CN105224257A - The disposal route of large files and system in a kind of cloud storage system - Google Patents
The disposal route of large files and system in a kind of cloud storage system Download PDFInfo
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Abstract
This application provides the disposal route of large files in a kind of cloud storage system, determine the size of file destination; When the size of file destination exceedes default size, described file destination is split, convert one group of fragment objects and an inventory object to; Described one group of fragment objects and an inventory object are all uploaded in cloud storage system.In the application, large files is divided into the form of one group of fragment objects, the size of each fragment objects all meets the requirement to file size in cloud storage system, like this, just can will exceed the files passe of default size in cloud storage system in cloud storage system, the described inventory object record information of all fragment objects, namely described one group of fragment objects and an inventory object represent whole large files, to solve in prior art Switf in cloud storage system and cannot upload the problem of the file being greater than 5GB.
Description
Technical field
The application relates to cloud field of storage, particularly the disposal route of large files and system in a kind of cloud storage system.
Background technology
Along with the development of technology, people more and more pay close attention to the disposal route of large files in cloud storage system.
At present, the largest object that Swift object storage system can store is 5GB, and the file exceeding this size can not upload in Swift, and the big file uploading of GB level is slow with download simultaneously.Oneself large files solution of having of Swift: static large objects (StaticLargeObjects) storage scheme and dynamic large objects (DynamicLargeObjects) storage scheme, be all the storage scheme of Swift service end, in dirigibility, extendability etc., there is certain deficiency.
Therefore, how effective to process large files in cloud storage system, solving the problem that Switf in cloud storage system cannot upload the file being greater than 5GB is the current technical issues that need to address of those skilled in the art.
Summary of the invention
Technical problems to be solved in this application are to provide disposal route and the system of large files in a kind of cloud storage system, to solve in prior art Switf in cloud storage system and cannot upload the problem of the file being greater than 5GB.
Its concrete scheme is as follows:
A disposal route for large files in cloud storage system, the method comprises:
Determine the size of file destination;
When the size of file destination exceedes default size, described file destination is split, convert one group of fragment objects and an inventory object to;
Described one group of fragment objects and an inventory object are all uploaded in cloud storage system.
Above-mentioned method, preferably, all uploads to described one group of fragment objects and an inventory object in cloud storage system, comprising:
Calculate the MD5 proof test value of each fragment in described one group of fragment objects;
The each fragment objects of asynchronous upload;
When all fragment objects are all uploaded complete, calculate the MD5 proof test value of whole file destination;
Upload described inventory object.
Above-mentioned method, preferably, described in upload described inventory object, comprising:
All information sequences in described one group of fragment objects are turned to the character string of JSON form, as the content of described inventory object;
Calculate the MD5 proof test value of the character string of described JSON form;
Upload the content of described inventory object.
Above-mentioned method, preferably, also comprises:
Object metadata is obtained from described cloud storage system;
When described object metadata is inventory object metadata, resolve the fragment objects information of JSON form;
Download all fragment objects corresponding in the fragment objects information of described JSON form;
The all fragment objects downloaded are merged into a large files.
Above-mentioned method, preferably, also comprises:
The MD5 proof test value of the file on verification disk and the MD5 proof test value of the whole file recorded when uploading.
A disposal system for large files in cloud storage system, this system comprises:
Determining unit, for determining the size of file destination;
Cutting unit, for when the size of file destination exceedes default size, splits described file destination, converts one group of fragment objects and an inventory object to;
Uploading unit, for all uploading to described one group of fragment objects and an inventory object in cloud storage system.
Above-mentioned system, preferably, described uploading unit comprises:
First computing unit, for calculating the MD5 proof test value of each fragment in described one group of fragment objects;
First uploads subelement, for each fragment objects of asynchronous upload;
Second computing unit, for when all fragment objects are all uploaded complete, calculates the MD5 proof test value of whole file destination;
Second uploads subelement, for uploading described inventory object.
Above-mentioned system, preferably, described second uploads subelement comprises:
Serialization unit, for all information sequences in described one group of fragment objects being turned to the character string of JSON form, as the content of described inventory object;
3rd computing unit, for calculating the MD5 proof test value of the character string of described JSON form;
3rd uploads subelement, for uploading the content of described inventory object.
