CN110019544B - Data query method and system - Google Patents
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Abstract
The invention discloses a data query method, which comprises the following steps: receiving a query instruction input by a user, wherein the query instruction comprises at least one query dimension; respectively querying a data set corresponding to each query dimension in a database cluster to be queried, wherein the database cluster to be queried comprises at least one database; and integrating the data sets obtained by query according to the dimension relation among the query dimensions to determine query data corresponding to the query instruction. According to the data query method provided by the invention, a user can query each query dimension in the query instruction in the database cluster to be queried respectively by inputting the query instruction once, so that the query data corresponding to the query instruction is obtained, query languages do not need to be input respectively for different databases to query, and the efficiency of querying the data is improved.
Description
Technical Field
The present invention relates to the field of data processing technologies, and in particular, to a data query method, a data query system, a storage medium, and a processor.
Background
With the development of information technology, in different industries, a large amount of data is generated at every moment, so that the storage performance requirement of mass data is formed, and the generated mass data is generally stored in a pre-established database. With the development of information systems in various industries, the demand for querying mass data is generated. In the existing query process of data in a database, a script language corresponding to the database is compiled to query the data stored in the database. Because the data structures of different databases are different, the query languages used in the data query process are also different.
Because different databases adopt different query languages, when a user queries data of different data, the user needs to continuously switch and input different query languages, so that the efficiency of data query is low.
Disclosure of Invention
In view of the above problems, the present invention is proposed to provide a data query method which overcomes or at least partially solves the above problems, and the specific scheme is as follows:
a method of data query, comprising:
receiving a query instruction input by a user, wherein the query instruction comprises at least one query dimension;
respectively querying a data set corresponding to each query dimension in a database cluster to be queried, wherein the database cluster to be queried comprises at least one database;
and integrating the data sets obtained by query according to the dimension relation among the query dimensions to determine query data corresponding to the query instruction.
In the foregoing method, preferably, the querying, in the database cluster to be queried, the data sets corresponding to the query dimensions respectively includes:
splitting each query dimension contained in the query instruction;
determining a target database to be queried in the database cluster to be queried for each query dimension which is split;
and converting each query dimension into a script query condition corresponding to a target database to be queried, and querying a data set corresponding to the query dimension in the target database according to the script query condition.
In the foregoing method, preferably, the splitting the query dimensions included in the query instruction includes:
traversing each dimension identifier contained in the query instruction;
determining a dimension text having an association relation with each dimension identification;
and taking each dimension text as a query dimension in the query instruction.
In the above method, preferably, the converting each query dimension into a script query condition corresponding to the target database to be queried includes:
acquiring a script comparison table corresponding to the target database;
determining a query language in the script comparison table;
and converting the query dimension into a script query condition corresponding to the query language.
The method preferably further comprises:
and storing the query instruction and the query data into a preset instruction mapping table.
A data query system, comprising:
the system comprises a receiving unit, a searching unit and a searching unit, wherein the receiving unit is used for receiving a searching instruction input by a user, and the searching instruction comprises at least one searching dimension;
the query unit is used for respectively querying the data sets corresponding to the query dimensions in the database cluster to be queried, and the database cluster to be queried comprises at least one database;
and the integration unit is used for integrating the data sets obtained by query according to the dimension relation among the query dimensions so as to determine the query data corresponding to the query instruction.
In the above system, preferably, the query unit includes:
a splitting subunit, configured to split each query dimension included in the query instruction;
the determining subunit is used for determining a target database to be queried in the database cluster to be queried of each split query dimension;
and the query subunit is used for converting each query dimension into a script query condition corresponding to the target database to be queried, and querying the data set corresponding to the query dimension in the target database according to the script query condition.
The above system, preferably, further comprises:
and the storage unit is used for storing the query instruction and the query data into a preset instruction mapping table.
A storage medium comprising a stored program, wherein the program performs the above-described data query method.
A processor, configured to execute a program, wherein the program executes the data query method.
By means of the technical scheme, the data query method provided by the invention comprises the following steps: receiving a query instruction input by a user, wherein the query instruction comprises at least one query dimension; respectively querying a data set corresponding to each query dimension in a database cluster to be queried, wherein the database cluster to be queried comprises at least one database; and integrating the data sets obtained by query according to the dimension relation among the query dimensions to determine query data corresponding to the query instruction. According to the data query method provided by the invention, when a user needs to query data, the user can query the data set corresponding to each query dimension in the query instruction in each database in the database cluster to be queried only by inputting the query instruction once, and different query languages do not need to be input for different databases, so that the query efficiency is improved.
