CN111581236A - Data query method and device - Google Patents
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- CN111581236A CN111581236A CN202010256459.3A CN202010256459A CN111581236A CN 111581236 A CN111581236 A CN 111581236A CN 202010256459 A CN202010256459 A CN 202010256459A CN 111581236 A CN111581236 A CN 111581236A
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- G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
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- G06F16/245—Query processing
- G06F16/2453—Query optimisation
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Abstract
The application relates to a data query method and a data query device, wherein the method comprises the following steps: when receiving a query request, converting the initial query parameters into interval query parameters; determining the interval of the query result according to the interval query parameter; and determining a query result according to the initial query parameters in the determined interval. The scheme of the application is based on a database index technology, the data columns with excessive data different values are subjected to interval division, and the interval is locked and then screened during query, so that the data query speed can be obviously improved; the execution steps of the scheme can be packaged into technical components, transparent use is provided for application, and normal development work is not influenced.
Description
Technical Field
The application relates to the technical field of database indexing, in particular to a data query method and device.
Background
An index is a structure that orders values of one or more columns in a database table, and can also be understood as: the auxiliary data structure of the record ID meeting the limitation condition can be found as soon as possible by the information searcher. One of the main purposes of the index is to speed up the retrieval of data in the table, and to use the index to quickly access specific information in the database table.
However, indexing a table comes at a corresponding cost: firstly, the index created in the database also occupies the storage space of the database, and secondly, when the data in the table is modified, such as adding, deleting or modifying operation, the index also needs to be dynamically maintained, so that the maintenance of the database takes much time.
From a data search implementation perspective, an index is also another type of file/record that contains various records that may indicate related data records. Each index has a corresponding search code, and any subset of the character segments can form a search code. Thus, the index is equivalent to a collection of all data directory entries that provides the various efficient support required for locating all data directory entries for a given search code value.
In the related art, in the current database indexing process, if different values of each row of data are too much, such as bank customer balance data, the speed of query cannot be increased by establishing the index, but the storage space of the index is increased, table scanning is caused during query, and the query performance is very low. In a bank marketing system, searching according to balance is a common scene; however, no mature technical scheme exists at present, and the query performance can be improved under the scenes.
Disclosure of Invention
To overcome, at least to some extent, the problems in the related art, the present application provides a data query method and apparatus.
According to a first aspect of embodiments of the present application, there is provided a data query method, including:
when receiving a query request, converting the initial query parameters into interval query parameters;
determining the interval of the query result according to the interval query parameter;
and determining a query result according to the initial query parameters in the determined interval.
Further, the method further comprises:
dividing a data column in a data table into a plurality of intervals according to preset interval parameters;
and establishing indexes for the divided intervals.
Further, the data columns in the data table are floating point data columns;
the dividing the data columns in the data table into a plurality of intervals according to preset interval parameters comprises:
determining an integer column corresponding to the floating point data column according to a preset interval parameter;
the obtained integer column is added to the data table.
Further, the determining the integer columns corresponding to the floating point data columns includes:
determining a mapping relation from floating point data to an integer according to a preset interval parameter;
and mapping each floating point data of the floating point data column into a corresponding integer according to the mapping relation.
Further, the converting the initial query parameter into the interval query parameter includes:
acquiring initial query parameters from the query request;
and mapping the initial query parameters to corresponding interval query parameters according to the mapping relation.
Further, the determining the interval where the query result is located according to the interval query parameter includes:
determining an interval upper limit and an interval lower limit according to the interval query parameters;
and determining the interval between the upper limit and the lower limit of the interval as the interval of the query result.
Further, the initial query parameter is floating point data;
the determining a query result according to the initial query parameter includes:
and screening the floating point data in the determined interval, and determining a screening result as a query result.
According to a second aspect of embodiments of the present application, there is provided a data query apparatus including:
the conversion module is used for converting the initial query parameters into interval query parameters when receiving the query request;
the interval determining module is used for determining the interval of the query result according to the interval query parameters;
and the result determining module is used for determining a query result according to the initial query parameters in the determined interval.
