CN111639095B - Data table query method, device and storage medium - Google Patents
Data table query method, device and storage medium Download PDFInfo
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Abstract
The embodiment of the invention provides a data table query method, which comprises the following steps: generating SQL for inquiring the main table according to the received inquiry request and inquiring the main table information to obtain a main table inquiry result; inquiring auxiliary table information according to the associated fields in the main table inquiry result to obtain an auxiliary table inquiry result; and feeding back the main table query result and the auxiliary table query result to a client. By classifying the data tables, a simplified and easy-to-use query interface is provided, the original complex query logic is decomposed, the table look-up efficiency is improved, and the performance of an application system is further improved.
Description
Technical Field
The invention relates to the technical field of information, in particular to a data table query method, a data table query device and a storage medium.
Background
The relational database is a database which adopts a relational model to organize data, and stores the data in a form of rows and columns so as to be convenient for a user to understand. In a relational database, a series of rows and columns make up a table, and a series of tables make up the database. The user obtains the data in the database through query. Structured Query Language (SQL) is a database Query and programming Language for accessing data and querying, updating, and managing relational database systems.
Improving the performance of complex multi-table association query is one of the main challenges faced by the relational database, and although the relational database does much work in the aspect of query optimization, the query efficiency is still inevitably reduced when the data managed in a single table is increased and the associated tables are increased.
The distributed cache refers to a technical component which stores common data in a database in a distributed mode and provides operations such as query and the like. One important application of distributed caching is to speed up relational database queries.
However, for a distributed cache component supporting SQL query, due to the limitation of a query optimizer and the characteristics of data distribution adopted by the cache component, for complex query with multi-table association, if simply loading data in a database into a cache and running the original SQL, the performance cannot be improved, and even performance degradation may be brought.
Disclosure of Invention
The invention provides a data table query method and a data table query device, which solve the problem of low efficiency in the conventional data table query through a more flexible data table query strategy.
The embodiment of the invention provides a data table query method, which comprises the following steps: generating a main table query SQL according to the received query request and querying the main table information to obtain a main table query result; inquiring auxiliary table information according to the associated fields in the main table inquiry result to obtain an auxiliary table inquiry result; and feeding back the main table query result and the auxiliary table query result to a client.
The embodiment of the invention also provides a data table query device, which comprises a first query module, a second query module and a feedback module, wherein the first query module is used for generating the main table query SQL according to the received query request and querying the main table information to obtain the main table query result; the second query module is used for querying auxiliary table information according to the associated fields in the main table query result to obtain an auxiliary table query result; and the feedback module is used for feeding back the main table query result and the auxiliary table query result to the client.
Embodiments of the present invention further provide a computer-readable storage medium, which stores a computer program, and when the computer program is executed by a processor, the computer program implements any one of the methods in the embodiments of the present invention.
The embodiment of the present invention further provides an electronic device, which includes a memory and a processor, and the processor implements any one of the methods in the embodiments of the present invention by executing a program in the memory.
According to the data table query method and device provided by the embodiment of the invention, the data table is divided into the main table and the auxiliary table, the data table is classified, a simplified and easy-to-use query interface is provided, and the original complex query logic is decomposed, so that the query efficiency of multi-table association query is improved, and the performance of an application system is further improved.
Drawings
FIG. 1 is a flow chart of a method for querying a data table according to an embodiment of the present invention;
FIG. 2 is a block diagram of a data table lookup apparatus according to an embodiment of the present invention;
fig. 3 is a block diagram of another database query device according to an embodiment of the present invention.
Detailed Description
To make the objects, technical solutions and advantages of the present application more apparent, embodiments of the present application will be described in detail below with reference to the accompanying drawings. It should be noted that the embodiments and features of the embodiments in the present application may be arbitrarily combined with each other without conflict.
