CN114244853B - Big data sharing method, device and system - Google Patents
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Abstract
The application provides a big data sharing method, a device and a big data sharing system, wherein the method comprises the following steps: receiving a data request sent by a data requiring party through a block chain, wherein the data request comprises index information of data, and the index information comprises storage position information of the data; retrieving data in a local memory of a data provider according to the index information to obtain target data; the target data is sent to the data demander through the blockchain. The method solves the problem of excessive block chain redundant information quantity adopted by big data sharing in the prior art.
Description
Technical Field
The present application relates to the field of big data sharing technologies, and in particular, to a big data sharing method, device, computer readable storage medium, processor, and big data sharing system.
Background
As the energy revolution advances, the energy is transformed to clean and distributed, the duty ratio of renewable energy in the energy system is gradually increased, and the large-scale application of distributed energy supply gradually forms a centralized and distributed energy supply pattern. The new energy cloud platform based on the blockchain can transversely aggregate industry resources such as suppliers, power grid enterprises, energy users and the like, longitudinally service business links such as user site building consultation, construction scheme evaluation, equipment purchase, operation maintenance, settlement subsidy, grid connection and the like, and perform full-flow uplink on business demand data, so that data credible sharing is realized, a data barrier is broken, and multiparty cooperative efficiency is improved.
Currently, data sharing adopts a secure multiparty computing method, namely, a plurality of data owners are allowed to perform collaborative computing under the condition of not trust each other, a computing result is output, and any party except the computing result cannot obtain any other redundant information. Data sharing applications under blockchains can be divided into two types of modes: (1) And the resource sharing service mode supports sharing data among two or more business departments, synchronizes the data of each node in real time through the decentralization characteristic, and realizes authorized sharing of internal data resources in a recorded manner under rules through the transparentization and intelligent contract characteristic. (2) business collaborative service mode: the characteristics of triggering generation and automatic operation of intelligent contracts on a blockchain are utilized to realize safe and reliable circulation among multiple departments and multiple units in the form of on-line data passing condition judgment.
The current blockchain technology mainly has 2 problems: on the one hand, the data expansion is insufficient, the performance is low due to the insufficient throughput of the sharing transaction, and for the energy block chain, the problems of various energy transaction varieties, increased frequency and concentrated participants and low data cooperative efficiency exist, so that an intermediate layer data processing mode with expansibility is needed. On the other hand, the large-energy data has large volume and wide distribution, and the block chain has limited storage space, so that distributed storage is generated, but storage nodes become more common along with the continuous expansion of the data scale. In order to solve the problem, erasure code encoding and decoding are more applied to blockchain storage, in the prior art, a multi-copy mechanism and an MDS code are most common, the multi-copy mechanism is simple in redundancy introduction, but the storage efficiency is very low, and the traditional MDS code is relatively low in storage cost and has higher repair cost and access delay.
The prior art has three main problems:
1) The amount of blockchain redundancy information is excessive: because any node in the blockchain network backs up all transaction information on the chain, the increase of the transaction carrying data volume seriously affects the efficiency of a consensus mechanism and causes unnecessary waste of storage and calculation resources;
2) The data source expansibility is weak: because the centralized database is difficult to meet and adapt to various data storage requirements, user-defined data sources are adopted, but the standards of the data sources are not uniform, the isomerism is strong, and an intermediate layer with expansibility is urgently needed for information connection. The distributed file system connects the computer network with the nodes, a user can play two roles of a client and a server without paying attention to specific storage positions, upload and acquire information files, and can perfectly adapt to file sharing of the distributed scene;
3) Repairing a data storage node: the distributed storage has the problem that nodes are unreliable, the fault tolerance is improved by introducing redundant data based on error correction codes, and compared with the traditional MDS codes, the energy block chain random slice storage method is provided by combining piggybacking frames, and the transmission bandwidth and the restoration cost of data restoration are reduced on the premise that the distribution and storage of the original system are not changed.
The above information disclosed in the background section is only for enhancement of understanding of the background art from the technology described herein and, therefore, may contain some information that does not form the prior art that is already known in the country to a person of ordinary skill in the art.
Disclosure of Invention
The application mainly aims to provide a big data sharing method, a big data sharing device, a computer readable storage medium, a processor and a big data sharing system, so as to solve the problem of excessive blockchain redundant information quantity adopted by big data sharing in the prior art.
