WO2020001108A1 - 基于区块链的数据处理方法和装置 - Google Patents

基于区块链的数据处理方法和装置 Download PDF

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WO2020001108A1
WO2020001108A1 PCT/CN2019/080032 CN2019080032W WO2020001108A1 WO 2020001108 A1 WO2020001108 A1 WO 2020001108A1 CN 2019080032 W CN2019080032 W CN 2019080032W WO 2020001108 A1 WO2020001108 A1 WO 2020001108A1
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data
blockchain
block
local database
block data
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PCT/CN2019/080032
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English (en)
French (fr)
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王吉元
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阿里巴巴集团控股有限公司
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Priority to EP19827111.6A priority Critical patent/EP3719668A4/en
Priority to AU2019295818A priority patent/AU2019295818B2/en
Priority to CA3087309A priority patent/CA3087309C/en
Priority to SG11202006179QA priority patent/SG11202006179QA/en
Publication of WO2020001108A1 publication Critical patent/WO2020001108A1/zh
Priority to US16/888,614 priority patent/US10949447B2/en

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    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
    • G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
    • G06F16/27—Replication, distribution or synchronisation of data between databases or within a distributed database system; Distributed database system architectures therefor
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q40/00—Finance; Insurance; Tax strategies; Processing of corporate or income taxes
    • G06Q40/04—Trading; Exchange, e.g. stocks, commodities, derivatives or currency exchange
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F21/00—Security arrangements for protecting computers, components thereof, programs or data against unauthorised activity
    • G06F21/60—Protecting data
    • G06F21/64—Protecting data integrity, e.g. using checksums, certificates or signatures
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q30/00—Commerce
    • G06Q30/06—Buying, selling or leasing transactions
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q40/00—Finance; Insurance; Tax strategies; Processing of corporate or income taxes
    • G06Q40/02—Banking, e.g. interest calculation or account maintenance
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L67/00—Network arrangements or protocols for supporting network services or applications
    • H04L67/01—Protocols
    • H04L67/10—Protocols in which an application is distributed across nodes in the network
    • H04L67/1095—Replication or mirroring of data, e.g. scheduling or transport for data synchronisation between network nodes
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L69/00—Network arrangements, protocols or services independent of the application payload and not provided for in the other groups of this subclass
    • H04L69/22—Parsing or analysis of headers
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L9/00—Cryptographic mechanisms or cryptographic arrangements for secret or secure communications; Network security protocols
    • H04L9/06—Cryptographic mechanisms or cryptographic arrangements for secret or secure communications; Network security protocols the encryption apparatus using shift registers or memories for block-wise or stream coding, e.g. DES systems or RC4; Hash functions; Pseudorandom sequence generators
    • H04L9/0643—Hash functions, e.g. MD5, SHA, HMAC or f9 MAC
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L9/00—Cryptographic mechanisms or cryptographic arrangements for secret or secure communications; Network security protocols
    • H04L9/32—Cryptographic mechanisms or cryptographic arrangements for secret or secure communications; Network security protocols including means for verifying the identity or authority of a user of the system or for message authentication, e.g. authorization, entity authentication, data integrity or data verification, non-repudiation, key authentication or verification of credentials
    • H04L9/3236—Cryptographic mechanisms or cryptographic arrangements for secret or secure communications; Network security protocols including means for verifying the identity or authority of a user of the system or for message authentication, e.g. authorization, entity authentication, data integrity or data verification, non-repudiation, key authentication or verification of credentials using cryptographic hash functions
    • H04L9/3239—Cryptographic mechanisms or cryptographic arrangements for secret or secure communications; Network security protocols including means for verifying the identity or authority of a user of the system or for message authentication, e.g. authorization, entity authentication, data integrity or data verification, non-repudiation, key authentication or verification of credentials using cryptographic hash functions involving non-keyed hash functions, e.g. modification detection codes [MDCs], MD5, SHA or RIPEMD
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L9/00—Cryptographic mechanisms or cryptographic arrangements for secret or secure communications; Network security protocols
    • H04L9/50—Cryptographic mechanisms or cryptographic arrangements for secret or secure communications; Network security protocols using hash chains, e.g. blockchains or hash trees

Definitions

  • This specification relates to the field of network communication technology, and in particular, to a data processing method and device based on a blockchain.
  • Blockchain technology also known as distributed ledger technology, is an emerging technology in which several computing devices participate in "accounting" and jointly maintain a complete distributed database.
  • the data on the chain has serious problems of difficulty in identification, statistics, and analysis.
