the addresses of the attribute values;

[0130] The attribute value calculation unit is used to calculate multiple combined attribute values ​​according to the function calculation formula selected by the user to obtain the calculation result between the attribute values.

[0131] In a feasible implementation, the list module 805 includes:

[0132] Add a queue unit to add multiple types of keywords corresponding to the root node to the message queue according to the hierarchical tree structure;

[0133] Generate a directory list unit, which is used to traverse the child nodes corresponding to each indicator field one by one for each indicator field. If the child node is not empty, the indicator field stored in the child node is added to the message queue to generate a directory list.

[0134] In a feasible implementation, the editing module 806 includes:

[0135] Adding a directory list unit, which is used to establish a directory list according to a tree structure, and to add multiple types of keywords and indicator fields stored in the target list;

[0136] The new directory list unit is used to store the new directory list of the root nodes corresponding to the added multiple types of keywords and the child nodes corresponding to the indicator fields in a file in Excel format.

[0137] In a feasible implementation, the display module 807 includes:

[0138] A visualization message unit is used for the visualization service terminal to push a visualization success message of the calculation result to the front-end access page for the tree structure directory list;

[0139] The visualization unit is used to respond to the reading instruction issued by the user, obtain the width and height selected values ​​of the latest target list, and display them on the visualization service terminal.

[0140] Figure 5 A schematic diagram of the structure of an electronic device 90 provided in an embodiment of the present application includes: a processor 901, a storage medium 902 and a bus 903, wherein the storage medium 902 stores machine-readable instructions executable by the processor 901. When the electronic device runs the above-mentioned information processing method, the processor 901 communicates with the storage medium 902 through the bus 903, and the processor 901 executes the machine-readable instructions to perform the following steps:

[0141] According to the data processing strategy corresponding to the processing strategy identifier selected by the user, the text data is processed to obtain an Excel format detailed data source with specific attribute information, the specific attribute information including: title name and indicator field;

[0142] Store the title name in the root node, and store the specific indicator fields under each title name in the corresponding child node;

[0143] In response to the selection instruction issued by the user, the title name stored in the root node is read to obtain multiple types of keywords in the title name;

[0144] According to the formula selected by the user, multiple attribute values ​​under the multiple types of keywords selected by the user are calculated to obtain the calculation results between the multiple attribute values;

[0145] Traverse multiple types of keywords corresponding to the root node, and traverse the index fields corresponding to multiple child nodes in turn to generate a directory list. The child nodes include: left child nodes and right child nodes;

[0146] For the directory list, edit the files in various keyword and indicator fields, and store the edited latest directory list structure in Excel format;

[0147] In response to the read instruction issued by the user, the selected value of the latest target list is obtained and displayed in the form of a tree structure on the visual service terminal.

[0148] In an embodiment of the present application, the storage medium 902 can also execute other machine-readable instructions to execute other methods described in the present application. For the specific execution method steps and principles, please refer to the above description and will not be repeated here.

[0149] The embodiment of the present application further provides a computer-readable storage medium, on which a computer program is stored, and the computer program is executed by a processor to perform the following steps:

[0150] According to the data processing strategy corresponding to the processing strategy identifier selected by the user, the text data is processed to obtain an Excel format detailed data source with specific attribute information, the specific attribute information including: title name and indicator field;

[0151] Store the title name in the root node, and store the specific indicator fields under each title name in the corresponding child node;

[0152] In response to the selection instruction issued by the user, the title name stored in the root node is read to obtain multiple types of keywords in the title name;

[0153] According to the formula selected by the user, multiple attribute values ​​under the multiple types of keywords selected by the user are calculated to obtain the calculation results between the multiple attribute values;

[0154] Traverse multiple types of keywords corresponding to the root node, and traverse the index fields corresponding to multiple child nodes in turn to generate a directory list. The child nodes include: left child nodes and right child nodes;

[0155] For the directory list, edit the files in various keyword and indicator fields, and store the edited latest directory list structure in Excel format;

[0156] In response to the read instruction issued by the user, the selected value of the latest target list is obtained and displayed in the form of a tree structure on the visual service terminal.

[0157] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. For those skilled in the art, the present invention may have various modifications and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention shall be included in the protection scope of the present invention.