According to a third aspect of embodiments of the present application, there is provided a computer device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, the processor implementing the following steps when executing the computer program: when receiving a query request, converting the initial query parameters into interval query parameters; determining the interval of the query result according to the interval query parameter; and determining a query result according to the initial query parameters in the determined interval.
According to a fourth aspect of embodiments of the present application, there is provided a computer-readable storage medium having stored thereon a computer program which, when executed by a processor, performs the steps of: when receiving a query request, converting the initial query parameters into interval query parameters; determining the interval of the query result according to the interval query parameter; and determining a query result according to the initial query parameters in the determined interval.
The technical scheme provided by the embodiment of the application has the following beneficial effects:
the scheme of the application is based on a database index technology, the data columns with excessive data different values are subjected to interval division, and the interval is locked and then screened during query, so that the data query speed can be obviously improved; the execution steps of the scheme can be packaged into technical components, transparent use is provided for application, and normal development work is not influenced.
It is to be understood that both the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the application.
Drawings
The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the present application and together with the description, serve to explain the principles of the application.
FIG. 1 is a flow chart illustrating a method of data querying in accordance with an exemplary embodiment.
FIG. 2 is a data flow diagram illustrating a method of data query in accordance with an exemplary embodiment.
Fig. 3 is a schematic diagram of a test result of a data test performed by applying the data query method of the present application.
Detailed Description
Reference will now be made in detail to the exemplary embodiments, examples of which are illustrated in the accompanying drawings. When the following description refers to the accompanying drawings, like numbers in different drawings represent the same or similar elements unless otherwise indicated. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with the present application. Rather, they are merely examples of methods and apparatus consistent with certain aspects of the present application, as detailed in the appended claims.
FIG. 1 is a flow chart illustrating a method of data querying in accordance with an exemplary embodiment. The method can be applied to a database indexing technology, and specifically comprises the following steps:
step S1: when receiving a query request, converting the initial query parameters into interval query parameters;
step S2: determining the interval of the query result according to the interval query parameter;
step S3: and determining a query result according to the initial query parameters in the determined interval.
The scheme of the application is based on a database index technology, the data columns with excessive data different values are subjected to interval division, and the interval is locked and then screened during query, so that the data query speed can be obviously improved; the execution steps of the scheme can be packaged into technical components, transparent use is provided for application, and normal development work is not influenced.
In some embodiments, the method further comprises:
dividing a data column in a data table into a plurality of intervals according to preset interval parameters;
and establishing indexes for the divided intervals.
According to the scheme of the application, before the specific query step is carried out, the data in the data table needs to be preprocessed. For example, if the interval parameter is 5 ten thousand, a plurality of intervals such as 0-50000, 50000-100000, 100000-150000, etc. need to be divided; then, indexes are established for the intervals, such as the interval 0-50000 corresponding to an integer 001, the interval 50000-100000 corresponding to an integer 002, the interval 100000-150000 corresponding to an integer 003, and the like.
In some embodiments, the data columns in the data table are floating point data columns;
the dividing the data columns in the data table into a plurality of intervals according to preset interval parameters comprises:
determining an integer column corresponding to the floating point data column according to a preset interval parameter;
the obtained integer column is added to the data table.
Floating point data is a column of data in the data table (column F) and the preprocessing process requires the addition of a column of data in the data table (column Z). For example, a floating point datum (column F datum) is 1234.656, and the interval parameter is 5 ten thousand; according to the interval parameter, the integer column (column Z) data corresponding to the floating point data is determined to be 001, and then 001 is written into the corresponding position of the column Z in the data table.
In some embodiments, the determining the integer columns corresponding to the floating point data columns includes:
determining a mapping relation from floating point data to an integer according to a preset interval parameter;
and mapping each floating point data of the floating point data column into a corresponding integer according to the mapping relation.
The mapping relationship is that the interval 0-50000 corresponds to an integer 001, the interval 50000-100000 corresponds to an integer 002, the interval 100000-150000 corresponds to an integer 003, and the like.
The following describes the scheme of the present application in an expanded manner with reference to a specific application scenario.
