WO2019080412A1

WO2019080412A1 - Data service method, electronic device and storage medium

Info

Publication number: WO2019080412A1
Application number: PCT/CN2018/076165
Authority: WO
Inventors: 韦邕; 常河; 徐亮; 肖京
Original assignee: 平安科技（深圳）有限公司
Priority date: 2017-10-27
Filing date: 2018-02-10
Publication date: 2019-05-02
Also published as: CN107729523A

Abstract

A data service method, comprising: an acquisition step: acquiring a data service request (S10); a configuration step: parsing the data service request, configuring an algorithm chain according to a parsing result (S20); an execution step: executing the configured algorithm chain, acquiring target data from original data in a database (S30); and an output step: outputting the target data (S40). The data service method can enable the provided data service to have good scalability, reliability, timeliness, and operability and maintainability.

Description

Data service method, electronic device and storage medium

This application claims the priority of the Chinese Patent Application filed on October 27, 2017, the Chinese Patent Application No. 201711025277.X, entitled "Data Service Method, Electronic Device and Storage Medium", the entire contents of which are incorporated by reference. In the application.

Technical field

The present application relates to the field of computer technologies, and in particular, to a data service method, an electronic device, and a storage medium.

Background technique

With the development of Internet technology, the amount of information owned by human beings has exploded. In order to enable people to quickly obtain the required data in massive data, various data service engines have appeared on the market, and these data service engines can provide corresponding data services according to people's input. For example, keyword search, query knowledge encyclopedia, find related words, and so on.

However, the current data service engine usually provides a single data service function. When it needs to expand multiple data service functions, the scalability is poor, and the reliability, timeliness, and serviceability of the data service are insufficient.

Summary of the invention

In view of the above reasons, it is necessary to provide a data service method, which can provide the data service with good scalability, reliability and serviceability, and the processing efficiency can be improved.

To achieve the above objective, the present application provides a data method, the method comprising: obtaining a step of: obtaining a data service request; and configuring a step of: parsing the data service request, configuring an algorithm chain according to the parsing result; and performing the step of: executing the configured algorithm Chain, obtaining target data from raw data in the database; output step: outputting the target data.

Preferably, the configuring step includes: parsing the data service request, determining respective computing requirements corresponding to the data service request; determining an operator and operator combination rule corresponding to each computing requirement; and obtaining the determined An operator; the algorithm chain is configured according to the obtained operator and the operator combination rule.

Preferably, the algorithm chain is composed of operators corresponding to respective computing requirements.

Optionally, each computing requirement corresponds to one or more identical operators, the one or more identical operators are executed in parallel in the algorithm chain, and the execution results are output in a preset priority order.

Optionally, the storage format of the original data in the database includes: a simple type: the primary key has only one related content and a weight; the unordered list: the primary key has a plurality of related content, and the related content is unordered ; There is an ordered list: the primary key has a number of related content, the multiple related content is previously ordered.

Optionally, the outputting step comprises: formatting and outputting the target data.

To achieve the above objective, the present application further provides an electronic device including a memory and a processor, wherein the memory includes a data service program, and when the data service program is executed by the processor, the following steps are performed: the obtaining step: Obtaining a data service request; configuring step: parsing the data service request, configuring an algorithm chain according to the parsing result; performing steps: executing the configured algorithm chain, acquiring target data from original data in the database; and outputting step: outputting the target data.

In addition, in order to achieve the above object, the present application further provides a computer readable storage medium including a data service program, when the data service program is executed by a processor, implementing the data service method as described above Any step.

The data service method, the electronic device and the computer readable storage medium provided by the present application can respond to the online data service request in a pipeline manner by an operator in the algorithm chain after receiving the data service request, and in the algorithm chain The data format of the input and output of the operator is encapsulated, so that the data format is kept uniform, so that the operators are loosely coupled, and the data between the operators is closely combined, so the data service provided is well scalable. Sex, reliability, timeliness and serviceability.

DRAWINGS

1 is a schematic diagram of an operating environment of a preferred embodiment of an electronic device of the present application;

2 is a schematic diagram of interaction between an electronic device and a client according to a preferred embodiment of the present application;

Figure 3 is a program block diagram of the data service program of Figure 1;

Figure 4 is a schematic diagram of an operator in an algorithm chain;

FIG. 5 is a schematic diagram of an input interface of a user in an example; FIG.

