CN113641706A - Data query method and device - Google Patents
Data query method and device Download PDFInfo
- Publication number
- CN113641706A CN113641706A CN202010393350.4A CN202010393350A CN113641706A CN 113641706 A CN113641706 A CN 113641706A CN 202010393350 A CN202010393350 A CN 202010393350A CN 113641706 A CN113641706 A CN 113641706A
- Authority
- CN
- China
- Prior art keywords
- data
- request
- data query
- identifier
- target fragment
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
- 238000000034 method Methods 0.000 title claims abstract description 32
- 239000012634 fragment Substances 0.000 claims abstract description 61
- 238000000605 extraction Methods 0.000 claims abstract description 8
- 238000006243 chemical reaction Methods 0.000 claims description 14
- 238000004590 computer program Methods 0.000 claims description 10
- 125000004122 cyclic group Chemical group 0.000 claims description 8
- 230000000875 corresponding effect Effects 0.000 description 18
- 238000010586 diagram Methods 0.000 description 12
- 238000004891 communication Methods 0.000 description 7
- 230000006870 function Effects 0.000 description 7
- 238000012545 processing Methods 0.000 description 5
- 230000004044 response Effects 0.000 description 5
- 230000003287 optical effect Effects 0.000 description 4
- 230000008569 process Effects 0.000 description 4
- 238000012986 modification Methods 0.000 description 3
- 230000004048 modification Effects 0.000 description 3
- 238000007493 shaping process Methods 0.000 description 3
- 238000012360 testing method Methods 0.000 description 3
- 230000008901 benefit Effects 0.000 description 2
- 238000013461 design Methods 0.000 description 2
- 239000000835 fiber Substances 0.000 description 2
- 230000000644 propagated effect Effects 0.000 description 2
- 239000004065 semiconductor Substances 0.000 description 2
- 238000010276 construction Methods 0.000 description 1
- 230000002596 correlated effect Effects 0.000 description 1
- 238000011161 development Methods 0.000 description 1
- 230000000694 effects Effects 0.000 description 1
- 238000005516 engineering process Methods 0.000 description 1
- 230000006872 improvement Effects 0.000 description 1
- 239000004973 liquid crystal related substance Substances 0.000 description 1
- 238000013507 mapping Methods 0.000 description 1
- 239000013307 optical fiber Substances 0.000 description 1
- 238000006467 substitution reaction Methods 0.000 description 1
- 238000011144 upstream manufacturing Methods 0.000 description 1
Images
Classifications
-
- 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
- G06F16/2455—Query execution
- G06F16/24552—Database cache management
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F11/00—Error detection; Error correction; Monitoring
- G06F11/07—Responding to the occurrence of a fault, e.g. fault tolerance
- G06F11/14—Error detection or correction of the data by redundancy in operation
- G06F11/1402—Saving, restoring, recovering or retrying
- G06F11/1446—Point-in-time backing up or restoration of persistent data
- G06F11/1458—Management of the backup or restore process
- G06F11/1464—Management of the backup or restore process for networked environments
-
- 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
- G06F16/27—Replication, distribution or synchronisation of data between databases or within a distributed database system; Distributed database system architectures therefor
Landscapes
- Engineering & Computer Science (AREA)
- Theoretical Computer Science (AREA)
- Databases & Information Systems (AREA)
- Physics & Mathematics (AREA)
- General Engineering & Computer Science (AREA)
- General Physics & Mathematics (AREA)
- Data Mining & Analysis (AREA)
- Computing Systems (AREA)
- Quality & Reliability (AREA)
- Computational Linguistics (AREA)
- Information Retrieval, Db Structures And Fs Structures Therefor (AREA)
Abstract
The invention discloses a data query method and device, and relates to the technical field of computers. One embodiment of the method comprises: acquiring a request identifier from a data query request, and converting the request identifier into an integer character string; utilizing the integer character string to perform modular extraction on the redundant backup copies to obtain target fragment identification; acquiring data to be queried corresponding to the data query request from a target fragment corresponding to the target fragment identifier; and performing redundancy backup on the data to be queried to a plurality of fragments in the distributed cache cluster in advance. According to the implementation method, the data query requests can be uniformly distributed to different fragments in the distributed cache cluster in a high-concurrency service scene, and service risks caused by high pressure of the fragments for caching the hot spot data are avoided.
