CN112597185A - Big data query method and device - Google Patents
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Abstract
The embodiment of the application discloses a big data query method and a big data query device, wherein the method comprises the following steps: classifying the plurality of query components according to the query language to obtain a query component set with the same query language classification; configuring the corresponding relation between each query component in the query component set and the name and query field of each data table; the method comprises the steps of obtaining names of data tables and input contents of query fields determined by users, determining corresponding query components in a query component set by utilizing corresponding relations, filling the names of the data tables and the input contents of the query fields into query languages, and querying data in the data tables according to the input contents of the query fields and the query fields by utilizing the corresponding query components. Therefore, the embodiment of the application does not need a user to select a specific query component of the database, and the query of the big data is more convenient and fast for the user.
Description
Technical Field
The present application relates to the field of computers, and in particular, to a big data query method and apparatus.
Background
With the rapid development of internet technology, the world enters the big data era. Currently, a plurality of databases can store big data, and when data needs to be queried, a user can query the data in the databases by using a query component. For example, the data can be queried in the database Hive by using the query component Impala, and when the data is queried, the query component queries the data table by using the query language. The query component locates the data table where the data to be queried is located according to the name of the data table in the query language, and queries the data in the data table according to the field name of the data in the query language, wherein the field name of the data represents an attribute of the data, for example, the field name of data page three is a client name, that is, the client name is an attribute of data page three. Although a user may query for large data in a database using a query component, different databases provide the user with a different query component for data queries. Therefore, it is very difficult for the user to find the desired big data in different databases accurately by using the correct query component.
In summary, the existing query of big data in different databases by using different query components is very inconvenient for users.
Disclosure of Invention
In order to solve the problem that the query of big data in different databases by using different query components in the prior art is very inconvenient for users, the application provides a big data query method which can meet the requirement of users on conveniently and quickly querying data.
The embodiment of the application provides a big data query method, which comprises the following steps:
classifying the plurality of query components according to the query language to obtain a query component set with the same query language classification;
configuring the corresponding relation between each query component in the query component set and the name and query field of each data table;
acquiring the name of a data table and the input content of a query field determined by a user, determining a corresponding query component in the query component set by using the corresponding relation, filling the name of the data table and the input content of the query field into the query language, and querying data in the data table according to the query field and the input content of the query field by using the corresponding query component.
Optionally, the query field includes a query condition field and a query result field;
the configuring the corresponding relationship between each query component in the query component set and the name and query field of each data table comprises:
and configuring the corresponding relation between each query component in the query component set and the name, the query condition field and the query result field of each data table, wherein the query condition field and the query result field are pre-specified.
Optionally, the obtaining the name of the data table determined by the user and the input content of the query field includes:
and acquiring the name of the data table selected by the user and the content input by the user in the query condition field on a pre-configured query page.
Optionally, the obtaining the name of the data table determined by the user and the input content of the query field includes:
and acquiring the query name selected by the user on a pre-configured query page, determining the name of the data table associated with the query name, and acquiring the content input by the user in the query condition field.
Optionally, the method further includes:
and displaying the query result of the data table on the query page.
Optionally, the query result is the pre-specified query result field.
Optionally, the method further includes:
and monitoring the query flow of each query assembly in the query assembly set, and if one query assembly has overlarge flow, distributing other query assemblies in the query assembly set to perform data query.
Optionally, after configuring the corresponding relationship between each query component in the query component set and the name and query field of each data table, the method further includes: and generating a corresponding data import program for each query component, and importing the source data.
The embodiment of the application provides a big data query device, the device includes:
the classification unit is used for classifying the plurality of query components according to the query language to obtain a query component set with the same query language classification;
the configuration unit is used for configuring the corresponding relation between each query component in the query component set and the name and query field of each data table;
and the query unit is used for acquiring the name of the data table and the input content of the query field determined by the user, determining the corresponding query component in the query component set by using the corresponding relation, filling the name of the data table and the input content of the query field into the query language, and querying data in the data table according to the query field and the input content of the query field by using the corresponding query component.
Optionally, the query field includes a query condition field and a query result field;
the configuring unit configures the corresponding relation between each query component in the query component set and the name and query field of each data table, and comprises the following steps:
the configuration unit configures the corresponding relation between each query component in the query component set and the name of each data table, the query condition field and the query result field, wherein the query condition field and the query result field are pre-specified.
Optionally, the obtaining, by the query unit, the name of the data table determined by the user and the input content of the query field includes:
and the query unit acquires the name of the data table selected by the user and the content input by the user in the query condition field on a pre-configured query page.
