CN110442644A - Block chain data filing storage method, device, computer equipment and storage medium - Google Patents
Block chain data filing storage method, device, computer equipment and storage medium Download PDFInfo
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Abstract
This application involves block storage system fields, a kind of block chain data filing storage method is provided, device, computer equipment and storage medium, by being periodically detected data to be archived and carrying out fragment processing to it, complete data filing, avoid data redundancy, storage mode can be flexibly selected according to fragment data source type, save the security availability of data from damage, and distribute fragment data to the memory node into corresponding distributed storage engine, by way of distributed storage, realize the dilatation of block chain data space, meet demand of the linear increase of block chain data to memory space, improve data-handling efficiency.
Description
Technical field
This application involves technical field of data storage, more particularly to a kind of block chain data filing storage method, device,
Computer equipment and storage medium.
Background technique
With the development of science and technology, internet has been deep into daily life.People can pass through interconnection
Net inquiry data, purchase commodity, social activity etc., have brought huge convenience.However as the explosive of internet data
Increase, the challenge of network security and mass data storage as each enterprise-like corporation then occurs using block chain
Technology carries out the mode of record storage to mass data, ensure that safety and the memory space of data.
Block chain technology, also referred to as distributed account book technology are that one kind is participated in remembering jointly by several computer equipments
Account, the new technology of common a complete distributed data base of maintenance, block chain technology have decentralization, open and clear spy
Property, every computer equipment can be participated in as the node device of block chain can between data-base recording and respectively calculating equipment
It is synchronized with being rapidly performed by data, each node device of block chain will usually handle the common recognition of block catenary system high concurrent, verifying
And read-write operation.
But block chain node storage space with block increase and linear increase, block node storage space are limited, increase
Area's data of amount can gradually influence the response speed of memory, so influence node device to the common recognition of high concurrent, verifying with
And the efficiency of read-write operation, it reduces to data-handling efficiency.
Summary of the invention
Based on this, it is necessary to reduce the data-handling efficiency of node device for existing block chain data storage scheme
Problem provides a kind of block chain data filing storage method, device, computer equipment and storage medium.
A kind of block chain data filing storage method, method include:
The data for meeting default archive condition in block chain data are periodically detected, data to be archived are obtained, preset filing
Condition includes height value condition and access frequency condition；
Fragment processing is carried out to data to be archived, obtains fragment data；
It identifies the data source type of fragment data, obtains distributed storage engine corresponding with data source type, obtain
To target distribution formula storage engines；
Fragment data is stored into the memory node into target distribution formula storage engines.
It is periodically detected the data for meeting default archive condition in block chain data in one of the embodiments, obtains
Data to be archived include:
It is counted in block chain link point between the data of minimum altitude value and the data of maximum height value according to cycle time
Total amount of data, cycle time are less than the required time for generating the data set for meeting default total amount；
When total amount of data is greater than default total amount, then the data set for meeting default total amount is successively obtained from minimum altitude value；
Detection data concentrates the access frequency of each data；
When data each in data set are respectively less than default access frequency, then the data in data set are determined as to be archived
Data.
In one of the embodiments, distributed storage engine include privately owned formula storage engines, alliance's formula storage engines with
And publicly-owned formula storage engines, it identifies the data source type of fragment data, obtains distribution corresponding with data source type and deposit
Storing up engine includes:
When recognizing fragment data from privately owned block chain, the corresponding entrance ginseng of general privately owned formula storage engines is modified
Number, obtains privately owned formula storage engines；
When recognizing fragment data and being based on intelligent contract from alliance's block chain, general alliance's formula storage engines are modified
Corresponding suction parameter obtains alliance's formula storage engines；
When recognizing fragment data from publicly-owned formula block chain, the corresponding entrance of general publicly-owned formula storage engines is modified
Parameter obtains the publicly-owned formula storage engines of target.
Fragment data is stored to the memory node packet into target distribution formula storage engines in one of the embodiments,
It includes:
According to hash algorithm, the cryptographic Hash of fragment data is calculated；
Fragment data is stored into target distribution formula storage engines to the memory node of cryptographic Hash direction.
Fragment data is stored to the memory node packet into target distribution formula storage engines in one of the embodiments,
It includes:
Assessment classification is carried out to each memory node, determines the storage performance of each memory node；
Weight distribution assessment is carried out to fragment data, determines the storage demand of fragment data；
According to the storage demand of the storage performance of each memory node and each fragment data, fragment data is stored to target
Memory node in distributed storage engine.
The data fragmentation where fragment data includes multiple data groupings in one of the embodiments,；By fragment data
After storing the memory node into target distribution formula storage engines, further includes:
Calculate the cryptographic Hash of each data grouping；
According to the cryptographic Hash of each data grouping, Mei Keer tree corresponding with the data fragmentation where each data grouping is constructed；
Record the corresponding relationship of the memory node where each Mei Keer tree and each data fragmentation.
In one of the embodiments, further include:
Capacity check is carried out to each memory node；
When each memory node capacity reaches default memory capacity, memory node extended requests are sent.
A kind of block chain data filing storage device, device include:
Data detection module, for being periodically detected the data for meeting default archive condition in block chain data, obtain to
File data, default archive condition includes height value condition and access frequency condition；
Data fragmentation module obtains fragment data for carrying out fragment processing to data to be archived；
Distributed storage engine obtains module, for identification the data source type of fragment data, acquisition and data source
The corresponding distributed storage engine of type, obtains target distribution formula storage engines；
Data memory module, for fragment data to be stored to the memory node into target distribution formula storage engines.
A kind of computer equipment, including memory and processor, the memory are stored with computer program, the processing
Device performs the steps of when executing the computer program
The data for meeting default archive condition in block chain data are periodically detected, data to be archived are obtained, preset filing
Condition includes height value condition and access frequency condition；
Fragment processing is carried out to data to be archived, obtains fragment data；
It identifies the data source type of fragment data, obtains distributed storage engine corresponding with data source type, obtain
To target distribution formula storage engines；
Fragment data is stored into the memory node into target distribution formula storage engines.