Above-mentioned system, preferably, also comprises:
Acquiring unit, for obtaining object metadata from described cloud storage system;
Resolution unit, for when described object metadata is inventory object metadata, resolves the fragment objects information of JSON form;
Download unit, for downloading all fragment objects corresponding in the fragment objects information of described JSON form;
Merge cells, for being merged into a large files by all fragment objects downloaded.
Above-mentioned system, preferably, also comprises:
Verification unit, the MD5 proof test value of the whole file recorded during for verifying the MD5 proof test value of the file on disk and uploading.
In a kind of cloud storage system that the application provides large files disposal route in, determine the size of file destination; When the size of file destination exceedes default size, described file destination is split, convert one group of fragment objects and an inventory object to; Described one group of fragment objects and an inventory object are all uploaded in cloud storage system.In the application, large files is divided into the form of one group of fragment objects, the size of each fragment objects all meets the requirement to file size in cloud storage system, like this, just can will exceed the files passe of default size in cloud storage system in cloud storage system, the described inventory object record information of all fragment objects, namely described one group of fragment objects and an inventory object represent whole large files, to solve in prior art Switf in cloud storage system and cannot upload the problem of the file being greater than 5GB.
Accompanying drawing explanation
In order to be illustrated more clearly in the technical scheme in the embodiment of the present application, below the accompanying drawing used required in describing embodiment is briefly described, apparently, accompanying drawing in the following describes is only some embodiments of the application, for those of ordinary skill in the art, under the prerequisite not paying creative work, other accompanying drawing can also be obtained according to these accompanying drawings.
Fig. 1 is the process flow diagram of the disposal route embodiment 1 of large files in a kind of cloud storage system of the application;
Fig. 2 is the process flow diagram of the disposal route specific implementation of large files in a kind of cloud storage system of the application;
Fig. 3 is the process flow diagram of the disposal route embodiment 2 of large files in a kind of cloud storage system of the application;
Fig. 4 is the structural representation of the disposal system embodiment 1 of large files in a kind of cloud storage system of the application;
Fig. 5 is the structural representation of the disposal system embodiment 2 of large files in a kind of cloud storage system of the application.
Embodiment
Below in conjunction with the accompanying drawing in the embodiment of the present application, be clearly and completely described the technical scheme in the embodiment of the present application, obviously, described embodiment is only some embodiments of the present application, instead of whole embodiments.Based on the embodiment in the application, those of ordinary skill in the art are not making the every other embodiment obtained under creative work prerequisite, all belong to the scope of the application's protection.
With reference to figure 1, show the process flow diagram of the disposal route embodiment 1 of large files in a kind of cloud storage system of the application, can comprise the following steps:
Step S101: the size determining file destination.
In the application, before file destination is uploaded in cloud storage system, need the size determining file, when file belongs to small documents category, do not need to carry out the process such as segmentation to file, but directly files passe to cloud storage system, before uploading, also need the MD5 proof test value of calculation document; When file belongs to the category of large files, according to the disposal route of follow-up large files, file is processed.
Step S102: when the size of file destination exceedes default size, splits described file destination, converts one group of fragment objects and an inventory object to.
Fragment objects a: large files is split into little fragment, upload these fragments respectively as an independent object, these objects are called fragment objects.
In concrete realization, large files might not be split into small documents and upload in cloud storage system again, but by directly reading the data in large files specified bytes interval.
Inventory object: the function of inventory object is the information of all fragment objects of a record formation large files, comprise the Container Name at fragment objects place, the name of fragment objects, the side-play amount of fragment objects in large files (Offset), the binary data length of fragment objects.
When the size of file exceedes default size, then file destination is large files, can not directly by this files passe in cloud storage system, now, need to process described file.
According to fragment objects and inventory object two kinds of object information, a large files pack section can be split as, and a pack section original can be synthesized again.
Fragment objects and general object are without any difference, but inventory object is very special, it represent the large files in disk.When downloading inventory object, needing that all fragment objects are connected into an entirety and returning to user; When inquiring about the information of inventory object, the metadata of inventory object represents the association attributes of large files.
Step S103: described one group of fragment objects and an inventory object are all uploaded in cloud storage system.
A large files stores end at cloud and is made up of unique inventory object and one group of fragment objects.