According to an aspect of the embodiment of the present invention, there is provided a big data sharing method, including: receiving a data request sent by a data requiring party through a block chain, wherein the data request comprises index information of data, and the index information comprises storage position information of the data; retrieving data in a local memory of a data provider according to the index information to obtain target data; and sending the target data to the data demander through the blockchain.
Optionally, retrieving data in a local memory of the data provider according to the index information to obtain target data, including: determining a storage node where a corresponding data block is located according to the storage position information, wherein the data in the local memory comprises a plurality of data blocks, the data blocks are in one-to-one correspondence with the storage nodes, and the index information also comprises the data block information of the target data and the storage position information of the data block of the target data; and reading the data block stored by the storage node to obtain the target data.
Optionally, the storage node of the local memory includes a data node and a check node, the data node is configured to store the target data, the data node is configured to store check data corresponding to the target data, and before the data block stored in the storage node is read to obtain the target data, the method further includes: under the condition that a data node corresponding to the target data fails, calculating according to the check data to obtain the target data; and under the condition that the check node corresponding to the target data fails, calculating to obtain the check data according to the target data.
Optionally, in the case that the data node fails or the check node fails, performing data restoration by adopting a Bayesian fault-tolerant algorithm.
Optionally, the nodes of the blockchain communicate over a P2P network.
Optionally, the index information is stored on the blockchain after being encrypted.
According to another aspect of the embodiment of the present invention, there is provided a big data sharing apparatus, including: a receiving unit, configured to receive a data request sent by a data demander through a blockchain, where the data request includes index information of data, and the index information includes storage location information of the data; the acquisition unit is used for retrieving data in a local memory of the data provider according to the index information to obtain target data; and the sending unit is used for sending the target data to the data demander through the blockchain.
According to still another aspect of the embodiments of the present invention, there is provided a computer-readable storage medium including a stored program, wherein the program performs any one of the methods.
According to yet another aspect of an embodiment of the present invention, there is provided a processor for running a program, wherein the program when run performs any one of the methods.
According to yet another aspect of an embodiment of the present invention, there is provided a big data sharing system including a blockchain, a local memory of a blockchain node, and a big data sharing device including means for performing any one of the methods.
In the embodiment of the invention, in the big data sharing method, firstly, a receiving data request party sends a data request through a block chain, wherein the data request comprises index information of data, and the index information comprises storage position information of the data; then, retrieving data in a local memory of the data provider according to the index information to obtain target data; finally, the target data is sent to the data demander through the blockchain. According to the method, a data owner randomly stores data in a local memory under a chain, each independent data index is encrypted and then uploaded to a block chain consensus node, when data transaction sharing is needed, a data demand party sends a data request to the data owner through a block chain, after verification, the data demand party retrieves and obtains the local coded data, and decoding is carried out to obtain complete data, and therefore, only the local memory of the consensus node of the block chain stores all the block data, large data sharing can be achieved, all the nodes are not required to backup all the block data, and the problem that the redundant information quantity of the block chain adopted by the large data sharing in the prior art is excessive is solved.
Drawings
The accompanying drawings, which are included to provide a further understanding of the application and are incorporated in and constitute a part of this specification, illustrate embodiments of the application and together with the description serve to explain the application. In the drawings:
FIG. 1 shows a flow chart of a big data sharing method according to one embodiment of the application;
FIG. 2 illustrates a schematic diagram of a blockchain local data store in accordance with an embodiment of the present application;
FIG. 3 illustrates a schematic diagram of a blockchain big data sharing model in accordance with an embodiment of the application;
FIG. 4 shows a schematic diagram of a data random access model according to one embodiment of the application.
Detailed Description
It should be noted that the following detailed description is illustrative and is intended to provide further explanation of the application. Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application belongs.
It is noted that the terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting of exemplary embodiments according to the present application. As used herein, the singular is also intended to include the plural unless the context clearly indicates otherwise, and furthermore, it is to be understood that the terms "comprises" and/or "comprising" when used in this specification are taken to specify the presence of stated features, steps, operations, devices, components, and/or combinations thereof.
It will be understood that when an element such as a layer, film, region, or substrate is referred to as being "on" another element, it can be directly on the other element or intervening elements may also be present. Furthermore, in the description and in the claims, when an element is described as being "connected" to another element, the element may be "directly connected" to the other element or "connected" to the other element through a third element.
