CN113946721A - Data query method, device, equipment and storage medium - Google Patents
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Abstract
The embodiment of the invention discloses a data query method, a data query device, data query equipment and a storage medium. The method comprises the following steps: determining a data query object based on the received data query request; searching comprehensive data information matched with the data query object from a preset data information association table and displaying the comprehensive data information in a set format; the data information association table comprises at least one data object and a data information unit associated with the data object, wherein the data information unit comprises all data information of different data types of the data object. According to the technical scheme of the embodiment of the invention, more comprehensive information associated with the data object can be obtained by inquiring the data information association table containing the data object and the data information unit associated with the data object, and compared with the prior art that only single and independent data can be obtained when data is inquired, the information content obtained by data inquiry is enriched, and the integrity of data information is improved.
Description
Technical Field
The embodiment of the invention relates to the technical field of data query, in particular to a data query method, a data query device, data query equipment and a storage medium.
Background
In the prior art, different data information is mostly single and mutually independent, and when a user inquires data, the user can only search for different types for many times to obtain complete data information. In addition, data query at the present stage can only search homogeneous data information, and more relevant comprehensive information cannot be screened through limited data conditions.
Disclosure of Invention
Embodiments of the present invention provide a data query method, apparatus, device, and storage medium, which can obtain more comprehensive information associated with a data object by querying a data information association table including the data object and a data information unit associated with the data object, enrich information content obtained by data query, and improve integrity of data information.
In a first aspect, an embodiment of the present invention provides a data query method, including:
determining a data query object based on the received data query request;
searching the comprehensive data information matched with the data query object from a preset data information association table and displaying the comprehensive data information in a set format;
the data information association table comprises at least one data object and a data information unit associated with the data object, wherein the data information unit comprises all data information of different data types of the data object.
In a second aspect, an embodiment of the present invention further provides a data query apparatus, including:
the data query object determining module is used for determining a data query object based on the received data query request;
the comprehensive data information searching module is used for searching the comprehensive data information matched with the data query object from a preset data information association table and displaying the comprehensive data information in a set format;
the data information association table comprises at least one data object and a data information unit associated with the data object, wherein the data information unit comprises all data information of different data types of the data object.
In a third aspect, an embodiment of the present invention further provides a computer device, where the computer device includes: the system comprises a memory, a processor and a computer program stored on the memory and capable of running on the processor, wherein the processor executes the program to realize the data query method according to the embodiment of the invention.
In a fourth aspect, an embodiment of the present invention further provides a computer-readable storage medium, on which a computer program is stored, where the computer program, when executed by a processing apparatus, implements the data query method according to the embodiment of the present invention.
The embodiment of the invention discloses a data query method, a data query device, data query equipment and a storage medium. The method comprises the following steps: determining a data query object based on the received data query request; searching comprehensive data information matched with the data query object from a preset data information association table and displaying the comprehensive data information in a set format; the data information association table comprises at least one data object and a data information unit associated with the data object, wherein the data information unit comprises all data information of different data types of the data object. According to the technical scheme of the embodiment of the invention, more comprehensive information associated with the data object can be obtained by inquiring the data information association table containing the data object and the data information unit associated with the data object, and compared with the prior art that only single and independent data can be obtained when data is inquired, the information content obtained by data inquiry is enriched, and the integrity of data information is improved.
Drawings
Fig. 1 is a flowchart of a data query method according to an embodiment of the present invention;
FIG. 2 is a diagram illustrating an example of data query results provided in accordance with an embodiment of the present invention;
fig. 3 is a flowchart of a data query method according to a second embodiment of the present invention;
FIG. 4 is a diagram illustrating deep data query results according to a second embodiment of the present invention;
fig. 5 is a schematic structural diagram of a data query device according to a third embodiment of the present invention;
fig. 6 is a schematic structural diagram of a computer device according to a fourth embodiment of the present invention.
Detailed Description
The present invention will be described in further detail with reference to the accompanying drawings and examples. It is to be understood that the specific embodiments described herein are merely illustrative of the invention and are not limiting of the invention.