  • the main cause of this problem is that in the process of storing data in a distributed form by the blockchain, the globally unique Hash code is usually used as the parent-child blood connection between the blocks.
  • the data information contained in the block cannot be connected to the hash code, and the data inside the block data cannot be connected. Therefore, the blockchain is an inefficient and expensive way to store data.
  • Blockchain data storage structure makes the data stored on the chain difficult to be used by upper-layer applications, which creates a big bottleneck for the promotion and development of blockchain technology.
  • this specification provides a blockchain-based data processing method, which is applied to a data center that interfaces with the blockchain, including:
  • the step of synchronizing the block data on the blockchain to a local database includes:
  • the block data of the latest block is synchronized to the local database based on the enabled timing task.
  • the step of synchronizing the block data on the blockchain to a local database includes:
  • the parsed block data is stored in the local database according to a preset storage format.
  • the parsing rule is a plug-in parsing rule.
  • the parsing rule includes one or more of a business scenario parsing rule, a data filtering rule, and a preset index field parsing rule.
  • the preset storage format includes a JSON format.
  • the step of synchronizing the block data on the blockchain to a local database further includes:
  • Generate a query index for the parsed block data create an index table based on the mapping relationship between the generated query index and the corresponding block data, and save it locally.
  • this specification also provides a data processing device based on a blockchain, which is applied to a data center connected to the blockchain and includes:
  • a synchronization unit that synchronizes the block data on the blockchain to a local database
  • a receiving unit that receives a data use request sent by a target application
  • the processing unit in response to the data use request, queries the requested data corresponding to the data use request in the local database, and returns the requested data to the target application.
  • the synchronization unit is further configured to:
  • the block data of the latest block is synchronized to the local database based on the enabled timing task.
  • the synchronization unit is further configured to:
  • the parsed block data is stored in the local database according to a preset storage format.
  • the parsing rule is a plug-in parsing rule.
  • the parsing rule includes one or more of a business scenario parsing rule, a data filtering rule, and a preset index field parsing rule.
  • the preset storage format includes a JSON format.
  • the synchronization unit is further configured to:
  • Generate a query index for the parsed block data create an index table based on the mapping relationship between the generated query index and the corresponding block data, and save it locally.
  • this specification also provides a computer device including: a memory and a processor; the memory stores a computer program executable by the processor; and when the processor runs the computer program, the area-based The steps described in the blockchain data processing method.
  • the present specification also provides a computer-readable storage medium on which a computer program is stored.
  • the computer program is executed by a processor, the steps described in the above-mentioned blockchain-based data processing method are performed.
  • the data center can provide a more convenient data processing method for the target application based on the data storage method and data retrieval method of the local database, which overcomes the inconvenience of data in the blockchain.
  • FIG. 1 is a connection architecture diagram of a blockchain system, an upper-layer application, and a data center according to an exemplary embodiment of the present specification
  • FIG. 2 is a flowchart of a blockchain-based data processing method provided by an exemplary embodiment of the present specification
  • FIG. 3 is a schematic structural diagram of a data center according to an exemplary embodiment of the present specification.
  • FIG. 4 is a schematic diagram of a blockchain-based data processing device according to an exemplary embodiment of the present specification
  • FIG. 5 is a hardware structure diagram of an embodiment of a method or device for processing data based on a blockchain provided by this specification.
  • Blockchain can specifically refer to a P2P network system with a distributed data storage structure reached by each node through a consensus mechanism.
  • the data in this blockchain is distributed in time and connected by “blocks.”
  • the latter block contains the data summary of the previous block, and according to the specific consensus mechanism (such as POW, POS, DPOS, or PBFT, etc.), all or part of the node's data is fully backed up.
  • the consensus mechanism such as POW, POS, DPOS, or PBFT, etc.
  • the blockchain system has the characteristics of ensuring data security and preventing change that other centralized database systems cannot match.
  • the data in the block is usually collected in the form of a transaction.There is no connection between the transactions, and each transaction cannot be related to the data summary of the block from the content (but only mathematically like Merkel The tree method establishes a connection). Due to the lack of a unified analysis and statistics and indexing mechanism for the data in the block or the data in the transaction, the data in the block chain is difficult to be used by the upper-level applications of the block chain.
  • FIG. 1 illustrates a flowchart of a blockchain-based data processing method provided by an exemplary embodiment of the present specification. The method is applied to a data center that interfaces with the blockchain, and includes:
  • Step 102 Synchronize the block data on the blockchain to a local database.
  • Step 104 Receive a data use request sent by the target application
  • Step 106 In response to the data use request, query the requested data corresponding to the data use request in the local database, and return the requested data to the target application.