As described in the background art, in order to solve the problem of excessive amount of blockchain redundancy information used in large data sharing in the prior art, in an exemplary embodiment of the present application, a large data sharing method, apparatus, computer readable storage medium, processor, and large data sharing system are provided.
According to an embodiment of the application, a big data sharing method is provided.
Fig. 1 is a flowchart of a big data sharing method according to an embodiment of the present application. As shown in fig. 1, the method comprises the steps of:
step S101, a data request is sent by a receiving data demand party through a block chain, wherein the data request comprises index information of data, and the index information comprises storage position information of the data;
step S102, retrieving data in a local memory of a data provider according to the index information to obtain target data;
step S103, the target data is sent to the data requesting party through the block chain.
In the big data sharing method, firstly, a data request is sent by a receiving data demand party through a block chain, the data request comprises index information of data, and the index information comprises storage position information of the data; then, retrieving data in a local memory of the data provider according to the index information to obtain target data; finally, the target data is sent to the data demander through the blockchain. According to the method, a data owner randomly stores data in a local memory under a chain, each index information is encrypted and then uploaded to a block chain, when data transaction sharing is needed, a data demand party sends a data request to the data owner through the block chain, after verification, the data demand party searches and obtains local coded data, and complete data is obtained through decoding, and therefore large data sharing can be achieved only by storing all block data in a local memory of a common node of the block chain, all the block data do not need to be backed up by all nodes, and the problem that redundant information quantity of the block chain adopted in large data sharing in the prior art is excessive is solved.
In one embodiment of the present application, retrieving data in a local memory of a data provider according to the index information to obtain target data includes: determining a storage node where a corresponding data block is located according to the storage position information, wherein the data in the local memory comprises a plurality of data blocks, the data blocks are in one-to-one correspondence with the storage nodes, and the index information also comprises the data block information of the target data and the storage position information of the data block of the target data; and reading the data block stored by the storage node to obtain the target data.
Specifically, as shown in fig. 2, a data slice of a data block N is divided into a plurality of sub-blocks to form a plurality of sub-strips, a coding matrix B is set, and independent multiplication is performed on each sub-strip of the coding matrix and the block matrix N to obtain a basic coding matrix, i.e.Wherein, Piggybacking a partial check of a check in a previous sub-stripe onto check data of a subsequent sub-stripe, taking a data block as k terms, generating a check term as r terms, dividing f 1 (a) into (r-1) groups of partial checks, and piggybacking p groups of data into a second sub-stripe to form a new check, namelyWhere p= (k/(r-1)) represents the number of data per group piggybacked, the data owner performs random address allocation on the sliced data X 1、X2…Xk+r, the original data X 1、X2…Xk is stored in the data nodes under the chain, and the check data xk+1, xk+ … xx+r are stored in the check nodes under the chain. An index is generated using a hash function for different nodes of the data under the chain, each index information containing slice information, storage location information, and the like of the data. Generating a private key of a data provider by utilizing a random function, further generating a public key, then carrying out hash operation on the public key to obtain a hash value, adding a check code to ensure the existence of the hash value, carrying out base58 encoding to obtain an account address, and storing index information on a block chain after the index information is encrypted by the public key of the data provider, so that target data can be obtained according to the index information.
In one embodiment of the present application, as shown in fig. 2, the storage node of the local memory includes a data node and a check node, the data node is configured to store the target data, the data node is configured to store check data corresponding to the target data, and before reading the data block stored in the storage node to obtain the target data, the method further includes: under the condition that the data node corresponding to the target data fails, calculating according to the check data to obtain the target data; and under the condition that the check node corresponding to the target data fails, calculating the check data according to the target data.
Specifically, when the data needs to be reconstructed, a request is submitted through a block chain to obtain enough coding slices, and the node can reconstruct the block data through decoding operation. Taking (14, 10) -MDS codes as an example,Cutting data N into 20 sub-blocks and 2 sub-strips (A, B), setting a coding matrix B, respectively multiplying the coding matrix with each independent sub-strip to code the matrix, and obtaining the number of each group of piggybacked data according to p= (k/(r-1)) (k=10) to be 3, wherein the groups cannot be divided completely at this time, and q=k mod (r-1) can obtain the last group of piggybacked data with the number of p+q to be 4. 10 data blocks can constitute a complete original data without decoding. If check node X 11 fails, 10 nodes X 1-X10 may be connected, based on,Then { f 1(a),f1 (b) }, if the data node X 1 fails, firstly using MDS property connection X 2-X11 to download { b 2,...,b10,f1 (b) } 10 data sub-blocks, and using the product of the inverse of the coding matrix and the coding slice to obtain b1, namelyDownload { a 2,a3,f2(b)+a1+a2+a3 } at connection X 2,X3 and X 12, f 2 (b) can be obtained by equation 2, thus obtaining a1, from which a complete raw data is composed. The total data block downloading amount is 11 blocks, and compared with the method for directly using MSD codes to decode and encode the data downloading amount is at least 20 blocks, the network bandwidth is obviously saved.