It should be further noted that, for the convenience of description, only some but not all of the relevant aspects of the present invention are shown in the drawings. Before discussing exemplary embodiments in more detail, it should be noted that some exemplary embodiments are described as processes or methods depicted as flowcharts. Although a flowchart may describe the operations (or steps) as a sequential process, many of the operations can be performed in parallel, concurrently or simultaneously. In addition, the order of the operations may be re-arranged. The process may be terminated when its operations are completed, but may have additional steps not included in the figure. The processes may correspond to methods, functions, procedures, subroutines, and the like.
The terms "first" and "second," and the like in the description and claims of embodiments of the invention and in the drawings, are used for distinguishing between different objects and not for describing a particular order. Furthermore, the terms "comprising" and "having," as well as any variations thereof, are intended to cover non-exclusive inclusions. For example, a process, method, system, article, or apparatus that comprises a list of steps or elements is not set forth for a listed step or element but may include steps or elements not listed.
In the prior art, data information of different data sources is mostly single and mutually independent, and when a user inquires data, the user can only search for different types for many times to obtain complete data information. There is no method for querying data, which can summarize and merge related information according to categories into a complete information unit in units of objects. In addition, data query at the present stage can only search homogeneous data information, and more relevant comprehensive information cannot be screened through limited data conditions. Therefore, it is necessary to search for common aggregation and perform line expansion query on various complex text data. The embodiment of the invention provides a data query method.
Example one
Fig. 1 is a flowchart of data query according to an embodiment of the present invention, where the embodiment is applicable to a case of performing data query, and the method may be executed by a data query apparatus, and the apparatus may be implemented by software and/or hardware, and is generally integrated in a computer device. The method specifically comprises the following steps:
s110, determining a data query object based on the received data query request.
The human-computer interaction interface can display the objects contained in each category in a category mode, and a user can select the object to be inquired by the user through the human-computer interaction interface. When the user selects the data query object, a corresponding query request is generated and sent to the data query device.
In this embodiment, the data query object may be specifically understood as a main body of data query, and the integrated data information is a complete data unit containing different types of information and having the object as the main body. Specifically, when a data query request is received, the data query request carries an object to be queried, and the data query device determines the data query object according to the data query request.
Illustratively, five category selection items including a person, a map, an organization, an object and time are displayed in the human-computer interaction interface, specific data objects are respectively arranged below each category selection item, for example, different names are arranged below the category of the person, when the names of three persons are selected, a data query request is received, it is determined that the data query object is the three selected persons, and then the acquired data information is also the related data information of the three persons.
And S120, searching the comprehensive data information matched with the data query object from a preset data information association table and displaying the comprehensive data information in a set format.
The data information association table comprises at least one data object and a data information unit associated with the data object, wherein the data information unit comprises all data information of different data types of the data object. The preset data information association table is formed by splitting and reconstructing original data in an original data file.
In this embodiment, the data object may be specifically understood as a main body of the data information unit. For example, if a person, a map, an organization, an object and time five types of data information are in a data information association table, if the person is the subject and the data information related to the person is acquired, the person is the data object, and all other data information related to the person jointly form a data information unit related to the person. The plurality of data information units constitute a data information association table.
Specifically, according to the data query object, the comprehensive data information matched with the data query object is queried from the preset data information association table, and the query mode may be a query mode performed by a program with a data query function, which is not specifically limited herein. Searching the comprehensive data information matched with the data query object and displaying the comprehensive data information in a set format through a human-computer interaction interface. The setting format can be customized by an administrator or a user, such as displaying in the form of a text message box.
The embodiment of the invention discloses a data query method, a data query device, data query equipment and a storage medium. The method comprises the following steps: determining a data query object based on the received data query request; searching comprehensive data information matched with the data query object from a preset data information association table and displaying the comprehensive data information in a set format; the data information association table comprises at least one data object and a data information unit associated with the data object, wherein the data information unit comprises all data information of different data types of the data object. According to the technical scheme of the embodiment of the invention, more comprehensive information associated with the data object can be obtained by inquiring the data information association table containing the data object and the data information unit associated with the data object, and compared with the prior art that only single and independent data can be obtained when data is inquired, the information content obtained by data inquiry is enriched, and the integrity of data information is improved.
As an optional embodiment of the present invention, on the basis of the above embodiment, the step of constructing the data association information table may be:
and S121, acquiring an original data file.
