CN110825953B - Data query method, device and equipment - Google Patents
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Classifications
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/90—Details of database functions independent of the retrieved data types
- G06F16/95—Retrieval from the web
- G06F16/953—Querying, e.g. by the use of web search engines
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
- G06F16/24—Querying
- G06F16/245—Query processing
- G06F16/2457—Query processing with adaptation to user needs
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
- G06F16/24—Querying
- G06F16/245—Query processing
- G06F16/2458—Special types of queries, e.g. statistical queries, fuzzy queries or distributed queries
- G06F16/2474—Sequence data queries, e.g. querying versioned data
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/90—Details of database functions independent of the retrieved data types
- G06F16/95—Retrieval from the web
- G06F16/953—Querying, e.g. by the use of web search engines
- G06F16/9538—Presentation of query results
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q10/00—Administration; Management
- G06Q10/08—Logistics, e.g. warehousing, loading or distribution; Inventory or stock management
- G06Q10/083—Shipping
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- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02D—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN INFORMATION AND COMMUNICATION TECHNOLOGIES [ICT], I.E. INFORMATION AND COMMUNICATION TECHNOLOGIES AIMING AT THE REDUCTION OF THEIR OWN ENERGY USE
- Y02D10/00—Energy efficient computing, e.g. low power processors, power management or thermal management
Abstract
The application provides a data query method, a device and equipment, wherein the method comprises the following steps: receiving an input query condition; distributing a query thread to query according to the query condition to obtain a data set corresponding to the query condition; and performing set splicing on the data sets according to a preset splicing mode to obtain a query result. The method and the device realize that different query conditions adopt different threads to query, and improve the flexibility and the query efficiency of data query.
Description
Technical Field
The present application relates to the field of information technologies, and in particular, to a data query method, device and equipment.
Background
With the development of logistics traffic, the traffic data query volume is larger and larger. The logistics data of the users are generally stored in a special database, and the huge pressure is brought to the database due to the increasing data query quantity.
In the prior art, when data is queried, a user inputs a query keyword through a terminal, and then a search engine queries the data in a database. Sometimes, the data volume queried at one time is huge, so that huge calculation pressure is brought to a query system, and the data volume meeting the query keywords often has a plurality of concurrent conditions, so that the query result is not convenient for users to review.
Disclosure of Invention
An object of an embodiment of the present invention is to provide a data query method, device, and equipment, so as to allocate a corresponding thread for query according to a query condition input by a user, so as to obtain a query result meeting requirements.
An embodiment of the present application provides a data query method, including: receiving an input query condition; distributing a query thread to query according to the query condition to obtain a data set corresponding to the query condition; and performing set splicing on the data sets according to a preset splicing mode to obtain a query result.
In one embodiment, the allocating the query thread to query according to the query condition, to obtain the dataset corresponding to the query condition includes: obtaining the data volume corresponding to the query condition according to the query condition; dividing the data volume according to a preset rule to obtain a plurality of groups of sub-data volumes; distributing corresponding target query threads according to each group of sub data volume; and querying the data set conforming to the query condition according to the target query thread and the query condition.
In one embodiment, the allocating the corresponding target query thread according to each group of the sub-data amounts includes: and distributing a corresponding data volume query interval for the target query thread according to the sub data volume corresponding to the target query thread.
In one embodiment, said querying the dataset for compliance with the query condition according to the target query thread and the query condition comprises: acquiring a target data set corresponding to the query condition according to the target query thread; judging whether the target data set has a plurality of concurrent data volumes; if a plurality of data volumes exist in the target data set in parallel, respectively setting identification information for the plurality of data volumes in parallel; sequentially sequencing the concurrent data volumes in the target data set according to the identification information to obtain a first data set conforming to the query condition; and if the target data set does not have a plurality of concurrent data volumes, sequencing the data in the target data set according to a preset sequencing rule to obtain a second data set which accords with the query condition.
In one embodiment, the query conditions include: one or more of a customer number, a data date, and a data amount.
A second aspect of an embodiment of the present application provides a data query device, including: the receiving module is used for receiving the input query condition; the query module is used for distributing a query thread to query according to the query condition to obtain a data set corresponding to the query condition; and the splicing module is used for carrying out set splicing on the data sets according to a preset splicing mode to obtain a query result.
