CN104361030A - Distributed cache architecture with task distribution function and cache method - Google Patents
Distributed cache architecture with task distribution function and cache method Download PDFInfo
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- CN104361030A CN104361030A CN201410578562.4A CN201410578562A CN104361030A CN 104361030 A CN104361030 A CN 104361030A CN 201410578562 A CN201410578562 A CN 201410578562A CN 104361030 A CN104361030 A CN 104361030A
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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
- G06F16/2471—Distributed queries
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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
- G06F16/2455—Query execution
- G06F16/24552—Database cache management
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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
- G06F16/28—Databases characterised by their database models, e.g. relational or object models
- G06F16/284—Relational databases
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L67/00—Network arrangements or protocols for supporting network services or applications
- H04L67/01—Protocols
- H04L67/10—Protocols in which an application is distributed across nodes in the network
- H04L67/1097—Protocols in which an application is distributed across nodes in the network for distributed storage of data in networks, e.g. transport arrangements for network file system [NFS], storage area networks [SAN] or network attached storage [NAS]
Abstract
The invention discloses a distributed cache architecture with a task distribution function, which comprises a distributed task scheduling system, a relational database Mysql and a redis distributed cache system. The dynamic distributed cache architecture solves the situation that the traditional database can not process and access a large amount of data. The invention discloses another cache method adopting the distributed cache architecture, can achieve automatic task distribution and fault tolerance for scenes in which computation is required, and guarantees the reliability during processing.
Description
Technical field
The invention belongs to large technical field of data processing, relate to a kind of distributed caching framework method with task distribution function.
Background technology
Along with various non-structural data grows is many, the performance requirement for database in data Storage and Processing is more and more higher, and the demand of read-write operation amount also constantly increases, and traditional Relational DataBase seems painstaking in reply mass data processing.As, relevant database stores at low volume data, high speed access, mass data storage, distributed system support, and data consistency ensures, it is handy that the aspects such as clustered node interpolation easily or deletion cannot be accomplished.
For above problem, in typical application architecture, use this memory object caching system of mamcache, but, along with the continuous increase of portfolio and the sustainable growth of visit capacity, many problems can be run into:
(1) database needs constantly to carry out tearing storehouse open and tears table open, and mamcache also needs continuous dilatation, and dilatation and maintenance work will occupy a large amount of development times.
(2) there is consistency problem in the data of memcache and database.
(3) the low or machine of delaying of the hit rate of memcache data, a large amount of access needs directly to be penetrated into database, and this cannot support a large amount of direct access for this kind of database of such as mysql.
(4) across machine room cache stationary problem.
And, for rate of change data quickly, if select static cache mode (Memcached/File system etc.) display data, very large expense may be had in the access of buffer memory, can not well satisfy the demand.
There is the distributed caching of task distribution function for following consideration, first be the horizontal linearity scaling problem of buffer memory itself, next is the large and performance issue of of giving of buffer memory itself, is the Single Point of Faliure problem (many copies and copy consistency) avoiding buffer memory again.The core technology of distributed caching comprises management to internal memory itself, the distribution of internal memory, management and reclaim mechanism.Next is distributed management and distributed algorithm, is finally the management of buffer memory key assignments and route.Distributed cache system has plurality of advantages:
1) high-performance: when traditional database faces large-scale data access, magnetic disc i/o often becomes performance bottleneck, thus causing too high operating lag. distributed caching is using the storage medium of high-speed internal memory as data object, data store with key/value form, ideally can obtain the readwrite performance of DRAM level;
2) dynamic scalability: support resilient expansion, by dynamically increasing or reduce the data access load of node challenging changes, provide predictable performance and extendability; Meanwhile, resource utilization is improved to greatest extent;
3) high availability: availability comprises availability of data and service availability two aspect. realize high availability based on redundancy scheme, without single point failure (single point of failure), support the automatic discovery of fault, implement failover pellucidly, buffer service can not be caused to interrupt or loss of data because of server failure. automatic equalization data partition during dynamic expansion, ensures that buffer service continues available simultaneously;
4) ease for use: single data and administration view are provided; Api interface is simple, and has nothing to do with topological structure; Without the need to human configuration when dynamic expansion or failure recovery; Automatically backup node is chosen; Most caching system provides patterned supervisor console, is convenient to unified maintenance;
5) distributed code performs (distributed code execution): task code is transferred to each back end executed in parallel, client conglomerate returns results, thus effectively prevent data cached movement and transmission.