Description
Technical Field
The present invention relates to the field of computer technologies, and in particular, to a method and an apparatus for querying data.
Background
In a high-concurrency service scene, a distributed cache mode is usually adopted to store data so as to reduce the pressure of a database and improve the response speed of data query. With the increase of user bases and the further development of services, the pressure of the fragments for caching the hot spot data in the distributed cache cluster is high, and service risks are easily caused by the increase of flow.
Disclosure of Invention
In view of this, embodiments of the present invention provide a method and an apparatus for data query, which can uniformly distribute data query requests to different segments in a distributed cache cluster in a highly concurrent service scenario, and avoid a service risk caused by a high pressure of a segment caching hot spot data.
To achieve the above object, according to an aspect of an embodiment of the present invention, there is provided a method for querying data, including:
acquiring a request identifier from a data query request, and converting the request identifier into an integer character string;
utilizing the integer character string to perform modular extraction on the redundant backup copies to obtain target fragment identification;
acquiring data to be queried corresponding to the data query request from a target fragment corresponding to the target fragment identifier;
and performing redundancy backup on the data to be queried to a plurality of fragments in the distributed cache cluster in advance.
Optionally, converting the request identifier into an integer string includes:
and converting the request identification into an integer character string by adopting a cyclic redundancy check algorithm.
Optionally, the request identifier includes: and the data query request corresponds to the PIN code of the user.
Optionally, the request identifier further includes: and the data query request corresponds to the client type and/or the client version number.
According to a second aspect of the embodiments of the present invention, there is provided an apparatus for querying data, including:
the conversion module is used for acquiring a request identifier from a data query request and converting the request identifier into an integer character string;
the module taking module is used for taking a module for the redundant backup number by utilizing the integer character string to obtain a target fragment identifier;
the acquisition module is used for acquiring the data to be queried corresponding to the data query request from the target fragment corresponding to the target fragment identifier;
and performing redundancy backup on the data to be queried to a plurality of fragments in the distributed cache cluster in advance.
Optionally, the conversion module converts the request identifier into an integer string by using a cyclic redundancy check algorithm.
Optionally, the request identifier includes: and the data query request corresponds to the PIN code of the user.
Optionally, the request identifier further includes: and the data query request corresponds to the client type and/or the client version number.
According to a third aspect of the embodiments of the present invention, there is provided an electronic device for data query, including:
one or more processors;
a storage device for storing one or more programs,
when the one or more programs are executed by the one or more processors, the one or more processors are caused to implement the method provided by the first aspect of the embodiments of the present invention.
According to a fourth aspect of embodiments of the present invention, there is provided a computer readable medium, on which a computer program is stored, which when executed by a processor, implements the method provided by the first aspect of embodiments of the present invention.
One embodiment of the above invention has the following advantages or benefits: by means of the technical means that data to be queried are redundantly backed up to each fragment in the distributed cache cluster in advance, and a target fragment identifier corresponding to each data query request is determined in a shaping conversion and module extraction mode, each data query request can be uniformly distributed to different fragments in the distributed cache cluster in a high-concurrency service scene, and service risks caused by high pressure of fragments caching hot spot data are avoided.
Further effects of the above-mentioned non-conventional alternatives will be described below in connection with the embodiments.
Drawings
The drawings are included to provide a better understanding of the invention and are not to be construed as unduly limiting the invention. Wherein:
FIG. 1 is a schematic diagram of the main flow of a method of data query in an embodiment of the invention;
FIG. 2 is a schematic diagram of a redundant memory hierarchy according to an embodiment of the present invention;
FIG. 3 is a schematic diagram of the main modules of an apparatus for data query according to an embodiment of the present invention;
FIG. 4 is an exemplary system architecture diagram in which embodiments of the present invention may be employed;
fig. 5 is a schematic block diagram of a computer system suitable for use in implementing a terminal device or server of an embodiment of the invention.
Detailed Description
Exemplary embodiments of the present invention are described below with reference to the accompanying drawings, in which various details of embodiments of the invention are included to assist understanding, and which are to be considered as merely exemplary. Accordingly, those of ordinary skill in the art will recognize that various changes and modifications of the embodiments described herein can be made without departing from the scope and spirit of the invention. Also, descriptions of well-known functions and constructions are omitted in the following description for clarity and conciseness.
According to one aspect of the embodiments of the present invention, a method for data query is provided.
