CN111831222B - Distributed object storage method and system - Google Patents
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- G06F3/06—Digital input from, or digital output to, record carriers, e.g. RAID, emulated record carriers or networked record carriers
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Abstract
The embodiment of the invention provides a distributed object storage method and a distributed object storage system, wherein the method comprises the following steps: the intelligent data life cycle management subsystem acquires data in the standard data storage subsystem; the intelligent data life cycle management subsystem classifies the data according to cold and hot degrees according to preset rules, and respectively stores the classified data to a corresponding medium storage system according to the classification, and the intelligent data life cycle management subsystem comprises: when the data is created, the data is divided into hot data, low frequency data or archive data; and, for accessible data, classifying the data as hot data, low frequency data, or archived data based on the amount of access the data has to log in real time. According to the scheme, the data are respectively stored into different storages according to the cold and hot degrees, so that cold and hot separation of the data and mixed storage of various media are realized, the storage efficiency and the data safety are improved, and meanwhile, the energy consumption and the storage cost are also greatly reduced.
Description
Technical Field
The invention relates to the field of data processing, in particular to a distributed object storage method and system.
Background
With the rapid development of the internet, especially the rapid development and popularization of technologies such as the mobile internet, the internet of things (IoT), the cloud computing, the 5G, IPv and the like, the data is in explosive growth, and how to store mass data more efficiently and safely becomes a new challenge.
In the prior art, a magnetic storage structure such as a mechanical hard disk, a magnetic tape and the like is generally adopted, and an electric storage structure such as a solid state hard disk, a high-speed flash memory and the like is used for storing mass data.
In the process of implementing the present invention, the inventor finds that at least the following problems exist in the prior art:
Magnetic and dielectric storage systems in enterprise-level storage systems currently provide real-time online services, and provide highly reliable, highly available, high-performance data storage services. However, the current magneto-electric hybrid storage architecture brings a large amount of electric energy consumption according to real-time online; meanwhile, due to the short service lives (3-5 years) of the magnetic and electric storage media, a plurality of problems such as periodic migration of data are caused. Facing the increasing data, the existing storage architecture faces new challenges, and cannot meet the storage requirements of high reliability, high availability, high performance, long-term storage, low cost and green energy conservation of massive data at the same time.
Disclosure of Invention
The embodiment of the invention provides a distributed object storage method and a distributed object storage system, which are used for respectively storing data into different storages according to the cold and hot degrees, so that the cold and hot separation of the data and the mixed storage of various media are realized, the storage efficiency and the data safety are improved, and the energy consumption and the storage cost are also greatly reduced.
To achieve the above object, in one aspect, an embodiment of the present invention provides a distributed object storage method, including:
the intelligent data life cycle management subsystem acquires data in the standard data storage subsystem;
The intelligent data life cycle management subsystem classifies the data according to the cold and hot degrees according to a preset rule, and stores the classified data to a corresponding medium storage system respectively according to the classification, wherein the classifying the data according to the cold and hot degrees according to the preset rule comprises the following steps:
When the data is created, the data is divided into hot data, low frequency data or archive data; and
For accessible data, the data is classified as hot data, low frequency data, or archived data based on the amount of access the data is logged in real time.
In another aspect, an embodiment of the present invention provides a distributed object storage system, where the apparatus includes:
a standard data storage subsystem for storing data;
The intelligent data life cycle management subsystem is used for acquiring data in the standard data storage subsystem; classifying the data according to the cold and hot degrees according to preset rules, and respectively storing the classified data to a corresponding medium storage system according to the classification;
The intelligent data life cycle management subsystem is specifically configured to:
When the data is created, the data is divided into hot data, low frequency data or archive data; and
For accessible data, the data is classified as hot data, low frequency data, or archived data based on the amount of access the data is logged in real time.
The technical scheme has the following beneficial effects:
according to the technical scheme of the layered cold and hot mixed storage scheme of the distributed object storage, data are stored into different storages according to the cold and hot degrees through preset rules, cold and hot separation of the data and mixed storage of various media are realized, so that storage efficiency and data safety are improved, and meanwhile, energy consumption and storage cost are also greatly reduced.
Drawings
In order to more clearly illustrate the embodiments of the invention or the technical solutions in the prior art, the drawings that are required in the embodiments or the description of the prior art will be briefly described, it being obvious that the drawings in the following description are only some embodiments of the invention, and that other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.
FIG. 1 is a flow chart of a distributed object storage method according to an embodiment of the present invention;
FIG. 2 is a schematic diagram of a distributed object storage system according to an embodiment of the present invention.
Detailed Description
The following description of the embodiments of the present invention will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present invention, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
As shown in fig. 1, a flowchart of a distributed object storage method according to an embodiment of the present invention includes:
S101: the intelligent data life cycle management subsystem acquires data in the standard data storage subsystem; preferably, the data in the standard data storage subsystem is data produced by a service application program, and the data produced by the service application program is stored in the standard data storage subsystem through a distributed object Storage (SDK) or an Application Program Interface (API).
