CN104679897A - Data retrieval method under big data environment - Google Patents
Data retrieval method under big data environment Download PDFInfo
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- CN104679897A CN104679897A CN201510118155.XA CN201510118155A CN104679897A CN 104679897 A CN104679897 A CN 104679897A CN 201510118155 A CN201510118155 A CN 201510118155A CN 104679897 A CN104679897 A CN 104679897A
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Abstract
The invention provides a data retrieval method under a big data environment. The method comprises the following steps: when a plurality of copies are different due to storage abnormality, achieving data storage under normal and abnormal conditions by using additional operation, and distinguishing normal and abnormal data through a version number to prevent data in a disk from rewriting or migrating during the storage abnormality; when data synchronization is carried out after failure nodes are recovered, replacing the data in a previous version with the data in a newest version, so that the normal data are not mixed with the abnormal data generated by time return at the overlapped part of a time period. The multiple backup and consistency maintenance of the data can be achieved, the method can adapt to dynamic adjustment of a system structure and has higher performance, reliability and extensibility, and the current practical application requirement can be met.
Description
Technical field
The present invention relates to data retrieval, the data retrieval method particularly under a kind of large data environment.
Background technology
Search data memory provides the basis of every data, services as system, and the quality of its design and implimentation directly has influence on the operational efficiency of whole real-time data base, data security and resilient expansion ability.Available data retrieval technique make use of the time step response of business datum, but main towards centralized environment, is difficult to the availability and the reliability requirement that meet system, is difficult to play its performance in the distributed environment of large data scale.
Summary of the invention
For solving the problem existing for above-mentioned prior art, the present invention proposes the data retrieval method under a kind of large data environment, comprising:
When occurring that storage causes producing difference between the multiple copy of data extremely, by using the data storage adding and operate and realize under normal and abnormal conditions, and carry out differentiation that is normal and abnormal data by version number, prevent the data when storing abnormal in disk from occurring to rewrite or migration, laggard row data syn-chronization is recovered at failure node, use latest edition data to substitute the data of previous version, the abnormal data produced after realizing normal data and time of origin knock-oning does not mix in the part that the time period is overlapping;
With the page of regular length for minimum unit carries out data management, page type comprises data record page, index page and version page, this data point of data record page record is at the instantaneous value of certain period, Quality Codes and timestamp, do not switch the page when this page of recording process occurs abnormal, but use page record side-play amount when cumulative version number and abnormal generation to identify; The brief information of index page record data record page, the version that described brief information comprises data record page changes mark, page number and markers index; Version page have recorded beginning and ending time corresponding to each version number, associated data record page Base Serial Number and page record offset information thereof, associates between each page in chained list mode;
Primary copy corresponding node sends it to the single or multiple backup nodes of specifying while data page write disk, realize the write operation of multiple copies, the treatment scheme of each backup node to the data record page received is identical with primary copy, and primary copy corresponding node is informed by particular message after the page successfully writes disk, regularly carry out self-test operations at each backup node simultaneously, by detecting the continuity of all start contexts in designation number strong point, and the continuity that in each version, all data record pages are numbered, be confirmed whether to there is shortage of data, if data are complete, in destination file, then record current detection position, the data content detected is prevented to be detected repeatedly, otherwise operation is repaired in initiation, backup node and primary copy corresponding node are held consultation, determine the Serial Number Range that the data record page of disappearance is corresponding, to the data record page of primary copy corresponding node request disappearance, the current archive file of write is added after getting all pages, and revise the markers index information safeguarded in index page, if there is version number's change, then corresponding version page also will carry out synchronously, when user adds node in configuration, cluster management node calculates the data memory range of this newly-increased node by consistance hashing algorithm, and this newly-increased node is to all data record pages in former primary copy corresponding node request memory range subsequently, when node failure or network failure cause accessing a certain node, its forward direction node determined by consistance hashing algorithm is acted on behalf of, and all real time datas are stored by agent node, when this node recovers access, carry out data syn-chronization, thus obtain the data content lacked between anomalistic period according to data sign processing mechanism with agent node, after data syn-chronization completes, agent node stops agent functionality, and present node recovers to store.