A kind of computer readable storage medium, is stored thereon with computer program, and the computer program is held by processor
It is performed the steps of when row
The data for meeting default archive condition in block chain data are periodically detected, data to be archived are obtained, preset filing
Condition includes height value condition and access frequency condition；
Fragment processing is carried out to data to be archived, obtains fragment data；
It identifies the data source type of fragment data, obtains distributed storage engine corresponding with data source type, obtain
To target distribution formula storage engines；
Fragment data is stored into the memory node into target distribution formula storage engines.
Above-mentioned block chain data filing storage method, device, computer equipment and storage medium, by be periodically detected to
Filing data simultaneously carry out fragment processing to it, complete data filing, avoid data redundancy, can according to fragment data source type
Flexible selection storage mode, saves the security availability of data from damage, and fragment data is distributed to corresponding distributed storage
Memory node in engine realizes the dilatation of block chain data space, meets block chain by way of distributed storage
Demand of the linear increase of data to memory space improves data-handling efficiency.
Detailed description of the invention
Fig. 1 is the applied environment figure of block chain data filing storage method in one embodiment；
Fig. 2 is the flow diagram of block chain data filing storage method in one embodiment；
Fig. 3 is the detailed process schematic diagram of block chain data filing storage method in another embodiment；
Fig. 4 is the schematic diagram of Hash ring in one embodiment；
Fig. 5 is the structural block diagram of block chain data filing storage device in another embodiment；
Fig. 6 is the detailed block diagram of block chain data filing storage device in another embodiment；
Fig. 7 is the internal structure chart of computer equipment in one embodiment.
Specific embodiment
It is with reference to the accompanying drawings and embodiments, right in order to which the objects, technical solutions and advantages of the application are more clearly understood
The application is further elaborated.It should be appreciated that specific embodiment described herein is only used to explain the application, not
For limiting the application.
Block chain data filing storage method provided by the present application, can be applied in application environment as shown in Figure 1.Area
Block chain network 102 includes multiple block chain nodes, block chain network 102, control system 104 and distributed memory system 106
Between communicated two-by-two by network implementations.Wherein, block chain node and control system 104 can be different computer equipment
(computer or server), is also possible to the application program being deployed on same computer or server, and every computer is set
The standby node device as block chain can participate in rapidly being counted between data-base recording and each computer equipment
According to synchronization, each block chain node has corresponding control system 104, and distributed memory system 106 may include more and deposit
Store up equipment, wherein more storage equipment are got up by application program or software assembly externally provides data storage and access jointly
Function.Distributed memory system 106 can provide block chain block data storage service at least one block chain node.Wherein,
Control system 104 is illustrated by taking multiple servers as an example, and server, which is periodically periodically detected in block chain data, to be met in advance
If the data of archive condition obtain data to be archived, fragment processing is carried out to the data to be archived, fragment data is obtained, knows
The data source type of other fragment data obtains distributed storage engine corresponding with data source type, obtains target distribution
Fragment data is stored the memory node into target distribution formula storage engines by formula storage engines.Above scheme is being realized to area
While block chain data carry out filing processing, further through the mode of distributed storage, the expansion of block chain data space is realized
Hold, meets demand of the linear increase of block chain data to memory space.Wherein, server can with independent server or
It is the server cluster of multiple server compositions to realize.
In one of the embodiments, as shown in Fig. 2, a kind of block chain data filing storage method is provided, with the party
It is illustrated for the server in control system 104 that method is applied in Fig. 1, comprising the following steps:
Step S200 is periodically detected the data for meeting default archive condition in block chain data, obtains data to be archived,
Default archive condition includes height value condition and access frequency condition.
Block chain, also referred to as distributed account book technology are that one kind is participated in keeping accounts jointly by several computer equipments, altogether
With the new technology of a complete distributed data base (account book can be regarded as) of maintenance.Block chain data refer to sequentially in time by
Block file (folio can be regarded as) one by one is bound into, and strings together the data to form chain form.Specifically, block chain
For each in data " block number evidence " just like " folio " in account book, every page all has recorded several data transaction records,
Account page page by page is bound up sequentially in time just forms a complete account book i.e. distributed data base.User can pass through
Block chain node in terminal block chain network 102 initiates data trade request, submits data to be processed, the block chain node
After receiving data processing request, corresponding data processing is carried out to data to be processed, for example, clicking through with other block chain links
Row data common recognition processing, storage etc..Data filing is that the data that will be no longer commonly used move on to an individually storage equipment
To carry out the process of long-term preservation.The height value of block number evidence in block chain and access can intuitively reflect block again and again
Whether the block number of chain node is according to being the data (dsc data) being commonly used or long-term not used data (cold data), therefore this implementation
In, using data height value condition and access frequency condition as the default filing item of data to be archived in detection block chain data
Part.Specifically, default filing item will be met according to the data for meeting default archive condition in cycle time detection block chain data
The data of part are determined as data to be archived, and default archive condition includes height value condition and access frequency condition.
Step S400 carries out fragment processing to data to be archived, obtains fragment data.
After obtaining data to be archived, it can be and data to be archived are divided into multiple (at least two) data groupings,
Each data grouping is at least added in two data fragmentations, guarantees that the data of every two data fragmentation storage include all
Packet data (data to be archived), and each data fragmentation does not include all packet datas.Specifically, by number to be archived
According to being grouped, the packet mode of average division can be used, data to be archived are divided into the packet data including same quantity of data,
Or by way of random division, data to be archived are divided into the packet data including different data amount, then will be divided
Each data grouping afterwards is added at least two data fragmentations.It will not be lost when some data fragmentation is by malicious sabotage
Partial data is lost, and file can be repaired using other two data fragmentations.
Step S600 identifies the data source type of fragment data, obtains distribution corresponding with data source type and deposits
Engine is stored up, target distribution formula storage engines are obtained.
Storage engines are for by the number in MySQL (Structured Query Language, constructionization inquire speech)
It is stored in memory according to a variety of different technologies, each technology in these technologies all uses different memory mechanisms, rope
Draw skill, locking level and extensive different function and ability are finally provided, by selecting different technologies, obtains additional
Speed or function, so as to improve allomeric function is applied.It can obtain and come with data by identifying block chain data source type
The corresponding distributed storage engine of Source Type, obtains target distribution formula storage engines.
Fragment data is stored the memory node into target distribution formula storage engines by step S800.