Fig. 1 is a schematic diagram of a main flow of a data query method according to an embodiment of the present invention, and as shown in fig. 1, the data query method includes: step S101, step S102, and step S103.
In the embodiment of the invention, the data to be queried is redundantly backed up to a plurality of fragments in the distributed cache cluster, and one copy of the data to be queried is stored in each fragment of the plurality of fragments. The number of the fragments corresponding to the plurality of fragments is the redundancy backup number. Illustratively, 100 redundant copies of all configuration information are stored in advance and stored in 100 segments of the distributed cache cluster, where the redundant copy is 100. The value of the redundant backup copies can be selectively set according to actual conditions, such as 50 copies, 60 copies and the like. In the actual application process, the value of the redundant backup copy number can be determined through a pressure test based on the service calling amount of a service scene.
In step S101, a request identifier is obtained from a data query request, and the request identifier is converted into an integer character string.
The request identifier refers to an identifier of a data query request, and the identifier may uniquely correspond to one data query request, or may uniquely correspond to a type of data query request, for example, data query requests sent by the same user or the same client IP, and the like. The content of the request identifier can be selectively set according to actual conditions.
In some optional embodiments, the request identification comprises: the data query request corresponds to a PIN (Personal Identification Number) code of the user. The target fragment identification is determined by performing shaping conversion and modulus extraction based on the user PIN code, each data query request can be uniformly distributed to different fragments in the distributed cache cluster in a high-concurrency service scene, service risks caused by high pressure of fragments caching hot data are avoided, the calculated amount is small, and the response speed of the system can be improved.
In other alternative embodiments, the requesting identification may include, in addition to the user PIN code: the data query request corresponds to a client type (e.g., Android client, IOS client) and/or a client version number (e.g., 8.3.2, 8.3.0, etc.). The target fragment identification is determined by adopting information of multiple dimensions to perform integer conversion and modulus extraction, each data query request can be more uniformly distributed to different fragments in a distributed cache cluster in a high-concurrency service scene, service risks caused by high pressure of fragments caching hot spot data are avoided, the calculated amount is small, and the response speed of the system can be improved.
The manner of converting the request identifier into the integer string may be selectively set according to actual situations, for example, a cyclic redundancy check algorithm (CRC32) is adopted to convert the request identifier into the integer string, and then, for example, a hashcode () function carried by Java Object is used to convert the request identifier string into the integer value by an operation of taking the absolute value and modulo the absolute value. In the actual application process, the mode of integer conversion can be determined in a mode of pressure test in a service scene. Through integer conversion, the load balance of each fragment in the distributed cache cluster can be ensured while the data query response speed is improved.
In step S102, the integer character string is used to perform modulo operation on the redundant backup number to obtain the target fragment identifier. In step S103, the data to be queried corresponding to the data query request is obtained from the target segment corresponding to the target segment identifier. And carrying out redundancy backup on the data to be queried to a plurality of fragments in the distributed cache cluster in advance.
Through modular operation, all data query requests can be uniformly distributed to each fragment of the distributed cache cluster, service risks caused by high pressure of fragments caching hot spot data are avoided, the calculated amount is small, and the response speed of the system can be improved.
The distributed cache cluster of the embodiment of the invention can adopt Redis (a key-value database).
The method for querying data according to the embodiment of the present invention is described below with reference to specific examples in the e-commerce field.
If the user PIN is used as a key and the unique configuration information is mapped through a single key, the hot spot problem is easy to occur when the online flow is high, and the pressure on a single fragment in the distributed cache cluster is high.
If the mode of introducing the client type and the client version number factor into the key is adopted, and the configuration information of different client types and client version numbers is stored on different fragments, the condition that the access times of the client type and the client version are obviously unevenly distributed easily exists, and the access frequency of the key of the latest version is far ahead of that of other versions, for example, the access key statistics of a certain minute of the 8.3.2 version of the A client is 245 ten thousand, and the access key statistics of the 8.2.0 version of the same client is 4 thousand. Such data distribution has little impact on the hotspot key problem, which has already been at risk for new hotspot keys.
The configuration information is mapped according to the user dimension, and the user PIN factor is introduced into the cache key design of the configuration information, namely, each piece of configuration information is stored by using a corresponding PIN, and all the user PINs store the same piece of configuration information, so that the risk of hot keys can be avoided. However, each user maps and stores the same piece of configuration information, so that the consumption of cache resources is positively correlated with the increase of the user, and the consumption is usually meaningless and obviously unreasonable.