The present invention compared to existing technology, has the following advantages:
The present invention, and can the dynamic conditioning of adaptive system structure to the multiple duplication of data and consistency maintenance, possesses higher performance and reliability, extensibility, can meet current practical application request.
Accompanying drawing explanation
Fig. 1 is the process flow diagram according to the data retrieval method under the large data environment of the embodiment of the present invention.
Embodiment
Detailed description to one or more embodiment of the present invention is hereafter provided together with the accompanying drawing of the diagram principle of the invention.Describe the present invention in conjunction with such embodiment, but the invention is not restricted to any embodiment.Scope of the present invention is only defined by the claims, and the present invention contain many substitute, amendment and equivalent.Set forth many details in the following description to provide thorough understanding of the present invention.These details are provided for exemplary purposes, and also can realize the present invention according to claims without some in these details or all details.
The present invention proposes a kind of real time data retrieval method of distributed redundancy.The basis ensureing data access real-time realizes the Core Features such as backup is synchronous, consistance reparation, thus the large data effectively improving real-time data base store and processing power, adapt to the application demand of data high availability, high reliability.Fig. 1 is according to the data retrieval method process flow diagram under the large data environment of the embodiment of the present invention.
The data retrieval method that the present invention proposes carries out redundancy backup and the consistency maintenance of internodal data under the distributed structure/architecture meeting real-time.The data that mobile terminal is uploaded are stored to respectively by the communication server in multiple nodes of company-data server and form multiple redundancy, when certain node normally cannot work and cause this node data to copy inefficacy, the node that other copies are corresponding still can store, retrieve, and provides the on all four data, services with failure node.Data security aspect, by realizing the redundancy backup of varying number between multiple physical server, can treat core data and non-core data with a certain discrimination, taking into account carrying cost and the reliability of system.
The communication server in system is a distributed communication system, is also called large data system, for complex network, multi-platform application provide large data receiver, send service, ensures the reliability of data transmission, real-time, security and high efficiency.
Be linked into the communication server by company-data server and data mobile terminal, as the data storage layer of distributed application services, externally provide real-time and historical data service.In cluster, each server node of equity serves unified distribution token number by system registry, is calculated the data point memory range of each server by consistance hashing algorithm.
The data Stored Procedure of system can be divided into following 3 steps:
(1) data mobile terminal obtains current real-time data by active poll or event triggered fashion, mails to the communication server after compressed filtration.
(2) real time data is uploaded to company-data server by user configured data point configuration by the communication server.
(3) data in real time data are called the roll and are converted to data point ID by the management node of company-data server, and set up the mapping of data point ID and physical server according to consistance hashing algorithm, thus send data in the server node of specifying.
Large real-time property security mechanism in storing process and multiple redundancy backup method as follows:
For ensureing the real-time of large data write storage server, data upload mechanism is optimized as follows:
(1) mobile terminal is divided into groups, and press group name foundation and the mapping of physical server, prevent data from storing and too disperse.Mobile terminal, after carrying out store location to cluster management node, can directly be connected to the physical server of specifying, thus reduce unnecessary data retransmission as far as possible.
(2) namely mobile terminal is thought write the memory cache of first physical server in data after and is write successfully, follow-up redundancy backup flow process is performed by this server node, thus the obstruction stand-by period decreased when data send, under the prerequisite meeting high availability, improve throughput of system.The reliability that data send is ensured by the communication server.
For ensureing the availability of data, services, need to carry out redundancy backup to history data store.The number of copies of system default is 1, can the data reliability requirement by production application in configuration process be configured number of copies.Backup Data is stored in different physical servers from primary copy data, and script that storage rule is loaded by primary copy corresponding node realizes, and is defaulted as and is stored in successively on forward direction two nodes that consistance hashing algorithm calculates.