The storage mode of the present embodiment block chain data is distributed storage, is that the dispersion of block chain data is stored in more
In independent equipment, using expansible system structure, storage load is shared using more storage servers, it is not only increased
Reliability, availability and the access efficiency of system, are also easy to extend.A memory node i.e. platform is independent for storing data
Equipment (storage server).After getting corresponding distributed storage engine, fragment data is stored to target distribution formula and is deposited
Store up memory node in engine.Specifically, can be the cryptographic Hash according to fragment data, fragment data is stored to cryptographic Hash and is directed toward
Memory node.Be also possible to identify the data volume or data significance level level identification of fragment data, according to data volume or
Fragment data is distributed to the corresponding each memory node of level identification and is stored by data significance level level identification.
Above-mentioned block chain data filing storage method, by being periodically detected data to be archived and being carried out at fragment to it
Reason can be avoided data redundancy, reduces arithmetic speed, can flexibly select storage mode according to fragment data source, save from damage
The security availability of data, and the memory node that fragment data is distributed into corresponding distributed storage engine can be saved
Node storage space guarantees memory space formedness and data high availability, improves data-handling efficiency.
Meet default archive condition in block chain data as shown in figure 3, being periodically detected in one of the embodiments,
Data, obtaining data to be archived includes: step S220, according to the data of minimum altitude value in cycle time statistics block chain link point
Total amount of data between the data of maximum height value, cycle time, which is less than, generates being taken for the data set for meeting default total amount
Between, when total amount of data is greater than default total amount, then the data set for meeting default total amount, testing number are successively obtained from minimum altitude value
It then will be in data set when data each in data set are respectively less than default access frequency according to the access frequency for concentrating each data
Data be determined as data to be archived.
The number that block chain node is locally stored, the i.e. data of minimum altitude value and maximum height value can be specifically to look at
Data between all total amount of data (i.e. data total number), if total amount of data is greater than default total amount, from minimum altitude value
Data start to obtain the data of default total amount, if each the data access amount of default total amount be respectively less than it is default when visiting frequency, really
Surely default total amount is to meet the data of archive condition, wherein cycle time is less than the generation time for reaching the data of default total amount.
Preset data total amount can be n, specifically can carry out free setting according to the data-handling capacity of server, generate default total amount
The required times of data can be determined by data traffic in business procession.The cycle time that will test is set smaller than pre-
If the data generation time of total amount, could will meet before the data for generating default total amount again the data of default total amount into
Row filing, avoids the data accumulation for meeting archive condition.Specifically, the minimum altitude value for the data being for example locally stored is H0,
Maximum height Value Data is H31, then it is H31-H0+1=31, i.e. minimum altitude value to maximum height that total amount of data, which is locally stored,
Have 31 data between value, when default total amount is 20, the data of the minimum altitude value being locally stored and maximum height value it
Between total amount of data (31) be greater than default total amount (20), then obtain that meet this default total since the data of minimum altitude value
The data of amount 20, the i.e. data of H0-H19.It further, is more than pre- using access frequency in list records nearest a period of time
If the corresponding height value of data and data of access frequency, presetting access frequency is p, and access frequency is more than the data of p can be with
For { X1...X30 }, when the data H0-H19 of default total amount is not at { X1...X30 }, determine that the H0-H19 is number to be archived
According to.In the present embodiment, the cycle time that will test is set smaller than the required time for generating the data of default total amount, can be again
Data filing will be carried out with the data block for meeting default total amount before generating the data of default total amount, avoids local data to be archived
Accumulation, causes data redundancy.
As shown in figure 3, carrying out fragment processing to data to be archived in one of the embodiments, packet segment is obtained
Include: step S420 carries out fragment processing to data to be archived using consistency hash algorithm, obtains fragment data.
By taking consistency Hash (Hash) algorithm as an example, consistency Hash can be used cuts ring algorithm to realize data fragmentation,
Hash ring cutting is segmented into the fragment of same size, then these fragments is given to different memory nodes and is responsible for.Specifically, passing through
Corresponding Key (key assignments, K1 as shown in Figure 4) is hashing onto annular hash space by hash algorithm, and packet data is passed through spy
The corresponding cryptographic Hash of data is calculated in fixed hash function, by cryptographic Hash hash to Hash ring (Hash ring, it is as shown in Figure 4
Annulus) on, fragment data is formed, when a memory node exits, the fragment being responsible for does not need to merge it clockwise
After give memory node, memory node a, b and c as described in Figure 4, but can be more flexible using entire fragment as one
Entirety gives any memory node.In practice, a fragment is mostly as the smallest Data Migration and backup unit.It is understood that
, in other embodiments, fragment processing method can also be that the modes such as placement or interval division carry out in turn.This programme
In, data grouping at least forms 3 data fragmentations, and each data fragmentation is made of part packet data and (does not need to include institute
Some packet datas), the number of data packets in each data fragmentation can be the same or different, and equally be also required to guarantee every
A data grouping is at least added to two data fragmentations, at least two stored copies is formed, even if some in storage system is deposited
Storage node is attacked, and complete data will not be revealed, can be according to the copy data of other memory nodes to loss data
It is repaired.By carrying out fragment processing to data, data processing speed and data throughout are improved, prevents data volume is excessive from making
At obstruction, and consistency Hash can be very good to solve stability problem, all memory nodes can be arranged in ending phase
On the Hash ring connect.
As shown in figure 3, distributed storage engine includes publicly-owned formula storage engines, alliance's formula in one of the embodiments,
Storage engines and privately owned formula storage engines identify the data source type of fragment data, obtain corresponding with data source type
Distributed storage engine, obtaining target distribution formula storage engines includes: step S620, when recognize fragment data from private
When having block chain, the corresponding suction parameter of general privately owned formula storage engines is modified, privately owned formula storage engines are obtained, when recognizing point
When sheet data is based on intelligent contract from alliance's block chain, the corresponding suction parameter of general alliance's formula storage engines is modified, is obtained
Alliance's formula storage engines are taken, when recognizing fragment data from publicly-owned formula block chain, modify general publicly-owned formula storage engines
Corresponding suction parameter obtains publicly-owned formula storage engines.