The above description is only an overview of the technical solutions of the present invention, and the present invention can be implemented in accordance with the content of the description so as to make the technical means of the present invention more clearly understood, and the above and other objects, features, and advantages of the present invention will be more clearly understood.
Drawings
Various other advantages and benefits will become apparent to those of ordinary skill in the art upon reading the following detailed description of the preferred embodiments. The drawings are only for purposes of illustrating the preferred embodiments and are not to be construed as limiting the invention. Also, like reference numerals are used to refer to like parts throughout the drawings. In the drawings:
FIG. 1 is a flow chart of a data query method disclosed in an embodiment of the present application;
FIG. 2 is a flow chart of another method of a data query method disclosed in an embodiment of the present application;
FIG. 3 is a flow chart of another method of a data query method disclosed in an embodiment of the present application;
FIG. 4 is a flow chart of another method of a data query method disclosed in an embodiment of the present application;
FIG. 5 is a block diagram of a data query system disclosed in an embodiment of the present application;
fig. 6 is a block diagram of another structure of a data query system disclosed in the embodiment of the present application.
Detailed Description
Exemplary embodiments of the present disclosure will be described in more detail below with reference to the accompanying drawings. While exemplary embodiments of the present disclosure are shown in the drawings, it should be understood that the present disclosure may be embodied in various forms and should not be limited by the embodiments set forth herein. Rather, these embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the scope of the disclosure to those skilled in the art.
The previous description of the disclosed embodiments is provided to enable any person skilled in the art to make or use the present invention. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the generic principles defined herein may be applied to other embodiments without departing from the spirit or scope of the invention. Thus, the present invention is not intended to be limited to the embodiments shown herein but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.
The invention provides a data query method, which is applied to a user terminal, can be a processor of the user terminal and is used for querying data required by a user in a database, and a flow chart of the data query method is shown in figure 1 and comprises the following steps:
s101: receiving a query instruction input by a user, wherein the query instruction comprises at least one query dimension;
in the data query method provided by the invention, the query instruction comprises at least one query dimension, and the query dimension can be in a text format, and can be characters, numerical values, letters, special characters or a combination of the texts.
S102: respectively querying a data set corresponding to each query dimension in a database cluster to be queried, wherein the database cluster to be queried comprises at least one database;
according to the data query method provided by the invention, the data to be queried by the user can be data stored in the same database, can also be data in different databases in the same database platform, and can also be data in different databases in different database platforms.
S103: and integrating the data sets obtained by query according to the dimension relation among the query dimensions to determine query data corresponding to the query instruction.
In the data query method provided by the invention, certain dimension relation exists among the query dimensions, and the queried data sets are integrated according to the dimension relation among the query dimensions so as to determine the data to be queried of the query instruction.
According to the data query method provided by the invention, a user can query the data set corresponding to each query dimension in the query instruction in each database in the database cluster to be queried by inputting the query instruction for the data to be queried, and the query efficiency is improved without inputting different query languages for different databases.
Referring to fig. 2, a specific process of querying a data set corresponding to each query dimension in a database cluster to be queried according to the data query method provided by the present invention is shown, where the specific process includes:
s201: splitting each query dimension contained in the query instruction;
in the method provided by the invention, all the query dimensions in the query instruction are combined together according to a certain dimension relation, and all the query dimensions in the received query instruction are split according to a preset splitting rule.
S202: determining a target database to be queried in the database cluster to be queried for each query dimension which is split;
in the method provided by the invention, the data corresponding to each query dimension can be stored in different databases.
S203: and converting each query dimension into a script query condition corresponding to a target database to be queried, and querying a data set corresponding to the query dimension in the target database according to the script query condition.
In the method provided by the invention, each target database corresponds to a query language of the target database, the query dimensionality for data query is converted into a script language which can be identified by the corresponding target database, and the data to be queried can be directly queried in the target database according to the script query condition.
In the data query method provided by the invention, for each query dimension in the query instruction input by the user, after determining the database which needs to be queried by the query dimension, the query dimension is converted into a script query condition which can be identified by the database for querying. Namely, the query dimension in the query instruction is converted into the script language corresponding to the database for query. For the user, the user only needs to input the query instruction once, and does not need to input different query languages among different databases to perform switching query, so that the efficiency of data query is improved.