Compared with the prior art, the method has the advantages that:
the embodiment of the application provides a big data query method, which comprises the following steps: classifying the plurality of query components according to the query language to obtain a query component set with the same query language classification; configuring the corresponding relation between each query component in the query component set and the name and query field of each data table; acquiring the name of a data table and the input content of a query field determined by a user, determining a corresponding query component in the query component set by using the corresponding relation, filling the name of the data table and the input content of the query field into the query language, and querying data in the data table according to the query field and the input content of the query field by using the corresponding query component. Therefore, according to the embodiment of the application, the corresponding relation among the data table name, the query field and the query component is established, the query language can be filled in only by acquiring the name of the data table determined by a user and the input content of the query field, the query component is determined, the query component utilizes the query language to perform data query, the user does not need to select a specific query component of the database, and the query of big data is more convenient for the user.
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In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings needed to be used in the description of the embodiments or the prior art will be briefly described below, it is obvious that the drawings in the following description are only some embodiments described in the present application, and other drawings can be obtained by those skilled in the art without creative efforts.
FIG. 1 is a flowchart of an embodiment of a big data query method provided in the present application;
fig. 2 is a block diagram illustrating a structure of an embodiment of a big data query apparatus according to the present disclosure.
Detailed Description
In order to make the technical solutions of the present application better understood, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application, and it is obvious that the described embodiments are only a part of the embodiments of the present application, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present application.
Referring to fig. 1, the figure is a flowchart of a big data query method provided in an embodiment of the present application.
The big data query method provided by the embodiment comprises the following steps:
step S101: and classifying the plurality of query components according to the query language to obtain a query component set with the same query language classification.
In embodiments of the present application, there are a plurality of different query components for different databases, and the query language of each query component may be the same or different. When the query component is used for querying in the database, a user is required to install the query component in advance, and the query component queries data according to the query language. And classifying the plurality of query components, screening out a set of query components with the same query language classification, and using the set as a basis for subsequent data query.
As an example, Hadoop is a distributed file system, also a non-relational database, where multiple databases are owned to store data, such as a Hive database or HBase database. Hadoop also provides query components Impala, HBase, Phoenix, and Kylin for querying data in a database. The data can be queried by using structured query language SQL for Impala, Phoenix and Kylin, and the query language of HBase is different from that of Impala, Phoenix and Kylin, so that the query components Impala, Phoenix and Kylin are classified into a set of query components with the same query language.
Step S102: and configuring the corresponding relation between each query component in the query component set and the name and query field of each data table.
In the embodiment of the application, each query component in the query component set with the same query language classification establishes a corresponding relation with each data table name and a query field in each database. Specifically, the name of the data table may be an english name, or an english name and a chinese name.
It should be noted that the query field includes a query condition field and a query result field, so that a corresponding relationship between each query component in the query component set and a name of each data table, the query condition field, and the query result field can be configured, where the query condition field and the query result field are pre-specified. In practical applications, the query result field does not have to be specified in advance. Pre-specifying query result fields may reduce the query pressure of the query component, and thus pre-specifying query result fields is a preferred approach.
As an example, the set of query components has three query components, Impala, Phoenix, and Kylin. And configuring the corresponding relation between the query component Impala and the English name of the data table in the Hive database, and configuring the corresponding relation between the query component Impala and all query condition fields and all query result fields in the data table in the Hive database. And configuring a corresponding relation between the name of a secondary index table in the query assembly Phoenix and an English name of a data table in an HBase database, and configuring a corresponding relation between the query assembly Phoenix and a pre-specified query condition field in the data table in the HBase database, a query condition field of the secondary index in the Phoenix and a query result field of the secondary index in the Phoenix. And configuring a corresponding relation between the query component Kylin and English names of the data tables in the HBase database, and configuring a corresponding relation between the query component Kylin and pre-specified query condition fields and all query result fields in the data tables in the HBase database.
It should be noted that after the corresponding relationship between each query component in the query component set and the name and query field of each data table is configured, a corresponding data import program is generated for each query component, and the source data is imported into the corresponding data table according to the corresponding relationship.
As an example, a corresponding table may be established in the database Hive for the query component Impala according to the correspondence, and the source data may be imported into the corresponding table.
Step S103: acquiring the name of a data table and the input content of a query field determined by a user, determining a corresponding query component in the query component set by using the corresponding relation, filling the name of the data table and the input content of the query field into the query language, and querying data in the data table according to the query field and the input content of the query field by using the corresponding query component.