As shown in fig. 2, the solution of the present application is based on a database indexing technique, and for floating point data of a balance class of a client, the floating point data is first divided into an interval according to 5 ten thousand (which can be customized by parameters) to obtain an integer, and then an index is established on the integer, so that an index is established on a limited data set, and balance class data screening is performed in each interval, which can greatly reduce table scanning, and can significantly improve query performance.
Referring to FIG. 2, SQL is queried by the column F values, the query statement is:
"Select from Table
where column F-1234.656 "
Referring to fig. 2, parameters are automatically combined, and the combined query statement is:
"Select from Table
where column Z between interval upper limit and interval lower limit
And column F-1234.656 "
In some embodiments, the converting the initial query parameters into interval query parameters includes:
acquiring initial query parameters from the query request;
and mapping the initial query parameters to corresponding interval query parameters according to the mapping relation.
In some embodiments, the determining, according to the interval query parameter, an interval in which the query result is located includes:
determining an interval upper limit and an interval lower limit according to the interval query parameters;
and determining the interval between the upper limit and the lower limit of the interval as the interval of the query result.
In some embodiments, the initial query parameter is floating point data;
the determining a query result according to the initial query parameter includes:
and screening the floating point data in the determined interval, and determining a screening result as a query result.
Referring to fig. 3, the scheme is tested on Sybase ASE and Sybase IQ, and the test is divided into two groups, and the second group uses the technical scheme of the application. The two sets of test comparison data are as follows:
through experimental data, the scheme of the application can shorten the query time under the same system environment, and has equivalent ASE lifting ratio reaching 495 times and 16 times lifting effect on IQ.
The scheme of the application is mainly based on a database indexing technology, indexes generally adopt a B + tree structure, indexes are established for different value-limited columns in a database, and the data types such as integers, character types and the like can obviously improve the data query speed.
The scheme of the application can be applied to the use scene of bank balance data, floating point numbers are converted into integers, and indexes are built for the integers, so that the query performance is improved. The scheme of the application also encapsulates the conversion storage function of the data column and the Sql conversion function of the query parameters into technical components (namely an automatic data conversion component and an automatic query SQL conversion component), provides transparent use for application, and does not influence normal development work.
The present application further provides the following embodiments:
a data query apparatus, comprising:
the conversion module is used for converting the initial query parameters into interval query parameters when receiving the query request;
the interval determining module is used for determining the interval of the query result according to the interval query parameters;
and the result determining module is used for determining a query result according to the initial query parameters in the determined interval.
With regard to the apparatus in the above embodiment, the specific steps in which the respective modules perform operations have been described in detail in the embodiment related to the method, and are not described in detail herein.
The present application further provides the following embodiments:
a computer device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, the processor implementing the following steps when executing the computer program: when receiving a query request, converting the initial query parameters into interval query parameters; determining the interval of the query result according to the interval query parameter; and determining a query result according to the initial query parameters in the determined interval.
The present application further provides the following embodiments:
a computer-readable storage medium, on which a computer program is stored which, when executed by a processor, carries out the steps of: when receiving a query request, converting the initial query parameters into interval query parameters; determining the interval of the query result according to the interval query parameter; and determining a query result according to the initial query parameters in the determined interval.
It is understood that the same or similar parts in the above embodiments may be mutually referred to, and the same or similar parts in other embodiments may be referred to for the content which is not described in detail in some embodiments.
It should be noted that, in the description of the present application, the terms "first", "second", etc. are used for descriptive purposes only and are not to be construed as indicating or implying relative importance. Further, in the description of the present application, the meaning of "a plurality" means at least two unless otherwise specified.
Any process or method descriptions in flow charts or otherwise described herein may be understood as representing modules, segments, or portions of code which include one or more executable instructions for implementing specific logical functions or steps of the process, and the scope of the preferred embodiments of the present application includes other implementations in which functions may be executed out of order from that shown or discussed, including substantially concurrently or in reverse order, depending on the functionality involved, as would be understood by those reasonably skilled in the art of the present application.