Summary of the invention
The object of this invention is to provide a kind of distributed caching framework with task distribution function, solve traditional database and cannot tackle the process of big data quantity and the situation of access.
Another object of the present invention is to provide a kind of distributed caching method with task distribution function, for calculative scene can accomplish automatic task distribution and fault-tolerant, guarantee processing procedure reliability.
A kind of technical scheme of the present invention is, a kind of distributed caching framework with task distribution function, the distributed task dispatching system comprising relevant database Mysql, redis distributed cache system and be connected by network with client.
The feature of a kind of technical scheme of the present invention is also,
Redis distributed cache system comprise connect successively caching management module, distributed caching module, Data distribution8 module, replace algoritic module, cache synchronization module, Cache Communication module, reliability services module.
Another kind of technical scheme of the present invention is, a kind of distributed caching method with task distribution function, adopt a kind of distributed caching framework with task distribution function, its structure is: the distributed task dispatching system comprising relevant database Mysql, redis distributed cache system and be connected by network with client;
Wherein, redis distributed cache system comprise connect successively caching management module, distributed caching module, Data distribution8 module, replace algoritic module, cache synchronization module, Cache Communication module, reliability services module.
Adopt the caching method of above-mentioned distributed cache system, specifically implement according to following steps:
Step 1, when user has data query requirements, system call consistance hash algorithm finds node, and calling communication module reads data;
Data if communication module finds data, are then returned to user by step 2; If communication module does not find data, then the direct accessing database of user carries out digital independent, and performs step 3;
Step 3, data are write buffer memory host node by database;
Step 4, database by the data in buffer memory host node and buffer memory from the data syn-chronization node.
The feature of the another kind of technical scheme of the present invention is also,
Step 4 is specifically implemented according to following steps:
Step 4.1, user writes data in database;
Step 4.2, the flip-flop toggle of database, and enable Mysql udf;
Step 4.3, enables gearman udf, and starts Gearman-worker;
Step 4.4, upgrades the data in redis distributed cache system.
The invention has the beneficial effects as follows,
1) high-level efficiency: for the data that change frequency is fast, adopts this Dram caching technology of redis greatly can reduce the system overhead in buffer memory access; And adopt the high distributed caching of this read-write efficiency can alleviate the pressure of relevant database Mysql, replace the part wherein producing lock because read-write frequency is higher.
2) asynchronous computing is achieved: by dispensed more consuming time to the process of distributed computer cluster, pressure and the processing delay phenomenon of server in station can be decreased.
3) high-performance: when traditional database faces large-scale data access, magnetic disc i/o often becomes performance bottleneck, thus cause too high operating lag, distributed caching is using the storage medium of high-speed internal memory as data object, data store with key/value form, ideally can obtain the readwrite performance of DRAM level;
4) dynamic scalability: support resilient expansion, by dynamically increasing or reduce the data access load of node challenging changes, provide predictable performance and extendability, meanwhile, improve resource utilization to greatest extent;
3) high availability: availability comprises availability of data and service availability two aspect, high availability is realized based on redundancy scheme, without single point failure (single point of failure), support the automatic discovery of fault, implement failover pellucidly, buffer service can not be caused because of server failure to interrupt or loss of data, automatic equalization data partition during dynamic expansion, ensure that buffer service continues available simultaneously;
4) ease for use: single data and administration view are provided; Api interface is simple, and has nothing to do with topological structure; Without the need to human configuration when dynamic expansion or failure recovery; Automatically backup node is chosen; Most caching system provides patterned supervisor console, is convenient to unified maintenance.
Accompanying drawing explanation
Fig. 1 is a kind of structural representation with the distributed caching framework of task distribution function of the present invention;
Fig. 2 is the structural representation by distributed task dispatching system in the present invention;
Fig. 3 is the schematic flow sheet that the present invention has data query in the distributed caching method of task distribution function;
Fig. 4 is the schematic flow sheet of the method for database data and cache synchronization in the present invention.
In figure, 1. distributed task dispatching system, 2. relevant database Mysql, 3.redis distributed cache system, 4. caching management module, 5. distributed caching module, 6. Data distribution8 module, 7. replace algoritic module, 8. cache synchronization module, 9. Cache Communication module, 10. reliability services module.
Embodiment
Below in conjunction with the drawings and specific embodiments, the present invention is described in detail.