In this example, the configuration information shown to the client is used as the data to be queried, and the configuration information is redundantly backed up by 100 and stored in one segment of the distributed cache cluster. The distributed cache cluster is constructed by Redis. As shown in fig. 2, the redundant storage system adopts a key-value storage structure key: [ icon _ cold: crc32($ { pin })% 100 ]. Wherein icon _ cold represents a fragment identifier of the fragment, in this example, the user PIN is used as a request identifier, $ { PIN } represents converting the user PIN into an integer, CRC32($ { PIN }) represents performing CRC32 check on the converted integer, and CRC32($ { PIN })% 100 represents modulo the check result to 100.
For example, assuming that the user PIN is fdd-9527-test _972, which passes CRC32 cyclic redundancy check and has a modulo value of 80 with respect to 100, the configuration information is obtained from the key corresponding to icon _ cold: 80. This subsequent PIN access is also obtained from the key. The operation of the other PINs is similar. And finally, a redundant storage system of configuration information key { icon _ cold:0, icon _ cold:1, … and icon _ cold:99} is realized. The user PIN and one of the keys have a permanent mapping relationship, and as long as the PIN is not changed (the PIN is the unique identification of the user, and if the PIN is changed, the user is not the same user), the accessed cache resources are always cache information corresponding to the same key. If the cache fails, the data may be retrieved from the initial values of the configuration information, for example, from another cache, a database, or an upstream interface. Of course, the cold start data may be still in the cache and be permanently valid, that is, the initial value of the cold start configuration information is never expired.
Based on the redundant storage system, the statistics of the access key with the concurrent PIN at a certain time is performed, which is specifically shown in table 1 below. As can be seen from table 1, as long as the base of the user PIN is large enough, the distribution is relatively uniform, and there is no case where the frequency of access of a certain key value is particularly prominent.
The redundant cache configuration information can avoid the business risk of the hot key; and a redundancy storage system is constructed by adopting CRC32 cyclic redundancy check and modular 100 cache keys, so that the distribution of cache acquisition of configuration information under high concurrency is uniform enough, and the access pressure is uniformly shared on different distributed Redis fragments.
According to a second aspect of the embodiments of the present invention, there is provided an apparatus for implementing the above method.
Fig. 3 is a schematic diagram of main modules of an apparatus for querying data according to an embodiment of the present invention, and as shown in fig. 3, the apparatus 300 for querying data includes:
the conversion module 301 obtains a request identifier from a data query request, and converts the request identifier into an integer character string;
the module taking module 302 is used for taking a module of the redundant backup number by using the integer character string to obtain a target fragment identifier;
an obtaining module 303, configured to obtain data to be queried corresponding to the data query request from a target segment corresponding to the target segment identifier;
and performing redundancy backup on the data to be queried to a plurality of fragments in the distributed cache cluster in advance.
Optionally, the conversion module converts the request identifier into an integer string by using a cyclic redundancy check algorithm.
Optionally, the request identifier includes: and the data query request corresponds to the PIN code of the user.
Optionally, the request identifier further includes: and the data query request corresponds to the client type and/or the client version number.
According to a third aspect of the embodiments of the present invention, there is provided an electronic device for data query, including:
one or more processors;
a storage device for storing one or more programs,
when the one or more programs are executed by the one or more processors, the one or more processors are caused to implement the method provided by the first aspect of the embodiments of the present invention.
According to a fourth aspect of embodiments of the present invention, there is provided a computer readable medium, on which a computer program is stored, which when executed by a processor, implements the method provided by the first aspect of embodiments of the present invention.
Fig. 4 shows an exemplary system architecture 400 of a data query method or a data query apparatus to which an embodiment of the present invention may be applied.
As shown in fig. 4, the system architecture 400 may include terminal devices 401, 402, 403, a network 404, and a server 405. The network 404 serves as a medium for providing communication links between the terminal devices 401, 402, 403 and the server 405. Network 404 may include various types of connections, such as wire, wireless communication links, or fiber optic cables, to name a few.
A user may use terminal devices 401, 402, 403 to interact with a server 405 over a network 404 to receive or send messages or the like. The terminal devices 401, 402, 403 may have installed thereon various communication client applications, such as shopping-like applications, web browser applications, search-like applications, instant messaging tools, mailbox clients, social platform software, etc. (by way of example only).