6 is a schematic diagram showing a display interface of target data in an example;

FIG. 7 is a flowchart of a preferred embodiment of a data service method according to the present application.

The implementation, functional features and advantages of the present application will be further described with reference to the accompanying drawings.

Detailed ways

The principles and spirit of the present application are described below with reference to a number of specific embodiments. It is understood that the specific embodiments described herein are merely illustrative of the application and are not intended to be limiting.

Those skilled in the art will appreciate that embodiments of the present application can be implemented as a method, apparatus, device, system, or computer program product. Accordingly, the application can be embodied in a complete hardware, complete software (including firmware, resident software, microcode, etc.), or a combination of hardware and software.

According to an embodiment of the present application, a data service method, an electronic device, and a storage medium are proposed.

1 is a schematic diagram of an operating environment of a preferred embodiment of an electronic device of the present application.

The electronic device 1 may be a terminal device having a storage and computing function such as a server, a portable computer, or a desktop computer.

The electronic device 1 includes a memory 11, a processor 12, a network interface 13, and a communication bus 14. The network interface 13 can optionally include a standard wired interface and a wireless interface (such as a WI-FI interface). The communication bus 14 is used to implement connection communication between the above components.

The memory 11 includes at least one type of readable storage medium. The at least one type of readable storage medium may be a non-volatile storage medium such as a flash memory, a hard disk, a multimedia card, a card type memory, or the like. In some embodiments, the readable storage medium may be an internal storage unit of the electronic device 1, such as a hard disk of the electronic device 1. In other embodiments, the readable storage medium may also be an external memory 11 of the electronic device 1, such as a plug-in hard disk equipped on the electronic device 1, a smart memory card (SMC). , Secure Digital (SD) card, Flash Card, etc.

In the present embodiment, the readable storage medium of the memory 11 is generally used to store a data service program 10 and a program configuration file installed in the electronic device 1, a database in which original data is stored, and the like. The memory 11 can also be used to temporarily store data that has been output or is about to be output.

The processor 12, in some embodiments, may be a Central Processing Unit (CPU), microprocessor or other data processing chip for running program code or processing data stored in the memory 11, such as executing a data service program. 10 and so on.

1 shows only the electronic device 1 having the components 11-14 and the data service program 10, but it should be understood that not all illustrated components may be implemented, and more or fewer components may be implemented instead.

Optionally, the electronic device 1 may further include a user interface, and the user interface may include an input unit such as a keyboard, a voice input device such as a microphone, a device with a voice recognition function, a voice output device such as an audio, a headphone, and the like. . Optionally, the user interface may also include a standard wired interface and a wireless interface.

Optionally, the electronic device 1 may further include a display, which may also be referred to as a display screen or a display unit. In some embodiments, it may be an LED display, a liquid crystal display, a touch liquid crystal display, and an Organic Light-Emitting Diode (OLED) display. The display is used to display information processed in the electronic device 1 and a user interface for displaying visualizations.

Optionally, the electronic device 1 further comprises a touch sensor. The area provided by the touch sensor for the user to perform a touch operation is referred to as a touch area. Further, the touch sensor described herein may be a resistive touch sensor, a capacitive touch sensor, or the like. Moreover, the touch sensor includes not only a contact type touch sensor but also a proximity type touch sensor or the like. Furthermore, the touch sensor may be a single sensor or a plurality of sensors arranged, for example, in an array. The user can start the data service program 10 by touching the touch area.

In addition, the area of the display of the electronic device 1 may be the same as or different from the area of the touch sensor. Optionally, a display is stacked with the touch sensor to form a touch display. The device detects a user-triggered touch operation based on a touch screen display.

The electronic device 1 may further include a radio frequency (RF) circuit, a sensor, an audio circuit, and the like, and details are not described herein.

Referring to FIG. 2, it is a schematic diagram of interaction between the electronic device and the client in the preferred embodiment of the present application. The data service program 10 runs in the electronic device 1. In Fig. 2, the preferred embodiment of the electronic device 1 is a server. The electronic device 1 is connected to the client 2 via a network. The client 2 can run in various types of terminal devices, such as smart phones, portable computers, and the like. After the user logs in to the electronic device 1 through the client 2, the data service method can provide various data services for the user, for example, querying similar cases from a large number of cases, querying related words by keywords, querying a disease encyclopedia, and the like.

