CN106101212A - Big data access method under cloud platform - Google Patents
Big data access method under cloud platform Download PDFInfo
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- CN106101212A CN106101212A CN201610404823.XA CN201610404823A CN106101212A CN 106101212 A CN106101212 A CN 106101212A CN 201610404823 A CN201610404823 A CN 201610404823A CN 106101212 A CN106101212 A CN 106101212A
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L67/00—Network arrangements or protocols for supporting network services or applications
- H04L67/01—Protocols
- H04L67/10—Protocols in which an application is distributed across nodes in the network
- H04L67/1097—Protocols in which an application is distributed across nodes in the network for distributed storage of data in networks, e.g. transport arrangements for network file system [NFS], storage area networks [SAN] or network attached storage [NAS]
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L43/00—Arrangements for monitoring or testing data switching networks
- H04L43/10—Active monitoring, e.g. heartbeat, ping or trace-route
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L43/00—Arrangements for monitoring or testing data switching networks
- H04L43/16—Threshold monitoring
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L67/00—Network arrangements or protocols for supporting network services or applications
- H04L67/01—Protocols
- H04L67/10—Protocols in which an application is distributed across nodes in the network
- H04L67/1001—Protocols in which an application is distributed across nodes in the network for accessing one among a plurality of replicated servers
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L67/00—Network arrangements or protocols for supporting network services or applications
- H04L67/01—Protocols
- H04L67/10—Protocols in which an application is distributed across nodes in the network
- H04L67/104—Peer-to-peer [P2P] networks
- H04L67/1044—Group management mechanisms
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Abstract
The invention provides the big data access method under a kind of cloud platform, the method includes: during the data access of cloud storage platform, obtain storage load balancing strategy and data access frequency, distribute memory node according to described strategy and frequency, to be optimized server cluster.The present invention proposes the big data access method under a kind of cloud platform, simplifies server cluster deployment way, it is to avoid server cluster is directly operated by user, it is ensured that the reasonability of memory node and data stability.
Description
Technical field
The present invention relates to cloud storage, particularly to the big data access method under a kind of cloud platform.
Background technology
Cloud storage have employed the technology such as cloud computing, distributed file system and server cluster, deposits various in network
Storage resource is aggregating, common externally offer data storage and Operational Visit function.Current cloud storage is divided into publicly-owned service type
Storage, i.e. provides storage service to enterprise or individual；One is privately owned architected cloud storage, i.e. enterprises build based on
Storage server cluster and distributed file system, be deployed in the node trustship place of enterprise data center or safety, for enterprise
Industry self provides corresponding storage service.Cloud storage platform confidentiality is higher, and storing process is not necessarily to too many I/O operation, therefore
Using and building private cloud storage system to preserve its data file is best selection.At present, private cloud storage building plan has
A variety of: to include key assignments type distributed file system, have employed the mode of packet, server cluster is by one or more groups of structures
Become, be standby relation mutually with the service node in group.The mode using packet storage can make storage server cluster more flexible,
Controllability is also relatively strong.But, Hadoop, as a distributed storage Computational frame increased income, also has lacking of its own
Point.That is exactly system architecture design complexity, and operation maintenance difficulty is bigger.Use to cloud storage platform not only needs many
Knowledge accumulation, and also have a lot of technical ability to remove learning and mastering in terms of its operation maintenance, limit cloud storage to a certain extent
The industry of platform is promoted and uses.In building cloud storage platform, the also problem of two impact deployment and systematic function: first
Individual is in running, and node is susceptible to fault.Once node failure occurs and can not prepare to process in time, will
Affecting in the storage server cluster build process of multiple node, each node has the operation of a lot of repetition so that built
Cheng Feichang is loaded down with trivial details and easily makes mistakes；Second is because that node is ordinary personal computers, rather than minicomputer or large scale computer
Etc private server, therefore data are in use, be subject to such as CPU, internal memory and magnetic disc i/o etc. impact more tight
Weight.
Content of the invention
For solving the problem existing for above-mentioned prior art, the present invention proposes the big data access side under a kind of cloud platform
Method, comprising:
During the data access of cloud storage platform, obtain storage load balancing strategy and data access frequency, according to
Described strategy and frequency distribution memory node, to be optimized to server cluster.