Distributed storage engine includes publicly-owned formula storage engines, alliance's formula storage engines and privately owned formula storage engines, number
It may include that privately owned block chain (privately owned chain), alliance's block chain (alliance's chain) and publicly-owned formula block chain are (publicly-owned according to source type
Chain), privately owned formula storage engines, alliance's formula storage engines and publicly-owned formula storage engines refer respectively to above-mentioned privately owned for storing
The storage engines of the data of the data of block chain, the data of alliance's block chain and publicly-owned formula block chain.When completion is to be archived
The fragment of data is handled, and after obtaining fragment data, is identified the data source type of fragment data, is obtained corresponding with data source
Distributed storage engine.Specifically, modifying general privately owned formula storage engines when identifying that fragment data derives from privately owned block chain
Corresponding suction parameter obtains privately owned formula storage engines, and privately owned formula storage engines are used to store the data of the privately owned block chain in source,
It is used for itself；When identifying that fragment data is based on intelligent contract from alliance's block chain, modifies general alliance's formula storage and draw
Corresponding suction parameter is held up, alliance's formula storage engines are obtained, alliance's formula storage engines are used to store from alliance's block chain
Data, for specific multi-party use；When identifying that fragment data derives from publicly-owned formula block chain, modifies general publicly-owned formula storage and draw
Corresponding suction parameter is held up, publicly-owned formula storage engines are obtained, publicly-owned formula storage engines derive from publicly-owned formula block chain for storing
Data, for using in many ways.It is also possible to receive parameter change request, the target modification that request carries is modified according to parameter and is joined
Number, builds storage engines corresponding with target modification parameter.In the present embodiment, according to the data source type of fragment data, spirit
Selection storage mode living, guarantees the security availability of data.
As shown in figure 3, fragment data is stored depositing into target distribution formula storage engines in one of the embodiments,
Storing up node includes: step S820, according to hash algorithm, calculates the cryptographic Hash of fragment data, and fragment data is stored to target point
The memory node that cryptographic Hash is directed toward in cloth storage engines.
After obtaining corresponding distributed storage engine, the Kazakhstan that each fragment data is calculated according to hash algorithm can be
Uncommon value, cryptographic Hash are directed toward the storage address of fragment data, fragment data are stored the cryptographic Hash into target distribution formula storage engines
The memory node of direction.By taking privately owned formula storage engines as an example, according to the storage address that the cryptographic Hash of fragment data is directed toward, by fragment
Data store the corresponding memory node of storage address into privately owned formula storage engines.In other embodiments, it can also preset
The default significance level rank of fragment data identifies the important level mark of each fragment data, when the important journey of fragment data
When degree rank is high-grade, selection is calculated the memory node that power is strong, calculation speed is fast and is stored.It is also possible to the number of default fragment data
According to amount, data volume possessed by fragment data is identified, when the data volume entrained by the fragment data is higher than preset threshold, by fragment
Data distribute the memory node big to capacity.In the present embodiment, the storage of fragment data is completed according to the cryptographic Hash of fragment data
The distribution of node, corresponding storage distribute data, can be convenient for the corresponding relationship of record distribution data and memory node.
Fragment data is stored to the memory node packet into target distribution formula storage engines in one of the embodiments,
Include: step S840 carries out assessment classification to each memory node, determines the storage performance of each memory node, carries out to fragment data
Weight distribution assessment, determines the storage demand of fragment data, according to the storage performance of each memory node and each fragment data
Fragment data is stored the memory node into target distribution formula storage engines by storage demand.
The storage mode of fragment data, which can also be, carries out assessment classification to memory node in advance, specifically, according to storage
Capacity, calculation speed and calculation power (computing capability) of node etc. make assessment to memory node, determine the storage performance of memory node；
Weight distribution assessment is carried out to significance level, data volume and type of fragment data etc. simultaneously, determines the storage of fragment data
Demand carries out reciprocity selection, by fragment data then according to the storage performance of each both candidate nodes and each fragment data storage demand
Store the suitable memory node into target distribution formula storage engines.Wherein, memory node is the node respectively to work independently.Tool
Body, it can be data confidentiality degree, data volume and the data type etc. of identification fragment data, according to the calculation of each memory node
Power calculates speed and each memory node is numbered in the performances such as capacity, such as will calculate that power is most strong, it is most fast to calculate speed or capacity is maximum
Memory node number consecutively is 1,2,3 ... m etc., by significant data or data volume is big or data confidentiality degree is high data successively
The memory node that number is 1,2,3 ... m is sent to be stored.In the present embodiment, by being sent out to data fragmentation, and by data
It send and realizes that the height of data is handled up to corresponding memory node, reduce the technical costs of equipment.
As shown in figure 3, the data fragmentation where fragment data includes multiple data groupings in one of the embodiments,；
After fragment data to store to the memory node into target distribution formula storage engines, further includes: step S900 calculates each data
The cryptographic Hash of grouping constructs plum gram corresponding with the data fragmentation where each data grouping according to the cryptographic Hash of each data grouping
You set, and record the corresponding relationship of the memory node where each Mei Keer tree and each data fragmentation.
Mei Keer tree or Merck tree, Hash tree, are a kind of tree form data structures, and each leaf node of tree stores data
The cryptographic Hash of block.Data fragmentation where fragment data includes multiple data groupings, in the Hash that each data grouping is calculated
After value, Mei Keer corresponding with the data fragmentation where each data grouping can be established based on the cryptographic Hash of each data grouping
Tree can be referred to as fragment Mei Keer tree for ease of understanding, and the corresponding fragment Mei Keer tree of each data fragmentation is each getting
It, can will be where each fragment Mei Keer tree and each data fragmentation between memory node after the corresponding fragment Mei Keer tree of data fragmentation
Corresponding relationship recorded.In the present embodiment, lookup and verifying to data can be realized by Mei Keer tree, improve storage
The privacy and safety of data.
As shown in figure 3, in one of the embodiments, further include: step S950 carries out capacity inspection to each memory node
It surveys, when each memory node capacity reaches default memory capacity, sends memory node extended requests.
It detects according to capacity of the cycle time to each memory node, holds when each memory node capacity reaches default storage
When amount, then memory node extended requests are sent, specifically can be the main section for sending memory node extended requests into memory node
Point, host node increase other memory nodes actively after receiving memory node extended requests to achieve the purpose that expanding node.