The original data file contains original data of different data sources. The original data file may be imported into the data querying device in any manner as a source of subsequent data processing.
And S122, splitting and reconstructing each original data in the original data file to generate a data association information table containing each set data object and related data information unit.
Specifically, the original data in the original data file is split according to categories to obtain different categories of data information, a certain category is taken as a data object, the different categories of information with correlation are associated to the corresponding data object to form a plurality of data information units, and the plurality of data objects and the data information units are assembled into a data association information table.
Optionally, the process of splitting and reconstructing each original data in the original data file to generate the data association information table including each set data object and the related data information unit may be expressed as:
s1221, classifying the original data contained in the original data file according to the set data type to obtain at least one data classification set.
Wherein the set data type may be an attribute of the thing the data represents. Illustratively, the classification processing is performed on the raw data contained in a certain raw data file to obtain five classification data sets of people, maps, organizations, objects and time.
And S1222, traversing each data classification set for each data object, summarizing the data information of each different data type related to the data object, and performing data reconstruction to form a data information unit of the data object.
Illustratively, the classification processing is performed on the raw data contained in a certain raw data file to obtain five classification data sets of people, maps, organizations, objects and time. If the data object is a man-made data object, traversing four other category data classification sets of a map, an organization, an object and time, inquiring data information of different data categories related to the data object, and reconstructing to form a data information unit of the data object.
S1223, the data table including each data object and the related data information unit is written as a data-related information table.
Specifically, all data tables containing data objects and related data information units are referred to as data association information tables, and the data association information tables are stored in the data query device as data sources for data query.
Fig. 2 is an exemplary diagram of a data query result according to an embodiment of the present invention, and the following description is taken as an example to describe the embodiment of the present invention more clearly. As shown in fig. 2:
the data is divided into five categories of data information including people, a map, an organization, an object and time, specific information of each category is displayed in a list or graphic mode under each category, when a user selects three persons D, E and F under the category of the people, the data query object is determined to be the three persons, and when the time selects the XX time period, comprehensive data information matched with the data query object is searched from a preset data information association table and displayed in a text information mode. The figure shows a summary of D, E, F, where D operates on the nail during the "YY hours", E shops on the Japanese during the "ZZ hours", and F shops on the nail during the "WW hours".
As an optional embodiment of the invention, the construction step of the data association information table is refined, the related information is summarized and fused together according to the category by taking the data object as a unit to form a complete information unit, and the association of the data object and other related category information is realized.
Example two
Fig. 3 is a flowchart of a data query method according to a second embodiment of the present invention. On the basis of the foregoing embodiment, in this embodiment, optionally, the method further includes: and performing deep query on the data query object based on the data analysis trigger request sent by the user. As shown in fig. 3, the method specifically includes the following steps:
s210, determining a data query object based on the received data query request.
S220, searching the comprehensive data information matched with the data query object from the preset data information association table and displaying the comprehensive data information in a set format.
The data information association table comprises at least one data object and a data information unit associated with the data object, wherein the data information unit comprises all data information of different data types of the data object.
And S230, performing deep query on the data query object based on the data analysis trigger request sent by the user.
The user may select the data analysis object through the human-computer interaction interface, and trigger the data analysis request, for example, by clicking an analysis button to trigger the data analysis request. And the data object can be deeply inquired by setting an analysis rule, so that the data information corresponding to the analysis rule is obtained.
As an optional embodiment of the present invention, on the basis of the above-mentioned embodiment, based on the data analysis trigger request sent by the user, the step of performing deep query on the data query object may be expressed as:
and S231, after receiving the data analysis triggering request, displaying an analysis rule configuration window to a user.
The analysis rule can be satisfied content, analysis dimension, minimum satisfied condition number, expanded line level, etc. For example, the content to be satisfied may be, for example, setting time and setting location, and filtering out information to be queried by the user by filling in the content to be satisfied.
Specifically, after a user selects a data query object on the human-computer interaction interface, the user clicks the analysis button to pop up an analysis rule configuration window, and the user can select an analysis rule in the analysis rule configuration window according to the user's own requirements.
And S232, receiving the analysis rule edited in the analysis rule configuration window by the user.
Specifically, after the user configures the analysis rule, the analysis rule edited by the user in the analysis rule configuration window is received.