In the embodiment of the application, the names of the data tables and the input contents of the query fields determined by a user can be obtained, the corresponding query components are determined by utilizing the corresponding relations between the configured query components and the names and the query fields of each data table, the names of the data tables and the input contents of the query fields are filled in the query language, and the data are queried in the data tables according to the input contents of the query fields and the query fields by utilizing the corresponding query components. Specifically, when the query component performs data query by using the query language, the query component analyzes the query language so as to perform data query by using the query component.
It should be noted that the name of the data table and the input content of the query field determined by the user may be obtained on a pre-configured query page.
As an implementation mode, the name of the data table selected by the user and the content input by the user in the query condition field can be obtained in a pre-configured query page. Specifically, a drop-down box may be preconfigured on the query page, the user selects a name of a data table that the user wants to query, and an input box of a query condition field may be preconfigured on the query page. The number of the configuration condition fields is not limited in the embodiment of the present application.
As an example, if the user selects the customer information look-up table in the drop-down box of the data table name in the pre-configured query page, and the query condition field of the pre-configured customer information table of the query page is the customer code, the input box of the query condition field inputs the value of the specific customer code, such as 15689524.
As another implementation manner, a query name selected by a user may be obtained on a pre-configured query page, a name of a data table associated with the query name is determined, and content input by the user in a query condition field is obtained. Specifically, the data tables may be classified according to names and query fields of the data tables, a query name may be defined for the data tables classified into the same portion, the query name may be associated with the data tables classified into the same portion, and the data tables classified into the same portion may be associated with the data tables according to the query fields.
As an example, if the user selects a customer query transaction in the drop-down box of the query name in the preconfigured query page, the data table associated with the customer query transaction is determined, and the corresponding data table name is determined, and if the query condition field of the preconfigured customer query transaction of the query page is the customer code, the value of the specific customer code, for example 15689524, is entered in the input box of the query condition field.
It should be noted that, after the query component finishes querying in the data table, the query result of the data table may be displayed on a preconfigured query page. Specifically, if the query result field is pre-specified during configuration, the query page displays only the pre-specified query result field in the query result of the data table. Specifically, the returned query result may be packaged in a preset query page, and the packaged result changes with the change of the query condition of the user.
In practical application, the query traffic of each query component in the query component set can be monitored, and if one of the query component sets has too large traffic, other query components in the query component set are allocated to perform data query. The purpose of this is to balance the query pressure of each query component and avoid the crash phenomenon that one query component is too high in query pressure.
As an example, the query module Impala supports a query mode of all query fields, the application of query scenarios is frequent, and the query pressure may be high, and at this time, for the input content of the query field with the query condition field being pre-specified, the input content is branched to Phoenix and Kylin for query.
The embodiment of the application provides a big data query method, which comprises the following steps: classifying the plurality of query components according to the query language to obtain a query component set with the same query language classification; configuring the corresponding relation between each query component in the query component set and the name and query field of each data table; acquiring the name of a data table and the input content of a query field determined by a user, determining a corresponding query component in the query component set by using the corresponding relation, filling the name of the data table and the input content of the query field into the query language, and querying data in the data table according to the query field and the input content of the query field by using the corresponding query component. Therefore, according to the embodiment of the application, the corresponding relation among the data table name, the query field and the query component is established, the query language can be filled in only by acquiring the name of the data table determined by a user and the input content of the query field, the query component is determined, the query component utilizes the query language to perform data query, the user does not need to select a specific query component of the database, and the query of big data is more convenient for the user.
Based on the big data query method provided by the above embodiment, the embodiment of the present application further provides a big data query device, and the working principle of the big data query device is described in detail below with reference to the accompanying drawings.
Referring to fig. 2, the figure is a block diagram of a big data query apparatus according to an embodiment of the present application.
The big data query device 200 provided in this embodiment includes:
a classifying unit 210, configured to classify the multiple query components according to the query language to obtain a query component set with the same query language classification;
a configuration unit 220, configured to configure a corresponding relationship between each query component in the query component set and a name and a query field of each data table;
the query unit 230 is configured to obtain a name of a data table and input content of a query field determined by a user, determine a corresponding query component in the query component set by using the correspondence, fill the name of the data table and the input content of the query field in the query language, and query data in the data table according to the query field and the input content of the query field by using the corresponding query component.
Optionally, the query field includes a query condition field and a query result field;
the configuring unit 220 configures the corresponding relationship between each query component in the query component set and the name and query field of each data table, including:
the configuration unit 220 configures the corresponding relationship between each query component in the query component set and the name of each data table, the query condition field, and the query result field, where the query condition field and the query result field are pre-specified.