In one embodiment, the query module is configured to: obtaining the data volume corresponding to the query condition according to the query condition; dividing the data volume according to a preset rule to obtain a plurality of groups of sub-data volumes; distributing corresponding target query threads according to each group of sub data volume; and querying the data set conforming to the query condition according to the target query thread and the query condition.
In one embodiment, the allocating the corresponding target query thread according to each group of the sub-data amounts includes: and distributing a corresponding data volume query interval for the target query thread according to the sub data volume corresponding to the target query thread.
In one embodiment, said querying the dataset for compliance with the query condition according to the target query thread and the query condition comprises: acquiring a target data set corresponding to the query condition according to the target query thread; judging whether the target data set has a plurality of concurrent data volumes; if a plurality of data volumes exist in the target data set in parallel, respectively setting identification information for the plurality of data volumes in parallel; sequentially sequencing the concurrent data volumes in the target data set according to the identification information to obtain a first data set conforming to the query condition; and if the target data set does not have a plurality of concurrent data volumes, sequencing the data in the target data set according to a preset sequencing rule to obtain a second data set which accords with the query condition.
In one embodiment, the query conditions include: one or more of a customer number, a data date, and a data amount.
A third aspect of the embodiments of the present application provides an electronic device, including: a memory for storing a computer program; the processor is configured to execute the method according to the first aspect of the embodiments of the present application and any one of the embodiments of the present application, so as to allocate a corresponding thread for querying according to a query condition input by a user, thereby obtaining a query result meeting the requirement.
According to the data query method, the device and the equipment, corresponding query threads are distributed for data query according to the received query conditions input by the user, a data set conforming to the query conditions is obtained, the data set is spliced in a set manner according to the preset splicing manner, a final query result is obtained, different threads are adopted for query under different query conditions, and the flexibility and the query efficiency of data query are improved.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings that are needed in the embodiments of the present application will be briefly described below, it should be understood that the following drawings only illustrate some embodiments of the present application and should not be considered as limiting the scope, and other related drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.
Fig. 1 is a schematic structural diagram of an electronic device according to an embodiment of the present application;
FIG. 2 is a flow chart of a data query method according to an embodiment of the present application;
FIG. 3 is a flow chart of a data query method according to an embodiment of the present application;
FIG. 4 is a flow chart of a data query method according to an embodiment of the present application;
fig. 5 is a schematic structural diagram of a data query device according to an embodiment of the present application.
Detailed Description
The technical solutions in the embodiments of the present application will be described below with reference to the drawings in the embodiments of the present application. In the description of the present application, the terms "first," "second," and the like are used merely to distinguish between descriptions and are not to be construed as indicating or implying relative importance.
As shown in fig. 1, the present embodiment provides an electronic device 100, including: at least one processor 11 and a memory 12, one processor being exemplified in fig. 1. The processor 11 and the memory 12 are connected through the bus 10, and the memory 12 stores instructions executable by the processor 11, and the instructions are executed by the processor 11 to allocate corresponding threads for inquiry according to inquiry conditions input by a user, so as to obtain an inquiry result meeting requirements.
Please refer to fig. 2, which is a data query method according to an embodiment of the present application, the method may be executed by the electronic device 100 shown in fig. 1, so as to allocate corresponding threads for query according to the query condition input by the user, so as to obtain a query result meeting the requirement. The method comprises the following steps:
step 201: an input query condition is received.
In this step, when the user needs to query data, the query terminal may input a corresponding query condition, and the query terminal receives the query condition according to the operation of the user.
In one embodiment, the query conditions include: one or more of a customer number, a data date, and a data amount. The query conditions may also be keywords entered by the user.
Step 202: and distributing the query threads to query according to the query conditions to obtain a data set corresponding to the query conditions.
In this step, the query conditions input by the user are different, the corresponding data amounts are often different, and some of the query conditions correspond to a large amount of data, and some of the query conditions are small. Different threads can query data in corresponding databases according to query resources, each thread can query corresponding data, and the data sets are data sets meeting query conditions. By allocating proper threads for different query conditions to query, query resources can be reasonably utilized.