In the data query method provided by the present invention, the splitting of each query dimension included in the query instruction includes:
traversing each dimension identification contained in the query instruction;
determining a dimension text having an association relation with each dimension identification;
and taking each dimension text as a query dimension in the query instruction.
In the data query method provided by the present invention, for each query dimension in the query instruction, for example, the user can input the query instruction, where the region is beijing and the time is 2017and the case type is criminal case, and the query instruction indicates: in the invention, an and in the query instruction can be found as a split identifier, each query dimension is split according to a certain splitting rule, or all the query dimensions in the query instruction can be found, and the text on both sides is combined with the split.
The data query method provided by the invention can adopt different splitting rules according to the character composition relation among all query dimensions.
Referring to fig. 3, a specific process of converting each query dimension into a script query condition corresponding to a target database that needs to be queried in the present invention is shown, which includes:
s301: acquiring a script comparison table corresponding to the target database;
s302: determining a query language in the script comparison table;
s303: and converting the query dimension into a script query condition corresponding to the query language.
In the data query method provided by the invention, different databases correspond to respective script comparison tables, and the query language adopted for querying the databases is recorded in the script comparison tables.
The data query method provided by the invention can be applied to a database platform established by a single database storage mode and can also be applied to a database platform established by a plurality of database storage modes, when a plurality of types of databases exist in the data query platform, a plurality of script converters for converting the query instruction into the script query condition corresponding to the current database to be queried also exist, in order to avoid conflict, preferably, different distinguishing identifications can be established for each database in the data query platform, the distinguishing identifications are carried when the query instruction is input, and the distinguishing identifications are distributed to the script converters corresponding to the current database to be queried so as to distinguish the database and the converters corresponding to the database by the distinguishing identifications.
According to the data query method provided by the invention, each query dimension in the query instruction can be obtained firstly, and then each query dimension is converted into a script query condition corresponding to the current database to be queried respectively. Or converting the query instruction into a script query condition corresponding to the current database to be queried, acquiring each query dimension in the script query condition, and converting each query dimension into a script query condition corresponding to the current database to be queried.
In the data query method provided by the invention, in the process of integrating the acquired data sets, the priority order of the data sets can be determined according to the dimension relation; and sequentially integrating the data sets with adjacent relations according to the priority sequence.
The data query method provided by the invention is applied to a pre-established data query platform, and integrates each data set queried in each database into the data query platform in the invention, and each data set obtained by query is integrated in the data query platform according to the dimension relation among each query dimension.
In the data query method provided by the invention, the priority order of each data set depends on the dimension identification corresponding to the dimension relation. Dimension relations exist among all query dimensions, the dimension relations depend on dimension identifications among all query dimensions, the priority order is specified by a user and depends on actual conditions and storage quantity of data in the current database to be queried.
In the embodiment of the present invention, the dimension identifier may be one or a combination of several of various dimension identifiers such as "&", "|", "and", "or", and the like.
In the embodiment of the present invention, after determining query data corresponding to the query instruction, mapping each query dimension with an original sequence of each query dimension corresponding to the query instruction may be performed, and determining the query data corresponding to the query instruction according to the original sequence.
In the embodiment of the present invention, the query instruction and the query data may be stored in a preset instruction mapping table. And when the query request identical to the query instruction appears again, directly calling the query data for display.
Referring to fig. 4, a specific example of the data query method provided by the present invention is shown, taking a search process of a decision book in the judicial field as an example, in the case query database, if the query instruction includes "region ═ beijing and time ═ 2017and type ═ criminal case". The query instruction comprises three query dimensions, namely 'region ═ Beijing', 'time ═ 2017', 'type ═ criminal case', and a user wants to query data of all criminal cases in 2017 in the Beijing region.
When the data query method provided by the invention is used for querying, the three query dimensions are firstly split, then the databases in which the data to be queried of each query dimension are specifically stored are respectively determined, the three query dimensions are respectively converted into query conditions written by the query language of the databases when the query language adopted by the databases is determined, the query is carried out, and then intersection calculation is carried out on each data set obtained by query at the front end of a query platform to obtain the query data corresponding to the query instruction.