In the operating environment diagram of the preferred embodiment of the electronic device 1 shown in FIG. 1, the memory 11 including the readable storage medium may include an operating system, a data service program 10, a program configuration file, and a database. When the processor 12 executes the data service program 10 stored in the memory 11, the following steps are implemented:

Acquisition step: obtaining a data service request;

Configuration step: parsing the data service request, and configuring an algorithm chain according to the parsing result;

Performing steps: executing the configured algorithm chain to obtain target data from the original data in the database;

Output step: output the target data.

The configuration steps include:

Parsing the data service request, and determining respective computing requirements corresponding to the data service request;

Determining the operator and operator combination rules corresponding to each computing requirement;

Obtain the determined operator from the program configuration file;

The algorithm chain is configured according to the obtained operator and the operator combination rule.

For specific principles, please refer to the following FIG. 3 for a description of the program module diagram of the data service program 10 and FIG. 7 for a flowchart of the preferred embodiment of the data service method.

Referring to FIG. 3, it is a program module diagram of the data service program 10 in FIG. In the present embodiment, the data service program 10 is divided into a plurality of modules that are stored in the memory 11 and executed by the processor 12 to complete the present application. A module as referred to in this application refers to a series of computer program instructions that are capable of performing a particular function.

The data service program 10 can be divided into: an acquisition module 110, a configuration module 120, an execution module 130, and an output module 140.

The obtaining module 110 is configured to obtain a data service request. In this embodiment, a data service request input by the user may be obtained from a user interface of the client, such as inputting a keyword and requesting to query a related word of the keyword.

The configuration module 120 is configured to parse the data service request, and configure an algorithm chain according to the parsing result.

Specifically, a plurality of operators (also referred to as plug-ins) are stored in the program configuration file of the electronic device 1. Each operator corresponds to a specific computing requirement. For example, the computational requirement corresponding to the operator CommonHead is to obtain input data from the page and store it in the system general data structure MyTupleList, and the computational requirement corresponding to the operator Hanlp is keyword extraction. The operator is written and developed by the developer in accordance with the rules and stored in the program configuration file for the data service program 10 to call when providing the data service, thereby performing data processing.

Thus, the configuration module 120 is specifically configured to:

Obtain the determined operator from the program configuration file;

The execution module 130 is configured to execute the configured algorithm chain to obtain target data from the original data in the database.

Wherein, the algorithm chain adopts a serial mode, that is, the algorithm chain is composed of operators corresponding to respective computing requirements. When the program corresponding to the algorithm chain is executed, the operator corresponding to each calculation requirement is sequentially executed in the stated order, and after the execution of the operator corresponding to the previous calculation requirement is completed, the intermediate data is output to the operator corresponding to the next calculation requirement. The next operator corresponding to the calculation demand is then calculated and outputted, and so on, and the final calculation operator corresponding to the operator is executed after the execution of the output data. This process is similar to the pipeline processing process. The algorithm chain is split into several operators corresponding to the calculation requirements in a pipeline manner. The operator processing data corresponding to each calculation requirement passes the result to the operator corresponding to the next calculation requirement. This modular processing of the pipeline can improve the operational efficiency of data services.

Moreover, in order to improve the reliability of the algorithm chain and increase the fault tolerance mechanism, each computing requirement in the algorithm chain may correspond to one or more identical operators, and the one or more identical operators are in the algorithm chain. The execution is performed in parallel and the execution results are output in a preset priority order.

[Correct according to Rule 91 14.08.2018]
For example, the structure of the algorithm chain can be seen in FIG. 4, where a container represents a step of calculation, that is, a computational requirement. The operator contained in a container, that is, the specific operator, performs a specific computational requirement. In order to improve the reliability of the algorithm chain, a container can contain several identical operators. These several identical operators are executed in parallel, and the main thread is set for each operator. The access to the execution results of each operator is prioritized. When the current main thread of the operator times out but still does not return the execution result, then discard the

The result of the execution of the operator, while waiting to return the execution result of the operator of the next priority.