Wherein, host node has some changes in management cluster, such as create or delete index, increase or remove other nodes etc..
It is also possible to transmission memory node extended requests and increases it after management terminal receives memory node extended requests to management terminal
His memory node extended storage capacity.In the present embodiment, by periodically carrying out capacity check to memory node, it is empty to expand storage
Between, it can be avoided the problem of memory space inadequate of memory node causes loss of data.
It should be understood that although each step in the flow chart of Fig. 2-3 is successively shown according to the instruction of arrow,
These steps are not that the inevitable sequence according to arrow instruction successively executes.Unless expressly stating otherwise herein, these steps
Execution there is no stringent sequences to limit, these steps can execute in other order.Moreover, at least one in Fig. 2-3
Part steps may include that perhaps these sub-steps of multiple stages or stage are not necessarily in synchronization to multiple sub-steps
Completion is executed, but can be executed at different times, the execution sequence in these sub-steps or stage is also not necessarily successively
It carries out, but can be at least part of the sub-step or stage of other steps or other steps in turn or alternately
It executes.
In one of the embodiments, as shown in figure 5, providing a kind of block chain data filing storage device, comprising: number
Module 430 and data memory module 440 are obtained according to detection module 410, data fragmentation module 420, distributed storage engine,
In:
Data detection module 410 is obtained for being periodically detected the data for meeting default archive condition in block chain data
Data to be archived, default archive condition include height value condition and access frequency condition；
Data fragmentation module 420 obtains fragment data for carrying out fragment processing to data to be archived；
Distributed storage engine obtains module 430, for identification the data source type of fragment data, obtains and comes with data
The corresponding distributed storage engine of Source Type, obtains target distribution formula storage engines；
Data memory module 440, for fragment data to be stored to the memory node into target distribution formula storage engines.
As shown in fig. 6, block chain data filing storage device further includes relation record module in one of the embodiments,
450, for calculating the cryptographic Hash of each data grouping, according to the cryptographic Hash of each data grouping, where building and each data grouping
The corresponding Mei Keer tree of data fragmentation records the corresponding relationship of the memory node where each Mei Keer tree and each data fragmentation.
As shown in fig. 6, block chain data filing storage device further includes capacity check module in one of the embodiments,
460, for carrying out capacity check to each memory node, when each memory node capacity reaches default memory capacity, send storage
Point spread request.
Data detection module 410 is also used to when total amount of data is greater than default total amount in one of the embodiments, then from
Minimum altitude value successively obtains the data set for meeting default total amount, and detection data concentrates the access frequency of each data, works as data
When each data being concentrated to be respectively less than default access frequency, then the data in data set are determined as data to be archived.
Distributed storage engine acquisition module 430, which is also used to work as, in one of the embodiments, recognizes fragment data
When derived from privately owned block chain, the corresponding suction parameter of general privately owned formula storage engines is modified, privately owned formula storage engines is obtained, works as knowledge
When being clipped to fragment data and being based on intelligent contract from alliance's block chain, the corresponding entrance ginseng of general alliance's formula storage engines is modified
Number obtains alliance's formula storage engines, when recognizing fragment data from publicly-owned formula block chain, modifies general publicly-owned formula storage
The corresponding suction parameter of engine obtains the publicly-owned formula storage engines of target.
Data memory module 440 is also used to calculate the Kazakhstan of fragment data according to hash algorithm in one of the embodiments,
Fragment data, is stored into target distribution formula storage engines the memory node of cryptographic Hash direction by uncommon value；Alternatively, being saved to each storage
Point carries out assessment classification, determines the storage performance of each memory node, carries out weight distribution assessment to fragment data, determines fragment number
According to storage demand fragment data is stored according to the storage demand of the storage performance of each memory node and each fragment data
Memory node into target distribution formula storage engines.
Specific restriction about block chain data filing storage device may refer to above for block chain data filing
The restriction of storage method, details are not described herein.Modules in above-mentioned block chain data filing storage device can whole or portion
Divide and is realized by software, hardware and combinations thereof.Above-mentioned each module can be embedded in the form of hardware or independently of computer equipment
In processor in, can also be stored in a software form in the memory in computer equipment, in order to processor calling hold
The corresponding operation of the above modules of row.
A kind of computer equipment is provided in one of the embodiments, which can be server, in
Portion's structure chart can be as shown in Figure 7.The computer equipment includes that the processor, memory, network connected by system bus connects
Mouth and database.Wherein, the processor of the computer equipment is for providing calculating and control ability.The storage of the computer equipment
Device includes non-volatile memory medium, built-in storage.The non-volatile memory medium be stored with operating system, computer program and
Database.The built-in storage provides environment for the operation of operating system and computer program in non-volatile memory medium.It should
The database of computer equipment is used for memory block chain data.The network interface of the computer equipment is used for logical with external terminal
Cross network connection communication.To realize a kind of block chain data filing storage method when the computer program is executed by processor.
It will be understood by those skilled in the art that structure shown in Fig. 7, only part relevant to application scheme is tied
The block diagram of structure does not constitute the restriction for the computer equipment being applied thereon to application scheme, specific computer equipment
It may include perhaps combining certain components or with different component layouts than more or fewer components as shown in the figure.
A kind of computer equipment, including memory and processor are provided in one of the embodiments, are deposited in memory
Computer program is contained, which performs the steps of when executing computer program is periodically detected in block chain data completely
The data of the default archive condition of foot, obtain data to be archived, default archive condition includes height value condition and access frequency item
Part carries out fragment processing to data to be archived, obtains fragment data, identifies the data source type of fragment data, obtains and counts
According to the corresponding distributed storage engine of source type, target distribution formula storage engines are obtained, fragment data is stored to target point
Memory node in cloth storage engines.
It also performs the steps of when processor executes computer program in one of the embodiments, according to cycle time
The total amount of data in block chain link point between the data of minimum altitude value and the data of maximum height value is counted, cycle time is less than
Generate the required time for meeting the data set of default total amount, when total amount of data is greater than default total amount, then from minimum altitude value according to
Secondary to obtain the data set for meeting default total amount, detection data concentrates the access frequency of each data, when data each in data set
When respectively less than presetting access frequency, then the data in data set are determined as data to be archived.