S102: the intelligent data life cycle management subsystem classifies the data according to the cold and hot degrees according to a preset rule, and stores the classified data to a corresponding medium storage system respectively according to the classification, wherein the classifying the data according to the cold and hot degrees according to the preset rule comprises the following steps: when the data is created, the data is divided into hot data, low frequency data or archive data; and, for accessible data, classifying the data as hot data, low frequency data, or archived data based on the amount of access the data has to log in real time.
Preferably, the data, when created, classifies the data as hot data, low frequency data, or archived data, including:
When the data is created, the user terminal classifies the data according to the default or the user definition of the system, and the data is classified into hot data, low-frequency data or archive data; or the user terminal classifies the storage space corresponding to the data according to the default or the user definition of the system, and classifies the data into hot data, low-frequency data or archive data; or the user terminal classifies the files in which the data are located according to the default or the user definition of the system, and the data are classified into hot data, low-frequency data or archive data. The method specifically comprises the following steps:
User level rules: and supporting the data cold and hot hierarchical storage setting when the User is created. If the default data policy is archive data when the A1 user creates, the default data policy is archive data when the data is stored, and the archive data is stored in the optical storage system.
2. Storage space Bucket level rules: and supporting the data cold and hot hierarchical storage setting during the creation of the socket. If the default is hot data when the B1 socket is created, the default is hot data when the data is stored, and the hot data is stored in the electric storage system.
Object level rule: data cold and hot hierarchical storage settings are supported at Object creation. If File1 is created by default as low frequency data, the data is default as low frequency data and stored in the magnetic storage system.
TTL rules: life cycle management in the dimension of days (calculated by last modification time of the object) is supported. Such as an expiration date, specifying an expiration date, such as 2018.01.01, may delete all file objects that were consistent with the last modification time before or after that date.
5. File category rules: lifecycle management by file category is supported. E.g., delete all files ending in exe.
6. File name rule: lifecycle management with file names as rules is supported.
Preferably, the classifying the data into hot data, low frequency data or archive data according to the access amount of the data real-time log record includes: marking the data with the access quantity reaching a first set threshold value in a set time period as hot data according to the access quantity recorded by the data real-time log; marking data of which the access amount reaches a second set threshold value and does not reach a first threshold value within a set time period as low frequency data; marking data of which the access quantity reaches a third set threshold value and does not reach a second threshold value in a set time period as archive data; wherein the first set threshold is greater than a second set threshold, which is greater than a third set threshold.
Specifically, through log real-time analysis, GET, HEAD, PUT, POST of statistical data objects Object and Client IP access are carried out, and objects of which the access amount in unit time reaches a certain threshold value are respectively marked as hot data, cold data and archive data by standard data. For example, data accessed up to 1000 times per minute GET is marked as hot data; marking data accessed less than 100 times per day by GET, HEAD as cold data; data accessed less than 1 time per month is marked as archived data.
Preferably, the storing the classified data in the corresponding media storage system according to the classification includes:
Storing the data to an electrical storage system when the category of the data is hot data;
when the category of the data is low-frequency data, storing the data into a magnetic storage system;
when the category of data is archival data, the data is stored to an optical storage system.
In general, the specific structure of the technical scheme is that data produced by a service application program is stored into a distributed object storage system through a distributed object storage SDK or an API, the data is firstly stored into a distributed object storage-standard data storage subsystem, meanwhile, the distributed object storage-intelligent data life management subsystem performs cold and hot analysis on the data through comprehensive analysis on a plurality of dimensions such as users, services, bucket, object, access logs and the like, standard data are respectively adjusted to be corresponding hot data, low-frequency data and archive data, cold and hot layering is realized, and the data is stored into a corresponding medium storage system, so that data storage optimization is realized, and storage efficiency and storage cost optimization are comprehensively improved.
Corresponding to the above method, as shown in fig. 2, a schematic structural diagram of a distributed object storage system according to an embodiment of the present invention is shown, where the apparatus includes:
A standard data storage subsystem 21 for storing data;
An intelligent data lifecycle management subsystem 22 for acquiring data in the standard data storage subsystem; classifying the data according to the cold and hot degrees according to preset rules, and respectively storing the classified data to a corresponding medium storage system according to the classification;
The intelligent data life cycle management subsystem is specifically configured to:
When the data is created, the data is divided into hot data, low frequency data or archive data; and
For accessible data, the data is classified as hot data, low frequency data, or archived data based on the amount of access the data is logged in real time.
Preferably, the data in the standard data storage subsystem is data produced by a service application program, and the data produced by the service application program is stored in the standard data storage subsystem through a distributed object Storage (SDK) or an Application Program Interface (API).
