CN104573064B - A kind of data processing method under big data environment - Google Patents
A kind of data processing method under big data environment Download PDFInfo
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- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/10—File systems; File servers
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- G06F16/10—File systems; File servers
- G06F16/17—Details of further file system functions
- G06F16/174—Redundancy elimination performed by the file system
- G06F16/1748—De-duplication implemented within the file system, e.g. based on file segments
- G06F16/1752—De-duplication implemented within the file system, e.g. based on file segments based on file chunks
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Abstract
The invention provides the data processing method under a kind of big data environment, this method includes：According to the operation granularity of file, blocks of files, physical file and logical file are splitted the file into, and defines blocks of files metadata, physical file metadata and logical file metadata respectively；The file metadata of new and old two versions is compared in server end, redundancy duplicate removal is carried out to identical data by blocks of files in accumulation layer, so as to perform the differentiation transmission of new and old edition data in client and server.The present invention realizes the data syn-chronization under big data environment, alleviates server end and calculates pressure, improves efficiency of transmission and resource utilization.
Description
Technical field
The present invention relates to data processing, more particularly to a kind of big data synchronization processing method.
Background technology
With the development of cloud computing technology, increasing user selects long-range storage service to carry out management by synchronization personal document
Resource.File synchronization transmission under shared scene, upload download with personal document and be very different.One file may be shared
To the different terminals of multiple users, the transmission path of file data is the star being formed by connecting by central server and each client
The topological structure of type.The now modification of a client file, all user terminals for participating in sharing and cluster service can be brought
File data simultaneously operating between device.In the case of high concurrent, the I/O pressure of server end can sharply increase.It is and remote
Under journey storage environment, there is great limitation in traditional File Transmission Algorithm with reference to specific transmission environment, exist further excellent
The necessity of change.
Therefore, for the above mentioned problem in the presence of correlation technique, effective solution is not yet proposed at present.
The content of the invention
To solve the problems of above-mentioned prior art, the present invention proposes the data processing under a kind of big data environment
Method, including：
According to the operation granularity of file, blocks of files, physical file and logical file are splitted the file into, and define file respectively
Block metadata, physical file metadata and logical file metadata；
The file metadata of new and old two versions is compared in server end, by blocks of files in accumulation layer to identical
Data carry out redundancy duplicate removal, so as to perform the differentiation transmission of new and old edition data in client and server.
Preferably, each logical file associates a physical file, and a physical file is divided into multiple blocks of files
Accumulation layer is stored, blocks of files is exercisable file data unit minimum in system, and multiple logical files can associate together
One physical file, and multiple physical files can share a blocks of files.
Preferably, if client uploads new edition file and made to server, client as sender, cluster server
For recipient, when the identical copies for having a original document on cluster server and client, user have modified client original
When beginning duplicate of the document forms more new file, the more new file of client is uploaded on cluster server to the process for forming redaction
Including:
1. client initiates more new file upload request to step to cluster server；
2. original document is divided into blocks of files to step by cluster server by fixed size, calculates the Hash schools of each blocks of files
Code and MD5 check codes are tested, and two check code set of each blocks of files are transferred to transmitting terminal.
Step is after 3. cluster server receives the set of two check codes, the sliding window to updating file opening fixed size
Mouthful verified, the verification of sliding window is carried forward by single distance of 1 byte, every 1 byte carry out a Hash verification with
MD5 is verified, and after verification travels through whole file, orients the position of more new file and all identical blocks of original document,
It is then communicated to the data block information of the more new file of cluster server；
After 4. cluster server receives the content of client transmissions, by file data blocks and the piecemeal metadata of more new file
Be associated, formed new edition file, it is necessary to association blocks of files be made up of two parts, the exclusive blocks of files of more new file and
More new file and the public blocks of files of original document；The more new file that client is uploaded increases point of blocks of files and more new file newly
Block metadata is associated；Then will orient common file block in the existing original document in cluster server end, and by its with
Renewal file metadata is associated, and so far forms complete more new file in cluster server, is uploaded file processes and is terminated.
Preferably, the sliding window progress checking procedure of the step 3. further comprises:
The hashed value of data in sliding window is calculated first, and is searched the hashed value in check code set and be whether there is；
If there is no the hashed value, then the byte of sliding window forward slip 1；If there is the hashed value, then further calculate and slide
The MD5 values of data in window, if MD5 values exist in check code set, it is determined that data are repetition in sliding window at present
Data, if there is no MD5 values, then the byte of sliding window forward slip 1；
Wherein described check code only calculates different byte values between window twice every time, calculates each during Hash check codes
Enter internal memory from next byte after disk reading sliding window, slided with sliding window first character joint number according to replacement, renewal
The information of check code of dynamic window.