  • the "upper-layer application” or “target application” described in the embodiments of this specification refers to an application program built on the distributed data storage architecture of the blockchain, which can use the blockchain's consensus mechanism, a distributed database, or Mechanism features such as an auto-executable smart contract provide data services for the application's specific business implementation (such as renting business, vehicle scheduling business, insurance claims business, credit service, medical service, etc.).
  • the data center described in the embodiments of this specification refers to both communicating with the blockchain (which can be used as a node device of the above blockchain) and communicating with the target application of the blockchain (also called upper-layer application). Connected data processing equipment.
  • FIG. 2 illustrates a connection architecture diagram of a blockchain system, an upper-layer application, and a data center according to an embodiment of the present specification.
  • the data center is connected to both the blockchain system and an upper-layer application of the blockchain.
  • DAPP Decentralized Application
  • the upper-layer application is also in communication with the blockchain system so that the upper-layer application writes the business data generated by it directly into the distributed database of the blockchain.
  • DAPP Decentralized Application
  • the block data of the blockchain is synchronized to the local database of the data center, and the data center is used to provide the requested data for the data usage request of the upper-level application.
  • the construction of this data center can more conveniently provide data services for the upper-layer applications of the blockchain.
  • the above block data may include one or more of data content such as all transaction data in the block, transaction summary data in the block, and block summary data, and may be based on the specific business requirements of the data center or its upper-layer applications. set up.
  • the data center described in the above embodiments can provide data services for multiple upper-layer applications, which is not limited in the present invention.
  • the transaction described in this specification refers to a piece of data created by a user through a client of the blockchain and that needs to be finally published to the distributed database of the blockchain.
  • the transactions in the blockchain are divided into narrow transactions and broad transactions.
  • a narrow transaction refers to a value transfer issued by a user to the blockchain; for example, in a traditional Bitcoin blockchain network, a transaction can be a transfer initiated by a user in the blockchain.
  • the generalized transaction refers to a piece of business data with business intent issued by the user to the blockchain; for example, an operator can build an alliance chain based on actual business needs and rely on the alliance chain to deploy other types that are not related to value transfer.
  • the transaction can be a transaction issued by the user in the alliance chain.
  • Intent business message or business request The description of this "transaction" is not limited in this specification, and may be specifically determined according to the business nature of the blockchain described in this specification.
  • the blockchain can be directly connected to its upper-layer application.
  • the upper-layer application DAPP of the blockchain writes the business data generated directly into the blockchain; this description is not limited to this.
  • the upper-layer application DAPP can also send the business data generated by it to the data center for preprocessing. Or filtering and other operations, and then send the data that should be uploaded to the blockchain, thereby further saving the data footprint of the blockchain.
  • step 102 synchronizing the block data on the blockchain to a local database
  • step 104 receiving data sent by the target application.
  • the order of requests is not unique.
  • the data center can first synchronize the latest block data of the blockchain to a local database according to a preset synchronization rule, and then receive the data usage request sent by the target application to process the data usage request in the local database; it can also receive the target first
  • the data use request sent by the application is then used to synchronize the block data, and if the received data use request contains a list of block heights that are related to or should be obtained from the data use request, the data center can selectively synchronize the area Block height block data included in the block height list, eliminating the need to obtain block data for all blocks of the blockchain, thereby further saving data center storage space and improving the use efficiency of data center computer resources.
  • the above-mentioned data center may also implement a variety of specific implementation methods for synchronizing the latest data of the blockchain to a local database.
  • the data center and the blockchain maintain a real-time acquisition mode, that is, the data center obtains the latest block from the blockchain system in real time.
  • the data center can immediately synchronize the new block to the local database.
  • the above data center synchronizes the block data on the blockchain to the local database in real time, which is not prone to data delay.
  • the blocks on the blockchain are not increased in real time High, so there is a waste of computing resources in the data center.
  • the data center can select the offline timing acquisition mode to synchronize the block data on the blockchain. That is, the data center enables the timing acquisition task and downloads data from the blockchain every predetermined period of time. Obtain new block data and synchronize the acquired new block data to the local database.
  • the offline timing acquisition mode increases the effective utilization of computer resources in the data center, but the data center cannot accurately know the time when the block height increases.
  • there is a disadvantage of delaying the obtained data Even because the data center does not know the details of the synchronized blocks, the block data obtained at regular intervals may not be the data required by the data center to provide data services for its target applications. Waste of computer resources.
  • this specification also provides an implementation that combines the advantages of the two data synchronization methods described above, that is, the data center can monitor the data center in real time.