Claims

1. A streaming data computing method, characterized in that: The method comprises: Processing the text data according to the data processing strategy corresponding to the processing strategy identifier selected by the user to obtain an Excel format detailed data source with specific attribute information, wherein the specific attribute information includes: a title name and an indicator field; The title name is stored in the root node, and the specific indicator field under each title name is stored in the corresponding child node; In response to the selection instruction issued by the user, the title name stored in the root node is read to obtain multiple types of keywords in the title name; the multiple types of keywords include: time, attribute name, data value, and area; According to the formula selected by the user, multiple attribute values ​​under the multiple types of keywords selected by the user are calculated to obtain calculation results between the multiple attribute values; wherein attribute value 1 is a combination of statistical path 1 and statistical path 2; attribute value 2 is a combination of attribute value 1 and statistical path 3; attribute value 3 is a combination of attribute value 1 and attribute value 2; statistical path 1 is time; statistical path 2 is composed of time and region; statistical path 3 is time, attribute name, data value, region; Traversing multiple types of keywords corresponding to the root node, and traversing the index fields corresponding to multiple child nodes in turn, to generate a directory list, wherein the child nodes include: a left child node and a right child node; For the directory list, the plurality of types of keywords and indicator fields are edited, and the edited latest directory list structure is stored in Excel format; In response to a read instruction issued by a user, the selected value of the latest directory list is obtained and displayed on the visual service terminal in the form of a tree structure.

2. The streaming data computing method according to claim 1, characterized in that: According to the data processing strategy corresponding to the processing strategy identifier selected by the user, the text data is processed to obtain an Excel format detailed data source with specific attribute information, including: In response to the processing strategy identifier of the ETL tool selected by the user, the data processing strategy corresponding to the processing strategy identifier is executed on the text data to obtain the Excel format detailed data source having the title name and the indicator field.

3. The streaming data computing method according to claim 1, characterized in that: In response to the selection instruction issued by the user, the title name stored in the root node is read to obtain multiple types of keywords in the title name, including: Randomly selecting at least one of the multiple keywords in the title name to generate a statistical path of the title name; The selected keywords are internally associated with each other through addresses to obtain multiple attribute values ​​of the keywords.

4. The streaming data computing method according to claim 1, characterized in that: According to the formula selected by the user, multiple attribute values ​​under the multiple types of keywords selected by the user are calculated to obtain calculation results between the multiple attribute values, including: Establishing address associations between the multiple types of keywords and the attribute values, and after the associations, moving the addresses of the attribute values ​​according to the latest mouse positions issued by the user; Selecting multiple attribute values ​​under the multiple types of keywords, and combining and associating addresses of the attribute values; According to the function calculation formula selected by the user, the attribute values ​​after multiple combinations are calculated to obtain the calculation results between the attribute values.

5. The streaming data computing method according to claim 1, characterized in that: Traversing multiple types of keywords corresponding to the root node, and sequentially traversing the index fields corresponding to multiple child nodes to generate a directory list, including: According to the hierarchical tree structure, multiple types of keywords corresponding to the root node are added to the message queue according to the hierarchy; For each indicator field, traverse the child nodes corresponding to each indicator field one by one. If the child node is not empty, add the indicator field stored in the child node to the message queue to generate a directory list.

6. The streaming data computing method according to claim 1, characterized in that: For the directory list, the multiple types of keywords and indicator fields are edited, and the edited latest directory list structure is stored in Excel format, including: Establish a directory list according to the tree structure, and add multiple types of keywords and indicator fields stored in the target list; A new directory list of the added root nodes corresponding to the multiple types of keywords and the child nodes corresponding to the index fields is saved in a file in Excel format.

7. The streaming data computing method according to claim 1, characterized in that: Respond to the read command issued by the user, obtain the selected value of the latest directory list, and display it in the form of a tree structure on the visual service terminal, including: For the tree structure directory list, the visualization service terminal pushes a visualization success message of the calculation result to the front-end access page; In response to a read instruction issued by a user, the selected values ​​of the width and height of the latest directory list are obtained and displayed on a visual service terminal with a tree structure.

8. An electronic device, characterized in that: include: A processor, a storage medium and a bus, wherein the storage medium stores machine-readable instructions executable by the processor, and when the electronic device is running, the processor and the storage medium communicate via the bus, and the processor executes the machine-readable instructions to perform the steps of the streaming data computing method as described in any one of claims 1 to 7.

9. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the steps of the streaming data computing method according to any one of claims 1 to 7 are executed.

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