It also performs the steps of to work as when processor executes computer program in one of the embodiments, and recognizes fragment
Data source modifies the corresponding suction parameter of general privately owned formula storage engines, obtains privately owned formula storage and draw when privately owned block chain
It holds up, when recognizing fragment data and being based on intelligent contract from alliance's block chain, it is corresponding to modify general alliance's formula storage engines
Suction parameter, obtain alliance's formula storage engines, when recognizing fragment data from publicly-owned formula block chain, modify general public affairs
There is the corresponding suction parameter of formula storage engines, obtains the publicly-owned formula storage engines of target.
It also performs the steps of when processor executes computer program in one of the embodiments, according to hash algorithm,
Fragment data is stored into target distribution formula storage engines the storage section of cryptographic Hash direction by the cryptographic Hash for calculating fragment data
Point.
It also performs the steps of when processor executes computer program in one of the embodiments, to each memory node
Assessment classification is carried out, determines the storage performance of each memory node, weight distribution assessment is carried out to fragment data, determines fragment data
Storage demand, according to the storage demand of the storage performance of each memory node and each fragment data, by fragment data store to
Memory node in target distribution formula storage engines.
It is also performed the steps of when processor executes computer program in one of the embodiments, and calculates each data point
The cryptographic Hash of group constructs Mei Keer corresponding with the data fragmentation where each data grouping according to the cryptographic Hash of each data grouping
Tree records the corresponding relationship of the memory node where each Mei Keer tree and each data fragmentation.
It also performs the steps of when processor executes computer program in one of the embodiments, to each memory node
Capacity check is carried out, when each memory node capacity reaches default memory capacity, sends memory node extended requests.
A kind of computer readable storage medium is provided in one of the embodiments, is stored thereon with computer program,
It performs the steps of to be periodically detected when computer program is executed by processor and meets default archive condition in block chain data
Data, obtain data to be archived, and default archive condition includes height value condition and access frequency condition, to data to be archived into
The processing of row fragment, obtains fragment data, identifies the data source type of fragment data, obtains corresponding with data source type point
Cloth storage engines obtain target distribution formula storage engines, and fragment data is stored depositing into target distribution formula storage engines
Store up node.
When also performing the steps of when computer program is executed by processor in one of the embodiments, according to the period
Between count total amount of data between the data of minimum altitude value and the data of maximum height value in block chain link point, cycle time is small
In generating the required time for meeting the data set of default total amount, when total amount of data is greater than default total amount, then from minimum altitude value
The data set for meeting default total amount is successively obtained, detection data concentrates the access frequency of each data, when number every in data set
When according to being respectively less than default access frequency, then the data in data set are determined as data to be archived.
It is also performed the steps of when computer program is executed by processor in one of the embodiments, when recognizing point
When sheet data derives from privately owned block chain, the corresponding suction parameter of general privately owned formula storage engines is modified, obtains privately owned formula storage
Engine modifies general alliance's formula storage engines pair when recognizing fragment data and being based on intelligent contract from alliance's block chain
The suction parameter answered obtains alliance's formula storage engines, when recognizing fragment data from publicly-owned formula block chain, modifies general
The corresponding suction parameter of publicly-owned formula storage engines, obtains the publicly-owned formula storage engines of target.
It also performs the steps of when computer program is executed by processor in one of the embodiments, and is calculated according to Hash
Method calculates the cryptographic Hash of fragment data, and fragment data is stored into target distribution formula storage engines to the storage of cryptographic Hash direction
Node.
It is also performed the steps of when computer program is executed by processor in one of the embodiments, and each storage is saved
Point carries out assessment classification, determines the storage performance of each memory node, carries out weight distribution assessment to fragment data, determines fragment number
According to storage demand fragment data is stored according to the storage demand of the storage performance of each memory node and each fragment data
Memory node into target distribution formula storage engines.
It is also performed the steps of when computer program is executed by processor in one of the embodiments, and calculates each data
The cryptographic Hash of grouping constructs plum gram corresponding with the data fragmentation where each data grouping according to the cryptographic Hash of each data grouping
You set, and record the corresponding relationship of the memory node where each Mei Keer tree and each data fragmentation.
It is also performed the steps of when computer program is executed by processor in one of the embodiments, and each storage is saved
Point carries out capacity check, when each memory node capacity reaches default memory capacity, sends memory node extended requests.
Those of ordinary skill in the art will appreciate that realizing all or part of the process in above-described embodiment method, being can be with
Relevant hardware is instructed to complete by computer program, the computer program can be stored in a non-volatile computer
In read/write memory medium, the computer program is when being executed, it may include such as the process of the embodiment of above-mentioned each method.Wherein,
To any reference of memory, storage, database or other media used in each embodiment provided herein,
Including non-volatile and/or volatile memory.Nonvolatile memory may include read-only memory (ROM), programming ROM
(PROM), electrically programmable ROM (EPROM), electrically erasable ROM (EEPROM) or flash memory.Volatile memory may include
Random access memory (RAM) or external cache.By way of illustration and not limitation, RAM is available in many forms,
Such as static state RAM (SRAM), dynamic ram (DRAM), synchronous dram (SDRAM), double data rate sdram (DDRSDRAM), enhancing
Type SDRAM (ESDRAM), synchronization link (Synchlink) DRAM (SLDRAM), memory bus (Rambus) direct RAM
(RDRAM), direct memory bus dynamic ram (DRDRAM) and memory bus dynamic ram (RDRAM) etc..
Each technical characteristic of above embodiments can be combined arbitrarily, for simplicity of description, not to above-described embodiment
In each technical characteristic it is all possible combination be all described, as long as however, the combination of these technical characteristics be not present lance
Shield all should be considered as described in this specification.
The several embodiments of the application above described embodiment only expresses, the description thereof is more specific and detailed, but simultaneously
It cannot therefore be construed as limiting the scope of the patent.It should be pointed out that coming for those of ordinary skill in the art
It says, without departing from the concept of this application, various modifications and improvements can be made, these belong to the protection of the application
Range.Therefore, the scope of protection shall be subject to the appended claims for the application patent.