The terminal devices 401, 402, 403 may be various electronic devices having a display screen and supporting web browsing, including but not limited to smart phones, tablet computers, laptop portable computers, desktop computers, and the like.
The server 405 may be a server providing various services, such as a background management server (for example only) providing support for shopping websites browsed by users using the terminal devices 401, 402, 403. The backend management server may analyze and perform other processing on the received data such as the product information query request, and feed back a processing result (for example, target push information, product information — just an example) to the terminal device.
It should be noted that the method for querying data provided by the embodiment of the present invention is generally executed by the server 405, and accordingly, the apparatus for querying data is generally disposed in the server 405.
It should be understood that the number of terminal devices, networks, and servers in fig. 4 is merely illustrative. There may be any number of terminal devices, networks, and servers, as desired for implementation.
Referring now to FIG. 5, shown is a block diagram of a computer system 500 suitable for use with a terminal device implementing an embodiment of the present invention. The terminal device shown in fig. 5 is only an example, and should not bring any limitation to the functions and the scope of use of the embodiments of the present invention.
As shown in fig. 5, the computer system 500 includes a Central Processing Unit (CPU)501 that can perform various appropriate actions and processes according to a program stored in a Read Only Memory (ROM)502 or a program loaded from a storage section 508 into a Random Access Memory (RAM) 503. In the RAM 503, various programs and data necessary for the operation of the system 500 are also stored. The CPU 501, ROM 502, and RAM 503 are connected to each other via a bus 504. An input/output (I/O) interface 505 is also connected to bus 504.
The following components are connected to the I/O interface 505: an input portion 506 including a keyboard, a mouse, and the like; an output portion 507 including a display such as a Cathode Ray Tube (CRT), a Liquid Crystal Display (LCD), and the like, and a speaker; a storage portion 508 including a hard disk and the like; and a communication section 509 including a network interface card such as a LAN card, a modem, or the like. The communication section 509 performs communication processing via a network such as the internet. The driver 510 is also connected to the I/O interface 505 as necessary. A removable medium 511 such as a magnetic disk, an optical disk, a magneto-optical disk, a semiconductor memory, or the like is mounted on the drive 510 as necessary, so that a computer program read out therefrom is mounted into the storage section 508 as necessary.
In particular, according to the embodiments of the present disclosure, the processes described above with reference to the flowcharts may be implemented as computer software programs. For example, embodiments of the present disclosure include a computer program product comprising a computer program embodied on a computer readable medium, the computer program comprising program code for performing the method illustrated in the flow chart. In such an embodiment, the computer program may be downloaded and installed from a network through the communication section 509, and/or installed from the removable medium 511. The computer program performs the above-described functions defined in the system of the present invention when executed by the Central Processing Unit (CPU) 501.
It should be noted that the computer readable medium shown in the present invention can be a computer readable signal medium or a computer readable storage medium or any combination of the two. A computer readable storage medium may be, for example, but not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination of the foregoing. More specific examples of the computer readable storage medium may include, but are not limited to: an electrical connection having one or more wires, a portable computer diskette, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing. In the present invention, a computer readable storage medium may be any tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device. In the present invention, however, a computer readable signal medium may include a propagated data signal with computer readable program code embodied therein, for example, in baseband or as part of a carrier wave. Such a propagated data signal may take many forms, including, but not limited to, electro-magnetic, optical, or any suitable combination thereof. A computer readable signal medium may also be any computer readable medium that is not a computer readable storage medium and that can communicate, propagate, or transport a program for use by or in connection with an instruction execution system, apparatus, or device. Program code embodied on a computer readable medium may be transmitted using any appropriate medium, including but not limited to: wireless, wire, fiber optic cable, RF, etc., or any suitable combination of the foregoing.
The flowchart and block diagrams in the figures illustrate the architecture, functionality, and operation of possible implementations of systems, methods and computer program products according to various embodiments of the present invention. In this regard, each block in the flowchart or block diagrams may represent a module, segment, or portion of code, which comprises one or more executable instructions for implementing the specified logical function(s). It should also be noted that, in some alternative implementations, the functions noted in the block may occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. It will also be noted that each block of the block diagrams or flowchart illustration, and combinations of blocks in the block diagrams or flowchart illustration, can be implemented by special purpose hardware-based systems which perform the specified functions or acts, or combinations of special purpose hardware and computer instructions.