Preferably, also include: described cloud storage platform arranges service watch thread, the cloud storage platform clothes to management node
Business is polled, and monitors the running status of each node on server cluster in real time, realizes increasing node and deleting simultaneously
Division operation；Using observer's pattern to realize cloud storage platform service monitor, wherein node manager is observer, cloud storage
Platform service monitor is the person of being observed；Supervision includes monitoring server cluster operation conditions, including all node health,
File system service condition；Manage unlatching, the closedown including server cluster node and service, the increase of node and deletion；Pipe
Reason node starts server cluster and monitors, periodically initiates nodal information and obtains server cluster node index, simultaneously by cloud
Storage platform nodes manager selects the operation that node increases or deletes；If there being new node server cluster to be added,
Then cloud storage platform nodes manager obtains the nodal information of server cluster to be added, sends that information to cloud storage platform
Mobile network device, by performing related Shell order, it is judged that whether this node can join server cluster, and feed back phase
Pass information, to cloud storage platform nodes manager, is selected the concrete behavior of node by node manager, first when knot removal
The nodal information first will deleted from cloud storage platform nodes manager is sent to cloud storage platform nodes monitor, monitor
Judge the state of this node, perform node and remove operation；Arrange node to select and scheduling in the file system of cloud storage platform
Monitor, its interior joint selection strategy is implemented among namenode, is called when selecting service node by namenode, scheduling
Monitor is used for monitoring server cluster operation conditions, including the memory capacity of the access frequency of data block and service node,
System is when idle state, and management node, according to data access frequency and power system capacity, dispatches copy deposit position；Files passe
Before, service node sends write data requests to namenode, and namenode calls node preference pattern, passes through dispatching and monitoring
Device, obtains server cluster operation information, calculates the stored ratio of node, calculates the stored ratio of each frame node, and press
According to backup factor number, prioritizing selection stored ratio node the highest forms node queue and is sent to client, will by client
Data to be stored are divided into multiple data block, are stored on different service nodes；It has been stored in service at All Files
After device cluster, collect server cluster operation information by dispatch monitor, get the data access frequency of all nodes
And the memory capacity of all nodes, if the access frequency of data exceedes predefined threshold value, then by Replica placement in access frequency
On low node；If system spare capacity is less than threshold value, then by Replica placement at the highest node of stored ratio.
The present invention compared to existing technology, has the advantage that
The present invention proposes the big data access method under a kind of cloud platform, simplifies server cluster deployment way, keeps away
Exempt from user directly to operate server cluster, it is ensured that the reasonability of memory node and data stability.
Brief description
Fig. 1 is the flow chart of the big data access method under cloud platform according to embodiments of the present invention.
Detailed description of the invention
Hereafter provide retouching in detail to one or more embodiment of the present invention together with the accompanying drawing of the diagram principle of the invention
State.Describe the present invention in conjunction with 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 also can realize the present invention according to claims.
An aspect of of the present present invention provides the big data access method under a kind of cloud platform.Fig. 1 is to implement according to the present invention
Big data access method flow chart under the cloud platform of example.
In order to preferably manage server cluster, the whole life to cloud storage platform Distributed Architecture running for the present invention
The life cycle carries out automatic management, including install, builds and monitors, provides visualization interface, improves the efficiency of keeper.With
When storage resource control system carry out fault alarm and process.Except the operation maintenance operation to server cluster, in addition it is also necessary to right
The performance of server cluster is optimized.In server cluster after newly-increased node, re-optimization performance of server cluster.For cloud
Variety of problems during deployment, operation maintenance and use for the storage server cluster, the present invention is directed to the server set built
Group, utilizes the node scheduling Optimized model in reading and writing data stage, realizes convenient management and the optimization of server cluster.The present invention
Aspect for the deployment framework of server cluster, node administration and server Optimized Operation is described in detail.
The present invention uses host-guest architecture, comprises a management node and multiple service node.Management node is used for and business
Node is mutual, the heartbeat request that node of accepting business sends, and completes centralized management watchdog logic, and each service node is responsible for
The state acquisition of place node and maintenance work.Management node deployment is at single node, as server cluster deployment framework
Management node, its responsibility be receive user send order performs request, with rear to service node send order, employing JSON
Mode sends order, and this JSON data include installation, beginning, the configuration information stopping service.