The present invention compared with prior art, has advantages below：
The present invention realizes the data syn-chronization under big data environment, alleviates server end and calculates pressure, improves transmission
Efficiency and resource utilization.
Brief description of the drawings
Fig. 1 is the flow chart of the data processing method under big data environment according to embodiments of the present invention.
Embodiment
Retouching in detail to one or more embodiment of the invention is hereafter provided together with the accompanying drawing for illustrating the principle of the invention
State.The present invention is described with reference to such embodiment, but the invention is not restricted to any embodiment.The scope of the present invention is only by right
Claim limits, and the present invention covers many replacements, modification and equivalent.Illustrate in the following description many details with
Thorough understanding of the present invention is just provided.These details are provided for exemplary purposes, and without in these details
Some or all details can also realize the present invention according to claims.
Therefore, the present invention proposes the method for data synchronization under a kind of big data environment, is made by optimizing server end internal memory
With and Computation for apportionment pressure give each client mode, as far as possible reduce server end CPU calculate and I/O expense,
Make the utilization rate of efficiency of transmission and cluster server resource all more efficient.Fig. 1 is big data ring according to embodiments of the present invention
Data processing method flow chart under border.
File metadata is defined first, the granularity operated according to file, file metadata is divided into blocks of files, physics text
Part metadata and logical file metadata.Each logical file associates a physical file.One physical file cutting is multiple
Accumulation layer is arrived in blocks of files storage.Blocks of files is exercisable file data unit minimum in system.Wherein, it is allowed to occur multiple
Logical file associates the situation of same physical file, it is allowed to the situation that multiple physical files share a blocks of files occurs.
Because the operation operated with actually descending load physical file of logical file separates, framework is apparent.Piecemeal pair
It is more convenient in differentiation transmission.
Multiple client forms the application layer of big data processing system；The cores such as file service, user management, equipment control
Business function forms service layer；The bottom is the accumulation layer of cluster server, there is provided can be adapted to depositing for multiple different storage devices
Interface is stored up, support is locally stored remotely to be stored with third party.File data transfer mainly carries out data interaction in adjacent two layers
When occur.Data storage transmission i.e. between the network transmission and intermediate layer and bottom in upper strata and intermediate layer.
During passing new edition file on the client, definition client is sender, and cluster server is recipient.Collection
There are text document file.old identical copies on group server and client side.Then when user have modified client
File.old copies, form file.new.Therefore need to upload to the file.new in client on cluster server and formed
Redaction.Differentiation transmission can be divided into four steps:
1. client initiates file.new upload requests to cluster server.
2. file.old is divided into blocks of files by cluster server by fixed size, the Hash check codes of each blocks of files are calculated
With MD5 check codes, and two check code set of each blocks of files are transferred to transmitting terminal.
After 3. cluster server receives the set of two check codes, to the sliding window of file.new file opening fixed sizes
Mouth is verified.The verification of sliding window is carried forward by single distance of 1 byte, every 1 byte carry out a Hash verification and
MD5 is verified., can be to orient all identical blocks of file.new and file.old after verification travels through whole file
Position, remaining is exactly the data block information for needing to be transferred to the file.new of cluster server.So last client needs
The data of transmission are the data blocks differed in file.new with file.old, and redaction file.new piecemeal metadata
Information.
After 4. cluster server receives the content of client differentiation transmission, by file data blocks and file.new piecemeal
Metadata is associated, and forms new edition file.The blocks of files for needing to associate is made up of two parts, file exclusive file.new
Block and file.new and blocks of files public file.old.Therefore need to do the operation of two steps:1. client is uploaded
File.new increases blocks of files newly and file.new piecemeal metadata is associated；It is 2. cluster server end is existing
Common file block is oriented in file.old files, and itself and file.new file metadatas are associated.So far, in cluster
Server forms complete file.new files.File processes are once uploaded to terminate.
Wherein, 3. in the verification mentioned be time overhead main in transmitting procedure, checking procedure is specific as follows:
1. first calculating the hashed value of data in sliding window, and search the hashed value in check code set and whether there is.
2. the if it does not exist, then byte of sliding window forward slip 1.If it is present further calculate in sliding window
The MD5 values of data.If MD5 values exist in check code set, it is determined that data are duplicate data in sliding window at present, such as
The then byte of sliding window forward slip 1 is not present in fruit.
Data transmission method can be applied respectively is uploading and is downloading two processes.In foregoing upload synchronizing process, because
Identical data between the new old edition of upper transmitting file is stored in bottom accumulation layer in the form of blocks of files.System can be to phase
Redundancy duplicate removal, the blocks of files of the stored legacy version of multiplexing are carried out with data block.Therefore, it is necessary to which the content of renewal is new edition
The blocks of files of this document metadata information and redaction knots modification.