Preferably, the intelligent data lifecycle management subsystem 22 is further specifically configured to:
When the data is created, the user terminal classifies the data according to the default or the user definition of the system, and the data is classified into hot data, low-frequency data or archive data; or alternatively
The user terminal classifies the storage space corresponding to the data according to the default or the custom of the system, and classifies the data into hot data, low-frequency data or archive data; or alternatively
The user terminal classifies the files where the data are located according to the default or the user definition of the system, and the data are classified into hot data, low-frequency data or archive data.
Preferably, the intelligent data lifecycle management subsystem 22 is further specifically configured to:
Marking the data with the access quantity reaching a first set threshold value in a set time period as hot data according to the access quantity recorded by the data real-time log;
Marking data of which the access amount reaches a second set threshold value and does not reach a first threshold value within a set time period as low frequency data;
Marking data of which the access quantity reaches a third set threshold value and does not reach a second threshold value in a set time period as archive data; wherein,
The first set threshold is greater than a second set threshold, which is greater than a third set threshold.
Preferably, the intelligent data lifecycle management subsystem 22 is further specifically configured to:
Storing the data to an electrical storage system when the category of the data is hot data;
when the category of the data is low-frequency data, storing the data into a magnetic storage system;
when the category of data is archival data, the data is stored to an optical storage system.
According to the technical scheme, the intelligent data life cycle management function can store archive data to the optical storage system, and when the data is migrated to the optical storage system from low-frequency storage, corresponding metadata in the distributed object system is updated. At the same time, the archive data is converted into archive EC data in order to ensure the data security. The method has the following advantages:
1. Data protection, high availability. By using the hybrid storage, the high availability of the data is greatly improved, particularly, the introduction of an optical storage system reduces the periodical migration work of the archived data, and the safety of the cold data and the archived data is greatly improved.
2. And the cold and hot layering and medium-layered storage of the data improve the reading performance of the hot data and the comprehensive storage efficiency.
3. The hybrid storage architecture meets the storage requirement of mass data, particularly the introduction of an optical storage system, greatly improves the data storage safety, and reduces the energy consumption and the cost.
It should be understood that the specific order or hierarchy of steps in the processes disclosed are examples of exemplary approaches. Based on design preferences, it is understood that the specific order or hierarchy of steps in the processes may be rearranged without departing from the scope of the present disclosure. The accompanying method claims present elements of the various steps in a sample order, and are not meant to be limited to the specific order or hierarchy presented.
In the foregoing detailed description, various features are grouped together in a single embodiment for the purpose of streamlining the disclosure. This method of disclosure is not to be interpreted as reflecting an intention that the claimed embodiments of the subject matter require more features than are expressly recited in each claim. Rather, as the following claims reflect, invention lies in less than all features of a single disclosed embodiment. Thus the following claims are hereby expressly incorporated into this detailed description, with each claim standing on its own as a separate preferred embodiment of this invention.
The previous description of the disclosed embodiments is provided to enable any person skilled in the art to make or use the present application. As will be apparent to those skilled in the art; various modifications to these embodiments will be readily apparent, and the generic principles defined herein may be applied to other embodiments without departing from the spirit or scope of the disclosure. Thus, the present disclosure is not intended to be limited to the embodiments shown herein but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.
The foregoing description includes examples of one or more embodiments. It is, of course, not possible to describe every conceivable combination of components or methodologies for purposes of describing the aforementioned embodiments, but one of ordinary skill in the art may recognize that many further combinations and permutations of various embodiments are possible. Accordingly, the embodiments described herein are intended to embrace all such alterations, modifications and variations that fall within the scope of the appended claims. Furthermore, as used in the specification or claims, the term "comprising" is intended to be inclusive in a manner similar to the term "comprising," as interpreted when employed as a transitional word in a claim. Furthermore, any use of the term "or" in the specification of the claims is intended to mean "non-exclusive or".
The foregoing description of the embodiments has been provided for the purpose of illustrating the general principles of the invention, and is not meant to limit the scope of the invention, but to limit the invention to the particular embodiments, and any modifications, equivalents, improvements, etc. that fall within the spirit and principles of the invention are intended to be included within the scope of the invention.