In addition, in the embodiments of the present invention, the words "optional" or "exemplary" are used to mean serving as an example, instance, or illustration. Any embodiment or design described as "optional" or "exemplary" in embodiments of the invention is not to be construed as preferred or advantageous over other embodiments or designs. Rather, use of the terms "optional" or "exemplary" are intended to present relevant concepts in a concrete fashion.
Fig. 1 is a flowchart of a data table query method according to an embodiment of the present invention, and as shown in fig. 1, the method according to the embodiment may include the following steps:
s102, generating a main table query SQL according to the received query request and querying main table information to obtain a main table query result;
s104, inquiring auxiliary table information according to the associated fields in the main table inquiry result to obtain an auxiliary table inquiry result;
and S106, feeding back the query result of the main table and the query result of the auxiliary table to the client.
By the data table query method and the data table query device, the data table is divided into the main table and the auxiliary table. The main table is usually a data table containing main service data, and the updating frequency is high (such as daily updating); the auxiliary table is usually a data table containing codes and mechanism definitions, and is updated less frequently (not updated every day), but is accessed very frequently, and may be accessed repeatedly in the same SQL query request, for example, by ID conversion of staff names, conversion of code values into user-friendly descriptions, etc., and the auxiliary table does not affect the number of SQL final results, and is only used for expanding SQL query information. The auxiliary table comprises a primary key field and a non-primary key field, and the non-primary key field needs to appear in the final query result; the primary key of the secondary table is present as an association field in the primary table of data for associating the primary table with the secondary table.
Optionally, an interface for externally providing a query data table includes the following inputs:
(1) A main table which needs to be associated and inquired in an SQL mode;
(2) The association mode between the main tables is as follows: inner association, left association and right association;
(3) A master table association condition;
(4) Additional query conditions on the master table;
(5) The main table inquires fields needing to be returned;
(6) Information that requires a secondary table lookup: the auxiliary table caches table names, field names which need to be used as key values to be inquired by the auxiliary table and field names which need to return inquiry values.
One or more columns should be determined for the primary table as a distribution key that will be used as input for data distribution policy formation if the primary table is placed into a distributed cache. The table classifications, field classifications, and distribution key definitions are stored as metadata for the system. After receiving the query request, automatically forming SQL queried by the main table according to the input query conditions.
Optionally, the querying the main table information according to the received query request includes: determining the query position of the main table according to the received query request; under the condition that the query position of the main table is a distributed cache, querying the main table information in the distributed cache; and in the case that the query position of the main table is a relational database, querying the information of the main table in the relational database.
Optionally, the determining the query location of the main table according to the received query request includes: judging whether the main table meets the following conditions: the main table is stored in the distributed cache, and the product of the row number of the main table is greater than a first threshold, and the distribution keys of the main tables are the same (i.e. the distribution keys of the plurality of main tables involved in the query are the same); if the judgment result is yes, determining the query position of the main table as a distributed cache; and under the condition that the judgment result is negative, determining the query position of the main table as a relational database.
Optionally, the query relates to a main table which needs to be associated with the query in an SQL manner, and the number of tables does not exceed 3. And obtaining query results of a plurality of main tables in the relational database or the distributed cache according to the strategy. ,
optionally, before querying the main table information according to the received query request, the method further includes: storing the main table in the distributed cache according to a preset strategy; and storing the secondary table in the distributed cache.
Optionally, the storing the main table in the distributed cache according to a preset policy includes: deciding whether to load the main table into the distributed cache based on any one of the following policies:
1) The system decides the strategy: and setting the data volume of the main table, and loading the main table into the distributed cache if the data volume of the table is greater than a certain threshold, such as 100 ten thousand pieces of data.
2) Manually setting a strategy: and manually setting a flag to load the main table into the distributed cache, and if the flag is set to be loaded, loading the main table into the distributed cache.
Optionally, the method further includes: under the condition that a main table data updating request is received, updating the main table in a relational database; and judging whether the main table is stored in the distributed cache or not, and updating the main table in the distributed cache if the judgment result is yes.