Step 203: and performing set splicing on the data sets according to a preset splicing mode to obtain a query result.
In this step, the data sets obtained in step 202 are the results of the query performed by each thread, and in an embodiment, the data sets may be spliced together according to a preset splicing manner to obtain a final query result, where the preset splicing rule may be to splice the corresponding data sets according to the sequence number of each thread.
According to the data query method, corresponding query threads are distributed for data query according to the received input query conditions, so that a data set conforming to the query conditions is obtained, the data set is spliced together according to the preset splicing mode, a final query result is obtained, different threads are adopted for query under different query conditions, and the flexibility and the query efficiency of data query are improved.
Please refer to fig. 3, which is a data query method according to an embodiment of the present application, the method may be executed by the electronic device 100 shown in fig. 1, so as to allocate corresponding threads for query according to the query condition input by the user, so as to obtain a query result meeting the requirement. The method comprises the following steps:
step 301: an input query condition is received. See the description of step 201 in the above embodiments for details.
Step 302: and obtaining the data volume corresponding to the query condition according to the query condition.
In this step, after the user inputs the query condition to query each time, the query record is recorded, wherein the query record includes the data quantity corresponding to the query condition, and the corresponding relation table of the query condition and the data quantity can be established according to the previous data query record. When the query condition of the user is received again, the corresponding data volume is searched and determined according to the corresponding relation table.
Step 303: dividing the data volume according to a preset rule to obtain a plurality of groups of sub-data volumes.
In this step, the data size corresponding to the query condition is divided according to a preset rule, for example, the data size is 10 ten thousand, and the data size can be divided into 8 groups of sub-data sizes, and each group of sub-data sizes has 12500 data sizes.
Step 304: and distributing corresponding target query threads according to each group of sub-data volume.
In this step, as in step 303, each group of sub-data amounts is divided into 12500 data amounts, and then corresponding target query threads are allocated to 8 groups of sub-data amounts, so as to allocate a suitable thread number for the current data query.
Step 305: and querying the data set conforming to the query conditions according to the target query thread and the query conditions.
In this step, data query is performed on 12500 data amounts obtained corresponding to the query conditions according to the assigned target query threads, respectively, and each target query thread obtains a corresponding data set according to the query conditions, respectively.
Step 306: and performing set splicing on the data sets according to a preset splicing mode to obtain a query result. See for details the description of step 203 in the above embodiments.
Please refer to fig. 4, which is a data query method according to an embodiment of the present application, the method may be executed by the electronic device 100 shown in fig. 1, so as to allocate a corresponding thread for querying according to a query condition input by a user, thereby obtaining a query result meeting the requirement. The method comprises the following steps:
step 401: an input query condition is received. See the description of step 201 in the above embodiments for details.
Step 402: and obtaining the data volume corresponding to the query condition according to the query condition. See the description of step 302 in the above embodiments for details.
Step 403: dividing the data volume according to a preset rule to obtain a plurality of sub-data volumes. See for details the description of step 303 in the above embodiments.
Step 404: and distributing a corresponding data volume query interval for the target query thread according to the sub data volume corresponding to the target query thread.
In this step, if each sub-data size in step 303 is 12500, a corresponding target query thread may be allocated to each of 8 groups of sub-data sizes, each target query thread may be allocated to a suitable query interval, for example, the data is ordered according to the data time in the query condition, the data may be ordered into data sizes of 12500 before the interval, allocated to the first target query thread for query, the data sizes of 12501 to 25001 between the interval are allocated to the second target query thread for query, and so on, until each target query thread is allocated to a corresponding data size query interval, so as to implement allocation of a suitable thread number for the current data query.
Step 405: and acquiring a target data set corresponding to the query condition according to the target query thread.
In this step, each target query thread queries according to the division result of the query interval, and each target query thread captures a corresponding data set, that is, a corresponding target data set.
Step 406: it is determined whether there are multiple data volumes concurrently in the target data set. If yes, go to step 407, otherwise go to step 409.