If the query dimension "region ═ Beijing" is stored in the database A, the query dimension "time ═ 2017" and "type ═ criminal case" are stored in the database B, the region ═ Beijing "is converted into the script query language corresponding to the database A, the query is performed in the database A, the" time ═ 2017 "and" type ═ criminal case "are respectively converted into the script query language corresponding to the database B, the query is performed in the database B, each queried data set is subjected to intersection calculation at the front end of the query platform, and the query data corresponding to the query instruction is obtained.
Corresponding to the above query method, the present invention further provides a data query system, whose schematic structural diagram is shown in fig. 5, including:
a receiving unit 401, configured to receive a query instruction input by a user, where the query instruction includes at least one query dimension;
a querying unit 402, configured to query, in a to-be-queried database cluster, a data set corresponding to each query dimension, where the to-be-queried database cluster includes at least one database;
an integrating unit 403, configured to integrate the queried data sets according to the dimension relationship between the query dimensions, so as to determine query data corresponding to the query instruction.
According to the data query system provided by the invention, when a user needs to query data, the user can query the data set corresponding to each query dimension in the query instruction in each database in the database cluster to be queried only by inputting the query instruction once, and different query languages do not need to be input for different databases, so that the query efficiency is improved.
On the basis of fig. 5, referring to fig. 6, there is shown another schematic structural diagram of the query system provided by the present invention, where the query unit 402 includes:
a splitting subunit 404, configured to split each query dimension included in the query instruction;
a determining subunit 405, configured to determine a target database to be queried in the to-be-queried database cluster for each split query dimension;
a query subunit 406, configured to convert each query dimension into a script query condition corresponding to the target database that needs to be queried, and query, according to the script query condition, a data set corresponding to the query dimension in the target database.
The system provided by the invention also comprises:
the storage unit 407 is configured to store the query instruction and the query data in a preset instruction mapping table.
The data query system comprises a processor and a memory, wherein the receiving unit, the query unit, the integration unit, the splitting subunit, the determining subunit, the query subunit, the storage unit and the like are stored in the memory as program units, and the processor executes the program units stored in the memory to realize corresponding functions.
The processor comprises a kernel, and the kernel calls the corresponding program unit from the memory. The kernel can be set to be one or more, and the query efficiency is improved by adjusting the kernel parameters.
The memory may include volatile memory in a computer readable medium, Random Access Memory (RAM) and/or non-volatile memory, such as Read Only Memory (ROM) or flash memory (flash RAM), including at least one memory chip.
An embodiment of the present invention provides a storage medium, on which a program is stored, and the program implements the data query method when executed by a processor.
The embodiment of the invention provides a processor, which is used for running a program, wherein the data query method is executed when the program runs.
The embodiment of the invention provides equipment, which comprises a processor, a memory and a program which is stored on the memory and can run on the processor, wherein the processor executes the program and realizes the following steps:
a method of data query, comprising:
receiving a query instruction input by a user, wherein the query instruction comprises at least one query dimension;
respectively querying a data set corresponding to each query dimension in a database cluster to be queried, wherein the database cluster to be queried comprises at least one database;
and integrating the data sets obtained by query according to the dimension relation among the query dimensions to determine query data corresponding to the query instruction.
In the foregoing method, the querying, in the database cluster to be queried, the data sets corresponding to the query dimensions respectively includes:
splitting each query dimension contained in the query instruction;
determining a target database to be queried in the database cluster to be queried for each split query dimension;
and converting each query dimension into a script query condition corresponding to a target database to be queried, and querying a data set corresponding to the query dimension in the target database according to the script query condition.
In the above method, the splitting each query dimension included in the query instruction includes:
traversing each dimension identification contained in the query instruction;
determining a dimension text having an association relation with each dimension identification;
and taking each dimension text as a query dimension in the query instruction.
In the above method, the converting each query dimension into a script query condition corresponding to the target database to be queried includes:
acquiring a script comparison table corresponding to the target database;
determining a query language in the script comparison table;
and converting the query dimension into a script query condition corresponding to the query language.
The method described above, further comprising:
and storing the query instruction and the query data into a preset instruction mapping table.
The device herein may be a server, a PC, a PAD, a mobile phone, etc.
As will be appreciated by one skilled in the art, embodiments of the present application may be provided as a method, system, or computer program product. Accordingly, the present application may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present application may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and so forth) having computer-usable program code embodied therein.