And S233, acquiring data information related to the data query object from data information units corresponding to other data objects in the data information association table according to the analysis rule, and using the data information as a deep query result.
The deep query result can be the associated path of the query data object and other data objects and the information expansion information associated with the expansion layer level.
Specifically, attribute parameters contained in the analysis rules are analyzed according to the analysis rules, and data information associated with the data query object is acquired from data information units corresponding to other data objects in the data information association table through the attribute parameters.
Optionally, according to the analysis rule, the process of obtaining the data information associated with the data query object from the data information units corresponding to other data objects in the data information association table may be expressed as:
s2331, analyzing the analysis rule, and determining the attribute parameters contained in the analysis rule.
Illustratively, information such as satisfied content, analyzed dimensionality, minimum satisfied condition number, expanded line level, etc. is determined according to parsing rules.
S2332, determining the extended data object related to the data query object from the data information association table according to the attribute parameters.
Specifically, through each attribute parameter, an extended data object having a common attribute parameter with the data query object is found from the data information association table.
For example, if a is associated with B through address information, it can be understood that the common attribute parameter of a and B is address information, and when the data query object is a, through a first-level expansion line, it can be determined that B is an expansion object of a. If A is associated with B through address information and C is associated with B through article information, the common attribute parameter of A and B can be understood to be address information, the common attribute parameter of C and B is article information, and when the data query object is B, the expansion object of A and C as B can be determined through primary expansion.
S2333, extracting data information related to the data query object from the data information unit associated with each extended data object as a deep query result.
Exemplary, such as: first-stage line expansion, namely searching B with the same time and the same place information as A; and (3) secondary wire expansion: b with the same time and the same place information as A is found, and C with the same time and the same place information as B is found; and (4) three-stage line expansion, namely finding B with the same time and the same place information as A, finding C with the same time and the same place information as B, and finding D with the same organization mechanism as C.
Optionally, after performing deep query on the data query object based on the data analysis trigger request sent by the user, the method further includes: and displaying the deep query result according to the display mode matched with the determined deep query result for the user to view or use.
And displaying information such as the associated path, the expanded line result, information statistics and the like according to the display mode matched with the determined depth query result.
Fig. 4 is an exemplary diagram of a data deep query result provided in the second embodiment of the present invention, and the following is taken as an example to describe the second embodiment of the present invention more clearly. As shown in fig. 4:
when three persons, namely 'D', 'E' and 'F', are used as query objects, when a user selects the three persons 'D', 'E' and 'F' under the category of 'person', the first-stage line expansion and the second-stage line expansion are selected respectively. As can be seen, the interface displays the associated path on top: g is a new object mined, D is associated with F through address information A, D is not directly associated with E, but is indirectly associated with E through G, wherein D is associated with G through a container with the number XX, and D, G is associated with E through B. The first-level wire expansion information and the second-level wire expansion information are displayed below the interface, and the displayed information on the right side of the interface statistically shows how many objects are respectively associated through which data, so that how many associated objects are displayed.
On the basis of the embodiment, the embodiment of the invention adds a data analysis triggering request sent by a user and carries out a deep query step on a data query object. More data objects relevant to the analysis object and other information relevant to the data objects can be mined by setting the analysis rule, and the effect of screening more comprehensive information relevant to the analysis object through limited data conditions is achieved.
EXAMPLE III
Fig. 5 is a block diagram of a data query apparatus according to a third embodiment of the present invention, and as shown in fig. 5, the apparatus includes: a data query object determination module 31 and an integrated data information search module 32.
A data query object determining module 31, configured to determine a data query object based on the received data query request;
the comprehensive data information searching module 32 is configured to search comprehensive data information matched with the data query object from a preset data information association table and display the comprehensive data information in a set format;
the data information association table comprises at least one data object and a data information unit associated with the data object, wherein the data information unit comprises all data information of different data types of the data object.
Optionally, the integrated data information searching module 32 includes:
the device comprises an original data file acquisition unit, a data processing unit and a data processing unit, wherein the original data file acquisition unit is used for acquiring an original data file which comprises original data of different data sources;
and the data association information table generating unit is used for splitting and reconstructing each original data in the original data file and generating a data association information table containing each set data object and the related data information unit.