In this embodiment, the database is pre-stored with a plurality of original data, such as a certain word and related words and relevance data of the word, a certain symptom and its three symptoms and corresponding treatment measures data. The storage format of the original data in the database may be the following three types:

1, simple type

Simple types apply when the primary key has only one related content and weight, and its storage can be abstracted as id, name, doc(weight#info). For example, the original data is the word "cold", the word "fever" with the highest degree of association with "cold", the degree of association "1", the original data can be stored in the database in the following format with a simple type:

字段Field	idId	nameName	docDoc	create_dateCreate_date
类型Types of	intInt	textText	textText	dateDate
举例Example	11	感冒#1 Cold #1	1#发烧1# fever	2017-03-172017-03-17

2, no sequence list

The unordered list is applicable to the case where the primary key has a plurality of related contents, and the related contents are unordered, and the weight of each related content can be saved as 1 to represent the disorder. Its storage can be abstracted as id, name, doc(key1#weight#info1*key2#weight#info2*...keyn#weight#infon). For example, the raw data is the disease "cold", and the three symptoms of "cold" "headache", "rogue", "throat pain", the raw data can be stored in the database in the following format using an unordered list:

3, the ordered list

The ordered list is applicable to the primary key having a plurality of related contents, and the related contents are in an orderly manner, and the weight of each related content can be used to indicate the order. Its storage can be abstracted as id, name, doc(key1#weight1#info1*key2#weight2#info2*...keyn#weightn#infon). For example, the original data is the word "intra-domain", with 10 related words and relevance of the word, the original data can be stored in the database in the following format using an ordered list:

From above, the execution module 130 acquires target data from the original data of the database by executing a program corresponding to the configured algorithm chain. For example, the algorithm chain for implementing the function of finding similar cases is:

Operator Hanlp—> operator Retrieval—> operator Scoring—> operator HeapSort—> operator RetrievalDoc

The functions of the above operators Hanlp, Retrieval, Scoring, HeapSort, and RetrievalDoc are as follows: cutting the Chinese words, obtaining the document IDs that may meet the requirements, scoring the document IDs by the BM25 algorithm, sorting the scoring results by heap sorting, and passing the document ID. Retrieve the body of the document. By sequentially executing the above-mentioned operators, similar cases requested by the user can be obtained from the case raw data in the database as target data.

The output module 140 is configured to output the target data. In order to adapt to various sources, different formats, different number of fields, and different types of input data, the target data may be formatted, that is, unified normalization processing. For example, the target data may be output in the form of a triplet of MyTupleList (Key, Weight, Info).

[Correct according to Rule 91 14.08.2018]
In FIG. 4, "InputResult" and "OutputResult" are common data structures for transferring intermediate results between operators, and the output data can be formatted in a packaged manner, that is, unified normalization. For example, in this embodiment, the function selection and encapsulation can be implemented by the tools PGToolT and RAOTool, and the classes of various format data are implemented as an interface of IDaoBasic, and the external output is MyTupleList (Key, Weight, Info). The form of the triple.

In the following embodiment, the original data stored in the database is a plurality of related word records, each record consisting of a word and its 10 most relevant words and relevance information, as shown below. For the word "intra-domain" and its 10 related words and relevance data:

Intra-domain #1, intra-area, 1.0, distribution area, 0.28298, brain area, 0.2413, area, 0.2016, arm, 0.15518, area, 0.12988, inter-area, 0.12308, aspect, 0.09344, CDF, 0.08009, clearance, 0.06984.

Since the relevance of the related words is different, there is a sequence. Therefore, if the original data is stored in the PostgreSQL (PG) database in the format of the ordered list, the original data is in the form of the following after the storage:

The obtaining module 110 acquires a data service request, which is generated according to input information of the user, and the input interface of the user is as shown in FIG. 5, for example.

After obtaining the data service request, the configuration module 120 parses the data service request, determines that the data service request is a related word of the query term “intra-domain”, and outputs the related words and the relevance degree of the word according to the ascending order (or descending order) of the association degree.

According to the data service request, the configuration module 120 determines that the computing requirement is (1), obtains a query key (inside the domain) from the user interface, and the corresponding operator is “CommonHead”; (2) according to the query key, the slave database The corresponding data is pulled in Redis or PostgreSQL (PG), and the corresponding operator is "Retrieval". The configuration module 120 configures the algorithm chain according to the operators "CommonHead" and "Retrieval" according to the operator combination rules corresponding to the respective calculation requirements:

10001#022#base

10001#022#8002;

Com:CommonHeadV2#-1#-1#1;

Retr: RetrievalV2#6#1#2_2.

The "10001#022#base" and the "10001#022#8002" are algorithm numbers, and the algorithm numbers are the operator combination rules corresponding to the respective calculation requirements.