A kind of distributed caching framework with task distribution function of the present invention, as shown in Figure 1, the distributed task dispatching system 1 comprising relevant database Mysql2, redis distributed cache system 3 and be connected by network with client;
As shown in Figure 2, redis distributed cache system 3 comprise connect successively caching management module 4, distributed caching module 5, Data distribution8 module 6, replace algoritic module 7, cache synchronization module 8, Cache Communication module 9, reliability services module 10.
The principle of work of buffer structure of the present invention is, first starts the server end of distributed task scheduling dissemination system; Secondly, user writes process specific tasks processing module as specific tasks end for process, and starts; Then, write concrete dispatching system client according to demand by user, and start; Finally, the request of the received server-side client of task dissemination system is also needed distribution of services to be processed to process to the actual working node being applicable to this business of process, after having processed, result is turned back to client through server end.
In distributed caching structure in the present invention, the effect of modules is as follows:
Data distribution8 module 6 comprises based on the Data Distribution copied and the Data Distribution based on subregion.Wherein be suitable at data reading operation more than data write operation application scenario based on the Data Distribution copied; Data distribution8 based on subregion is then more suitable for write operation occasion frequently.
It is data cached that cache synchronization module 8 is mainly used in solving when in other servers of synchronized update after the data in raw data base or the data in certain caching server change.
Replace algoritic module 7, because the hardware resource of caching server is limited, therefore when the data of buffer memory exceed the memory size of system, the a certain partial data in buffer memory will be selected to replace, in order to improve the hit rate of buffer memory, need to use rational cache replacement algorithm to ensure that the data in buffer memory have higher hit rate.
Cache Communication module 9, in distributed caching, each caching server is by cooperating with each other jointly for upper layer application provides buffer service, and each caching server needs to realize between its server and client side by communication protocol, and the real-time Communication for Power between each caching server, make its collaborative work, ensure real-time and the reliability of caching system.
Reliability services module 10, if before memory image is persisted to disk, there is the machine of delaying in the server at buffer memory place, and so these Update Tables not being written to disk all will be lost.In order to ensure the high reliability of data, distributed caching provides the reliability that a kind of data persistence mechanism ensures data.
The mode of distributed caching framework of the present invention by redis distributed cache system and gearman are combined, not only can realize the buffer memory to data, and the persistence that can realize data, for calculative scene can accomplish automatic task distribution and fault-tolerant, guarantee processing procedure reliability.
The present invention's another kind has the distributed caching method of task distribution function, as shown in Figure 3, adopts the caching method of above-mentioned distributed cache system, specifically implements according to following steps:
Step 1, when user has data query requirements, system call consistance hash algorithm finds node, and calling communication module reads data;
Data if Cache Communication module 9 finds data, are then returned to user by step 2; If Cache Communication module 9 does not find data, then the direct accessing database of user carries out digital independent, and performs step 3;
Step 3, data are write buffer memory host node by database;
Step 4, database by the data in buffer memory host node and buffer memory from the data syn-chronization node.
As shown in Figure 4, step 4 is specifically implemented according to following steps:
Step 4.1, user writes data in database;
Step 4.2, the flip-flop toggle of database, and enable Mysql udf;
Step 4.3, enables gearman udf, and starts Gearman-worker;
Step 4.4, upgrades the data in redis distributed cache system.
Claims (4)
1. one kind has the distributed caching framework of task distribution function, it is characterized in that, the distributed task dispatching system (1) comprising relevant database Mysql (2), redis distributed cache system (3) and be connected by network with client.
2. a kind of distributed caching framework with task distribution function according to claim 1, it is characterized in that, described redis distributed cache system (3) comprise connect successively caching management module (4), distributed caching module (5), Data distribution8 module (6), replace algoritic module (7), cache synchronization module (8), Cache Communication module (9), reliability services module (10).
3. one kind has the distributed caching method of task distribution function, it is characterized in that, adopt a kind of distributed caching framework with task distribution function, its structure is: the distributed task dispatching system (1) comprising relevant database Mysql (2), redis distributed cache system (3) and be connected by network with client;
Wherein, described redis distributed cache system (3) comprise connect successively caching management module (4), distributed caching module (5), Data distribution8 module (6), replace algoritic module (7), cache synchronization module (8), Cache Communication module (9), reliability services module (10).
Adopt the caching method of above-mentioned distributed cache system, specifically implement according to following steps:
Step 1, when user has data query requirements, system call consistance hash algorithm finds node, and calling communication module reads data;
Data if Cache Communication module (9) finds data, are then returned to user by step 2; If Cache Communication module (9) does not find data, then the direct accessing database of user carries out digital independent, and performs step 3;
Step 3, data are write buffer memory host node by database;
Step 4, database by the data in buffer memory host node and buffer memory from the data syn-chronization node.