The modules described in the embodiments of the present invention may be implemented by software or hardware. The described modules may also be provided in a processor, which may be described as: a processor comprising: the conversion module is used for acquiring a request identifier from a data query request and converting the request identifier into an integer character string; the module taking module is used for taking a module for the redundant backup number by utilizing the integer character string to obtain a target fragment identifier; and the acquisition module acquires the data to be inquired corresponding to the data inquiry request from the target fragment corresponding to the target fragment identifier. The names of these modules do not in some cases form a limitation on the module itself, for example, the conversion module may also be described as a "module that uses the integer string to modulo the redundant copy number".
As another aspect, the present invention also provides a computer-readable medium that may be contained in the apparatus described in the above embodiments; or may be separate and not incorporated into the device. The computer readable medium carries one or more programs which, when executed by a device, cause the device to comprise: acquiring a request identifier from a data query request, and converting the request identifier into an integer character string; utilizing the integer character string to perform modular extraction on the redundant backup copies to obtain target fragment identification; acquiring data to be queried corresponding to the data query request from a target fragment corresponding to the target fragment identifier; and performing redundancy backup on the data to be queried to a plurality of fragments in the distributed cache cluster in advance.
According to the technical scheme of the embodiment of the invention, by adopting the technical means of redundantly backing up the data to be queried to each fragment in the distributed cache cluster in advance and determining the target fragment identifier corresponding to each data query request in a shaping conversion and module extraction mode, each data query request can be uniformly distributed to different fragments in the distributed cache cluster in a high-concurrency service scene, and the service risk caused by higher pressure of the fragment caching the hot data is avoided.
The above-described embodiments should not be construed as limiting the scope of the invention. Those skilled in the art will appreciate that various modifications, combinations, sub-combinations, and substitutions can occur, depending on design requirements and other factors. Any modification, equivalent replacement, and improvement made within the spirit and principle of the present invention should be included in the protection scope of the present invention.
Claims (10)
1. A method of data querying, comprising:
acquiring a request identifier from a data query request, and converting the request identifier into an integer character string;
utilizing the integer character string to perform modular extraction on the redundant backup copies to obtain target fragment identification;
acquiring data to be queried corresponding to the data query request from a target fragment corresponding to the target fragment identifier in the distributed cache cluster;
and performing redundancy backup on the data to be queried to a plurality of fragments in the distributed cache cluster in advance.
2. The method of claim 1, wherein converting the request identification to an integer string comprises:
and converting the request identification into an integer character string by adopting a cyclic redundancy check algorithm.
3. The method of claim 1, wherein the request identification comprises: and the data query request corresponds to the PIN code of the user.
4. The method of claim 3, wherein the request identification further comprises: and the data query request corresponds to the client type and/or the client version number.
5. An apparatus for querying data, comprising:
the conversion module is used for acquiring a request identifier from a data query request and converting the request identifier into an integer character string;
the module taking module is used for taking a module for the redundant backup number by utilizing the integer character string to obtain a target fragment identifier;
the acquisition module is used for acquiring the data to be queried corresponding to the data query request from the target fragment corresponding to the target fragment identifier;
and performing redundancy backup on the data to be queried to a plurality of fragments in the distributed cache cluster in advance.
6. The apparatus of claim 5, wherein the conversion module converts the request identification to an integer string using a cyclic redundancy check algorithm.
7. The apparatus of claim 5, wherein the request identification comprises: and the data query request corresponds to the PIN code of the user.
8. The apparatus of claim 7, wherein the request identification further comprises: and the data query request corresponds to the client type and/or the client version number.
9. An electronic device for data query, comprising:
one or more processors;
a storage device for storing one or more programs,
when executed by the one or more processors, cause the one or more processors to implement the method of any one of claims 1-4.