It should be noted that the master table may be stored in the distributed cache or may not be stored in the distributed cache. If the primary table is stored in the distributed cache, the data is updated not only in the relational database, but also in the distributed cache.
Optionally, the secondary table is stored in a distributed cache. Optionally, the auxiliary table is updated in the relational database and the distributed cache when the auxiliary table data update request is received.
Optionally, the data is updated at regular time, and the regular interval may be set to be updated every half day or once a day; when the data is updated, the method comprises the following steps: the tables involved are updated and the conditions are updated.
Optionally, an external method such as quasi-real-time data synchronization is adopted, that is, data update of a table corresponding to the external component capture database is referred to update the table data in the corresponding cache in a quasi-real-time manner.
Fig. 2 is a block diagram of a data table query device according to an embodiment of the present invention, as shown in fig. 2, the device according to this embodiment may include a first query module 22, a second query module 24, and a feedback module 26, wherein,
the first query module 22 is configured to generate a main table query SQL according to the received query request and query the main table information to obtain a main table query result;
the second query module 24 is configured to query the secondary table information according to the associated fields in the primary table query result, so as to obtain a secondary table query result;
the feedback module 26 is configured to feed back the primary table query result and the secondary table query result to the client.
Optionally, the first query module 22 includes a determining sub-module, a first query sub-module, and a second query sub-module, where the determining sub-module is configured to generate a main table query SQL according to the query request and determine a query position of the main table according to the received query request; the first query submodule is used for querying the information of the main table in the distributed cache under the condition that the query position of the main table is the distributed cache; the second query submodule is configured to query the information of the main table in the relational database when the query position of the main table is the relational database.
Optionally, the determining sub-module is specifically configured to generate a main table query SQL according to the query request, and determine whether the main table meets the following conditions: the main table is stored in the distributed cache, and the product of the row number of the main table is greater than a first threshold, and the distribution keys of the main tables are the same (i.e. the distribution keys of the plurality of main tables involved in the query are the same); determining that the query position of the main table is a distributed cache under the condition that the judgment result is yes; and under the condition that the judgment result is negative, determining the query position of the main table as a relational database.
Optionally, the apparatus further includes a storage module, configured to store the main table in the distributed cache according to a preset policy before querying information of the main table according to the received query request; and storing the secondary table in the distributed cache.
Optionally, the storage module is specifically configured to store the main table in the distributed cache when the data amount of the main table is greater than a second threshold.
Optionally, the apparatus further includes an update module, configured to update the main table in the relational database when a main table data update request is received; and judging whether the main table is stored in the distributed cache or not, and updating the main table in the distributed cache if the judgment result is yes.
Optionally, the updating module is further configured to update the auxiliary table in the relational database and the distributed cache when the auxiliary table data update request is received.
Fig. 3 is a block diagram of another database query device according to an embodiment of the present invention. The application system can directly access the relational database to inquire data and can also inquire the data in the distributed cache by means of the inquiry accelerating system. The following describes a database query method according to an embodiment of the present invention with reference to a specific application scenario.
Taking the common scenario of submitting and querying the reimbursement bill in the employee financial system as an example, the reimbursement bill system includes a reimbursement bill table (t _ close) for recording information of submitters, items, statuses, total amount and the like, and also includes record tables such as a reimbursement invoice table (t _ invoice) and a reimbursement bill approval history table (t _ approve), which correspond to the main tables in the foregoing embodiments. In addition to these main data records, there are data tables such as a code table (t _ code), an organization table (t _ org), a person information table (t _ staff), and the like, which correspond to the sub tables in the foregoing embodiments. Specifically, for example, each approval state of the reimbursement form is stored in the reimbursement form table (t _ close) as a state code (e.g., '10', '20', etc.), and the description information corresponding to the code (e.g., '10' corresponding to 'pending approval', '20' corresponding to 'approval pass') is stored in the code table.