In one embodiment of the application, under the condition that the data node fails or the check node fails, a Bayesian fault-tolerant algorithm is adopted to repair the data. Specifically, the flow of the bayer fault-tolerance algorithm PBFT is mainly divided into three stages: pre-preparation, preparation and submission. The PBFT algorithm can tolerate less than 1/3 of invalid or malicious nodes, and the algorithm can reach the final result faster, but requires a smaller number of nodes.
In one embodiment of the present application, the nodes of the blockchain communicate via a P2P network. In particular, using the P2P network architecture, which is typically constructed using the gossip transport protocol, the network layer may contain different protocols based on different requirements. The computers connected with each other are in a peer position, and can be used as a server to send a request and a workstation to respond, so that the decentralization is realized, and a central link is not needed. When the data demander needs complete information, the data demander sends a request to the data owner based on the P2P network of the blockchain, the data owner searches the locally stored data and then responds after receiving the request, and the node with the corresponding slice is connected with the request node to transmit the data to the data demander.
In one embodiment of the present application, the index information is stored in the blockchain after being encrypted. Specifically, the nodes of the blockchain can be divided into common nodes and common nodes, the common nodes are nodes participating in common recognition in the alliance chain, the nodes locally store all local blockdata, the common nodes are nodes normally executing a data sharing function in the alliance chain, and the index information is uploaded to the common nodes of the blockchain after being encrypted.
It should be noted that, as shown in fig. 3, the architecture of the blockchain big data sharing model may be divided into a data layer, a blockchain layer, a consensus layer, a contract layer and an application layer, where the data layer is based on erasure code encoding and decoding, and combines piggybacking frames, and on the premise of not changing the blockchain links and functions, the optimization of the distributed storage of the data slice is realized, and the reconstruction and repair of the data can also be realized; the network layer is the basis of block chain information interaction, carries the consensus process among the nodes, realizes the transparent data transmission between two end systems, and the consensus layer selects the Bayesian fault-tolerant algorithm PBFT as the consensus algorithm for further improvement, and provides the characteristics of high throughput and low delay; the contract layer comprises various codes, algorithm mechanisms and the like, encapsulates intelligent contracts, wherein the intelligent contracts are digital protocols essentially formed by computer programs, and each node automatically transacts according to contract content when the conditions written in source codes are met, and no intermediate operation is needed. By virtue of the non-modifiable blockchain, the intelligent contract can ensure that all parties jointly process things, execute codes and maintain the consistency of states and resources. The method starts to execute the intelligent contract after the data request is verified, locks the script according to access constraint conditions set by the node, decrypts the shared data according to the provided secret key, uses the public key of the access node to encrypt and output a result, randomly changes the address information of the data slice after the transaction sharing time passes, and feeds back the latest information to the data owner, and the data requester cannot check the data before the latest information is authorized again; the application layer mainly has the functions of inquiring, sharing and modifying the large energy data, linking new data and the like, and can be realized through one client. The clients comprise manager clients and user clients. The manager client can add new energy data for uplink, can realize data sharing under the authorized condition, and the user client can perform data query under the authorized condition.
The embodiment of the application also provides a big data sharing device, and the big data sharing device can be used for executing the big data sharing method provided by the embodiment of the application. The big data sharing device provided by the embodiment of the application is described below.
Fig. 4 is a schematic diagram of a big data sharing apparatus according to an embodiment of the present application. As shown in fig. 4, the apparatus includes:
a receiving unit 10 for receiving a data request from a data demander through a blockchain, the data request including index information of data, the index information including storage location information of the data;
An obtaining unit 20, configured to retrieve data in a local memory of a data provider according to the index information, and obtain target data;
And a transmitting unit 30 for transmitting the target data to the data demander through the blockchain.