The execution module 130 executes the configured algorithm chain, that is, each operator in the algorithm chain is sequentially executed in sequence, and the target data is obtained by processing the word “intra-domain” of the database and its 10 related words and association degree data, and Format the output target data. In one embodiment, the presentation interface of the target data is as shown in FIG.

Referring to FIG. 7, a flow chart of a preferred embodiment of the data service method of the present application is shown. The following steps are implemented when the processor 12 of the electronic device 1 executes the data service program 10 stored in the memory 11 to implement the data service method:

S10. The obtaining module 110 acquires a data service request.

S20. The configuration module 120 parses the data service request, and configures an algorithm chain according to the analysis result. Specifically, the configuration module 120 is configured to parse the data service request, determine each computing requirement corresponding to the data service request, determine an operator and an operator combination rule corresponding to each computing requirement, and obtain the determined one from the program configuration file. An operator; the algorithm chain is configured according to the obtained operator and the operator combination rule.

S30. The execution module 130 executes the configured algorithm chain to obtain target data from the original data in the database. Optionally, the algorithm chain may be serially composed of operators corresponding to respective computing requirements. Optionally, each computing requirement corresponds to one or more identical operators, the one or more identical operators are executed in parallel in the algorithm chain, and the execution results are output in a preset priority order. The storage format of the original data in the database may include, for example, a simple type: the primary key has only one related content and weight; the unordered list: the primary key has a plurality of related contents, and the plurality of related contents are unordered; ordered List: The primary key has a number of related content, which is previously ordered.

S40. The output module 140 outputs the target data. Optionally, the output module 140 may format and output the target data.

The data service method proposed in this embodiment can respond to the online data service request in a pipeline manner by an operator in the algorithm chain after receiving the data service request, and input and output data format of the operator in the algorithm chain. Encapsulation process to make the data format uniform, so that the operators are loosely coupled, and the data between the operators is closely combined, so the data service provided has good scalability, reliability, timeliness and Serviceability.

In addition, the embodiment of the present application further provides a computer readable storage medium, which may be a hard disk, a multimedia card, an SD card, a flash memory card, an SMC, a read only memory (ROM), and an erasable programmable Any combination or combination of any one or more of read only memory (EPROM), portable compact disk read only memory (CD-ROM), USB memory, and the like. The computer readable storage medium includes a program configuration file, a database storing the original data, a data service program 10, and the like. When the data service program 10 is executed by the processor 12, the following operations are implemented:

Acquisition step: obtaining a data service request;

Output step: output the target data.

The configuration steps include:

Obtain the determined operator from the program configuration file;

The specific implementation of the computer readable storage medium of the present application is substantially the same as the above-described data service method and the specific embodiment of the electronic device 1, and details are not described herein again.

It is to be understood that the term "comprises", "comprising", or any other variants thereof, is intended to encompass a non-exclusive inclusion, such that a process, apparatus, article, or method that comprises a series of elements includes those elements. It also includes other elements not explicitly listed, or elements that are inherent to such a process, device, item, or method. An element that is defined by the phrase "comprising a ..." does not exclude the presence of additional elements in the process, the device, the item, or the method of the element.

Through the description of the above embodiments, those skilled in the art can clearly understand that the foregoing embodiment method can be implemented by means of software plus a necessary general hardware platform, and of course, can also be through hardware, but in many cases, the former is better. Implementation. Based on such understanding, portions of the technical solution of the present application that contribute substantially or to the prior art may be embodied in the form of a software product stored in a storage medium as described above, including a number of instructions. To enable a terminal device (which may be a mobile phone, a computer, a server, or a network device, etc.) to perform the methods described in the various embodiments of the present application.

The above is only a preferred embodiment of the present application, and is not intended to limit the scope of the patent application, and the equivalent structure or equivalent process transformations made by the specification and the drawings of the present application, or directly or indirectly applied to other related technical fields. The same is included in the scope of patent protection of this application.