In this step, the plurality of data amounts are concurrent means: when the queried data is multiple, after being ordered according to a certain rule, the data quantity in the same serial number bit is multiple. For example, when 10 data are ordered in sequence according to time, the same sequence number bit exists, and when the data volume is paged, the data with the same sequence number bit are generally divided into the same page, so that the page position is insufficient, and the result of overflow of the data volume is often caused, which is the concurrence of a plurality of data volumes. Therefore, before the queried data is displayed, whether a plurality of data volumes exist in the target data set or not is judged and judged. If yes, go to step 407, otherwise go to step 409.
Step 407: identification information is set for the concurrent data amounts, respectively.
In this step, if there are multiple concurrent data volumes in the target data set, in order to avoid the phenomenon that the data volumes overflow due to insufficient page positions, identification information may be set for the multiple concurrent data volumes, for example, adding a unique ID for each concurrent data.
Step 408: sequentially sequencing the concurrent data volumes in the target data set according to the identification information to obtain a first data set meeting the query condition. And performs step 410.
In this step, if 10 data are sorted according to time and the same time exists, the multiple concurrent data are sequentially sorted in the target data set according to the unique identification information, so that the obtained first data set meeting the query condition can obtain new non-repeated serial number bits again, and when the data are displayed for paging, the data are not forcedly separated in the same page due to the same time, but the pages are reasonably allocated according to the new serial number bits of the unique ID.
Step 409: and ordering the data in the target data set according to a preset ordering rule to obtain a second data set meeting the query condition.
In this step, if there are no multiple concurrent data amounts in the target data set, the data in the target data set may be directly ordered according to a preset ordering rule to obtain a second data set meeting the query condition, where the preset ordering rule may be a time sequence or an ordering rule attached to the query condition input by the user, such as a query amount.
Step 410: and performing set splicing on the data sets according to a preset splicing mode to obtain a query result. See the description of step 306 in the above embodiments for details.
According to the data query method, corresponding query threads are distributed to perform data query according to the received query conditions input by the user, unique identification information is set for a plurality of concurrent data, the data sets meeting the query conditions are reordered to obtain the data sets, and finally the data sets are assembled and spliced according to the preset splicing mode to obtain the final query result, so that different query conditions are achieved, the problem of page data overflow caused by the concurrency of the plurality of data is greatly reduced, and the flexibility of data query is improved.
Please refer to fig. 5, which is a data query device 500 according to an embodiment of the present application, which can be applied to the electronic apparatus 100 shown in fig. 1, and can execute the methods in the corresponding embodiments of fig. 2 to fig. 4, so as to implement that corresponding threads are allocated for query according to the query conditions input by the user, so as to obtain the query result meeting the requirements. The device comprises: the principle relationship of the receiving module 501, the inquiring module 502 and the splicing module 503 is as follows:
a receiving module 501, configured to receive an input query condition. For details, see the description of step 201 in the above embodiment.
The query module 502 is configured to allocate a query thread to perform a query according to a query condition, and obtain a dataset corresponding to the query condition. See the description of step 202 in the above embodiments for details.
And the splicing module 503 is configured to perform set splicing on the data sets according to a preset splicing manner, so as to obtain a query result. See the description of step 203 in the above embodiments for details.
In one embodiment, the query module 502 is configured to: obtaining the data volume corresponding to the query condition according to the query condition; dividing the data volume according to a preset rule to obtain a plurality of groups of sub-data volumes; distributing corresponding target query threads according to each group of sub data volume; and querying the data set conforming to the query conditions according to the target query thread and the query conditions. For details, see the description of steps 302 to 305 in the above embodiments.
In one embodiment, assigning the corresponding target query thread according to each set of sub-data amounts includes: and distributing a corresponding data volume query interval for the target query thread according to the sub data volume corresponding to the target query thread. See the description of step 404 in the above embodiments for details.
In one embodiment, querying a dataset that meets a query condition according to a target query thread and the query condition comprises: acquiring a target data set corresponding to the query condition according to the target query thread; judging whether a target data set has a plurality of concurrent data volumes; if a plurality of data volumes exist in the target data set in parallel, respectively setting identification information for the plurality of data volumes in parallel; sequentially sequencing the concurrent data volumes in the target data set according to the identification information to obtain a first data set conforming to the query condition; if the target data set does not have a plurality of concurrent data volumes, sequencing the data in the target data set according to a preset sequencing rule to obtain a second data set meeting the query condition; the query conditions include: one or more of a customer number, a data date, and a data amount. For details, see the description of steps 405 to 409 in the above embodiments.