In the big data sharing device, the receiving unit receives a data request sent by a data demand party through a block chain, wherein the data request comprises index information of data, and the index information comprises storage position information of the data; the acquisition unit retrieves data in a local memory of the data provider according to the index information to obtain target data; the transmitting unit transmits the target data to the data demander through the blockchain. The data owner of the device randomly stores data in a local memory under a chain, each index information is encrypted and then uploaded to a block chain, when data transaction sharing is needed, a data demand party sends a data request to the data owner through the block chain, after verification, the data demand party searches and obtains the local coding data, and the local coding data is decoded to obtain complete data.
In one embodiment of the present application, the acquiring unit includes a determining module and a reading module, where the determining module is configured to determine, according to the storage location information, a storage node where a corresponding data block is located, where data in the local memory includes a plurality of data blocks, where the data blocks are in one-to-one correspondence with the storage nodes, and the index information further includes data block information of the target data and storage location information of the data block of the target data; the reading module is used for reading the data block stored by the storage node to obtain the target data.
Specifically, as shown in fig. 2, a data slice of a data block N is divided into a plurality of sub-blocks to form a plurality of sub-strips, a coding matrix B is set, and independent multiplication is performed on each sub-strip of the coding matrix and the block matrix N to obtain a basic coding matrix, i.e.Wherein, Piggybacking a partial check of a check in a previous sub-stripe onto check data of a subsequent sub-stripe, taking a data block as k terms, generating a check term as r terms, dividing f 1 (a) into (r-1) groups of partial checks, and piggybacking p groups of data into a second sub-stripe to form a new check, namelyWhere p= (k/(r-1)) represents the number of data per group piggybacked, the data owner performs random address allocation on the sliced data X 1、X2…Xk+r, the original data X 1、X2…Xk is stored in the data nodes under the chain, and the check data xk+1, xk+ … xx+r are stored in the check nodes under the chain. An index is generated using a hash function for different nodes of the data under the chain, each index information containing slice information, storage location information, and the like of the data. Generating a private key of a data provider by utilizing a random function, further generating a public key, then carrying out hash operation on the public key to obtain a hash value, adding a check code to ensure the existence of the hash value, carrying out base58 encoding to obtain an account address, and storing index information on a block chain after the index information is encrypted by the public key of the data provider, so that target data can be obtained according to the index information.
In one embodiment of the present application, as shown in fig. 2, the storage node of the local memory includes a data node and a check node, where the data node is used to store the target data, the data node is used to store check data corresponding to the target data, the apparatus further includes a calculation unit, where the calculation unit includes a first calculation module and a second calculation module, where the first calculation module is used to calculate the target data according to the check data before the data block stored in the storage node is read to obtain the target data when the data node corresponding to the target data fails; the second calculation module is configured to calculate, when the check node corresponding to the target data fails, the check data according to the target data before the data block stored in the storage node is read to obtain the target data.
Specifically, when the data needs to be reconstructed, a request is submitted through a block chain to obtain enough coding slices, and the node can reconstruct the block data through decoding operation. Taking (14, 10) -MDS codes as an example,Cutting data N into 20 sub-blocks and 2 sub-strips (A, B), setting a coding matrix B, respectively multiplying the coding matrix with each independent sub-strip to code the matrix, and obtaining the number of each group of piggybacked data according to p= (k/(r-1)) (k=10) to be 3, wherein the groups cannot be divided completely at this time, and q=k mod (r-1) can obtain the last group of piggybacked data with the number of p+q to be 4. 10 data blocks can constitute a complete original data without decoding. If check node X 11 fails, 10 nodes X 1-X10 may be connected, based on,Then { f 1(a),f1 (b) }, if the data node X 1 fails, firstly using MDS property connection X 2-X11 to download { b 2,...,b10,f1 (b) } 10 data sub-blocks, and using the product of the inverse of the coding matrix and the coding slice to obtain b1, namelyDownload { a 2,a3,f2(b)+a1+a2+a3 } at connection X 2,X3 and X 12, f 2 (b) can be obtained by equation 2, thus obtaining a1, from which a complete raw data is composed. The total data block downloading amount is 11 blocks, and compared with the method for directly using MSD codes to decode and encode the data downloading amount is at least 20 blocks, the network bandwidth is obviously saved.
In one embodiment of the application, under the condition that the data node fails or the check node fails, a Bayesian fault-tolerant algorithm is adopted to repair the data. Specifically, the flow of the bayer fault-tolerance algorithm PBFT is mainly divided into three stages: pre-preparation, preparation and submission. The PBFT algorithm can tolerate less than 1/3 of invalid or malicious nodes, and the algorithm can reach the final result faster, but requires a smaller number of nodes.