Claims (10)
1. a kind of block chain data filing storage method, which is characterized in that the described method includes:
The data for meeting default archive condition in block chain data are periodically detected, data to be archived, the default filing are obtained
Condition includes height value condition and access frequency condition；
Fragment processing is carried out to the data to be archived, obtains fragment data；
It identifies the data source type of the fragment data, obtains distributed storage engine corresponding with data source type, obtain
To target distribution formula storage engines；
The fragment data is stored into the memory node into the target distribution formula storage engines.
2. block chain data filing storage method according to claim 1, which is characterized in that described to be periodically detected block
Meet the data of default archive condition in chain data, obtaining data to be archived includes:
According to the data in cycle time statistics block chain link point between the data of minimum altitude value and the data of maximum height value
Total amount, the cycle time are less than the required time for generating the data set for meeting default total amount；
When the total amount of data is greater than the default total amount, then the data for meeting default total amount are successively obtained from minimum altitude value
Collection；
Check the access frequency of each data in the data set；
When data each in the data set are respectively less than default access frequency, then by the data in the data set be determined as to
File data.
3. block chain data filing storage method according to claim 1, which is characterized in that the distributed storage engine
Including privately owned formula storage engines, alliance's formula storage engines and publicly-owned formula storage engines；The number of the identification fragment data
According to source type, obtaining distributed storage engine corresponding with data source type includes:
When recognizing the fragment data from privately owned block chain, the corresponding entrance ginseng of general privately owned formula storage engines is modified
Number, obtains privately owned formula storage engines；
When recognizing the fragment data and being based on intelligent contract from alliance's block chain, general alliance's formula storage engines are modified
Corresponding suction parameter obtains alliance's formula storage engines；
When recognizing the fragment data from publicly-owned formula block chain, the corresponding entrance of general publicly-owned formula storage engines is modified
Parameter obtains publicly-owned formula storage engines.
4. block chain data filing storage method according to claim 1, which is characterized in that described by the fragment data
The memory node stored into the target distribution formula storage engines includes:
According to hash algorithm, the cryptographic Hash of the fragment data is calculated；
The fragment data is stored to the memory node being directed toward to cryptographic Hash described in target distribution formula storage engines.
5. block chain data filing storage method according to claim 1, which is characterized in that described by the fragment data
The memory node stored into the target distribution formula storage engines includes:
Assessment classification is carried out to each memory node, determines the storage performance of each memory node；
Weight distribution assessment is carried out to the fragment data, determines the storage demand of the fragment data；
According to the storage demand of the storage performance of each memory node and each fragment data, the fragment data is deposited
Store up the memory node into target distribution formula storage engines.
6. block chain data filing storage method according to any one of claim 1 to 5, which is characterized in that described point
Data fragmentation where sheet data includes multiple data groupings；Described store the fragment data to the target distribution formula is deposited
After memory node in storage engine, further includes:
Calculate the cryptographic Hash of each data grouping；
According to the cryptographic Hash of each data grouping, Mei Keer tree corresponding with the data fragmentation where each data grouping is constructed；
Record the corresponding relationship of the memory node where each Mei Keer tree and each data fragmentation.
7. block chain data filing storage method according to claim 1, which is characterized in that further include:
Capacity check is carried out to each memory node；
When each memory node capacity reaches default memory capacity, memory node extended requests are sent.
8. a kind of block chain data filing storage device, which is characterized in that described device includes:
Data detection module obtains to be archived for being periodically detected the data for meeting default archive condition in block chain data
Data, the default archive condition include height value condition and access frequency condition；
Data fragmentation module obtains fragment data for carrying out fragment processing to the data to be archived；
Distributed storage engine obtains module, for identification the data source type of the fragment data, acquisition and data source
The corresponding distributed storage engine of type, obtains target distribution formula storage engines；
Data memory module, for the fragment data to be stored to the memory node into the target distribution formula storage engines.
9. a kind of computer equipment, including memory and processor, the memory are stored with computer program, feature exists
In the step of processor realizes any one of claims 1 to 7 the method when executing the computer program.
10. a kind of computer readable storage medium, is stored thereon with computer program, which is characterized in that the computer program
The step of method described in any one of claims 1 to 7 is realized when being executed by processor.
Priority Applications (2)
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|---|---|---|---|
| CN201910611644.7A CN110442644A (en) | 2019-07-08 | 2019-07-08 | Block chain data filing storage method, device, computer equipment and storage medium |
| PCT/CN2019/123147 WO2021003985A1 (en) | 2019-07-08 | 2019-12-05 | Blockchain data archiving storage method and apparatus, computer device and storage medium |
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| CN201910611644.7A CN110442644A (en) | 2019-07-08 | 2019-07-08 | Block chain data filing storage method, device, computer equipment and storage medium |
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Citations (9)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102368261A (en) * | 2011-10-14 | 2012-03-07 | 成都勤智数码科技有限公司 | Expandable running maintenance report generation method |