Claims (8)
1. A method of distributed object storage, comprising:
the intelligent data life cycle management subsystem acquires data in the standard data storage subsystem;
The intelligent data life cycle management subsystem classifies the data according to the cold and hot degrees according to a preset rule, and stores the classified data to a corresponding medium storage system respectively according to the classification, wherein the classifying the data according to the cold and hot degrees according to the preset rule comprises the following steps:
When the data is created, the data is divided into hot data, low frequency data or archive data; and
For accessible data, according to the access amount of the real-time log record of the data, the data is divided into hot data, low-frequency data or archive data;
the data, when created, classifies the data as hot data, low frequency data, or archived data, including:
When the data is created, the user terminal classifies the data according to the default or the user definition of the system, and the data is classified into hot data, low-frequency data or archive data; or the user terminal classifies the storage space corresponding to the data according to the default or the user definition of the system, and classifies the data into hot data, low-frequency data or archive data; or the user terminal classifies the files in which the data are located according to the default or the user definition of the system, and the data are classified into hot data, low-frequency data or archive data;
The rule adopted by the data for dividing the data into hot data, low-frequency data or archive data when the data is created specifically comprises at least one of the following steps:
A User level rule supporting data cold and hot layered storage setting when a User is created;
The storage space socket level rule supports data cold and hot layered storage setting during socket creation;
object level rules supporting data cold and hot hierarchical storage settings when objects are created;
TTL rule, supporting life cycle management with day as dimension;
File category rules supporting lifecycle management by file category;
file name rule, support the life cycle management with file name as rule.
2. The distributed object storage method of claim 1, wherein the data in the standard data storage subsystem is data produced by a business application, and the data produced by the business application is stored in the standard data storage subsystem through a distributed object storage SDK or API.
3. The distributed object storage method of claim 1, wherein the classifying the data into hot data, low frequency data, or archived data according to the access amount of the data real-time log record comprises:
Marking the data with the access quantity reaching a first set threshold value in a set time period as hot data according to the access quantity recorded by the data real-time log;
Marking data of which the access amount reaches a second set threshold value and does not reach a first threshold value within a set time period as low frequency data;
Marking data of which the access quantity reaches a third set threshold value and does not reach a second threshold value in a set time period as archive data; wherein,
The first set threshold is greater than a second set threshold, which is greater than a third set threshold.
4. A distributed object storage method as claimed in claim 3, wherein said storing the classified data to corresponding media storage systems, respectively, by category, comprises:
Storing the data to an electrical storage system when the category of the data is hot data;
when the category of the data is low-frequency data, storing the data into a magnetic storage system;
when the category of data is archival data, the data is stored to an optical storage system.
5. A distributed object storage system, comprising:
a standard data storage subsystem for storing data;
The intelligent data life cycle management subsystem is used for acquiring data in the standard data storage subsystem; classifying the data according to the cold and hot degrees according to preset rules, and respectively storing the classified data to a corresponding medium storage system according to the classification;
The intelligent data life cycle management subsystem is specifically configured to:
When the data is created, the data is divided into hot data, low frequency data or archive data; and
For accessible data, according to the access amount of the real-time log record of the data, the data is divided into hot data, low-frequency data or archive data;
The intelligent data life cycle management subsystem is specifically configured to: when the data is created, the user terminal classifies the data according to the default or the user definition of the system, and the data is classified into hot data, low-frequency data or archive data; or the user terminal classifies the storage space corresponding to the data according to the default or the user definition of the system, and classifies the data into hot data, low-frequency data or archive data; or the user terminal classifies the files in which the data are located according to the default or the user definition of the system, and the data are classified into hot data, low-frequency data or archive data;
the rules adopted by the data in the creation process for classifying the data into hot data, low frequency data or archive data specifically comprise at least one of the following:
A User level rule supporting data cold and hot layered storage setting when a User is created;
The storage space socket level rule supports data cold and hot layered storage setting during socket creation;
object level rules supporting data cold and hot hierarchical storage settings when objects are created;
TTL rule, supporting life cycle management with day as dimension;
File category rules supporting lifecycle management by file category;
file name rule, support the life cycle management with file name as rule.
6. The distributed object storage system of claim 5 wherein the data in the standard data storage subsystem is business application generated data, the business application generated data being stored to the standard data storage subsystem via a distributed object storage SDK or API.
7. The distributed object storage system of claim 5 wherein said intelligent data lifecycle management subsystem is further operable to:
Marking the data with the access quantity reaching a first set threshold value in a set time period as hot data according to the access quantity recorded by the data real-time log;
Marking data of which the access amount reaches a second set threshold value and does not reach a first threshold value within a set time period as low frequency data;
Marking data of which the access quantity reaches a third set threshold value and does not reach a second threshold value in a set time period as archive data; wherein,
The first set threshold is greater than a second set threshold, which is greater than a third set threshold.
8. The distributed object storage system of claim 7 wherein said intelligent data lifecycle management subsystem is further operable to:
Storing the data to an electrical storage system when the category of the data is hot data;
when the category of the data is low-frequency data, storing the data into a magnetic storage system;
when the category of data is archival data, the data is stored to an optical storage system.
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| CN110765192A (en) * | 2019-10-18 | 2020-02-07 | 广东省城乡规划设计研究院 | GIS data management and processing method based on cloud platform |
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