Due to system real time restriction, data do not carry out backup operation during the memory cache of primary copy corresponding node.After recording capacity reaches buffer memory page size, or after exceeding the largest buffered time, stores archive service, while execution local data persistence, is sent to the backup node of specifying by data cached.
Due to the reason such as node failure, Network Abnormal, the data copy difference between multiple server may be caused.The management information of adding during by storing data can carry out the quick judgement of data consistency and the accurate location of missing data.Consistency checking and the repair of redundant copies are generally periodic triggers, complete reparation by the data of additional disappearance.
When occurring that storing abnormal (as time saltus step, operator's maloperation Update Table etc.) causes producing difference between multiple copy, need the functions such as the support of search data memory method is backed up synchronously, difference quick position.For realizing the Fast synchronization that can carry out data when distributed redundant storage, and tackle abnormal storage condition well, the present invention proposes the data management scheme controlled based on multi version, the data that can be realized under normal and abnormal conditions by the additional operation of record are stored, thus are convenient to the consistency maintenance of data.
The data management scheme controlled based on multi version stores by using the additional data realized under normal and abnormal conditions that operate, and carry out differentiation that is normal and abnormal data by version number, thus avoid the data when storing exception in disk to occur to rewrite or migration as far as possible, be also convenient to the data syn-chronization after failure node recovery simultaneously.The abnormal data produced after normal data and time of origin knock-on can not occur to mix in the part that the time period is overlapping.By the data using latest edition data to substitute previous version.
For the different editions data of same time period under efficient storage time rebound state, while additional record redaction data, formed by the version identifier in service data management information and legacy data and distinguish, to ensure that under abnormal conditions that data do not occur to lose and out of order.
In the data management scheme controlled based on multi version, with the page of regular length (being generally 1kB or 4kB) for minimum unit carries out data management, page type comprises data record page, index page and version page.Data record page have recorded this data point at the instantaneous value of certain period, Quality Codes and timestamp, can not switch the page when this page of recording process occurs abnormal, but uses cumulative version number and abnormal page record side-play amount when occurring to identify; Index page have recorded the brief information of data record page, and the version as data record page changes mark, page number and markers index etc.; Version page have recorded the information such as beginning and ending time corresponding to each version number, associated data record page Base Serial Number and page record side-play amount thereof.Associate in chained list mode between each page, be convenient to the quick position that fixed time section stores data.
While data page writes disk, send it to the single or multiple backup nodes of specifying by primary copy corresponding node, thus realize the write operation of multiple copies.The treatment scheme of each backup node to the data record page received is identical with primary copy, and informs primary copy corresponding node by particular message after the page successfully writes disk.Meanwhile, regularly carry out self-test operations at each backup node, by detecting the continuity of all start contexts in designation number strong point, and the continuity that in each version, all data record pages are numbered, can be confirmed whether to there is shortage of data fast.If data are complete, then in destination file, record current detection position, prevent the data content detected to be detected repeatedly, otherwise operation is repaired in initiation.
(1) hold consultation with primary copy corresponding node, determine the Serial Number Range that the data record page of disappearance is corresponding.(2) to the data record page of primary copy corresponding node request disappearance, after getting all pages, add the current archive file of write, and revise the markers index information safeguarded in index page.
(3) if there is version number's change, then corresponding version page also will carry out synchronously, to ensure the continuity of all start contexts.
When user adds node in configuration, cluster management node calculates the data memory range of this newly-increased node by consistance hashing algorithm.This newly-increased node is to all data record pages in former primary copy corresponding node request memory range subsequently, and the treatment scheme got after data record page is identical with primary copy.
When node failure or network failure cause accessing a certain node, the forward direction node determined by consistance hashing algorithm is acted on behalf of by its original storage responsibility.Now, all real time datas are stored by agent node, ensure the data integrity in backup node.
When this node recovers access, carry out data syn-chronization by according to data sign processing mechanism above with agent node, thus obtain the data content lacked between anomalistic period.After data syn-chronization completes, agent node stops agent functionality, and present node recovers original storage responsibility.