Service node is deployed on the node of all server clusters to be added, is used for performing by holding that management node sends
Row task requests, performed script be stored in management node on assigned catalogue under, this script by service node receive from
The content transformation of the command file of management node is dictionary format, it is simple to the use to configuration when script realizes disposing.Disposing
During state and behavior transmission all for by manage node be sent to service node, service node receives certain action row
For performing thread by behavior and performing corresponding method, and the message after performing feeds back to management joint by message queue
Point.
During server cluster is disposed, operating personnel perform different behaviors by the page, and management node is by this row
For being sent to service node. again the behavior of service node is performed thread and perform corresponding operation, complete server cluster portion
Administration.During service node performs, the status information in server cluster is sent back to manage node, by having of management node
Limit state machine judges.
In server cluster node configuration, the present invention gives tacit consent to all nodes and has all successfully installed operating system no matter
It is physical machine or virtual machine.Node joins two steps in server cluster, first is both sides' safety certifications, and second is
The configuration of node name.Both sides' safety certification uses Shell script to write, and system performs this script, by the PKI of management node
File distributing is to each service node, to reach the state without password login.
Configuration service device cluster service includes selecting service and selects service place node.Current information on services writes on
In JSON data, when selecting service by reading this JSON data, obtain all of cloud storage platform service, optionally enter
Row is installed.After selecting service, distribute at corresponding node to by service, the node listing before at this moment reading, then will
Each service carries out node selection.
Service and node configuration information all oneself after setting completed, system can by perform Shell, corresponding cloud is deposited
Storage platform service installation kit is distributed on corresponding node, and installs.The service profile information of all nodes is synchronized.
Server cluster is built after completing, and server cluster interior joint increases with the increase of data volume, adding of node
In addition and the complexity of process of malfunctioning node also exponentially goes up.The present invention utilizes node administration, by a cloud storage
Platform service monitors thread, is polled the cloud storage platform service of management node, monitors in real time on server cluster each
The running status of node, realizes carrying out increasing and deletion action to node simultaneously.
Node administration uses observer's pattern to realize cloud storage platform service monitor, and wherein node manager is observation
Person, cloud storage platform service monitor is the person of being observed.Supervision includes monitoring server cluster operation conditions, including all nodes
Operation conditions, file system service condition.Manage unlatching, the closedown including server cluster node and service, the increase of node
With deletion etc..
Cloud storage Platform Server is built after finishing, and management node can start server cluster and monitor, periodically initiates
Nodal information obtains server cluster node index.Selected node increase or delete by cloud storage platform nodes manager simultaneously
The operation removing.
If there being new node server cluster to be added, then cloud storage platform nodes manager is needed to obtain service to be added
The nodal information of device cluster, then send that information to cloud storage platform nodes monitor, by performing related Shell order,
Judge whether this node can join server cluster, and feedback-related information is to cloud storage platform nodes manager, by cloud
Storage platform nodes manager selects the concrete behavior of node.In like manner, knot removal is also required to first from cloud storage platform joint
In some manager, the nodal information that will delete is sent to cloud storage platform nodes monitor, and monitor judges the shape of this node
State, performs node and removes operation.
The server optimization that the present invention proposes includes that node selects and storage scheduling.Node selects to refer to data before write
Strategically specified memory node by some, ensure that storage load balance, after storage scheduling refers to data write, according to visit
Ask frequency or node storage capacity to redistribute copy memory node so that system can be run more efficiently.
File system is provided with node and selects and dispatch monitor.Its interior joint selection strategy is implemented among namenode,
Called when selecting service node by namenode.Dispatch monitor is used for monitoring server cluster operation conditions, including data
The access frequency of block and the memory capacity of service node, system is when idle state, and management node is according to data access frequency
And power system capacity, dispatch copy deposit position, improve running efficiency of system.