In one embodiment of the present application, the nodes of the blockchain communicate via a P2P network. In particular, using the P2P network architecture, which is typically constructed using the gossip transport protocol, the network layer may contain different protocols based on different requirements. The computers connected with each other are in a peer position, and can be used as a server to send a request and a workstation to respond, so that the decentralization is realized, and a central link is not needed. When the data demander needs complete information, the data demander sends a request to the data owner based on the P2P network of the blockchain, the data owner searches the locally stored data and then responds after receiving the request, and the node with the corresponding slice is connected with the request node to transmit the data to the data demander.
In one embodiment of the present application, the index information is stored in the blockchain after being encrypted. Specifically, the nodes of the blockchain can be divided into common nodes and common nodes, the common nodes are nodes participating in common recognition in the alliance chain, the nodes locally store all local blockdata, the common nodes are nodes normally executing a data sharing function in the alliance chain, and the index information is uploaded to the common nodes of the blockchain after being encrypted.
It should be noted that, as shown in fig. 3, the architecture of the blockchain big data sharing model may be divided into a data layer, a blockchain layer, a consensus layer, a contract layer and an application layer, where the data layer is based on erasure code encoding and decoding, and combines piggybacking frames, and on the premise of not changing the blockchain links and functions, the optimization of the distributed storage of the data slice is realized, and the reconstruction and repair of the data can also be realized; the network layer is the basis of block chain information interaction, carries the consensus process among the nodes, realizes the transparent data transmission between two end systems, and the consensus layer selects the Bayesian fault-tolerant algorithm PBFT as the consensus algorithm for further improvement, and provides the characteristics of high throughput and low delay; the contract layer comprises various codes, algorithm mechanisms and the like, encapsulates intelligent contracts, wherein the intelligent contracts are digital protocols essentially formed by computer programs, and each node automatically transacts according to contract content when the conditions written in source codes are met, and no intermediate operation is needed. By virtue of the non-modifiable blockchain, the intelligent contract can ensure that all parties jointly process things, execute codes and maintain the consistency of states and resources. The method starts to execute the intelligent contract after the data request is verified, locks the script according to access constraint conditions set by the node, decrypts the shared data according to the provided secret key, uses the public key of the access node to encrypt and output a result, randomly changes the address information of the data slice after the transaction sharing time passes, and feeds back the latest information to the data owner, and the data requester cannot check the data before the latest information is authorized again; the application layer mainly has the functions of inquiring, sharing and modifying the large energy data, linking new data and the like, and can be realized through one client. The clients comprise manager clients and user clients. The manager client can add new energy data for uplink, can realize data sharing under the authorized condition, and the user client can perform data query under the authorized condition.
The embodiment of the application also provides a big data sharing system which comprises a block chain, a local memory of the block chain node and a big data sharing device, wherein the big data sharing device comprises a device for executing any one of the methods.
In the big data sharing system, the receiving unit receives a data request sent by a data requiring party through a block chain, wherein the data request comprises index information of data, and the index information comprises storage position information of the data; the acquisition unit retrieves data in a local memory of the data provider according to the index information to obtain target data; the transmitting unit transmits the target data to the data demander through the blockchain. The data owner of the device randomly stores data in a local memory under a chain, each index information is encrypted and then uploaded to a block chain, when data transaction sharing is needed, a data demand party sends a data request to the data owner through the block chain, after verification, the data demand party searches and obtains the local coding data, and the local coding data is decoded to obtain complete data.
The big data sharing device comprises a processor and a memory, wherein the receiving unit, the acquiring unit, the transmitting unit and the like are all stored in the memory as program units, and the processor executes the program units stored in the memory to realize corresponding functions.
The processor includes a kernel, and the kernel fetches the corresponding program unit from the memory. The kernel can be provided with one or more than one kernel, and the problem of excessive blockchain redundant information quantity adopted by big data sharing in the prior art is solved by adjusting kernel parameters.
The memory may include volatile memory, random Access Memory (RAM), and/or nonvolatile memory, such as Read Only Memory (ROM) or flash memory (flash RAM), among other forms in computer readable media, the memory including at least one memory chip.
An embodiment of the present invention provides a computer-readable storage medium having stored thereon a program which, when executed by a processor, implements the above-described method.