When the reimbursement bill is inquired, due to the fact that different roles (submitter, approver and financial staff) and permissions exist, data and fields needing to be seen are different, SQL inquiry often needs to be associated with an reimbursement table, a bank table, an invoice table, an approval history record and the like, meanwhile, for various state codes (approval state, verification state and payment state) and the like in the reimbursement bill head table, multiple association code tables are needed to obtain corresponding Chinese descriptions, and for organization IDs, personnel IDs and the like recorded in the reimbursement bill head table and the approval table, corresponding tables are needed to be associated to obtain corresponding Chinese names. One section of SQL usually needs to be associated with a plurality of tables, particularly, a code table may be associated in one SQL for a plurality of times, the SQL is a complex SQL with a plurality of table associations, meanwhile, the code table is associated for a plurality of times, so that data hot spots are easily caused, and the overall SQL execution efficiency is not high.
The following is a multi-table query example of reimbursement invoice information:
by the method of the embodiment of the invention, the tables related to the query in the system are divided into a main table and an auxiliary table. The data record tables such as the reimbursement bill table, the invoice table, the examination and approval record table and the like are main tables, the updating and the change are frequent, but the query is generally carried out only once, and the number of query results is determined; the auxiliary tables are dimension tables such as code tables, personnel tables and organizational structure tables, data are relatively stable, but frequent access is needed, only query fields are supplemented, and the number of results is not influenced.
After metadata such as a main table, an auxiliary table list and the like are imported into a system, an interface realized by the system is deployed, and the interface comprises the following inputs:
(1) The main table of the query needs to be associated in an SQL mode: the reimbursement bill table t _ close and the reimbursement invoice table t _ invoice;
(2) The association mode between the main tables is as follows: internal association;
(3) The correlation condition is as follows: the user numbers of the main table are the same i.c _ ID = c.id;
(4) Additional query conditions on the main table, wherein the query dates are from '2018-06-01' to
'2018-08-31', and d c.o _ ID =1234;
(5) Main table lookup fields that need to be returned directly:
T.C_NO,T.C_ID,T.I_NO,T.I_CODE,T.I_DATE,T.T_FILED1,T.T_FIELD 2,T.T_FIELD3,T.I_DATE,T.D_STATUS,
T.D_CODE,T.C_STATUS,T.V_CODE,T.D_DATE,T.O_NAME,T.ID
(6) Information that requires a secondary table lookup: the auxiliary table caches the table name, which is used as the field name of the query key value and the field name of the return value:
T_CODE:(D_STATUS,D_STATUS_NAME),
(D_CODE,D_CODE_NAME),(C_STATUS C_STATUS_NAME)，
(V_CODE,V_CODE_NAME),(B_STATUS,B_STATUS_NAME),
(I_TYPE,I_TYPE_NAME)
T_ORG:(O_ID,ID，NAME)
after receiving the query request, completing the query and returning the result according to the following steps:
(1) Receiving input, and automatically splicing SQL inquired by a main table;
(2) Automatically judging whether the main table query SQL is queried in the distributed cache or not according to the following strategies: whether all the involved main tables have been loaded into the cache; whether the product of the number of rows of the primary table involved is greater than a certain threshold (e.g., 1000 ten thousand); whether the distribution keys of the plurality of main tables involved are the same.
If the above conditions are satisfied simultaneously, the SQL query of the main table is performed in the cache, and if the above conditions are not satisfied, the SQL query of the main table is completed in the relational database.
(3) Obtaining the query results of the reimbursement bill table and the reimbursement invoice table according to the strategy in the step (2);
(4) Inquiring the auxiliary table according to the associated field of the auxiliary table related to the inquiry result of the main table, and acquiring a return field according to the field name needing to be returned in the inquiry;
(5) And (4) combining the results of the steps (3) and (4) and returning the results to the client.
The embodiment of the invention also provides an electronic device, which comprises a processor and a memory; the number of processors in the electronic device may be one or more, and the memory, which is a computer-readable storage medium, may be used to store a computer-executable program. The processor executes various functional applications of the electronic device and data processing by executing software programs and instructions stored in the memory, namely, the method in any one of the above embodiments is realized.