Optionally, the data association information table generating unit is specifically configured to:
classifying the original data contained in the original data file according to the set data type to obtain at least one data classification set;
for each data object, traversing each data classification set, summarizing data information of different data classes related to the data object, and performing data reconstruction to form a data information unit of the data object;
and recording a data table containing each data object and the related data information unit as a data related information table.
Optionally, the apparatus further comprises:
and the deep query module is used for carrying out deep query on the data query object based on the data analysis trigger request sent by the user.
Optionally, the depth query module includes:
the configuration window display unit is used for displaying an analysis rule configuration window to a user after receiving the data analysis triggering request;
the analysis rule receiving unit is used for receiving the analysis rule edited in the analysis rule configuration window by a user;
and the deep query result acquisition unit is used for acquiring data information related to the data query object from the data information units corresponding to other data objects in the data information association table according to the analysis rule and taking the data information as a deep query result.
Optionally, the deep query result obtaining unit is specifically configured to:
analyzing the analysis rule, and determining attribute parameters contained in the analysis rule;
determining an extended data object related to the data query object from the data information association table through each attribute parameter;
and extracting data information related to the data query object from the data information unit associated with each expanded data object as a deep query result.
Optionally, the apparatus further comprises:
and the deep query result display module is used for displaying the deep query result according to the display mode matched with the determined deep query result so as to be viewed or used by the user.
The device can execute the methods provided by all the embodiments of the invention, and has corresponding functional modules and beneficial effects for executing the methods. For details not described in detail in this embodiment, reference may be made to the methods provided in all the foregoing embodiments of the present invention.
Example four
Fig. 6 is a block diagram of a computer device according to a fourth embodiment of the present invention, as shown in fig. 6, the computer device includes a processor 41, a memory 42, an input device 43, and an output device 44; the number of processors 41 in the computer device may be one or more, and one processor 41 is taken as an example in fig. 6; the processor 41, the memory 42, the input device 43 and the output device 44 in the computer apparatus may be connected by a bus or other means, and the connection by the bus is exemplified in fig. 6.
The memory 42 is used as a computer readable storage medium for storing software programs, computer executable programs, and modules, such as program instructions/modules corresponding to the data query method in the embodiment of the present invention (for example, the data query object determination module 31 and the comprehensive data information search module 32 in the data query device). The processor 41 executes various functional applications and data processing of the computer device by executing software programs, instructions and modules stored in the memory 42, that is, implements the data query method described above.
The memory 42 may mainly include a storage program area and a storage data area, wherein the storage program area may store an operating system, an application program required for at least one function; the storage data area may store data created according to the use of the terminal, and the like. Further, the memory 42 may include high speed random access memory, and may also include non-volatile memory, such as at least one magnetic disk storage device, flash memory device, or other non-volatile solid state storage device. In some examples, memory 42 may further include memory located remotely from processor 41, which may be connected to a computer device over a network. Examples of such networks include, but are not limited to, the internet, intranets, local area networks, mobile communication networks, and combinations thereof.
The input device 43 may be used to receive input numeric or character information and to generate key signal inputs related to user settings and function controls of the computer apparatus. The output device 44 may include a display device such as a display screen.
EXAMPLE five
An embodiment of the present invention further provides a storage medium containing computer-executable instructions, which when executed by a computer processor, perform a data query method, including:
determining a data query object based on the received data query request;
searching comprehensive data information matched with the data query object from a preset data information association table and displaying the comprehensive data information in a set format;
the data information association table comprises at least one data object and a data information unit associated with the data object, wherein the data information unit comprises all data information of different data types of the data object.
Of course, the storage medium provided by the embodiment of the present invention contains computer-executable instructions, and the computer-executable instructions are not limited to the operations of the method described above, and may also perform related operations in the data query method provided by any embodiment of the present invention.
From the above description of the embodiments, it is obvious for those skilled in the art that the present invention can be implemented by software and necessary general hardware, and certainly, can also be implemented by hardware, but the former is a better embodiment in many cases. Based on such understanding, the technical solutions of the present invention may be embodied in the form of a software product, which can be stored in a computer-readable storage medium, such as a floppy disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a FLASH Memory (FLASH), a hard disk or an optical disk of a computer, and includes several instructions for enabling a computer device (which may be a personal computer, a server, or a network device) to execute the methods according to the embodiments of the present invention.