4. a kind of distributed caching method with task distribution function according to claim 2, it is characterized in that, described step 4 is specifically implemented according to following steps:
Step 4.1, user writes data in database;
Step 4.2, the flip-flop toggle of database, and enable Mysql udf;
Step 4.3, enables gearman udf, and starts Gearman-worker;
Step 4.4, upgrades the data in redis distributed cache system.
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Cited By (20)
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| CN105426451A (en) * | 2015-11-11 | 2016-03-23 | 深圳市华讯方舟科技有限公司 | Key value pair-based data processing method and system |
| CN105511805A (en) * | 2015-11-26 | 2016-04-20 | 深圳市中博科创信息技术有限公司 | Data processing method and device for cluster file system |
| WO2016187771A1 (en) * | 2015-05-25 | 2016-12-01 | 武克易 | Cloud television data acquisition method and system based on user behaviour analysis |
| CN106528833A (en) * | 2016-11-14 | 2017-03-22 | 天津南大通用数据技术股份有限公司 | Method and device for dynamic redistribution of data of MPP (Massively Parallel Processing) database |
| CN107145570A (en) * | 2017-05-05 | 2017-09-08 | 上海携程商务有限公司 | The method and system of server are safeguarded based on database service framework |
| CN107346307A (en) * | 2016-05-04 | 2017-11-14 | 北京京东尚科信息技术有限公司 | Distributed cache system and method |
| CN107968804A (en) * | 2016-10-20 | 2018-04-27 | 创盛视联数码科技（北京）有限公司 | Distributed caching dispatches system and method |
| CN108076078A (en) * | 2016-11-09 | 2018-05-25 | 北京金山云网络技术有限公司 | A kind of cloud host creation method, device and cloud service system |
| CN108093010A (en) * | 2016-11-23 | 2018-05-29 | 成都阜特科技股份有限公司 | A kind of industrial real-time data system and its data processing method |
| CN108108310A (en) * | 2016-11-24 | 2018-06-01 | 腾讯科技（深圳）有限公司 | A kind of data processing method, device and server |
| CN108182213A (en) * | 2017-12-20 | 2018-06-19 | 福建新大陆软件工程有限公司 | A kind of data processing optimization device and method based on distributed system |
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| CN109739516A (en) * | 2018-12-29 | 2019-05-10 | 深圳供电局有限公司 | A kind of operation method and system of cloud caching |
| CN109923533A (en) * | 2016-11-10 | 2019-06-21 | 华为技术有限公司 | It will calculate and separate with storage to improve elasticity in the database |
| CN110333944A (en) * | 2019-04-19 | 2019-10-15 | 中国联合网络通信集团有限公司 | Call bill data method for processing business and equipment |
| CN110502539A (en) * | 2019-07-17 | 2019-11-26 | 苏宁云计算有限公司 | A kind of OLAP method for dynamically caching and device |
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| CN113127521A (en) * | 2021-05-19 | 2021-07-16 | 福建天晴在线互动科技有限公司 | Full-amount cache scheme and system under distributed system |
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| CN108182213A (en) * | 2017-12-20 | 2018-06-19 | 福建新大陆软件工程有限公司 | A kind of data processing optimization device and method based on distributed system |
| CN109739516A (en) * | 2018-12-29 | 2019-05-10 | 深圳供电局有限公司 | A kind of operation method and system of cloud caching |
| CN110333944A (en) * | 2019-04-19 | 2019-10-15 | 中国联合网络通信集团有限公司 | Call bill data method for processing business and equipment |
| CN110502539A (en) * | 2019-07-17 | 2019-11-26 | 苏宁云计算有限公司 | A kind of OLAP method for dynamically caching and device |
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| CN112307060B (en) * | 2019-08-01 | 2024-04-23 | 北京京东振世信息技术有限公司 | Method and device for processing picking task |
| CN111159144A (en) * | 2019-11-27 | 2020-05-15 | 北京中交兴路信息科技有限公司 | Cache system and method |
| CN111159144B (en) * | 2019-11-27 | 2023-09-08 | 北京中交兴路信息科技有限公司 | Caching system and method |
| CN113127521A (en) * | 2021-05-19 | 2021-07-16 | 福建天晴在线互动科技有限公司 | Full-amount cache scheme and system under distributed system |
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