Synchronous process is downloaded, is typical scene shared on a large scale.Now, server file compares client file
Version updating by new edition file, it is necessary to be synchronized to each client.The sender of parallel downloading is cluster server, on a large scale
In the case of parallel downloading, verification also can concurrently be carried out in server end.Because the version of downloading process client file will be low
In cluster server FileVersion, i.e. the FileVersion of client is an old version of server file.By above may be used
Know, all old versions of file can obtain in the storage of server end bottom, and new and old edition is differentiation storage
's.Therefore, by the way that the file metadata of two versions is compared in server end, it becomes possible to which blocks of files needs determined
It is transferred to client.At this point it is possible to the expense that server end is calculated to check code is transferred to client-side program.
It is different from end-to-end application, there is the characteristic of high concurrent under remote storage environment.And face cluster-based storage environment
Under differentiation transmission, server end, it is necessary to tackle the scene of high concurrent, is as the central point in star transmission topological structure
The concurrency of system is limited by memory size, network bandwidth, magnetic disc i/o read or write speed.
Check code only needs to calculate byte value different between window twice every time.Therefore magnetic disc i/o only needs concern to slide
The data of first the two bytes of tail of dynamic window one.Therefore, sliding window is read when calculating Hash check codes from disk every time
Next byte after mouthful enters internal memory, with sliding window first character joint number according to replacement, realizes the verification of renewal sliding window
Code information.EMS memory occupation depends on sliding window size when this mode can solve the problems, such as to calculate Hash verifications every time.
For the other slip of byte level, it is very frequently and time-consuming to read the operation of disk, if the present invention is pre-read using caching
Dry byte.Specific data cached update method is as follows:
Two cachings, headBuffer and tailBuffer are opened up, size is all bufferSize, and wherein size is much smaller than
Sliding window size.Sliding window removes HeadBuffer [i] and is a window sliding comprising tailBuffer [i].
After sliding window reading (bufferSize-1) is secondary, bufferSize data cached move to are cached the 1st
Individual position, (bufferSize-1) individual byte is then read in, complete the forward slip operation of caching.
In sliding window, data set caching effectively to optimize disk access end to end.Memory size and disk are taken into account
The limitation of read or write speed, algorithm is set to be more suitable for concurrent actual motion environment.
In summary, the multiple terminals file synchronization of long-range storage service can be transmitted optimization, and the present invention proposes pair
The optimization of memory headroom complexity and disk access frequency, the characteristics of taking high concurrent is stored for long-range, utilizes server end text
The metadata information of part old version, process optimization is downloaded, reduces amount of calculation；Redaction storing process optimizes, and realization is deposited
Redundancy duplicate removal is stored up, lifts memory space utilization rate.
Obviously, can be with general it should be appreciated by those skilled in the art, above-mentioned each module of the invention or each step
Computing system realize that they can be concentrated in single computing system, or be distributed in multiple computing systems and formed
Network on, alternatively, they can be realized with the program code that computing system can perform, it is thus possible to they are stored
Performed in storage platform by computing system.So, the present invention is not restricted to any specific hardware and software combination.
It should be appreciated that the above-mentioned embodiment of the present invention is used only for exemplary illustration or explains the present invention's
Principle, without being construed as limiting the invention.Therefore, that is done without departing from the spirit and scope of the present invention is any
Modification, equivalent substitution, improvement etc., should be included in the scope of the protection.In addition, appended claims purport of the present invention
Covering the whole changes fallen into scope and border or this scope and the equivalents on border and repairing
Change example.