File often has some attributes to need to be stored in cloud storage end, because inventory object and original are one-to-one relationships, therefore can represent the metadata of original by the metadata of inventory object, i.e. the association attributes of original.
In a kind of cloud storage system that the application provides large files disposal route in, large files is divided into the form of one group of fragment objects, the size of each fragment objects all meets the requirement to file size in cloud storage system, like this, just can will exceed the files passe of default size in cloud storage system in cloud storage system, the described inventory object record information of all fragment objects, namely described one group of fragment objects and an inventory object represent whole large files, to solve in prior art Switf in cloud storage system and cannot upload the problem of the file being greater than 5GB.
With reference to figure 2, show the process flow diagram of the disposal route specific implementation of large files in a kind of cloud storage system of the application.
In specific implementation process, described described one group of fragment objects and an inventory object all to be uploaded in cloud storage system, comprising:
Calculate the MD5 proof test value of each fragment in described one group of fragment objects.
The each fragment objects of asynchronous upload.
When all fragment objects are all uploaded complete, calculate the MD5 proof test value of whole file destination;
Upload described inventory object.
Describedly upload described inventory object, comprising:
All information sequences in described one group of fragment objects are turned to the character string of JSON form, as the content of described inventory object.
For the ease of organizational information, all fragment objects information sequences are turned to the character string of JSON form, as the content of inventory object.So the content of inventory object is exactly the list of all fragment objects information of JSON form.According to the title of Container Name and fragment objects, the position that cloud stores end fragment object can be located, according to side-play amount and clip size, the position of fragment objects in original can be located, so in the frag info list of JSON form, frag info do not need according to they in original order arrangement.
Calculate the MD5 proof test value of the character string of described JSON form.
Upload the content of described inventory object.
For the ease of carry out file School Affairs download, inventory object must possess following two self-defined:
Metadata.
Object-Meta-Echk: the MD5 proof test value of source document, carries out MD5 verification to the file downloaded on disk after download file.
Object-Meta-Length: the total length of source document.
Object stores service Swift defines a lot of intrinsic metadata of object, and in addition, all objects (comprising fragment objects and inventory object) must possess following two metadata:
Content-Type: the content type of inventory object is JSON form, so its value is Application/json; The value of general object is application/octet-stream, and the value of virtual directory object is application/vnd.swift-cloud.dir.
Echk: the Echk value of general object is the MD5 proof test value of whole file, and the Echk value of fragment objects is the MD5 proof test value of file fragment, and the Echk value of inventory object is the MD5 proof test value of JSON character string.During upload file, add Echk value in HttpHeader, Swift can contrast MD5 value and the Echk value of the object of server end after uploading end, to guarantee the consistance transmitting front and back data.
Uploading in downloading process, for ensureing the consistance of data at client, server end, uploading and downloading and according to certain flow process, consistent agreement must be followed.During upload file, needing first to determine whether to need segmentation to upload according to the size of file, if need segmentation, is one group of fragment objects and an inventory object by file transform.It is consistent for storing end in client with cloud in order to ensure data, upload file, file fragment and inventory object time, all to calculate the MD5 proof test value of data, in the Header uploading HTTP request, add Echk key-value pair, cloud stores end Swift can complete data consistency desired result according to Echk value.When uploading inventory object, except calculating the MD5 proof test value of its JSON character string, also needing the MD5 proof test value calculating whole large files, adding as X-Object-Meta-Echk key-value pair in the head of Http request.
With reference to figure 3, show the process flow diagram of the disposal route embodiment 2 of large files in a kind of cloud storage system of the application, can comprise the following steps:
Step S301: obtain object metadata from described cloud storage system.
Step S302: judge whether described object metadata is manifest metadata, if so, then performs step S303: the fragment objects information of resolving JSON form, if not, then performs step S307.
Step S304: download fragment objects corresponding in the fragment objects information of described JSON form.
Step S305: all fragment objects downloaded are merged into a large files.
Step S306: judge whether whole fragment has been downloaded, if so, then performs step S308, otherwise performs step S304.
Step S307: download general object.
Step S308: the MD5 proof test value of the file on verification disk and the MD5 proof test value of the whole file recorded when uploading.