Embodiments of the present application also provide a storage medium containing computer-executable instructions, which when executed by a computer processor implement the method in any of the above embodiments.
Optionally, the processor implements a method for querying a database table by executing an instruction, where the method includes:
s1, generating a main table query SQL according to a received query request and querying main table information to obtain a main table query result;
s2, inquiring auxiliary table information according to the associated fields in the main table inquiry result to obtain an auxiliary table inquiry result;
and S3, feeding back the query result of the main table and the query result of the auxiliary table to the client.
The above are merely exemplary embodiments of the present application, and are not intended to limit the scope of the present application.
In general, the various embodiments of the application may be implemented in hardware or special purpose circuits, software, logic or any combination thereof. For example, some aspects may be implemented in hardware, while other aspects may be implemented in firmware or software which may be executed by a controller, microprocessor or other computing device, although the application is not limited thereto.
Embodiments of the application may be implemented by a processor executing computer program instructions, for example in a processor entity, or by hardware, or by a combination of software and hardware. The computer program instructions may be assembly instructions, instruction Set Architecture (ISA) instructions, machine related instructions, microcode, firmware instructions, state setting data, or source code or object code written in any combination of one or more programming languages.
The block diagrams of any logic flows in the figures of this application may represent program steps, or may represent interconnected logic circuits, modules, and functions, or may represent a combination of program steps and logic circuits, modules, and functions. The computer program may be stored on a memory. The memory may be of any type suitable to the local technical environment and may be implemented using any suitable data storage technology, such as, but not limited to, read Only Memory (ROM), random Access Memory (RAM), optical storage devices and systems (digital versatile disks, DVDs, or CD discs), etc. The computer readable medium may include a non-transitory storage medium. The data processor may be of any type suitable to the local technical environment, such as but not limited to general purpose computers, special purpose computers, microprocessors, digital Signal Processors (DSPs), application Specific Integrated Circuits (ASICs), programmable logic devices (FGPAs), and processors based on a multi-core processor architecture.
The foregoing has provided by way of exemplary and non-limiting examples a detailed description of exemplary embodiments of the present application. Various modifications and adaptations to the foregoing embodiments may become apparent to those skilled in the relevant arts in view of the following drawings and the appended claims without departing from the scope of the invention. Therefore, the proper scope of the invention is to be determined according to the claims.
Claims (9)
1. A method for data table lookup, comprising:
generating a main table query SQL according to the received query request and querying main table information to obtain main table query results, including;
generating a main table query SQL according to the received query request and determining the query position of the main table, wherein the method comprises the following steps:
judging whether the main table meets the following conditions: the main table is stored in a distributed cache, the product of the row number of the main table is larger than a first threshold value, and the distribution keys of the main table are the same;
if the judgment result is yes, determining the query position of the main table as a distributed cache;
under the condition that the judgment result is negative, determining the query position of the main table as a relational database;
inquiring auxiliary table information according to the associated fields in the main table inquiry result to obtain an auxiliary table inquiry result;
and feeding back the main table query result and the auxiliary table query result to a client.
2. The method of claim 1, wherein generating a primary table query SQL and querying primary table information from the received query request comprises:
under the condition that the query position of the main table is a distributed cache, querying the main table information in the distributed cache;
and under the condition that the query position of the main table is a relational database, querying the main table information in the relational database.
3. The method of any of claims 1-2, further comprising, prior to querying primary table information according to the received query request:
storing the main table in the distributed cache according to a preset strategy; and
storing the secondary table in the distributed cache.
4. The method of claim 3, wherein the storing the primary table in the distributed cache according to a preset policy comprises:
and when the data volume of the main table is larger than a second threshold value, storing the main table in the distributed cache.
5. The method of claim 1 or 2, wherein the method further comprises:
updating the master table in the relational database in the case of receiving a master table data update request; and
and judging whether the main table is stored in the distributed cache, and updating the main table in the distributed cache under the condition that the judgment result is yes.