Node selects to specifically include, and before files passe, service node sends write data requests, name byte to namenode
Point calls node preference pattern, by dispatch monitor, obtains server cluster operation information, calculates the stored ratio of node,
Calculate the stored ratio of each frame node, and according to backup factor number, prioritizing selection stored ratio node composition the highest
Node queue, is sent to client, by client, data to be stored is divided into multiple data block, is stored in different business
On node.
Storage scheduling specifically includes, and after All Files has been stored in server cluster, is received by dispatch monitor
Collection server cluster operation information, gets the data access frequency of all nodes and the memory capacity of all nodes, in service
When device cluster is in idle state, management node, according to the data getting, carries out storage scheduling.If the access frequency of data surpasses
Cross predefined threshold value, then by Replica placement on the minimum node of access frequency；If system spare capacity is less than threshold value, then by pair
Originally it is placed on stored ratio node the highest.
Below for server optimization scheduling model, its monitor and optimisation strategy are described.
First, server cluster operation information needs to be supervised by the measurement of cloud storage platform operation information and display frame
Depending on survey tool is extended by described framework, provides one and can show real-time and historical data instrument, helps monitoring
The task related with scheduling cloud storage platform.
Cloud storage scheduling in the present invention is divided into two stages.Wherein first stage is service node during file write
Select, be to be realized by optimizing node selection strategy.Client selects to be divided into two ways at node: client is at server
Selection strategy on clustered node and selection mode outside server cluster node for the client.Implementation is as follows:
Assuming that server cluster has n frame, each frame has TR platform service node, and number of copies is r
If client is on server cluster service node, then
A) client sends write data requests to management node；
B) node is managed according to file content and system configuration scenarios, all service nodes of calculating client place frame
Stored ratio, process is as follows
If client is i-th frame, initialize selected node set SDN for sky；
The residual capacity of this j-th node of frame is CLij, the block number of storage is BLij, the storage preferred proportion RS of nodeij
=CLij/BLij, storage is preferably put into selected node set than two the highest nodes, i.e. SDN={DNia、DNib}；Wherein
DNia、DNibRepresent a and the b service node in i-th frame,
C) from remaining the node calculating r-2 storage each frame than maximum, r-2 node of maximum after sequence, is selected
Put into selected node set SDN, altogether r node, be used for depositing data block and copy thereof；
D) manage node by the node distribution service node in SDN set to client, write by client.
When client is not on service node, then the stored ratio of all nodes in direct calculation server cluster, choosing
Select first r maximum node, be data memory node.FromIn individual node, according to RSij=CLij/BLijSelect storage
R the highest node of ratio, puts in SDN list, is the optimum node chosen.
In sum, the present invention proposes the big data access method under a kind of cloud platform, simplifies server cluster portion
Management side formula, it is to avoid server cluster is directly operated by user, it is ensured that the reasonability of memory node and data stability.
Obviously, it should be appreciated by those skilled in the art, each module of the above-mentioned present invention or each step can be with general
Calculating system realize, they can concentrate in single calculating system, or be distributed in multiple calculating system and formed
Network on, alternatively, they can be realized by the executable program code of calculating system, it is thus possible to by they store
Performed by calculating system within the storage system.So, the present invention is not restricted to the combination of any specific hardware and software.
It should be appreciated that the above-mentioned detailed description of the invention of the present invention is used only for exemplary illustration or explains the present invention's
Principle, and be not construed as limiting the invention.Therefore, that is done in the case of without departing from the spirit and scope of the present invention is any
Modification, equivalent, improvement etc., should be included within the scope of the present invention.Additionally, claims purport of the present invention
Whole within covering to fall into the equivalents on scope and border or this scope and border change and repair
Change example.
Claims (2)
1. the big data access method under a cloud platform, it is characterised in that include:
During the data access of cloud storage platform, obtain storage load balancing strategy and data access frequency, according to described
Strategy and frequency distribute memory node, to be optimized server cluster.