The core process of download file is corresponding with the flow process of upload file.Inventory object during cloud stores represents a large files, and it have recorded the relevant information of the fragment objects of composition large files, and the general object during cloud stores can represent one not to be had to split the file uploaded, and can represent a fragment of a large files yet.So, for high in the clouds object to be downloaded, first must judge that this is to liking inventory object or general object, and then do different process respectively.
When object is general object, directly download this object, when object is inventory object, need to download after treatment, but, all need the MD5 proof test value of file after comparing download and the MD5 proof test value of original after both downloads complete, to guarantee the consistance of file.If the corresponding object of file, then the MD5 proof test value of file is the Echk value of object, if the corresponding inventory object of file and one group of fragment objects, then the MD5 proof test value of file is the X-Object-Meta-Echk value of inventory object.
Corresponding with the method that the disposal route embodiment 1 of large files in a kind of cloud storage system of above-mentioned the application provides, see Fig. 4, present invention also provides the disposal system embodiment 1 of large files in a kind of cloud storage system, in the present embodiment, this system comprises:
Determining unit 401, for determining the size of file destination.
Cutting unit 402, for when the size of file destination exceedes default size, splits described file destination, converts one group of fragment objects and an inventory object to.
Uploading unit 403, for all uploading to described one group of fragment objects and an inventory object in cloud storage system.
Described uploading unit comprises:
First computing unit, for calculating the MD5 proof test value of each fragment in described one group of fragment objects.
First uploads subelement, for each fragment objects of asynchronous upload.
Second computing unit, for when all fragment objects are all uploaded complete, calculates the MD5 proof test value of whole file destination.
Second uploads subelement, for uploading described inventory object.
Described second uploads subelement comprises:
Serialization unit, for all information sequences in described one group of fragment objects being turned to the character string of JSON form, as the content of described inventory object.
3rd computing unit, for calculating the MD5 proof test value of the character string of described JSON form.
3rd uploads subelement, for uploading the content of described inventory object.
See Fig. 5, present invention also provides the disposal system embodiment 2 of large files in a kind of cloud storage system, in the present embodiment, this system comprises:
Acquiring unit 501, for obtaining object metadata from described cloud storage system.
Resolution unit 502, for when described object metadata is inventory object metadata, resolves the fragment objects information of JSON form.
Download unit 503, for downloading all fragment objects corresponding in the fragment objects information of described JSON form.
Merge cells 504, for being merged into a large files by all fragment objects downloaded.
Verification unit 505, the MD5 proof test value of the whole file recorded during for verifying the MD5 proof test value of the file on disk and uploading.
It should be noted that, each embodiment in this instructions all adopts the mode of going forward one by one to describe, and what each embodiment stressed is the difference with other embodiments, between each embodiment identical similar part mutually see.For device class embodiment, due to itself and embodiment of the method basic simlarity, so description is fairly simple, relevant part illustrates see the part of embodiment of the method.
Finally, also it should be noted that, in this article, the such as relational terms of first and second grades and so on is only used for an entity or operation to separate with another entity or operational zone, and not necessarily requires or imply the relation that there is any this reality between these entities or operation or sequentially.And, term " comprises ", " comprising " or its any other variant are intended to contain comprising of nonexcludability, thus make to comprise the process of a series of key element, method, article or equipment and not only comprise those key elements, but also comprise other key elements clearly do not listed, or also comprise by the intrinsic key element of this process, method, article or equipment.When not more restrictions, the key element limited by statement " comprising ... ", and be not precluded within process, method, article or the equipment comprising described key element and also there is other identical element.
For convenience of description, various unit is divided into describe respectively with function when describing above device.Certainly, the function of each unit can be realized in same or multiple software and/or hardware when implementing the application.
As seen through the above description of the embodiments, those skilled in the art can be well understood to the mode that the application can add required general hardware platform by software and realizes.Based on such understanding, the technical scheme of the application can embody with the form of software product the part that prior art contributes in essence in other words, this computer software product can be stored in storage medium, as ROM/RAM, magnetic disc, CD etc., comprising some instructions in order to make a computer equipment (can be personal computer, server, or the network equipment etc.) perform the method described in some part of each embodiment of the application or embodiment.