6. The method of claim 1 or 2, wherein the method further comprises:
and updating the auxiliary table in the relational database and the distributed cache under the condition of receiving an auxiliary table data updating request.
7. A data table query device is characterized by comprising a first query module, a second query module and a feedback module, wherein,
the first query module is used for generating a main table query SQL according to the received query request and querying the main table information to obtain a main table query result;
the first query module comprises a determining submodule for generating a main table query SQL according to the query request and determining a query position of the main table according to the received query request, and further comprises:
judging whether the main table meets the following conditions: the main table is stored in a distributed cache, the product of the row number of the main table is larger than a first threshold value, and the distribution keys of the main table are the same;
if the judgment result is yes, determining the query position of the main table as a distributed cache;
under the condition that the judgment result is negative, determining the query position of the main table as a relational database;
the second query module is used for querying auxiliary table information according to the associated fields in the main table query result to obtain an auxiliary table query result;
and the feedback module is used for feeding back the main table query result and the auxiliary table query result to the client.
8. A computer-readable storage medium, characterized in that the computer-readable storage medium stores a computer program which, when executed by a processor, implements the method according to any one of claims 1-6.
9. An electronic device comprising a memory and a processor, wherein the processor implements the method of any one of claims 1-6 by executing a computer program in the memory.
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Citations (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP2000020385A (en) * | 1998-07-07 | 2000-01-21 | Hitachi Ltd | Data retrieving system and data caching method |
| CN105930407A (en) * | 2016-04-18 | 2016-09-07 | 北京思特奇信息技术股份有限公司 | Cross-database associated query method and system for distributed database |
| CN108170815A (en) * | 2017-12-29 | 2018-06-15 | 中国银联股份有限公司 | A kind of data processing method, device and storage medium |
| CN108268476A (en) * | 2016-12-30 | 2018-07-10 | 北京国双科技有限公司 | Data query method and device |
| CN108932313A (en) * | 2018-06-20 | 2018-12-04 | 斑马网络技术有限公司 | Data processing method, device, electronic equipment and storage medium |
| CN109656947A (en) * | 2018-11-09 | 2019-04-19 | 金蝶软件（中国）有限公司 | Data query method, apparatus, computer equipment and storage medium |
| CN109766354A (en) * | 2018-12-04 | 2019-05-17 | 北京辰森世纪科技股份有限公司 | Optimization method, device and the equipment of business datum inquiry |
Family Cites Families (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20180173762A1 (en) * | 2016-12-15 | 2018-06-21 | Futurewei Technologies, Inc. | System and Method of Adaptively Partitioning Data to Speed Up Join Queries on Distributed and Parallel Database Systems |
-
2020
- 2020-05-27 CN CN202010464356.6A patent/CN111639095B/en active Active
Patent Citations (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP2000020385A (en) * | 1998-07-07 | 2000-01-21 | Hitachi Ltd | Data retrieving system and data caching method |
| CN105930407A (en) * | 2016-04-18 | 2016-09-07 | 北京思特奇信息技术股份有限公司 | Cross-database associated query method and system for distributed database |
| CN108268476A (en) * | 2016-12-30 | 2018-07-10 | 北京国双科技有限公司 | Data query method and device |
| CN108170815A (en) * | 2017-12-29 | 2018-06-15 | 中国银联股份有限公司 | A kind of data processing method, device and storage medium |
| CN108932313A (en) * | 2018-06-20 | 2018-12-04 | 斑马网络技术有限公司 | Data processing method, device, electronic equipment and storage medium |
| CN109656947A (en) * | 2018-11-09 | 2019-04-19 | 金蝶软件（中国）有限公司 | Data query method, apparatus, computer equipment and storage medium |
| CN109766354A (en) * | 2018-12-04 | 2019-05-17 | 北京辰森世纪科技股份有限公司 | Optimization method, device and the equipment of business datum inquiry |
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