For promoting search efficiency and throughput of system, the advantage that multiple copies stores must be made full use of, each backup node is distributed in the magnetic disc i/o operation in query script as far as possible equably.Because first inquiry request arrives cluster management node, needing to carry out load balancing by cluster management node when processing inquiry request, prevent a certain storage server overload, and the phenomenon that the backup node of correspondence is in idle condition occurring.After cluster management node determination query aim server, carry out local search by inquiring client terminal directly to the server of correspondence.After entering local data querying flow, by the markers index recorded in the index page that interlinks, can quick position to the data storage location within the scope of the fixed time.If the version change mark of the page is set up, illustrate that in this page, mixed storage has normal data and abnormal data, if do not distinguished and directly carry out matching in chronological order, will the fitting result of mistake be produced.
Carried out the Version Control of time series data by version page, use the data of latest edition to carry out matching in the interval that version changes, thus avoid normal data to mix the staggered inquiry fitting result led to errors with abnormal data.
From the inquiry request of inquiring client terminal after communication server route, first submit to cluster management node, determine whether inquiry request decomposed by cluster management node according to query time length.If query time span is greater than preset value, then by original query temporally scope be decomposed into multiple subquery request, and be assigned to multiple storage server node by consistance hashing algorithm.After inquiring client terminal gets response message, set up direct-connected with each storage server node, complete respective local data querying flow respectively.If do not need to carry out inquiry request decomposition, then in master-slave back-up node, suitable single storage server is selected to carry out follow-up inquiry by load-balancing algorithm.
Each data storage server, after receiving local search query, judges whether there is version updating within the scope of query time by according to the content in version page.If the process data in this time period belongs to same version, then directly navigate to actual storage locations by index page and carry out digital independent, otherwise query context segmentation will be carried out by each version upgrading time point, use the data of latest edition to carry out matching in each cut section, thus complete local data querying flow.
For promoting search efficiency further, carry out Query Result buffer memory at each storage server node.Preferentially in Query Result buffer memory, search whether have corresponding record during process local search query, once search successfully, directly return cache result, thus decrease magnetic disc i/o number of times.
In sum, the present invention, and can the dynamic conditioning of adaptive system structure to the multiple duplication of data and consistency maintenance, possesses higher performance and reliability, extensibility, can meet current practical application request.
Obviously, it should be appreciated by those skilled in the art, above-mentioned of the present invention each module or each step can realize with general computing system, they can concentrate on single computing system, or be distributed on network that multiple computing system forms, alternatively, they can realize with the executable program code of computing system, thus, they can be stored and be performed by computing system within the storage system.Like this, the present invention is not restricted to any specific hardware and software combination.
Should be understood that, above-mentioned embodiment of the present invention only for exemplary illustration or explain principle of the present invention, and is not construed as limiting the invention.Therefore, any amendment made when without departing from the spirit and scope of the present invention, equivalent replacement, improvement etc., all should be included within protection scope of the present invention.In addition, claims of the present invention be intended to contain fall into claims scope and border or this scope and border equivalents in whole change and modification.