Optionally, the acquiring, by the querying unit 230, the name of the data table determined by the user and the input content of the query field includes:
the query unit 230 obtains the name of the data table selected by the user and the content input by the user in the query condition field on a pre-configured query page.
When introducing elements of various embodiments of the present application, the articles "a," "an," "the," and "said" are intended to mean that there are one or more of the elements. The terms "comprising," "including," and "having" are intended to be inclusive and mean that there may be additional elements other than the listed elements.
It should be noted that, as one of ordinary skill in the art would understand, all or part of the processes of the above method embodiments may be implemented by a computer program to instruct related hardware, where the computer program may be stored in a computer readable storage medium, and when executed, the computer program may include the processes of the above method embodiments. The storage medium may be a magnetic disk, an optical disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), or the like.
The embodiments in the present specification are described in a progressive manner, and the same and similar parts among the embodiments are referred to each other, and each embodiment focuses on the differences from the other embodiments. In particular, for the apparatus embodiment, since it is substantially similar to the method embodiment, it is relatively simple to describe, and reference may be made to some descriptions of the method embodiment for relevant points. The above-described apparatus embodiments are merely illustrative, and the units and modules described as separate components may or may not be physically separate. In addition, some or all of the units and modules may be selected according to actual needs to achieve the purpose of the solution of the embodiment. One of ordinary skill in the art can understand and implement it without inventive effort.
The foregoing is directed to embodiments of the present application and it is noted that numerous modifications and adaptations may be made by those skilled in the art without departing from the principles of the present application and are intended to be within the scope of the present application.
Claims (10)
1. A big data query method is characterized by comprising the following steps:
classifying the plurality of query components according to the query language to obtain a query component set with the same query language classification;
configuring the corresponding relation between each query component in the query component set and the name and query field of each data table;
acquiring the name of a data table and the input content of a query field determined by a user, determining a corresponding query component in the query component set by using the corresponding relation, filling the name of the data table and the input content of the query field into the query language, and querying data in the data table according to the query field and the input content of the query field by using the corresponding query component.
2. The method of claim 1, wherein the query field comprises a query condition field and a query result field;
the configuring the corresponding relationship between each query component in the query component set and the name and query field of each data table comprises:
and configuring the corresponding relation between each query component in the query component set and the name, the query condition field and the query result field of each data table, wherein the query condition field and the query result field are pre-specified.
3. The method of claim 2, wherein obtaining the user-specified data table name and the input content of the query field comprises:
and acquiring the name of the data table selected by the user and the content input by the user in the query condition field on a pre-configured query page.
4. The method of claim 2, wherein obtaining the user-specified data table name and the input content of the query field comprises:
and acquiring the query name selected by the user on a pre-configured query page, determining the name of the data table associated with the query name, and acquiring the content input by the user in the query condition field.
5. The method according to any one of claims 3 or 4, further comprising:
and displaying the query result of the data table on the query page.
6. The method of claim 5, wherein the query result is the pre-specified query result field.
7. The method of claim 1, further comprising:
and monitoring the query flow of each query assembly in the query assembly set, and if one query assembly has overlarge flow, distributing other query assemblies in the query assembly set to perform data query.
8. The method of claim 1, wherein after configuring the correspondence of each query component in the set of query components to the name and query field of each data table, the method further comprises:
and generating a corresponding data import program for each query component, and importing the source data into a corresponding data table according to the corresponding relation.
9. A big data query apparatus, the apparatus comprising:
the classification unit is used for classifying the plurality of query components according to the query language to obtain a query component set with the same query language classification;
the configuration unit is used for configuring the corresponding relation between each query component in the query component set and the name and query field of each data table;
and the query unit is used for acquiring the name of the data table and the input content of the query field determined by the user, determining the corresponding query component in the query component set by using the corresponding relation, filling the name of the data table and the input content of the query field into the query language, and querying data in the data table according to the query field and the input content of the query field by using the corresponding query component.
10. The apparatus of claim 9, wherein the query field comprises a query condition field and a query result field;
the configuring unit configures the corresponding relation between each query component in the query component set and the name and query field of each data table, and comprises the following steps:
the configuration unit configures the corresponding relation between each query component in the query component set and the name of each data table, the query condition field and the query result field, wherein the query condition field and the query result field are pre-specified.
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| CN113722324A (en) * | 2021-08-30 | 2021-11-30 | 平安国际智慧城市科技股份有限公司 | Report generation method and device based on artificial intelligence, electronic equipment and medium |
| CN113722324B (en) * | 2021-08-30 | 2023-08-18 | 深圳平安智慧医健科技有限公司 | Report generation method and device based on artificial intelligence, electronic equipment and medium |
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