The present application is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the application. It will be understood that each flow and/or block of the flow diagrams and/or block diagrams, and combinations of flows and/or blocks in the flow diagrams and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
In a typical configuration, a computing device includes one or more processors (CPUs), input/output interfaces, network interfaces, and memory.
The memory may include forms of volatile memory in a computer readable medium, Random Access Memory (RAM) and/or non-volatile memory, such as Read Only Memory (ROM) or flash memory (flash RAM). The memory is an example of a computer-readable medium.
Computer-readable media, including both permanent and non-permanent, removable and non-removable media, may implement the information storage by any method or technology. The information may be computer readable instructions, data structures, modules of a program, or other data. Examples of computer storage media include, but are not limited to, phase change memory (PRAM), Static Random Access Memory (SRAM), Dynamic Random Access Memory (DRAM), other types of Random Access Memory (RAM), Read Only Memory (ROM), Electrically Erasable Programmable Read Only Memory (EEPROM), flash memory or other memory technology, compact disc read only memory (CD-ROM), Digital Versatile Disks (DVD) or other optical storage, magnetic cassettes, magnetic tape magnetic disk storage or other magnetic storage devices, or any other non-transmission medium, which can be used to store information that can be accessed by a computing device. As defined herein, a computer readable medium does not include a transitory computer readable medium such as a modulated data signal and a carrier wave.
It should also be noted that the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising an … …" does not exclude the presence of other identical elements in the process, method, article, or apparatus that comprises the element.
As will be appreciated by one skilled in the art, embodiments of the present application may be provided as a method, system, or computer program product. Accordingly, the present application may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present application may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.
The above are merely examples of the present application and are not intended to limit the present application. Various modifications and changes may occur to those skilled in the art to which the present application pertains. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application should be included in the scope of the claims of the present application.
Claims (8)
1. A method of querying data, comprising:
receiving a query instruction input by a user, wherein the query instruction comprises at least one query dimension;
splitting each query dimension contained in the query instruction; the data corresponding to each query dimension are respectively stored in different databases;
determining a target database to be queried in the database cluster to be queried for each split query dimension; the database cluster to be queried comprises at least two databases;
converting each query dimension into a script query condition corresponding to a target database to be queried, and querying a data set corresponding to the query dimension in the target database according to the script query condition;
and integrating the data sets obtained by query according to the dimension relation among the query dimensions to determine query data corresponding to the query instruction.
2. The method of claim 1, wherein splitting the query dimensions contained in the query instruction comprises:
traversing each dimension identification contained in the query instruction;
determining a dimension text having an association relation with each dimension identification;
and taking each dimension text as a query dimension in the query instruction.
3. The method of claim 1, wherein converting each query dimension into a script query condition corresponding to a target database of its required query comprises:
acquiring a script comparison table corresponding to the target database;
determining a query language in the script comparison table;
and converting the query dimension into a script query condition corresponding to the query language.
4. The method of claim 1, further comprising:
and storing the query instruction and the query data into a preset instruction mapping table.
5. A data query system, comprising:
the system comprises a receiving unit, a searching unit and a processing unit, wherein the receiving unit is used for receiving a query instruction input by a user, and the query instruction comprises at least one query dimension; the data corresponding to each query dimension are respectively stored in different databases;
the query unit is used for respectively querying the data sets corresponding to the query dimensions in the database cluster to be queried, and the database cluster to be queried comprises at least two databases;
the integration unit is used for integrating the data sets obtained by query according to the dimension relation among the query dimensions so as to determine query data corresponding to the query instruction;
wherein the query unit comprises:
the splitting subunit is used for splitting each query dimension contained in the query instruction;
the determining subunit is used for determining a target database to be queried in the database cluster to be queried of each split query dimension;
and the query subunit is used for converting each query dimension into a script query condition corresponding to the target database to be queried, and querying the data set corresponding to the query dimension in the target database according to the script query condition.
6. The system of claim 5, further comprising:
and the storage unit is used for storing the query instruction and the query data into a preset instruction mapping table.
7. A storage medium characterized by comprising a stored program, wherein the program executes the data query method of any one of claims 1 to 4.
8. A processor, configured to run a program, wherein the program executes to perform the data query method of any one of claims 1 to 4.
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| CN114267348A (en) * | 2021-11-16 | 2022-04-01 | 北京执象科技发展有限公司 | Man-machine collaborative teaching interaction method, system, equipment and storage medium |
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