Claims (1)
1. the data retrieval method under large data environment, controlling for performing large data multi version, it is characterized in that, comprise:
When occurring that storage causes producing difference between the multiple copy of data extremely, by using the data storage adding and operate and realize under normal and abnormal conditions, and carry out differentiation that is normal and abnormal data by version number, prevent the data when storing abnormal in disk from occurring to rewrite or migration, laggard row data syn-chronization is recovered at failure node, use latest edition data to substitute the data of previous version, the abnormal data produced after realizing normal data and time of origin knock-oning does not mix in the part that the time period is overlapping;
With the page of regular length for minimum unit carries out data management, page type comprises data record page, index page and version page, this data point of data record page record is at the instantaneous value of certain period, Quality Codes and timestamp, do not switch the page when this page of recording process occurs abnormal, but use page record side-play amount when cumulative version number and abnormal generation to identify; The brief information of index page record data record page, the version that described brief information comprises data record page changes mark, page number and markers index; Version page have recorded beginning and ending time corresponding to each version number, associated data record page Base Serial Number and page record offset information thereof, associates between each page in chained list mode;
Primary copy corresponding node sends it to the single or multiple backup nodes of specifying while data page write disk, realize the write operation of multiple copies, the treatment scheme of each backup node to the data record page received is identical with primary copy, and primary copy corresponding node is informed by particular message after the page successfully writes disk, regularly carry out self-test operations at each backup node simultaneously, by detecting the continuity of all start contexts in designation number strong point, and the continuity that in each version, all data record pages are numbered, be confirmed whether to there is shortage of data, if data are complete, in destination file, then record current detection position, the data content detected is prevented to be detected repeatedly, otherwise operation is repaired in initiation, backup node and primary copy corresponding node are held consultation, determine the Serial Number Range that the data record page of disappearance is corresponding, to the data record page of primary copy corresponding node request disappearance, the current archive file of write is added after getting all pages, and revise the markers index information safeguarded in index page, if there is version number's change, then corresponding version page also will carry out synchronously, when user adds node in configuration, cluster management node calculates the data memory range of this newly-increased node by consistance hashing algorithm, and this newly-increased node is to all data record pages in former primary copy corresponding node request memory range subsequently, when node failure or network failure cause accessing a certain node, its forward direction node determined by consistance hashing algorithm is acted on behalf of, and all real time datas are stored by agent node, when this node recovers access, carry out data syn-chronization, thus obtain the data content lacked between anomalistic period according to data sign processing mechanism with agent node, after data syn-chronization completes, agent node stops agent functionality, and present node recovers to store.
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Cited By (11)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN104932956A (en) * | 2015-06-19 | 2015-09-23 | 华南理工大学 | Big-data-oriented cloud disaster tolerant backup method |
| CN105320754A (en) * | 2015-10-08 | 2016-02-10 | 上海瀚银信息技术有限公司 | Data searching system and method |
| CN106250478A (en) * | 2016-07-29 | 2016-12-21 | 珠海格力电器股份有限公司 | Curve data recording method and device of display terminal, display terminal and air conditioner |
| CN106776151A (en) * | 2017-01-14 | 2017-05-31 | 郑州云海信息技术有限公司 | SAMBA cluster TDB data-base recordings backup method, apparatus and system |
| CN109167690A (en) * | 2018-09-25 | 2019-01-08 | 郑州云海信息技术有限公司 | A kind of restoration methods, device and the relevant device of the service of distributed system interior joint |