It should be noted that, in the embodiment of the data query apparatus, the included units and modules are only divided according to functional logic, but are not limited to the above division as long as the corresponding functions can be implemented; in addition, specific names of the functional units are only for convenience of distinguishing from each other, and are not used for limiting the protection scope of the present invention.
It is to be noted that the foregoing is only illustrative of the preferred embodiments of the present invention and the technical principles employed. It will be understood by those skilled in the art that the present invention is not limited to the particular embodiments described herein, but is capable of various obvious changes, rearrangements and substitutions as will now become apparent to those skilled in the art without departing from the scope of the invention. Therefore, although the present invention has been described in greater detail by the above embodiments, the present invention is not limited to the above embodiments, and may include other equivalent embodiments without departing from the spirit of the present invention, and the scope of the present invention is determined by the scope of the appended claims. It is to be noted that the foregoing is only illustrative of the preferred embodiments of the present invention and the technical principles employed. It will be understood by those skilled in the art that the present invention is not limited to the particular embodiments described herein, but is capable of various obvious changes, rearrangements and substitutions as will now become apparent to those skilled in the art without departing from the scope of the invention. Therefore, although the present invention has been described in greater detail by the above embodiments, the present invention is not limited to the above embodiments, and may include other equivalent embodiments without departing from the spirit of the present invention, and the scope of the present invention is determined by the scope of the appended claims.
Claims (10)
1. A method for querying data, comprising:
determining a data query object based on the received data query request;
searching the comprehensive data information matched with the data query object from a preset data information association table and displaying the comprehensive data information in a set format;
the data information association table comprises at least one data object and a data information unit associated with the data object, wherein the data information unit comprises all data information of different data types of the data object.
2. The method of claim 1, wherein the step of constructing the data association information table comprises:
acquiring an original data file, wherein the original data file comprises original data of different data sources;
and splitting and reconstructing each original data in the original data file to generate a data association information table containing each set data object and related data information units.
3. The method according to claim 2, wherein the step of performing a splitting and reconstructing process on each original data in the original data file to generate a data association information table including the set data objects and related data information units comprises:
classifying the original data contained in the original data file according to a set data type to obtain at least one data classification set;
for each data object, traversing each data classification set, summarizing data information of different data classes related to the data object, and performing data reconstruction to form a data information unit of the data object;
and recording a data table containing each data object and the related data information unit as a data association information table.
4. The method according to any one of claims 1-3, further comprising:
and carrying out deep query on the data query object based on a data analysis trigger request sent by a user.
5. The method of claim 4, wherein the deep query of the data query object based on the data analysis trigger request sent by the user comprises:
after receiving a data analysis triggering request, displaying an analysis rule configuration window to a user;
receiving an analysis rule edited in the analysis rule configuration window by a user;
and acquiring the data information related to the data query object from the data information units corresponding to other data objects in the data information association table according to the analysis rule, and taking the data information as a deep query result.
6. The method according to claim 5, wherein the obtaining the data information associated with the data query object from the data information units corresponding to other data objects in the data information association table according to the analysis rule comprises:
analyzing the analysis rule, and determining attribute parameters contained in the analysis rule;
determining an extended data object related to the data query object from the data information association table through each attribute parameter;
and extracting data information related to the data query object from the data information unit associated with each expanded data object as a deep query result.
7. The method of claim 4, after performing a deep query on the data query object based on a data analysis trigger request sent by a user, further comprising:
and displaying the deep query result according to the display mode matched with the determined deep query result for the user to view or use.
8. A data query apparatus, comprising:
the data query object determining module is used for determining a data query object based on the received data query request;
the comprehensive data information searching module is used for searching the comprehensive data information matched with the data query object from a preset data information association table and displaying the comprehensive data information in a set format;
the data information association table comprises at least one data object and a data information unit associated with the data object, wherein the data information unit comprises all data information of different data types of the data object.
9. A computer device, the device comprising: memory, processor and computer program stored on the memory and executable on the processor, which when executed by the processor implements a data query method as claimed in any one of claims 1 to 7.
10. A computer-readable storage medium, on which a computer program is stored, which, when being executed by a processing device, carries out a data query method as claimed in any one of claims 1 to 7.
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