| CN107766147A (en) * | 2016-08-23 | 2018-03-06 | 上海宝信软件股份有限公司 | Distributed data analysis task scheduling system |
| KR101849912B1 (en) * | 2017-05-25 | 2018-04-19 | 주식회사 코인플러그 | Method for providing certificate service based on smart contract and server using the same |
| CN108664223A (en) * | 2018-05-18 | 2018-10-16 | 百度在线网络技术（北京）有限公司 | A kind of distributed storage method, device, computer equipment and storage medium |
| CN108900314A (en) * | 2018-07-19 | 2018-11-27 | 网宿科技股份有限公司 | A kind of the number of request charging method and device of network acceleration service |
| CN109376122A (en) * | 2018-09-25 | 2019-02-22 | 深圳市元征科技股份有限公司 | A kind of file management method, system and block chain node device and storage medium |
| CN109522362A (en) * | 2018-10-17 | 2019-03-26 | 北京瑞卓喜投科技发展有限公司 | Incomplete markets synchronous method, system and equipment based on block chain data |
| CN109815209A (en) * | 2019-03-20 | 2019-05-28 | 上海电力学院 | A kind of distributed memory system for Hospital Logistic lean management |
| CN109871366A (en) * | 2019-01-17 | 2019-06-11 | 华东师范大学 | A kind of storage of block chain fragment and querying method based on correcting and eleting codes |
Family Cites Families (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN109274752A (en) * | 2018-10-10 | 2019-01-25 | 腾讯科技（深圳）有限公司 | The access method and device, electronic equipment, storage medium of block chain data |
| CN109885256B (en) * | 2019-01-23 | 2022-07-08 | 平安科技（深圳）有限公司 | Data storage method, device and medium based on data slicing |
| CN109885619A (en) * | 2019-02-25 | 2019-06-14 | 篱笆墙网络科技有限公司 | Data write-in and read method and device based on distributed data base |
| CN110442644A (en) * | 2019-07-08 | 2019-11-12 | 深圳壹账通智能科技有限公司 | Block chain data filing storage method, device, computer equipment and storage medium |
-
2019
- 2019-07-08 CN CN201910611644.7A patent/CN110442644A/en active Pending
- 2019-12-05 WO PCT/CN2019/123147 patent/WO2021003985A1/en active Application Filing
Patent Citations (9)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102368261A (en) * | 2011-10-14 | 2012-03-07 | 成都勤智数码科技有限公司 | Expandable running maintenance report generation method |
| CN107766147A (en) * | 2016-08-23 | 2018-03-06 | 上海宝信软件股份有限公司 | Distributed data analysis task scheduling system |
| KR101849912B1 (en) * | 2017-05-25 | 2018-04-19 | 주식회사 코인플러그 | Method for providing certificate service based on smart contract and server using the same |
| CN108664223A (en) * | 2018-05-18 | 2018-10-16 | 百度在线网络技术（北京）有限公司 | A kind of distributed storage method, device, computer equipment and storage medium |
| CN108900314A (en) * | 2018-07-19 | 2018-11-27 | 网宿科技股份有限公司 | A kind of the number of request charging method and device of network acceleration service |
| CN109376122A (en) * | 2018-09-25 | 2019-02-22 | 深圳市元征科技股份有限公司 | A kind of file management method, system and block chain node device and storage medium |
| CN109522362A (en) * | 2018-10-17 | 2019-03-26 | 北京瑞卓喜投科技发展有限公司 | Incomplete markets synchronous method, system and equipment based on block chain data |
| CN109871366A (en) * | 2019-01-17 | 2019-06-11 | 华东师范大学 | A kind of storage of block chain fragment and querying method based on correcting and eleting codes |
| CN109815209A (en) * | 2019-03-20 | 2019-05-28 | 上海电力学院 | A kind of distributed memory system for Hospital Logistic lean management |
Cited By (27)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| WO2021003985A1 (en) * | 2019-07-08 | 2021-01-14 | 深圳壹账通智能科技有限公司 | Blockchain data archiving storage method and apparatus, computer device and storage medium |
| CN111163151A (en) * | 2019-12-26 | 2020-05-15 | 联想(北京)有限公司 | Information processing method and device and computer readable storage medium |
| CN111209336B (en) * | 2019-12-30 | 2020-09-15 | 广州博士信息技术研究院有限公司 | Data distribution method and device based on block chain and server |
| CN111209336A (en) * | 2019-12-30 | 2020-05-29 | 广州博士信息技术研究院有限公司 | Data distribution method and device based on block chain and server |
| CN111221910A (en) * | 2019-12-31 | 2020-06-02 | 杭州趣链科技有限公司 | Fragment storage method for improving block chain read-write performance |
| CN111522660A (en) * | 2020-04-16 | 2020-08-11 | 武汉有牛科技有限公司 | Big data monitoring solution based on block chain technology |
| CN111524006A (en) * | 2020-04-16 | 2020-08-11 | 武汉有牛科技有限公司 | Cross-chain payment solution based on block chain technology |
| CN111611319A (en) * | 2020-06-08 | 2020-09-01 | 杭州复杂美科技有限公司 | Distributed data storage method, device and storage medium |
| CN111770149A (en) * | 2020-06-23 | 2020-10-13 | 江苏荣泽信息科技股份有限公司 | Novel alliance chain based on distributed storage |
| CN111770149B (en) * | 2020-06-23 | 2023-02-14 | 江苏荣泽信息科技股份有限公司 | Novel alliance chain system based on distributed storage |
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| CN112231398A (en) * | 2020-09-25 | 2021-01-15 | 北京金山云网络技术有限公司 | Data storage method, device, equipment and storage medium |
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| CN112181945B (en) * | 2020-09-28 | 2023-11-21 | 中国平安人寿保险股份有限公司 | Data archiving processing method, device, computer equipment and storage medium |
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| CN112783440A (en) * | 2020-12-31 | 2021-05-11 | 深圳大学 | Data storage method and device for user node of block chain |
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| CN112291376B (en) * | 2020-12-31 | 2021-04-09 | 腾讯科技（深圳）有限公司 | Data processing method and related equipment in block chain system |
| CN112291376A (en) * | 2020-12-31 | 2021-01-29 | 腾讯科技（深圳）有限公司 | Data processing method and related equipment in block chain system |
| CN112948350A (en) * | 2021-02-02 | 2021-06-11 | 中央财经大学 | Distributed account book model cold data archiving and migration storage method based on MPT verification |
| CN113342418A (en) * | 2021-06-24 | 2021-09-03 | 国网黑龙江省电力有限公司 | Distributed machine learning task unloading method based on block chain |
| CN114546980A (en) * | 2022-04-25 | 2022-05-27 | 成都云祺科技有限公司 | Backup method, system and storage medium of NAS file system |
| CN114546980B (en) * | 2022-04-25 | 2022-07-08 | 成都云祺科技有限公司 | Backup method, system and storage medium of NAS file system |
| CN114595279A (en) * | 2022-05-06 | 2022-06-07 | 中国信息通信研究院 | Block chain data processing method and device |
| CN116755640A (en) * | 2023-08-21 | 2023-09-15 | 腾讯科技（深圳）有限公司 | Data processing method, device, computer equipment and storage medium of alliance chain |
| CN116755640B (en) * | 2023-08-21 | 2024-02-09 | 腾讯科技（深圳）有限公司 | Data processing method, device, computer equipment and storage medium of alliance chain |
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