| CN109542338A (en) * | 2018-10-19 | 2019-03-29 | 郑州云海信息技术有限公司 | A kind of realization distributed memory system interior joint consistency on messaging method and device |
| CN110046062A (en) * | 2019-03-07 | 2019-07-23 | 佳都新太科技股份有限公司 | Distributed data processing method and system |
| CN110659157A (en) * | 2019-08-30 | 2020-01-07 | 安徽芃睿科技有限公司 | Distributed multi-language retrieval platform and method for lossless recovery |
| CN112511283A (en) * | 2020-11-12 | 2021-03-16 | 鹏城实验室 | Method for counting cycle period time slots of time-sensitive network and electronic equipment |
| CN112948382A (en) * | 2021-02-26 | 2021-06-11 | 平安科技（深圳）有限公司 | Information processing method and device based on big data and related equipment |
| KR102389139B1 (en) * | 2021-02-17 | 2022-04-22 | 유비콘 주식회사 | Space improvement solution system with blockchain-based distributed storage |
Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US5313635A (en) * | 1991-09-26 | 1994-05-17 | Mitsubishi Denki Kabushiki Kaisha | Compiling system for distributed computer system with multiple types of computers |
| US5720024A (en) * | 1992-03-16 | 1998-02-17 | Hitachi, Ltd. | Highly reliable distributed computing system |
| CN102752322A (en) * | 2011-04-18 | 2012-10-24 | 中国科学院声学研究所 | Method for storing and querying distributed data in internet of things |
| CN104391737A (en) * | 2014-12-15 | 2015-03-04 | 成都英力拓信息技术有限公司 | Method for optimizing load balance in cloud platform |
| CN104407926A (en) * | 2014-12-15 | 2015-03-11 | 成都英力拓信息技术有限公司 | Scheduling method of cloud computing resources |
-
2015
- 2015-03-18 CN CN201510118155.XA patent/CN104679897A/en active Pending
Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US5313635A (en) * | 1991-09-26 | 1994-05-17 | Mitsubishi Denki Kabushiki Kaisha | Compiling system for distributed computer system with multiple types of computers |
| US5720024A (en) * | 1992-03-16 | 1998-02-17 | Hitachi, Ltd. | Highly reliable distributed computing system |
| CN102752322A (en) * | 2011-04-18 | 2012-10-24 | 中国科学院声学研究所 | Method for storing and querying distributed data in internet of things |
| CN104391737A (en) * | 2014-12-15 | 2015-03-04 | 成都英力拓信息技术有限公司 | Method for optimizing load balance in cloud platform |
| CN104407926A (en) * | 2014-12-15 | 2015-03-11 | 成都英力拓信息技术有限公司 | Scheduling method of cloud computing resources |
Cited By (15)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN104932956A (en) * | 2015-06-19 | 2015-09-23 | 华南理工大学 | Big-data-oriented cloud disaster tolerant backup method |
| CN104932956B (en) * | 2015-06-19 | 2018-02-27 | 华南理工大学 | A kind of cloud disaster-tolerant backup method towards big data |
| CN105320754A (en) * | 2015-10-08 | 2016-02-10 | 上海瀚银信息技术有限公司 | Data searching system and method |
| CN106250478A (en) * | 2016-07-29 | 2016-12-21 | 珠海格力电器股份有限公司 | Curve data recording method and device of display terminal, display terminal and air conditioner |
| CN106776151A (en) * | 2017-01-14 | 2017-05-31 | 郑州云海信息技术有限公司 | SAMBA cluster TDB data-base recordings backup method, apparatus and system |
| CN109167690A (en) * | 2018-09-25 | 2019-01-08 | 郑州云海信息技术有限公司 | A kind of restoration methods, device and the relevant device of the service of distributed system interior joint |
| CN109542338A (en) * | 2018-10-19 | 2019-03-29 | 郑州云海信息技术有限公司 | A kind of realization distributed memory system interior joint consistency on messaging method and device |
| CN109542338B (en) * | 2018-10-19 | 2022-02-18 | 郑州云海信息技术有限公司 | Method and device for realizing node information consistency in distributed storage system |
| CN110046062A (en) * | 2019-03-07 | 2019-07-23 | 佳都新太科技股份有限公司 | Distributed data processing method and system |
| CN110046062B (en) * | 2019-03-07 | 2021-03-19 | 佳都新太科技股份有限公司 | Distributed data processing method and system |
| CN110659157A (en) * | 2019-08-30 | 2020-01-07 | 安徽芃睿科技有限公司 | Distributed multi-language retrieval platform and method for lossless recovery |
| CN112511283A (en) * | 2020-11-12 | 2021-03-16 | 鹏城实验室 | Method for counting cycle period time slots of time-sensitive network and electronic equipment |
| CN112511283B (en) * | 2020-11-12 | 2022-05-31 | 鹏城实验室 | Method for counting cycle period time slots of time-sensitive network and electronic equipment |
| KR102389139B1 (en) * | 2021-02-17 | 2022-04-22 | 유비콘 주식회사 | Space improvement solution system with blockchain-based distributed storage |
| CN112948382A (en) * | 2021-02-26 | 2021-06-11 | 平安科技（深圳）有限公司 | Information processing method and device based on big data and related equipment |
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