It should be understood that portions of the present application may be implemented in hardware, software, firmware, or a combination thereof. In the above embodiments, the various steps or methods may be implemented in software or firmware stored in memory and executed by a suitable instruction execution system. For example, if implemented in hardware, as in another embodiment, any one or combination of the following techniques, which are known in the art, may be used: a discrete logic circuit having a logic gate circuit for implementing a logic function on a data signal, an application specific integrated circuit having an appropriate combinational logic gate circuit, a Programmable Gate Array (PGA), a Field Programmable Gate Array (FPGA), or the like.
It will be understood by those skilled in the art that all or part of the steps carried by the method for implementing the above embodiments may be implemented by hardware related to instructions of a program, which may be stored in a computer readable storage medium, and when the program is executed, the program includes one or a combination of the steps of the method embodiments.
In addition, functional units in the embodiments of the present application may be integrated into one processing module, or each unit may exist alone physically, or two or more units are integrated into one module. The integrated module can be realized in a hardware mode, and can also be realized in a software functional module mode. The integrated module, if implemented in the form of a software functional module and sold or used as a stand-alone product, may also be stored in a computer readable storage medium.
The storage medium mentioned above may be a read-only memory, a magnetic or optical disk, etc.
In the description herein, reference to the description of the term "one embodiment," "some embodiments," "an example," "a specific example," or "some examples," etc., means that a particular feature, structure, material, or characteristic described in connection with the embodiment or example is included in at least one embodiment or example of the application. In this specification, the schematic representations of the terms used above do not necessarily refer to the same embodiment or example. Furthermore, the particular features, structures, materials, or characteristics described may be combined in any suitable manner in any one or more embodiments or examples.
Although embodiments of the present application have been shown and described above, it is understood that the above embodiments are exemplary and should not be construed as limiting the present application, and that variations, modifications, substitutions and alterations may be made to the above embodiments by those of ordinary skill in the art within the scope of the present application.
Claims (10)
1. A method for querying data, comprising:
when receiving a query request, converting the initial query parameters into interval query parameters;
determining the interval of the query result according to the interval query parameter;
and determining a query result according to the initial query parameters in the determined interval.
2. The method of claim 1, further comprising:
dividing a data column in a data table into a plurality of intervals according to preset interval parameters;
and establishing indexes for the divided intervals.
3. The method of claim 2, wherein the data columns in the data table are floating point data columns;
the dividing the data columns in the data table into a plurality of intervals according to preset interval parameters comprises:
determining an integer column corresponding to the floating point data column according to a preset interval parameter;
the obtained integer column is added to the data table.
4. The method of claim 3, wherein determining the integer columns corresponding to the floating point data columns comprises:
determining a mapping relation from floating point data to an integer according to a preset interval parameter;
and mapping each floating point data of the floating point data column into a corresponding integer according to the mapping relation.
5. The method of claim 4, wherein converting the initial query parameters into interval query parameters comprises:
acquiring initial query parameters from the query request;
and mapping the initial query parameters to corresponding interval query parameters according to the mapping relation.
6. The method according to any one of claims 1 to 5, wherein the determining the interval in which the query result is located according to the interval query parameter includes:
determining an interval upper limit and an interval lower limit according to the interval query parameters;
and determining the interval between the upper limit and the lower limit of the interval as the interval of the query result.
7. The method of any of claims 1-5, wherein the initial query parameters are floating point data;
the determining a query result according to the initial query parameter includes:
and screening the floating point data in the determined interval, and determining a screening result as a query result.
8. A data query apparatus, comprising:
the conversion module is used for converting the initial query parameters into interval query parameters when receiving the query request;
the interval determining module is used for determining the interval of the query result according to the interval query parameters;
and the result determining module is used for determining a query result according to the initial query parameters in the determined interval.
9. A computer device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, characterized in that the steps of the method of any of claims 1 to 7 are implemented when the computer program is executed by the processor.
10. A computer-readable storage medium, on which a computer program is stored, which, when being executed by a processor, carries out the steps of the method of any one of claims 1 to 7.
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