The embodiment of the invention also provides an electronic device readable storage medium, which comprises: a program which, when run on an electronic device, causes the electronic device to perform all or part of the flow of the method in the above-described embodiments. The storage medium may be a magnetic Disk, an optical Disk, a Read-Only Memory (ROM), a random access Memory (Random Access Memory, RAM), a Flash Memory (Flash Memory), a Hard Disk (HDD), or a Solid State Drive (SSD), etc. The storage medium may also comprise a combination of memories of the kind described above.
Although embodiments of the present invention have been described in connection with the accompanying drawings, various modifications and variations may be made by those skilled in the art without departing from the spirit and scope of the invention, and such modifications and variations are within the scope of the invention as defined by the appended claims.
Claims (6)
1. A method of querying data, comprising:
receiving an input query condition;
distributing a query thread to query according to the query condition to obtain a data set corresponding to the query condition;
the data sets are subjected to set splicing according to a preset splicing mode, and a query result is obtained;
the step of distributing the query thread to query according to the query condition, and the step of obtaining the data set corresponding to the query condition comprises the following steps:
obtaining the data volume corresponding to the query condition according to the query condition;
dividing the data volume according to a preset rule to obtain a plurality of groups of sub-data volumes;
distributing corresponding target query threads according to each group of sub data volume;
querying a data set conforming to the query conditions according to the target query thread and the query conditions;
the querying the data set conforming to the query condition according to the target query thread and the query condition further comprises:
acquiring a target data set corresponding to the query condition according to the target query thread;
judging whether the target data set has a plurality of concurrent data volumes;
if a plurality of data volumes exist in the target data set in parallel, respectively setting identification information for the plurality of data volumes in parallel;
sequentially sequencing the concurrent data volumes in the target data set according to the identification information to obtain a first data set conforming to the query condition;
and if the target data set does not have a plurality of concurrent data volumes, sequencing the data in the target data set according to a preset sequencing rule to obtain a second data set which accords with the query condition.
2. The method of claim 1, wherein assigning the corresponding target query thread based on each of the sub-data amounts comprises:
and distributing a corresponding data volume query interval for the target query thread according to the sub data volume corresponding to the target query thread.
3. The method of claim 1, wherein the query conditions comprise: one or more of a customer number, a data date, and a data amount.
4. A data query device, comprising:
the receiving module is used for receiving the input query condition;
the query module is used for distributing a query thread to query according to the query condition to obtain a data set corresponding to the query condition;
the splicing module is used for carrying out set splicing on the data sets according to a preset splicing mode to obtain a query result;
the query module is specifically configured to:
obtaining the data volume corresponding to the query condition according to the query condition;
dividing the data volume according to a preset rule to obtain a plurality of groups of sub-data volumes;
distributing corresponding target query threads according to each group of sub data volume;
querying a data set conforming to the query conditions according to the target query thread and the query conditions;
the query module is specifically further configured to:
acquiring a target data set corresponding to the query condition according to the target query thread;
judging whether the target data set has a plurality of concurrent data volumes;
if a plurality of data volumes exist in the target data set in parallel, respectively setting identification information for the plurality of data volumes in parallel;
sequentially sequencing the concurrent data volumes in the target data set according to the identification information to obtain a first data set conforming to the query condition;
and if the target data set does not have a plurality of concurrent data volumes, sequencing the data in the target data set according to a preset sequencing rule to obtain a second data set which accords with the query condition.
5. The apparatus of claim 4, wherein assigning the corresponding target query thread based on each set of the sub-data amounts comprises:
and distributing a corresponding data volume query interval for the target query thread according to the sub data volume corresponding to the target query thread.
6. An electronic device, comprising:
a memory for storing a computer program;
a processor, configured to execute the method according to any one of claims 1 to 3, so as to allocate a corresponding thread for querying according to a query condition input by a user, so as to obtain a query result meeting the requirement.
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| CN113704577A (en) * | 2021-09-09 | 2021-11-26 | 北京天融信网络安全技术有限公司 | Data query method and device based on multithreading concurrent processing |
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