The embodiment of the invention provides a processor, which is used for running a program, wherein the method is executed when the program runs.
The embodiment of the invention provides equipment, which comprises a processor, a memory and a program stored in the memory and capable of running on the processor, wherein the processor realizes at least the following steps when executing the program:
step S101, a data request is sent by a receiving data demand party through a block chain, wherein the data request comprises index information of data, and the index information comprises storage position information of the data;
step S102, retrieving data in a local memory of a data provider according to index information to obtain target data;
in step S103, the target data is sent to the data demander through the blockchain.
The device herein may be a server, PC, PAD, cell phone, etc.
The application also provides a computer program product adapted to perform, when executed on a data processing device, a program initialized with at least the following method steps:
step S101, a data request is sent by a receiving data demand party through a block chain, wherein the data request comprises index information of data, and the index information comprises storage position information of the data;
step S102, retrieving data in a local memory of a data provider according to index information to obtain target data;
in step S103, the target data is sent to the data demander through the blockchain.
In the foregoing embodiments of the present invention, the descriptions of the embodiments are emphasized, and for a portion of this disclosure that is not described in detail in this embodiment, reference is made to the related descriptions of other embodiments.
In the several embodiments provided in the present application, it should be understood that the disclosed technology may be implemented in other manners. The above-described embodiments of the apparatus are merely exemplary, and the division of the units may be a logic function division, and there may be another division manner when actually implemented, for example, a plurality of units or components may be combined or may be integrated into another system, or some features may be omitted or not performed. Alternatively, the coupling or direct coupling or communication connection shown or discussed with each other may be through some interfaces, units or modules, or may be in electrical or other forms.
The units described above as separate components may or may not be physically separate, and components shown as units may or may not be physical units, may be located in one place, or may be distributed over a plurality of units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.
In addition, each functional unit in the embodiments of the present invention may be integrated in one processing unit, or each unit may exist alone physically, or two or more units may be integrated in one unit. The integrated units may be implemented in hardware or in software functional units.
The integrated units described above, if implemented in the form of software functional units and sold or used as stand-alone products, may be stored in a computer-readable storage medium. Based on such understanding, the technical solution of the present invention may be embodied in essence or a part contributing to the prior art or all or part of the technical solution in the form of a software product stored in a computer readable storage medium, comprising several instructions for causing a computer device (which may be a personal computer, a server or a network device, etc.) to perform all or part of the steps of the above-mentioned methods of the various embodiments of the present invention. And the aforementioned computer-readable storage medium includes: a usb disk, a Read-Only Memory (ROM), a random access Memory (RAM, random Access Memory), a removable hard disk, a magnetic disk, or an optical disk, or other various media capable of storing program codes.
From the above description, it can be seen that the above embodiments of the present application achieve the following technical effects:
1) In the big data sharing method, a receiving data demand party sends a data request through a block chain, wherein the data request comprises index information of data, and the index information comprises storage position information of the data; retrieving data in a local memory of a data provider according to the index information to obtain target data; and transmitting the target data to the data requesting party through the block chain. According to the method, a data owner randomly stores data in a local memory under a chain, each index information is encrypted and then uploaded to a block chain, when data transaction sharing is needed, a data demand party sends a data request to the data owner through the block chain, after verification, the data demand party searches and obtains local coded data, and complete data is obtained through decoding, and therefore large data sharing can be achieved only by storing all block data in a local memory of a common node of the block chain, all the block data do not need to be backed up by all nodes, and the problem that redundant information quantity of the block chain adopted in large data sharing in the prior art is excessive is solved.
2) In the big data sharing device, a receiving unit receives a data request sent by a data demand party through a block chain, wherein the data request comprises index information of data, and the index information comprises storage position information of the data; the acquisition unit retrieves data in a local memory of the data provider according to the index information to obtain target data; the transmitting unit transmits the target data to the data demander through the blockchain. The data owner of the device randomly stores data in a local memory under a chain, each index information is encrypted and then uploaded to a block chain, when data transaction sharing is needed, a data demand party sends a data request to the data owner through the block chain, after verification, the data demand party searches and obtains the local coding data, and the local coding data is decoded to obtain complete data.
3) In the big data sharing system of the application, the big data sharing device comprises a block chain, a local memory of a block chain node and the receiving unit receives a data request sent by a data requiring party through the block chain, wherein the data request comprises index information of data, and the index information comprises storage position information of the data; the acquisition unit retrieves data in a local memory of the data provider according to the index information to obtain target data; the transmitting unit transmits the target data to the data demander through the blockchain. The data owner of the device randomly stores data in a local memory under a chain, each index information is encrypted and then uploaded to a block chain, when data transaction sharing is needed, a data demand party sends a data request to the data owner through the block chain, after verification, the data demand party searches and obtains the local coding data, and the local coding data is decoded to obtain complete data.
The above description is only of the preferred embodiments of the present application and is not intended to limit the present application, but various modifications and variations can be made to the present application by those skilled in the art. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application should be included in the protection scope of the present application.
Claims (7)
1. A big data sharing method, comprising:
Receiving a data request sent by a data requiring party through a block chain, wherein the data request comprises index information of data, and the index information comprises storage position information of the data;
retrieving data in a local memory of a data provider according to the index information to obtain target data;
The target data is sent to the data demand party through the blockchain, and the data in the local memory of the data provider is searched according to the index information to obtain the target data, which comprises the following steps: determining a storage node where a corresponding data block is located according to the storage position information, wherein the data in the local memory comprises a plurality of data blocks, the data blocks are in one-to-one correspondence with the storage nodes, and the index information also comprises the data block information of the target data and the storage position information of the data block of the target data; reading the data block stored by the storage node to obtain the target data, wherein the storage node of the local memory comprises a data node and a check node, the data node is used for storing the target data, the check node is used for storing check data corresponding to the target data, and before reading the data block stored by the storage node to obtain the target data, the method further comprises the following steps: under the condition that a data node corresponding to the target data fails, calculating according to the check data to obtain the target data; under the condition that a check node corresponding to the target data fails, the check data is obtained through calculation according to the target data, the index information is stored on the blockchain after being encrypted, the nodes of the blockchain can be divided into common nodes and common nodes, the common nodes are nodes participating in common identification in a alliance chain, all local blockdata are locally stored in the nodes, the common nodes are nodes which normally execute a data sharing function in the alliance chain, and the index information is uploaded to the common nodes of the blockchain after being encrypted.
2. The method according to claim 1, wherein in case of failure of the data node or failure of the check node, a bayer fault tolerance algorithm is used for data repair.
3. The method of claim 1, wherein nodes of the blockchain communicate over a P2P network.
4. A big data sharing apparatus, characterized by comprising:
A receiving unit, configured to receive a data request sent by a data demander through a blockchain, where the data request includes index information of data, and the index information includes storage location information of the data;
The acquisition unit is used for retrieving data in a local memory of the data provider according to the index information to obtain target data;
the data storage device comprises a sending unit, an acquisition unit and a storage unit, wherein the sending unit is used for sending target data to a data requiring party through the blockchain, the acquisition unit comprises a determination module and a reading module, the determination module is used for determining storage nodes where corresponding data blocks are located according to storage position information, the data in a local storage comprises a plurality of data blocks, the data blocks are in one-to-one correspondence with the storage nodes, and the index information also comprises data block information of the target data and storage position information of the data blocks of the target data; the reading module is used for reading the data block stored by the storage node to obtain the target data, the storage node of the local memory comprises a data node and a check node, the data node is used for storing the target data, the data node is used for storing check data corresponding to the target data, the reading module further comprises a computing unit, the computing unit comprises a first computing module and a second computing module, and the first computing module is used for computing the target data according to the check data before the data block stored by the storage node is read to obtain the target data under the condition that the data node corresponding to the target data fails; the second calculation module is configured to calculate, according to the target data, the check data when the check node corresponding to the target data fails, before the data block stored in the storage node is read to obtain the target data, where the index information is stored on the blockchain after being encrypted, where the nodes of the blockchain may be divided into common nodes and common nodes, where the common nodes are nodes participating in common identification in the coalition chain, all local blockdata are stored locally by the nodes, and the common nodes are nodes in the coalition chain that normally execute a data sharing function, and the index information is uploaded to the common nodes of the blockchain after being encrypted.
5. A computer readable storage medium, characterized in that the computer readable storage medium comprises a stored program, wherein the program performs the method of any one of claims 1 to 3.
6. A processor for running a program, wherein the program when run performs the method of any one of claims 1 to 3.
7. A big data sharing system comprising a blockchain, a local memory of a blockchain node and a big data sharing device, characterized in that the big data sharing device comprises means for performing any of the methods of claims 1 to 3.
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