Claims

A data service method, applied to a computing device, characterized in that the method comprises:

Acquisition step: obtaining a data service request;

Configuration step: parsing the data service request, and configuring an algorithm chain according to the parsing result;

Performing steps: executing the configured algorithm chain to obtain target data from the original data in the database;

Output step: output the target data.
The data service method according to claim 1, wherein said configuring step comprises:

Parsing the data service request, and determining respective computing requirements corresponding to the data service request;

Determining the operator and operator combination rules corresponding to each computing requirement;

Obtain the determined operator from the program configuration file;

The algorithm chain is configured according to the obtained operator and the operator combination rule.
The data service method according to claim 2, wherein said algorithm chain is serially composed of operators corresponding to respective computational requirements.
The data service method according to claim 2, wherein each calculation requirement corresponds to one or more identical operators, and the one or more identical operators are executed in parallel in the algorithm chain, and are preset according to the preset The execution result is output in priority order.
The data service method according to claim 1, wherein the storage format of the original data in the database comprises:

Simple type: The primary key has only one related content and weight;

Unordered list: The primary key has a plurality of related contents, and the related contents are unordered;

There is an ordered list: the primary key has a number of related content, and the related content is previously ordered.
The data service method according to claim 2, wherein the storage format of the original data in the database comprises:

Simple type: The primary key has only one related content and weight;

Unordered list: The primary key has a plurality of related contents, and the related contents are unordered;

There is an ordered list: the primary key has a number of related content, and the related content is previously ordered.
The data service method according to any one of claims 1 to 6, wherein the outputting step comprises:

Formatting and outputting the target data.
An electronic device includes a memory and a processor, wherein the memory includes a data service program, and when the data service program is executed by the processor, the following steps are implemented:

Acquisition step: obtaining a data service request;

Configuration step: parsing the data service request, and configuring an algorithm chain according to the parsing result;

Performing steps: executing the configured algorithm chain to obtain target data from the original data in the database;

Output step: output the target data.
The electronic device of claim 8, wherein the configuring step comprises:

Parsing the data service request, and determining respective computing requirements corresponding to the data service request;

Determining the operator and operator combination rules corresponding to each computing requirement;

Obtain the determined operator from the program configuration file;

The algorithm chain is configured according to the obtained operator and the operator combination rule.
The electronic device according to claim 9, wherein said algorithm chain is serially composed of operators corresponding to respective computational requirements.
The electronic device according to claim 9, wherein each computing requirement corresponds to one or more identical operators, and the one or more identical operators are executed in parallel in the algorithm chain, and are preset according to a preset priority. The output is executed in sequence.
The electronic device according to claim 8, wherein the storage format of the original data in the database comprises:

Simple type: The primary key has only one related content and weight;

Unordered list: The primary key has a plurality of related contents, and the related contents are unordered;

There is an ordered list: the primary key has a number of related content, and the related content is previously ordered.
The electronic device according to claim 9, wherein the storage format of the original data in the database comprises:

Simple type: The primary key has only one related content and weight;

Unordered list: The primary key has a plurality of related contents, and the related contents are unordered;

There is an ordered list: the primary key has a number of related content, and the related content is previously ordered.
The electronic device according to any one of claims 8 to 13, wherein the outputting step comprises:

Formatting and outputting the target data.
A computer readable storage medium, comprising: a data service program, wherein the data service program is executed by a processor to implement the following steps:

Acquisition step: obtaining a data service request;

Configuration step: parsing the data service request, and configuring an algorithm chain according to the parsing result;

Performing steps: executing the configured algorithm chain to obtain target data from the original data in the database;

Output step: output the target data.
The computer readable storage medium of claim 15 wherein said configuring step comprises:

Parsing the data service request, and determining respective computing requirements corresponding to the data service request;

Determining the operator and operator combination rules corresponding to each computing requirement;

Obtain the determined operator from the program configuration file;

The algorithm chain is configured according to the obtained operator and the operator combination rule.
The computer readable storage medium of claim 16 wherein each computing requirement corresponds to one or more identical operators, said one or more identical operators being executed in parallel in said algorithm chain and The execution result is output in a preset priority order.
The computer readable storage medium of claim 16 wherein each computing requirement corresponds to one or more identical operators, said one or more identical operators being executed in parallel in said algorithm chain and The execution result is output in a preset priority order.
The computer readable storage medium according to claim 15 or 16, wherein the storage format of the original data in the database comprises:

Simple type: The primary key has only one related content and weight;

Unordered list: The primary key has a plurality of related contents, and the related contents are unordered;

There is an ordered list: the primary key has a number of related content, and the related content is previously ordered.
The computer readable storage medium of claim 19, wherein the outputting comprises:

Formatting and outputting the target data.