Claims (2)
1. the data processing method under a kind of big data environment, for the synchrodata between client and cluster server, its
It is characterised by, including：According to the operation granularity of file, blocks of files, physical file and logical file are splitted the file into, and it is fixed respectively
Adopted blocks of files metadata, physical file metadata and logical file metadata；
The file metadata of new and old two versions is compared in server end, by blocks of files in accumulation layer to identical data
Redundancy duplicate removal is carried out, so as to perform the differentiation transmission of new and old edition data in client and server；
Each logical file associates a physical file, and a physical file is divided into multiple blocks of files storages to storage
Layer, blocks of files is exercisable file data unit minimum in system, and multiple logical files associate same physical file, and
Multiple physical files share a blocks of files；If client uploads new edition file to server, client as sender,
Cluster server is as recipient, and when the identical copies for having a original document on cluster server and client, user repaiies
When having changed client original document copy formation more new file, the more new file of client is uploaded on cluster server and formed
The process of redaction includes:
1. client initiates more new file upload request to step to cluster server；
2. original document is divided into blocks of files to step by cluster server by fixed size, calculates the Hash check codes of each blocks of files
With MD5 check codes, and two check code set of each blocks of files are transferred to transmitting terminal；
Step carries out school after 3. client receives the set of two check codes, to the sliding window for updating file opening fixed size
To test, the verification of sliding window is carried forward by single distance of 1 byte, and every 1 byte carries out a Hash verification and MD5 verifications,
After verification travels through whole file, the position of more new file and all same file blocks of original document is oriented, is then transmitted
The blocks of files and the piecemeal metadata information of more new file differed to cluster server more new file and original document；
After 4. cluster server receives the content of client transmissions, the piecemeal metadata of blocks of files and more new file is closed
Connection, new edition file is formed, it is necessary to which the blocks of files of association is made up of two parts, the exclusive blocks of files of more new file and renewal are literary
Part and the public blocks of files of original document；The more new file that client is uploaded increases the piecemeal member number of blocks of files and more new file newly
According to being associated；Then common file block will be oriented in the existing original document in cluster server end, and itself and renewal is literary
Part piecemeal metadata is associated, and so far forms complete more new file in cluster server, is uploaded file processes and is terminated；
For the other slip of byte level, several bytes are pre-read using caching；Specific data cached update method is as follows:
Two cachings, headBuffer and tailBuffer are opened up, size is all bufferSize, and wherein bufferSize is far small
In sliding window size；
After sliding window reading (bufferSize-1) is secondary, bufferSize data cached move to are cached into the 1st position
Put, then read in (bufferSize-1) individual byte, complete the forward slip operation of caching.
2. according to the method for claim 1, it is characterised in that the sliding window of the step 3. carries out checking procedure and enters one
Step includes:
The hashed value of data in sliding window is calculated first, and is searched the hashed value in check code set and be whether there is；If
In the absence of the hashed value, then the byte of sliding window forward slip 1；If there is the hashed value, then sliding window is further calculated
The MD5 values of interior data, if MD5 values exist in check code set, it is determined that data are duplicate data in sliding window at present,
If there is no MD5 values, then the byte of sliding window forward slip 1；
Wherein described check code only calculates different byte values between window twice every time, every time from magnetic when calculating Hash check codes
Next byte after disk reading sliding window enters internal memory, with sliding window first character joint number according to replacement, updates sliding window
The information of check code of mouth.
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| CN107103051A (en) * | 2017-04-05 | 2017-08-29 | 成都爱途享科技有限公司 | Set up the quick loading device in processing data |
| US10795836B2 (en) * | 2017-04-17 | 2020-10-06 | Microsoft Technology Licensing, Llc | Data processing performance enhancement for neural networks using a virtualized data iterator |
| CN111241189A (en) * | 2018-11-29 | 2020-06-05 | 北京京东尚科信息技术有限公司 | Method and device for synchronizing data |
| CN109977077B (en) * | 2019-03-25 | 2021-09-24 | 腾讯科技（深圳）有限公司 | Model file storage method and device, readable storage medium and computer equipment |
| US10944697B2 (en) * | 2019-03-26 | 2021-03-09 | Microsoft Technology Licensing, Llc | Sliding window buffer for minimum local resource requirements |
| CN110795499B (en) * | 2019-09-17 | 2024-04-16 | 中国平安人寿保险股份有限公司 | Cluster data synchronization method, device, equipment and storage medium based on big data |
| CN110633257A (en) * | 2019-09-20 | 2019-12-31 | 中国银行股份有限公司 | Real-time synchronization method and system for bank parameter files in private cloud environment |
| CN111880956B (en) * | 2020-07-24 | 2023-12-05 | 北京达佳互联信息技术有限公司 | Data synchronization method and device |
| CN114490625A (en) * | 2022-04-06 | 2022-05-13 | 深圳嘉麟科技有限责任公司 | Artificial intelligence public data platform capable of automatically updating and removing redundancy based on big data processing |
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| EP2299652A1 (en) * | 2009-09-21 | 2011-03-23 | Thomson Licensing | Device and method for generating confirmations of data transfers between communication equipments, by data comparison |
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| CN101387976A (en) * | 2008-11-07 | 2009-03-18 | 清华大学 | Logical volume rapid synchronization method based on data differentia |
| CN101770515A (en) * | 2010-01-18 | 2010-07-07 | 杭州顺网科技股份有限公司 | Data block comparison based data updating method |
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Effective date of registration: 20231013 Address after: No. 204b, Building B, No.1 Keyuan Second Road, High tech Zone, Chengdu, Sichuan Province, 610000 (self numbered) Patentee after: Chengdu Kaiyuan Zhongzhi Information Technology Co.,Ltd. Address before: No. 603, 604, 6th Floor, Block B, Building 5, Jingrong International Plaza, No. 200 Tianfu Fifth Street, Chengdu High tech Zone, Chengdu, Sichuan Province, 610000 Patentee before: Sichuan Xian'en Airsuit Technology Co.,Ltd. |