In a kind of cloud storage system provided the application above, the disposal route of large files and system are described in detail, apply specific case herein to set forth the principle of the application and embodiment, the explanation of above embodiment is just for helping method and the core concept thereof of understanding the application; Meanwhile, for one of ordinary skill in the art, according to the thought of the application, all will change in specific embodiments and applications, in sum, this description should not be construed as the restriction to the application.
Claims (10)
1. the disposal route of large files in cloud storage system, it is characterized in that, the method comprises:
Determine the size of file destination;
When the size of file destination exceedes default size, described file destination is split, convert one group of fragment objects and an inventory object to;
Described one group of fragment objects and an inventory object are all uploaded in cloud storage system.
2. method according to claim 1, is characterized in that, described one group of fragment objects and an inventory object is all uploaded in cloud storage system, comprising:
Calculate the MD5 proof test value of each fragment in described one group of fragment objects;
The each fragment objects of asynchronous upload;
When all fragment objects are all uploaded complete, calculate the MD5 proof test value of whole file destination;
Upload described inventory object.
3. method according to claim 2, is characterized in that, described in upload described inventory object, comprising:
All information sequences in described one group of fragment objects are turned to the character string of JSON form, as the content of described inventory object;
Calculate the MD5 proof test value of the character string of described JSON form;
Upload the content of described inventory object.
4. method according to claim 3, is characterized in that, also comprises:
Object metadata is obtained from described cloud storage system;
When described object metadata is inventory object metadata, resolve the fragment objects information of JSON form;
Download all fragment objects corresponding in the fragment objects information of described JSON form;
The all fragment objects downloaded are merged into a large files.
5. method according to claim 4, is characterized in that, also comprises:
The MD5 proof test value of the file on verification disk and the MD5 proof test value of the whole file recorded when uploading.
6. the disposal system of large files in cloud storage system, it is characterized in that, this system comprises:
Determining unit, for determining the size of file destination;
Cutting unit, for when the size of file destination exceedes default size, splits described file destination, converts one group of fragment objects and an inventory object to;
Uploading unit, for all uploading to described one group of fragment objects and an inventory object in cloud storage system.
7. system according to claim 6, is characterized in that, described uploading unit comprises:
First computing unit, for calculating the MD5 proof test value of each fragment in described one group of fragment objects;
First uploads subelement, for each fragment objects of asynchronous upload;
Second computing unit, for when all fragment objects are all uploaded complete, calculates the MD5 proof test value of whole file destination;
Second uploads subelement, for uploading described inventory object.
8. system according to claim 7, is characterized in that, described second uploads subelement comprises:
Serialization unit, for all information sequences in described one group of fragment objects being turned to the character string of JSON form, as the content of described inventory object;
3rd computing unit, for calculating the MD5 proof test value of the character string of described JSON form;
3rd uploads subelement, for uploading the content of described inventory object.
9. system according to claim 8, is characterized in that, also comprises:
Acquiring unit, for obtaining object metadata from described cloud storage system;
Resolution unit, for when described object metadata is inventory object metadata, resolves the fragment objects information of JSON form;
Download unit, for downloading all fragment objects corresponding in the fragment objects information of described JSON form;
Merge cells, for being merged into a large files by all fragment objects downloaded.
10. system according to claim 9, is characterized in that, also comprises:
Verification unit, the MD5 proof test value of the whole file recorded during for verifying the MD5 proof test value of the file on disk and uploading.
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| CN109302368A (en) * | 2017-06-19 | 2019-02-01 | 中兴通讯股份有限公司 | A kind of document handling method and server |
| CN107592369A (en) * | 2017-10-18 | 2018-01-16 | 郑州云海信息技术有限公司 | The management method and device that file uploads in cloud computing system |
| CN107809423A (en) * | 2017-10-20 | 2018-03-16 | 国信嘉宁数据技术有限公司 | A kind of electronic evidence data transmission method, system and equipment |
| CN109889566A (en) * | 2018-12-27 | 2019-06-14 | 北京奇安信科技有限公司 | Suitable for the photograph document handling method and device under weak net environment |
| CN111610970A (en) * | 2019-02-22 | 2020-09-01 | 广东真才企链信息科技有限公司 | Method for asynchronously submitting large data scale list package |
| CN111193786A (en) * | 2019-12-23 | 2020-05-22 | 北京航天云路有限公司 | Method for reading large file in segmentation mode based on Blob object to improve uploading efficiency |
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