2. method according to claim 1, it is characterised in that also include: described cloud storage platform arranges service watch line
Journey, is polled to the cloud storage platform service of management node, monitors the running status of each node on server cluster in real time,
Realize carrying out increasing and deletion action to node simultaneously；Observer's pattern is used to realize cloud storage platform service monitor, its
Interior joint manager is observer, and cloud storage platform service monitor is the person of being observed；Supervision includes monitoring server cluster fortune
Row situation, including all node health, file system service condition；Management includes opening of server cluster node and service
Open, close, the increase of node and deletion；Management node starts server cluster and monitors, periodically initiates nodal information and obtains
Server cluster node index, is selected node increase or the operation deleted by cloud storage platform nodes manager simultaneously；As
Fruit has new node server cluster to be added, then cloud storage platform nodes manager obtains the node letter of server cluster to be added
Breath, sends that information to cloud storage platform nodes monitor, by performing related Shell order, it is judged that whether this node may be used
Joining server cluster, and feedback-related information is to cloud storage platform nodes manager, is selected joint by node manager
The concrete behavior of point, the nodal information first will deleted from cloud storage platform nodes manager when knot removal is sent to
Cloud storage platform nodes monitor, monitor judges the state of this node, performs node and removes operation；Literary composition at cloud storage platform
Arranging node in part system to select and dispatch monitor, its interior joint selection strategy is implemented among namenode, by name byte
Point calls when selecting service node, and dispatch monitor is used for monitoring server cluster operation conditions, including the access of data block
Frequency and the memory capacity of service node, system is when idle state, and management node holds according to data access frequency and system
Amount, dispatches copy deposit position；Before files passe, service node sends write data requests to namenode, and namenode is adjusted
Use node preference pattern, by dispatch monitor, obtain server cluster operation information, calculate the stored ratio of node, calculate
The stored ratio of each frame node, and according to backup factor number, prioritizing selection stored ratio node composition node the highest
Queue is sent to client, by client, data to be stored is divided into multiple data block, is stored in different service nodes
On；After All Files has been stored in server cluster, collects server cluster operation information by dispatch monitor, obtain
Get the data access frequency of all nodes and the memory capacity of all nodes, if the access frequency of data exceedes predefined threshold
Value, then by Replica placement on the minimum node of access frequency；If system spare capacity is less than threshold value, then Replica placement is being deposited
Storage ratio node the highest.
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Cited By (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN107623732A (en) * | 2017-09-15 | 2018-01-23 | 郑州云海信息技术有限公司 | A kind of date storage method based on cloud platform, device, equipment and storage medium |
| CN109947557A (en) * | 2017-12-20 | 2019-06-28 | 慧与发展有限责任合伙企业 | Distributed life cycle management for cloud platform |
| CN111726388A (en) * | 2019-03-22 | 2020-09-29 | 苏宁易购集团股份有限公司 | Cross-cluster high-availability implementation method, device, system and equipment |
| CN111880898A (en) * | 2020-07-27 | 2020-11-03 | 山东省计算中心（国家超级计算济南中心） | Service scheduling method based on micro-service architecture and implementation system thereof |
| CN113312328A (en) * | 2021-07-28 | 2021-08-27 | 阿里云计算有限公司 | Control method, data processing method, data access method and computing device |
| CN114615177A (en) * | 2022-03-03 | 2022-06-10 | 腾讯科技（深圳）有限公司 | Load detection method and device of cloud platform, electronic equipment and storage medium |
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| CN107623732A (en) * | 2017-09-15 | 2018-01-23 | 郑州云海信息技术有限公司 | A kind of date storage method based on cloud platform, device, equipment and storage medium |
| CN109947557A (en) * | 2017-12-20 | 2019-06-28 | 慧与发展有限责任合伙企业 | Distributed life cycle management for cloud platform |
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| CN113312328A (en) * | 2021-07-28 | 2021-08-27 | 阿里云计算有限公司 | Control method, data processing method, data access method and computing device |
| CN113312328B (en) * | 2021-07-28 | 2022-01-25 | 阿里云计算有限公司 | Control method, data processing method, data access method and computing device |
| CN114615177A (en) * | 2022-03-03 | 2022-06-10 | 腾讯科技（深圳）有限公司 | Load detection method and device of cloud platform, electronic equipment and storage medium |
| CN114615177B (en) * | 2022-03-03 | 2023-10-13 | 腾讯科技（深圳）有限公司 | Load detection method and device of cloud platform, electronic equipment and storage medium |
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Application publication date: 20161109 |
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