10. A computer-readable medium, on which a computer program is stored, which, when being executed by a processor, carries out the method according to any one of claims 1-4.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202010393350.4A CN113641706A (en) | 2020-05-11 | 2020-05-11 | Data query method and device |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202010393350.4A CN113641706A (en) | 2020-05-11 | 2020-05-11 | Data query method and device |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN113641706A true CN113641706A (en) | 2021-11-12 |
Family
ID=78415438
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202010393350.4A Pending CN113641706A (en) | 2020-05-11 | 2020-05-11 | Data query method and device |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN113641706A (en) |
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN114915593A (en) * | 2022-06-10 | 2022-08-16 | 北京世纪好未来教育科技有限公司 | Redis-based flow control method and device, electronic equipment and storage medium |
| CN117349321A (en) * | 2023-12-04 | 2024-01-05 | 凯美瑞德（苏州）信息科技股份有限公司 | Multi-table connection query method and device for document database |
Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US8180376B1 (en) * | 2008-05-01 | 2012-05-15 | Nokia Corporation | Mobile analytics tracking and reporting |
| CN109271360A (en) * | 2018-08-03 | 2019-01-25 | 北京城市网邻信息技术有限公司 | Distributed objects storing data redundancy approach, device, equipment and storage medium |
| CN110019350A (en) * | 2017-07-28 | 2019-07-16 | 北京京东尚科信息技术有限公司 | Data query method and apparatus based on configuration information |
-
2020
- 2020-05-11 CN CN202010393350.4A patent/CN113641706A/en active Pending
Patent Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US8180376B1 (en) * | 2008-05-01 | 2012-05-15 | Nokia Corporation | Mobile analytics tracking and reporting |
| CN110019350A (en) * | 2017-07-28 | 2019-07-16 | 北京京东尚科信息技术有限公司 | Data query method and apparatus based on configuration information |
| CN109271360A (en) * | 2018-08-03 | 2019-01-25 | 北京城市网邻信息技术有限公司 | Distributed objects storing data redundancy approach, device, equipment and storage medium |
Non-Patent Citations (3)
| Title |
|---|
| JAKUB ORAVEC: "An iterative approach for image coding using Mojette transform", IEEE, 26 May 2016 (2016-05-26) * |
| 张勇, 张轶博, 刘军, 雷振明: "基于取模运算哈希函数映射均衡性研究", 重庆邮电学院学报(自然科学版), no. 02, 30 April 2004 (2004-04-30) * |
| 王胜;杨超;崔蔚;黄高攀;张明明;: "基于MongoDB的分布式缓存", 计算机系统应用, no. 04, 15 April 2016 (2016-04-15) * |
Cited By (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN114915593A (en) * | 2022-06-10 | 2022-08-16 | 北京世纪好未来教育科技有限公司 | Redis-based flow control method and device, electronic equipment and storage medium |
| CN114915593B (en) * | 2022-06-10 | 2023-05-09 | 北京世纪好未来教育科技有限公司 | Redis-based flow control method and device, electronic equipment and storage medium |
| CN117349321A (en) * | 2023-12-04 | 2024-01-05 | 凯美瑞德（苏州）信息科技股份有限公司 | Multi-table connection query method and device for document database |
| CN117349321B (en) * | 2023-12-04 | 2024-03-05 | 凯美瑞德（苏州）信息科技股份有限公司 | Multi-table connection query method and device for document database |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN110019350B (en) | Data query method and device based on configuration information | |
| CN111460129B (en) | Method, device, electronic equipment and storage medium for generating identification | |
| CN107844488B (en) | Data query method and device | |
| CN110909022A (en) | Data query method and device | |
| CN113641706A (en) | Data query method and device | |
| CN113452733A (en) | File downloading method and device | |
| CN112948498A (en) | Method and device for generating global identification of distributed system | |
| CN110866001A (en) | Method and device for determining order to be processed | |
| CN113761565A (en) | Data desensitization method and apparatus | |
| CN111767495A (en) | Method and system for synthesizing webpage | |
| CN110705935B (en) | Logistics document processing method and device | |
| CN113760861A (en) | Data migration method and device | |
| CN110019671B (en) | Method and system for processing real-time message | |
| CN113779122A (en) | Method and apparatus for exporting data | |
| CN113761566A (en) | Data processing method and device | |
| CN113347052A (en) | Method and device for counting user access data through access log | |
| CN113220981A (en) | Method and device for optimizing cache | |
| CN111984616A (en) | Method, device and system for updating shared file | |
| CN112711572A (en) | Online capacity expansion method and device suitable for sub-warehouse and sub-meter | |
| CN112131287A (en) | Method and device for reading data | |
| CN110888939A (en) | Data management method and device | |
| CN110866002A (en) | Method and device for processing sub-table data | |
| CN111291038B (en) | Data query method and device | |
| CN109446183B (en) | Global anti-duplication method and device | |
| CN113239303A (en) | Data storage method and device |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination |