CN115964416A - Data storage system, method, device and medium for data in block chain - Google Patents
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Abstract
The embodiment of the disclosure discloses a data storage system, a method, a device and a medium for data in a block chain, wherein the system comprises: the system comprises a data acquisition module, a data classification module, a data analysis module and a data warehouse. The data acquisition module is used for acquiring data to be processed from any node of the block chain network; the data classification module is used for determining a data analyzer used for analyzing the data to be processed in the data analysis module; the data analysis module is used for analyzing the data to be processed by using a data analyzer which is determined by the data classification module and is used for analyzing the data to be processed to obtain format data, and the classification information of the data to be processed is used as the classification information of the format data; the data warehouse is used for determining a storage module for storing format data in the data warehouse based on the corresponding relation between the preset classification information and the storage module and the classification information, and storing the format data, the classification information and the data identification in the determined storage module.
Description
Technical Field
The present disclosure relates to data storage technologies and block chain technologies, and in particular, to a data storage system, method, device, and medium for data in a block chain.
Background
The Block Chain (Block Chain) is a Chain data structure which combines data blocks in a sequential connection mode according to a time sequence and is a distributed book which is cryptographically used for ensuring that the data cannot be tampered and forged. As the application of blockchains becomes more widespread, the amount of data in the nodes of blockchains is also increasing. In the prior art, the data is generally stored in a storage device directly and uniformly, which results in low data storage efficiency and confusion of the stored data, and affects subsequent use of the data.
Disclosure of Invention
The embodiment of the disclosure provides a data storage system, method, device and medium for data in a block chain, so as to solve the above problems.
In one aspect of the embodiments of the present disclosure, a data warehousing system for data in a block chain is provided, including: the data analysis module comprises a plurality of data analyzers, and the data warehouse comprises a plurality of storage modules; the data acquisition module is used for acquiring data to be processed from any node of the block chain network and pushing the data to be processed to the data classification module; the data classification module is used for classifying the data to be processed to obtain classification information of the data to be processed, and inquiring a data analyzer corresponding to the classification information in the data analysis module in a corresponding relation between preset classification information and a data analyzer; the data analysis module is used for carrying out data analysis on the data to be processed by using a data analyzer which is determined by the data classification module and corresponds to the classification information to obtain format data, taking the classification information of the data to be processed as the classification information of the format data, and distributing a data identifier to the format data; the data warehouse is used for inquiring the storage module corresponding to the classification information in the corresponding relation between the preset classification information and the storage module, and storing the format data, the classification information and the data identification in the storage module corresponding to the classification information.
Optionally, in the system according to any of the above embodiments of the present disclosure, the method further includes: an interface module; the interface module is used for acquiring format data corresponding to a data acquisition request from the data warehouse according to a data identifier in the data acquisition request after receiving the data acquisition request for acquiring the format data sent by a client, and sending the format data corresponding to the data acquisition request to the client.
Optionally, in the system according to any of the embodiments of the present disclosure, the interface module further stores a plurality of public-private key pair public keys and a correspondence between a preset public key and a digital identity; the interface module is further configured to: acquiring a public-private key pair public key corresponding to the digital identity in the data acquisition request based on the corresponding relation between the preset public key and the digital identity; verifying the signature of the verifiable certificate in the data acquisition request by using the public key; and responding to the verification that the signature of the verifiable certificate in the data acquisition request passes the verification, executing the operation of acquiring the format data corresponding to the data acquisition request from the data warehouse according to the data identification in the data acquisition request, and sending the format data corresponding to the data acquisition request to the client.
Optionally, in the system according to any of the embodiments of the present disclosure, the interface module further stores a corresponding relationship between a preset authority and a digital identity; the interface module is further configured to: determining whether the client has the authority to acquire format data corresponding to the data identifier in the data acquisition request according to the corresponding relation between the preset authority and the digital identity identifier; and in response to the client having the right to acquire the format data corresponding to the data identifier in the data acquisition request and the signature of the verifiable certificate in the data acquisition request passing the verification, executing an operation of acquiring the format data corresponding to the data identifier in the data acquisition request from the data warehouse, and sending the format data corresponding to the data identifier in the data acquisition request to the client.
Optionally, in the system according to any of the above embodiments of the present disclosure, the data warehouse is further configured to: and counting format data in each storage module of the plurality of storage modules based on a preset counting dimension and a preset counting time period to obtain a counting result, and performing visual processing on the counting result.
Optionally, in the system according to any of the above embodiments of the present disclosure, the acquisition module includes a data acquisition sub-module and a task queue sub-module; the data acquisition submodule is used for acquiring the data to be processed from any node of the block chain network; and the task queue submodule is used for sequencing the data to be processed according to a preset node importance degree list and the storage node of the data to be processed, and pushing the data to be processed to the data classification module according to the sequencing.
In another aspect of the embodiments of the present disclosure, a method for data storage of data in a block chain is provided, including: acquiring data to be processed from any node of a block chain network; classifying the data to be processed to obtain classification information of the data to be processed, and inquiring a data analyzer corresponding to the classification information in a data analysis module in a corresponding relation between preset classification information and a data analyzer; performing data analysis on the data to be processed by using a data analyzer corresponding to the classification information to obtain format data, taking the classification information of the data to be processed as the classification information of the format data, and distributing a data identifier to the format data; inquiring a storage module corresponding to the classification information in a data warehouse in a corresponding relation between preset classification information and the storage module, and storing the format data, the classification information and the data identification in the storage module corresponding to the classification information.
Optionally, in the method according to any of the foregoing embodiments of the present disclosure, the method further includes: and after receiving a data acquisition request sent by a client for acquiring format data, acquiring the format data corresponding to the data acquisition request from the data warehouse according to a data identifier in the data acquisition request, and sending the format data corresponding to the data acquisition request to the client.
In yet another aspect of the disclosed embodiments, there is provided an electronic device including: a memory for storing a computer program; and the processor is used for executing the computer program stored in the memory, and when the computer program is executed, the data storage method of the data in the block chain is realized.
In a further aspect of the embodiments of the present disclosure, a computer-readable storage medium is provided, on which a computer program is stored, and when the computer program is executed by a processor, the computer program implements the data warehousing method for data in a block chain.
The embodiment of the disclosure provides a data storage system, a data storage method, a data storage device and a data storage medium for data in a block chain. In addition, format information of different classification information is stored in different storage modules, so that data storage is more systematic, storage efficiency is improved, and follow-up utilization and development of format data are greatly facilitated.
The technical solution of the present disclosure is further described in detail by the accompanying drawings and embodiments.
Drawings
The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments of the disclosure and together with the description, serve to explain the principles of the disclosure.
The present disclosure may be more clearly understood from the following detailed description, taken with reference to the accompanying drawings, in which:
fig. 1 is a schematic structural diagram illustrating an embodiment of a data-in-block-chain data warehousing system according to the present disclosure;
FIG. 2 is a block diagram illustrating a block chain data-in-data storage method according to an embodiment of the present disclosure;
fig. 3 is a schematic structural diagram of an embodiment of an electronic device according to the present disclosure.
Detailed Description
Various exemplary embodiments of the present disclosure will now be described in detail with reference to the accompanying drawings. It should be noted that: the relative arrangement of the components and steps, the numerical expressions, and numerical values set forth in these embodiments do not limit the scope of the present disclosure unless specifically stated otherwise.
It will be understood by those of skill in the art that the terms "first," "second," and the like in the embodiments of the present disclosure are used merely to distinguish one element from another, and are not intended to imply any particular technical meaning, nor is the necessary logical order between them.
It is also understood that in embodiments of the present disclosure, "a plurality" may refer to two or more than two, and "at least one" may refer to one, two or more than two.
It is also to be understood that any reference to any component, data, or structure in the embodiments of the disclosure, may be generally understood as one or more, unless explicitly defined otherwise or stated otherwise.
In addition, the term "and/or" in the present disclosure is only one kind of association relationship describing an associated object, and means that three kinds of relationships may exist, for example, a and/or B may mean: a exists alone, A and B exist simultaneously, and B exists alone. In addition, the character "/" in the present disclosure generally indicates that the former and latter associated objects are in an "or" relationship.
It should also be understood that the description of the various embodiments of the present disclosure emphasizes the differences between the various embodiments, and the same or similar parts may be referred to each other, so that the descriptions thereof are omitted for brevity.
Meanwhile, it should be understood that the sizes of the respective portions shown in the drawings are not drawn in an actual proportional relationship for the convenience of description.
The following description of at least one exemplary embodiment is merely illustrative in nature and is in no way intended to limit the disclosure, its application, or uses.
Techniques, methods, and apparatus known to those of ordinary skill in the relevant art may not be discussed in detail but are intended to be part of the specification where appropriate.
It should be noted that: like reference numbers and letters refer to like items in the following figures, and thus, once an item is defined in one figure, further discussion thereof is not required in subsequent figures.
The disclosed embodiments may be applied to electronic devices such as terminal devices, computer systems, servers, etc., which are operational with numerous other general purpose or special purpose computing system environments or configurations. Examples of well known terminal devices, computing systems, environments, and/or configurations that may be suitable for use with electronic devices, such as terminal devices, computer systems, servers, and the like, include, but are not limited to: personal computer systems, server computer systems, thin clients, thick clients, hand-held or laptop devices, microprocessor-based systems, set-top boxes, programmable consumer electronics, networked personal computers, minicomputer systems, mainframe computer systems, distributed cloud computing environments that include any of the above, and the like.
Electronic devices such as terminal devices, computer systems, servers, etc. may be described in the general context of computer system-executable instructions, such as program modules, being executed by a computer system. Generally, program modules may include routines, programs, objects, components, logic, data structures, etc. that perform particular tasks or implement particular abstract data types. The computer system/server may be practiced in distributed cloud computing environments where tasks are performed by remote processing devices that are linked through a communications network. In a distributed cloud computing environment, program modules may be located in both local and remote computer system storage media including memory storage devices.
The narrowly defined blockchain technology may be a distributed ledger which is a chain data structure composed of data blocks in a sequential connection manner in chronological order and is cryptographically secured as being tamper-proof and forgery-proof. The generalized block chain technology can verify and store data by using a block chain type data structure, generate and update data by using a node consensus algorithm, ensure the safety of data transmission and access by using a cryptology mode, and use an intelligent contract consisting of automatic script codes. Nodes in the blockchain network generally refer to computers in the blockchain network, that is, any computer (including mobile phones, servers, etc.) connected to the blockchain network is called a Node, and the nodes may be divided into different nodes according to the data storage and processing region thereof, for example, shanghai nodes, guangzhou nodes, etc., or into light nodes and full nodes or super nodes according to the division of the data storage and processing thereof.
Fig. 1 is a schematic structural diagram of a data entry system for data in a block chain according to an embodiment of the present application, and as shown in fig. 1, the data entry system includes: the system comprises a data acquisition module, a data classification module, a data analysis module and a data warehouse, wherein the data analysis module comprises a plurality of data analyzers, and the data warehouse comprises a plurality of storage modules.
The data acquisition module is used for acquiring data to be processed from any node of the block chain network and pushing the data to be processed to the data classification module.
The data classification module is used for classifying the data to be processed to obtain the classification information of the data to be processed, and inquiring a data analyzer corresponding to the classification information in the data analysis module in the corresponding relation between the preset classification information and the data analyzer.
The data analysis module is used for carrying out data analysis on the data to be processed by using the data analyzer which is determined by the data classification module and corresponds to the classification information to obtain format data, taking the classification information of the data to be processed as the classification information of the format data, and distributing a data identifier to the format data.
The data warehouse is used for inquiring the storage module corresponding to the classification information in the corresponding relation between the preset classification information and the storage module, and storing the format data, the classification information and the data identification in the storage module corresponding to the classification information.
In the embodiment of the present disclosure, the data warehousing system may be deployed in one computing device, or the data acquisition module, the data classification module, the data analysis module, and the data warehouse are respectively deployed in different computing devices, where the computing devices may be servers, computers, and the like.
The data acquisition module is used for acquiring data to be processed by the nodes. Specifically, the data acquisition module is respectively connected with the nodes of the block chain network and the data classification module. The data acquisition module may be provided with at least one communication Protocol, and the set communication Protocol may interact with a node of the blockchain network to acquire data to be processed from the node, where the communication Protocol may be HTTP (hypertext Transfer Protocol), webSocket (web socket) Protocol, or the like. The data to be processed may be any data stored in the node, for example, the data to be processed may be transaction data, contract data, identification data, asset data, and the like.
The data classification module is used for determining classification information of the data to be processed and determining a data analyzer for analyzing the data to be processed. Specifically, the data classification module stores a corresponding relationship between preset classification information and a data analyzer, and the corresponding relationship between the preset classification information and the data analyzer may be in a form of a list. In the corresponding relation between the preset classification information and the data resolvers, each data resolution server of the plurality of data resolvers in the data classification module corresponds to at least one piece of classification information. The classification information of the information to be processed is used to indicate the classification of the data to be processed, and the classification information may include the classification of the data to be processed corresponding to the classification information. For example, the classification information may be transactions, house rental deals, contracts, logos, and the like. For example, when the classification information of the data to be processed is a contract, it indicates that the data to be processed is contract-related data.
In one embodiment, the data classification module may perform word segmentation on the data to be processed by using a word segmentation technology to obtain a keyword of the data to be processed, then query classification information corresponding to the keyword of the data to be processed in a corresponding list between preset keywords and the classification information, and determine the classification information as the classification information of the data to be processed, where the corresponding list between the preset keywords and the classification information includes at least one piece of classification information and a keyword corresponding to each piece of classification information in the at least one piece of classification information; or, the pre-trained Neural network for determining the classification information classifies the data to be processed to obtain the classification information of the data to be processed, where the Neural network for determining the classification information may be a CNN (Convolutional Neural network), and the like. The data classification module can determine a data analyzer corresponding to the classification information of the data to be processed in the corresponding relationship between the preset classification information and the data analyzer according to the corresponding relationship between the preset classification information and the data analyzer, and determine the data analyzer as the data analyzer corresponding to the classification information of the data to be processed in the data analysis module.
The data analysis module is used for carrying out data analysis on the data to be processed to obtain format data of the data to be processed. Specifically, the data analysis module is provided with a plurality of data analyzers, each data analyzer corresponds to at least one type of classification information, and each data analyzer is used for performing data analysis on the data to be processed of the classification information corresponding to the data analyzer. For example, when the classification information of the data to be processed is contract information, the data to be analyzed module performs data analysis on the data to be processed by using a data analyzer of which the corresponding classification information is the contract information.
Data parsing is a method for converting a string of data into different types of data, namely a method for formatting data, and a popular understanding can be a process for converting one data format into another data format. The data analyzer can pre-write codes and rules for data analysis according to the requirements on the data format, and then analyze the data to be processed by using the codes and the rules to obtain the data in the required data format. The format data may be structured data of the data to be processed, which is obtained by parsing the data to be parsed through the data parser, for example, the data parser may parse the data to be processed into structured data (format data) in a JSON format, a CSV format, or a table format. The data identifier is used for uniquely identifying one format data, the data identifier can be a custom code or a Digital Identification (DID) identifier, and the like, when the data analyzer completes data analysis of the data to be processed to obtain the format data of the data to be processed, the data analysis module can generate a unique data identifier according to a preset identifier generation rule, and the data identifier is distributed to the format data to identify the format data, and a user can query the format data identified by the data identifier through the data identifier; the preset identifier generation rule may be set according to a requirement, for example, when the format identifier is a DID identifier, the preset identifier generation rule may be a DID identifier generation rule. The data to be processed and the format data of the data to be processed correspond to the same classification information. In an embodiment, the to-be-processed data parsing module may allocate the to-be-processed data to a data parser corresponding to the classification information of the to-be-processed data, which is determined by the data classification module, that is, the to-be-processed data is allocated to a data parser corresponding to the same classification information as the to-be-processed data, the data parser parses the to-be-processed data to obtain format data of the to-be-processed data, the data parsing module allocates a data identifier uniquely identifying the format data to the format data, and meanwhile, the classification information of the to-be-processed data is determined as the classification information of the format data.
The data warehouse is used for storing format data. Specifically, the data warehouse is provided with a plurality of storage modules, and each storage module is used for storing format data corresponding to one type of classification information. The data warehouse also stores the corresponding relation between preset classification information and the storage modules, the corresponding relation between the preset classification information and the storage modules can be in a list form, and in the corresponding relation between the preset classification information and the storage modules, each storage module of a plurality of storage modules in the data warehouse corresponds to at least one piece of classification information. In one embodiment, the data warehouse queries the storage module corresponding to the classification information of the format data in the corresponding relationship between the preset classification information and the storage module, and stores the format data, the data identifier of the format data, and the classification information in the storage module. In addition, the data warehouse can also bind the format data with the data to be processed, so that the format data corresponds to the data to be processed, and then the data to be processed is stored in the storage block in which the format data is stored.
In the embodiment of the disclosure, the data classification module is used for determining the classification information of the data to be processed, and different data analyzers are used for analyzing the data to be processed according to different classification information, so that the data analysis efficiency of the data to be processed is effectively improved. In addition, format information of different classification information is stored in different storage modules, so that data storage is more systematic, storage efficiency is improved, and follow-up utilization and development of format data are greatly facilitated.
In an optional embodiment, the system in an embodiment of the present disclosure further comprises: and an interface module. The interface module is used for acquiring format data corresponding to a data acquisition request from a data warehouse according to a data identifier in the data acquisition request after receiving the data acquisition request for acquiring the format data sent by a client, and sending the format data corresponding to the data acquisition request to the client.
In the implementation of the present disclosure, the interface module is configured to obtain, according to the received data obtaining request, format data corresponding to the data obtaining request from the data warehouse. Specifically, the Interface module may be an API (Application Programming Interface) module, which may be deployed in a computer or a server, and the Interface module is connected to the client and the data warehouse, respectively, where at least one communication protocol may be set in the Interface module, and interacts with the client by using the set communication protocol, where the communication protocol may be HTTP, webSocket protocol, and the like. The client can be a computer or a server, etc. The data acquisition request comprises a data identifier of format data to be acquired.
In one embodiment, a user may send a data acquisition request to an interface module through a client, where the interface module searches, according to a data identifier in the data acquisition request, for format data corresponding to the data identifier in the data acquisition request in each storage module in a data warehouse, determines the format data corresponding to the data identifier in the data acquisition request as format data corresponding to the data acquisition request, and sends the format data to the client.
In an optional embodiment, the interface module in the embodiment of the present disclosure further stores a plurality of public-private key pair public keys, and a correspondence between a preset public key and a digital identity; the interface module is further configured to: acquiring a public-private key pair public key corresponding to the digital identity in the data acquisition request based on the corresponding relation between the preset public key and the digital identity; verifying the signature of the verifiable certificate in the data acquisition request by using the public key; and responding to the verification that the signature of the verifiable certificate in the data acquisition request passes the verification, executing the operation of acquiring the format data corresponding to the data acquisition request from the data warehouse according to the data identification in the data acquisition request, and sending the format data corresponding to the data acquisition request to the client.
In this embodiment, the data obtaining request further includes: a digital identity and a verifiable credential. The digital identities may include: a digital identity and a Verifiable Credential (VC) corresponding to the digital identity. The digital identity is used to identify the user or the client, for example, the digital identity may be a DID identity or the like. The verifiable credentials may be used to prove that a client or user identified by a digital identity has some identity, and one digital identity may correspond to at least one verifiable credential. The correspondence between the preset public key and the digital identity may include a plurality of public keys, and each public key corresponds to one digital identity. The public-private key pair includes a public key and a private key. The public key in the public-private key pair is used for verifying the signature generated by the private key in the public-private key pair, and the private key in the public-private key pair is used for signing data or information. In one embodiment, the user or client may generate the public-private key pair using a public SM2 algorithm, a symmetric encryption algorithm, an asymmetric encryption algorithm, or the like. When the data storage system is registered or used for the first time, a user sends a public key and a data identity in a public-private key pair to the interface module through a client of the user, the interface module binds the received public key and the data identity to establish a corresponding relation between the public key and the data identity, and the established corresponding relation between the public key and the data identity is updated to a corresponding relation between a preset public key and the digital identity.
In one embodiment, the interface module obtains a public-private key pair public key corresponding to the digital identity in the data obtaining request according to a corresponding relationship between the preset public key and the digital identity; verifying the signature of the verifiable certificate in the data acquisition request by using the public key; when the signature of the verifiable certificate in the data acquisition request passes the verification, acquiring format data corresponding to the data identifier in the data acquisition request from a data warehouse, and sending the format data corresponding to the data identifier in the data acquisition request to a client; and when the signature of the verifiable certificate in the data acquisition request is not verified, sending a data acquisition failure message to the client.
In an optional embodiment, in the embodiment of the present disclosure, the interface module further stores a corresponding relationship between a preset right and a digital identity; the interface module is further configured to: determining whether the client has the authority to acquire format data corresponding to the data identifier in the data acquisition request according to the corresponding relation between the preset authority and the digital identity identifier; and in response to that the client has the right to acquire the format data corresponding to the data identifier in the data acquisition request and the signature of the verifiable certificate in the data acquisition request passes the verification, executing the operation of acquiring the format data corresponding to the data identifier in the data acquisition request from the data warehouse and sending the format data corresponding to the data identifier in the data acquisition request to the client.
In this embodiment, the corresponding relationship between the preset authority and the digital identity may be in the form of a list, where the corresponding relationship between the preset authority and the digital identity includes a plurality of digital identities, and each digital identity corresponds to an authority that can obtain data.
In one embodiment, the interface module determines the permission of the digital identity in the data acquisition request according to the corresponding relationship between the preset permission and the digital identity, determines whether the data identity has the permission to acquire the format data corresponding to the data identity according to the permission of the data identity, and determines that the client has the permission to acquire the format data corresponding to the data identity when determining that the data identity has the permission to acquire the format data corresponding to the data identity. When the client side is determined to have the authority to acquire the format data corresponding to the data identification, the interface module verifies the signature of the verifiable certificate in the data acquisition request, and when the verification is passed, the interface module acquires the format data corresponding to the data identification from the data warehouse and sends the format data corresponding to the data identification to the client side; and when the client does not have the authority of acquiring the format data corresponding to the data identification and/or the signature of the verifiable certificate is not verified, sending a data acquisition failure message to the client.
In an alternative embodiment, the data warehouse in the embodiment of the present disclosure is further configured to: and counting the format data in each storage module of the plurality of storage modules based on a preset counting dimension and a preset counting time period to obtain a counting result, and performing visual processing on the counting result.
In this embodiment, the preset statistical dimension may be set according to an actual requirement, for example, the preset statistical dimension may be a region dimension, a category dimension, and the like. The preset statistical time period can be set according to actual requirements, and the preset statistical time period can comprise duration and start time and end time of statistics. For example, the preset statistical period may be 1/2022 to 2/1/2022, and the like. Visualization (Visualization) is the use of computer graphics and image processing techniques to convert data into graphics or images for display on a screen. For example, for format data in a storage module for storing the classification information as a contract, the format data in the storage module from 1/month 1/2022 to 3/month 1/2022 (a preset statistical time period) may be counted according to a regional dimension (a preset statistical dimension), and a statistical result is displayed (visualized) in a sector diagram.
In an optional embodiment, the acquisition module in the embodiment of the present disclosure includes: a data acquisition submodule and a task queue submodule.
The data acquisition submodule is used for acquiring data to be processed from any node of the block chain network.
The task queue submodule is used for sorting the data to be processed according to a preset node importance degree list and the storage node of the data to be processed, and pushing the data to be processed to the data classification module according to the sorting.
In this embodiment, a communication protocol may be set in the data collection sub-module, and the communication protocol is used to collect data to be processed from nodes, where each data to be processed corresponds to a node storing the data to be processed.
The task queue submodule stores a preset node importance degree list, and the list stores the importance degree of each node. The task queue submodule can create a task in advance, the file name of the task can be task.
Fig. 2 is a schematic flow chart of a data entering method for data in a block chain according to an embodiment of the present disclosure, where the data entering method for data in a block chain according to the embodiment of the present disclosure may be applied to a data entering system for data in a block chain, and as shown in fig. 2, the data entering method for data in a block chain includes the following steps:
step S110, acquiring data to be processed from any node of the block chain network;
step S120, classifying the data to be processed to obtain classification information of the data to be processed, and querying a data analyzer corresponding to the classification information in a data analysis module in a corresponding relation between preset classification information and a data analyzer;
step S130, a data analyzer corresponding to the classification information is used for carrying out data analysis on the data to be processed to obtain format data, the classification information of the data to be processed is used as the classification information of the format data, and a data identifier is distributed to the format data;
step S140, querying a storage module corresponding to the classification information in a data warehouse in a correspondence relationship between preset classification information and the storage module, and storing the format data, the classification information, and the data identifier in the storage module corresponding to the classification information.
In an alternative embodiment, the method in the embodiment of the present disclosure further includes: and after receiving a data acquisition request sent by a client for acquiring format data, acquiring the format data corresponding to the data acquisition request from the data warehouse according to a data identifier in the data acquisition request, and sending the format data corresponding to the data acquisition request to the client.
In an alternative embodiment, the method in the embodiment of the present disclosure further includes: pre-storing a plurality of public and private key pair public keys and presetting a corresponding relation between the public keys and the digital identity; the method further comprises the following steps: acquiring a public-private key pair public key corresponding to the digital identity in the data acquisition request based on the corresponding relation between the preset public key and the digital identity; verifying the signature of the verifiable certificate in the data acquisition request by using the public key; and responding to the verification that the signature of the verifiable certificate in the data acquisition request passes the verification, executing the operation of acquiring the format data corresponding to the data acquisition request from the data warehouse according to the data identification in the data acquisition request, and sending the format data corresponding to the data acquisition request to the client.
In an alternative embodiment, the method in the embodiment of the present disclosure further includes: preselecting and storing a corresponding relation between preset authority and a digital identity; the method further comprises the following steps: determining whether the client has the authority to acquire format data corresponding to the data identifier in the data acquisition request according to the corresponding relation between the preset authority and the digital identity identifier; and in response to that the client has the right to acquire the format data corresponding to the data identifier in the data acquisition request and the signature of the verifiable certificate in the data acquisition request passes the verification, executing the operation of acquiring the format data corresponding to the data identifier in the data acquisition request from the data warehouse and sending the format data corresponding to the data identifier in the data acquisition request to the client.
In an alternative embodiment, the method in the embodiment of the present disclosure further includes: and counting format data in each storage module of the plurality of storage modules based on a preset counting dimension and a preset counting time period to obtain a counting result, and performing visual processing on the counting result.
In an alternative embodiment, the method in the embodiment of the present disclosure further includes: acquiring the data to be processed from any node of the block chain network; and sorting the data to be processed according to a preset node importance degree list and the storage nodes of the data to be processed, and pushing the data to be processed to the data classification module according to the sorting.
In addition, an embodiment of the present disclosure also provides an electronic device, including:
a memory for storing a computer program;
a processor, configured to execute the computer program stored in the memory, and when the computer program is executed, implement the data storage method for data in a blockchain according to any of the embodiments of the present disclosure.
Fig. 3 is a schematic structural diagram of an application embodiment of the electronic device of the present disclosure. Next, an electronic apparatus according to an embodiment of the present disclosure is described with reference to fig. 3. The electronic device may be either or both of the first device and the second device, or a stand-alone device separate from them, which stand-alone device may communicate with the first device and the second device to receive the acquired input signals therefrom.
As shown in fig. 3, the electronic device includes one or more processors and memory.
The processor may be a Central Processing Unit (CPU) or other form of processing unit having data processing capabilities and/or instruction execution capabilities, and may control other components in the electronic device to perform desired functions.
The memory may include one or more computer program products that may include various forms of computer-readable storage media, such as volatile memory and/or non-volatile memory. The volatile memory may include, for example, random Access Memory (RAM), cache memory (cache), and/or the like. The non-volatile memory may include, for example, read Only Memory (ROM), hard disk, flash memory, etc. One or more computer program instructions may be stored on the computer-readable storage medium and executed by a processor to implement the data-binning method of data in a blockchain of the various embodiments of the present disclosure described above and/or other desired functions.
In one example, the electronic device may further include: an input device and an output device, which are interconnected by a bus system and/or other form of connection mechanism (not shown).
The input device may also include, for example, a keyboard, a mouse, and the like.
The output device may output various information including the determined distance information, direction information, and the like to the outside. The output devices may include, for example, a display, speakers, printer, and the like, as well as a communication network and remote output devices connected thereto.
Of course, for simplicity, only some of the components of the electronic device relevant to the present disclosure are shown in fig. 3, omitting components such as buses, input/output interfaces, and the like. In addition, the electronic device may include any other suitable components, depending on the particular application.
In addition to the above methods and apparatus, embodiments of the present disclosure may also be a computer program product comprising computer program instructions that, when executed by a processor, cause the processor to perform the steps in the data-binning method of data in a blockchain according to various embodiments of the present disclosure described in the above section of this specification.
The computer program product may write program code for carrying out operations for embodiments of the present disclosure in any combination of one or more programming languages, including an object oriented programming language such as Java, C + + or the like and conventional procedural programming languages, such as the "C" programming language or similar programming languages. The program code may execute entirely on the user's computing device, partly on the user's device, as a stand-alone software package, partly on the user's computing device and partly on a remote computing device, or entirely on the remote computing device or server.
Furthermore, embodiments of the present disclosure may also be a computer-readable storage medium having stored thereon computer program instructions that, when executed by a processor, cause the processor to perform the steps in the data-binning method of data in a blockchain according to various embodiments of the present disclosure described in the above section of this specification.
The computer-readable storage medium may take any combination of one or more readable media. The readable medium may be a readable signal medium or a readable storage medium. A readable storage medium may include, for example, but is not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or a combination of any of the foregoing. More specific examples (a non-exhaustive list) of the readable storage medium include: an electrical connection having one or more wires, a portable disk, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.
Those of ordinary skill in the art will understand that: all or part of the steps of implementing the method embodiments may be implemented by hardware related to program instructions, and the program may be stored in a computer-readable storage medium, and when executed, executes the steps including the method embodiments; and the aforementioned storage medium includes: various media that can store program codes, such as ROM, RAM, magnetic or optical disks.
The foregoing describes the general principles of the present disclosure in conjunction with specific embodiments, however, it is noted that the advantages, effects, etc. mentioned in the present disclosure are merely examples and are not limiting, and they should not be considered essential to the various embodiments of the present disclosure. Furthermore, the foregoing disclosure of specific details is for the purpose of illustration and description and is not intended to be limiting, since the disclosure is not intended to be limited to the specific details so described.
In the present specification, the embodiments are described in a progressive manner, and each embodiment focuses on differences from other embodiments, and the same or similar parts in each embodiment are referred to each other. For the system embodiment, since it basically corresponds to the method embodiment, the description is relatively simple, and for the relevant points, reference may be made to the partial description of the method embodiment.
The block diagrams of devices, apparatuses, systems referred to in this disclosure are only given as illustrative examples and are not intended to require or imply that the connections, arrangements, configurations, etc. must be made in the manner shown in the block diagrams. These devices, apparatuses, devices, systems may be connected, arranged, configured in any manner, as will be appreciated by those skilled in the art. Words such as "including," "comprising," "having," and the like are open-ended words that mean "including, but not limited to," and are used interchangeably therewith. The words "or" and "as used herein mean, and are used interchangeably with, the word" and/or, "unless the context clearly dictates otherwise. The word "such as" is used herein to mean, and is used interchangeably with, the phrase "such as but not limited to".
The method and apparatus of the present disclosure may be implemented in a number of ways. For example, the methods and apparatus of the present disclosure may be implemented by software, hardware, firmware, or any combination of software, hardware, and firmware. The above-described order for the steps of the method is for illustration only, and the steps of the method of the present disclosure are not limited to the order specifically described above unless specifically stated otherwise. Further, in some embodiments, the present disclosure may also be embodied as programs recorded in a recording medium, the programs including machine-readable instructions for implementing the methods according to the present disclosure. Thus, the present disclosure also covers a recording medium storing a program for executing the method according to the present disclosure.
It is also noted that in the devices, apparatuses, and methods of the present disclosure, each component or step can be decomposed and/or recombined. These decompositions and/or recombinations are to be considered equivalents of the present disclosure.
The previous description of the disclosed aspects is provided to enable any person skilled in the art to make or use the present disclosure. Various modifications to these aspects will be readily apparent to those skilled in the art, and the generic principles defined herein may be applied to other aspects without departing from the scope of the disclosure. Thus, the present disclosure is not intended to be limited to the aspects shown herein but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.
The foregoing description has been presented for purposes of illustration and description. Furthermore, this description is not intended to limit embodiments of the disclosure to the form disclosed herein. While a number of example aspects and embodiments have been discussed above, those of skill in the art will recognize certain variations, modifications, alterations, additions and sub-combinations thereof.
Claims (10)
1. A system for data warehousing of data in a blockchain, comprising: the data analysis module comprises a plurality of data analyzers, and the data warehouse comprises a plurality of storage modules;
the data acquisition module is used for acquiring data to be processed from any node of the block chain network and pushing the data to be processed to the data classification module;
the data classification module is used for classifying the data to be processed to obtain classification information of the data to be processed, and inquiring a data analyzer corresponding to the classification information in the data analysis module in a corresponding relation between preset classification information and a data analyzer;
the data analysis module is used for carrying out data analysis on the data to be processed by using a data analyzer which is determined by the data classification module and corresponds to the classification information to obtain format data, taking the classification information of the data to be processed as the classification information of the format data, and distributing a data identifier to the format data;
the data warehouse is used for inquiring the storage module corresponding to the classification information in the corresponding relation between the preset classification information and the storage module, and storing the format data, the classification information and the data identification in the storage module corresponding to the classification information.
2. The system of claim 1, further comprising: an interface module;
the interface module is used for acquiring format data corresponding to a data acquisition request from the data warehouse according to a data identifier in the data acquisition request after receiving the data acquisition request which is sent by a client and used for acquiring the format data, and sending the format data corresponding to the data acquisition request to the client.
3. The system according to claim 2, wherein the interface module further stores a plurality of public-private key pair public keys, and a corresponding relationship between a preset public key and a digital identity; the interface module is further configured to:
acquiring a public-private key pair public key corresponding to the digital identity in the data acquisition request based on the corresponding relation between the preset public key and the digital identity;
verifying the signature of the verifiable certificate in the data acquisition request by using the public key;
and responding to the verification that the signature of the verifiable certificate in the data acquisition request passes the verification, executing the operation of acquiring the format data corresponding to the data acquisition request from the data warehouse according to the data identification in the data acquisition request, and sending the format data corresponding to the data acquisition request to the client.
4. The system of claim 3, wherein the interface module further stores a corresponding relationship between a preset authority and a digital identity; the interface module is further configured to:
determining whether the client has the authority to acquire format data corresponding to the data identifier in the data acquisition request according to the corresponding relation between the preset authority and the digital identity identifier;
and in response to that the client has the right to acquire the format data corresponding to the data identifier in the data acquisition request and the signature of the verifiable certificate in the data acquisition request passes the verification, executing the operation of acquiring the format data corresponding to the data identifier in the data acquisition request from the data warehouse and sending the format data corresponding to the data identifier in the data acquisition request to the client.
5. The system of claim 1, wherein the data warehouse is further configured to:
and counting format data in each storage module of the plurality of storage modules based on a preset counting dimension and a preset counting time period to obtain a counting result, and performing visual processing on the counting result.
6. The system of claim 1, wherein the collection module comprises a data collection sub-module and a task queue sub-module;
the data acquisition submodule is used for acquiring the data to be processed from any node of the block chain network;
and the task queue submodule is used for sequencing the data to be processed according to a preset node importance degree list and the storage node of the data to be processed, and pushing the data to be processed to the data classification module according to the sequencing.
7. A method for data storage of data in a block chain, comprising:
acquiring data to be processed from any node of a block chain network;
classifying the data to be processed to obtain classification information of the data to be processed, and inquiring a data analyzer corresponding to the classification information in a data analysis module in a corresponding relation between preset classification information and a data analyzer;
performing data analysis on the data to be processed by using a data analyzer corresponding to the classification information to obtain format data, taking the classification information of the data to be processed as the classification information of the format data, and distributing a data identifier to the format data;
inquiring a storage module corresponding to the classification information in a data warehouse in a corresponding relation between preset classification information and the storage module, and storing the format data, the classification information and the data identification in the storage module corresponding to the classification information.
8. The method of claim 7, further comprising:
and after receiving a data acquisition request sent by a client for acquiring format data, acquiring the format data corresponding to the data acquisition request from the data warehouse according to a data identifier in the data acquisition request, and sending the format data corresponding to the data acquisition request to the client.
9. An electronic device, comprising:
a memory for storing a computer program;
a processor for executing the computer program stored in the memory, and when the computer program is executed, implementing the data-binning method for data in a blockchain according to any of the preceding claims 7 to 8.
10. A computer-readable storage medium, on which a computer program is stored, the computer program, when being executed by a processor, implementing the method for data warehousing of data in a blockchain according to any one of claims 7 to 8.
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