  • the block height on the block chain is described; when the block height on the block chain is monitored to change, the block data of the latest block is synchronized to the local database based on the enabled timing task.
  • the data center uses this implementation to synchronize block data on the blockchain, which significantly increases Effective utilization of computer resources.
  • the data center can be configured with a specific timing task to synchronize the block data of the latest block to the local database; by configuring the timing task, the data center can control what it gets The delay time of block data is given to the timing tasks with higher acquisition frequency for the blocks with higher data timeliness requirements, and the given timing tasks with lower acquisition frequency for the blocks with less timeliness data requirements.
  • the computer resources of the data center Moreover, since the data center should provide data services for its upper-level applications, the data required by the service may exist in certain specific blocks. The data center can listen to these specific blocks and then Obtain specific blocks through enabled scheduled tasks to further control the delay time of required data and increase the utilization of computer resources.
  • the process of the data center synchronizing the block data on the blockchain to the local database further includes: according to a preset parsing rule Parse the block data, and store the parsed block data in a local database according to a preset storage format.
  • the local database can be a standard relational database (for example: Rds) or a non-relational storage (for example: HBase). It is not limited in this specification.
  • the above parsing rules can be set according to the type of data content collected by the blockchain system or the specific business of the target application, including one of rules such as business scenario parsing rules, data filtering rules, or preset index field parsing rules. Or more.
  • the above-mentioned blockchain includes various content or types of transactions such as house lease contract transactions, rent deposit payment transactions, and rent payment transactions sent by different nodes or node clients. The entire process is to perform blockchain certificate storage.
  • the above-mentioned blockchain can also be used to record certificate information transactions in other business scenarios. Transactions generated under various business scenarios are mixed and recorded in this area.
  • the blockchain does not classify and store all transactions according to the business type of the transaction.
  • An upper-layer application for house lease management is built on this blockchain.
  • Various types of data information related to house lease business need to be obtained from this blockchain.
  • the center can analyze the block information obtained from the blockchain, and store the information related to the house lease management obtained from the analysis in a local database, which can be called by the above-mentioned upper-level application for rent lease management at any time.
  • the data center may set a data model (such as a Schema template) of a house rental business, use the data model to analyze block data, and fill the corresponding data into the data model.
  • the data model of the house leasing business may include the contents of the house leasing contract number, the house leasing ID, the house renter ID, the house address, the rent deposit, the rent, and the lease term.
  • the corresponding data information can be filled into the model and stored in the local database according to the data text save type of the local database, such as JSON format.
  • the above data analysis process can also use some filtering rules, such as specific public key rules, or filter out blacklist public key rules, select transactions issued by specific public keys for data analysis, or do not perform transactions issued for public keys that belong to the blacklist.
  • filtering rules such as specific public key rules, or filter out blacklist public key rules, select transactions issued by specific public keys for data analysis, or do not perform transactions issued for public keys that belong to the blacklist.
  • Data analysis to filter out dirty data to save computer resources; you can also use classification rules to classify transactions in the block and filter out transactions that are not part of the house leasing business, so as to analyze data only for the target business.
  • preset index field analysis rules can also be used.
  • the business index fields required by upper-level applications such as "rental contract number", "house area”, and "tenant ID card number” are set.
  • the synchronized block data is parsed one by one.
  • the above process of parsing according to various parsing rules can be set as a plug-in executable program, so as to flexibly apply various parsing rules or a combination of various parsing rules for different business scenarios. Improve the efficiency of data analysis and processing.
  • the above parsing process may also include operations such as checking the data, encrypting or decrypting, and desensitizing the data, which are not described in detail here.
  • the data generated according to the above various analysis rules are usually in Key-Value format, such as the lease contract number -1234567, the lessee ID number -1XXXXXXXXX, etc., in order to facilitate the data center's retrieval and query of the above-mentioned stored data.
  • the data center may generate a query index for the parsed data, create an index table based on the mapping relationship between the generated query index and corresponding block data, and save the index table in the local database.
  • the following instructions describe the various functions that a data center can implement in the housing rental business.
  • FIG. 3 illustrates the architecture of a data center 30 that can provide data processing services for upper-layer applications of house rental management.
  • the data center 30 can be divided into an external interface layer 302, an information parsing layer 304, a business index layer 306, a data synchronization layer 308,
  • the multi-layer architecture such as the bottom data source layer 310, provides various data processing operations such as transaction information data retrieval, statistics, and analysis to the upper-layer applications. It is worth noting that the above multi-layer architecture is only artificially divided based on the data processing functions that the data center can perform. There is no specific demarcation between the above layers, and the data center provided by this specification can achieve The function may not be limited to this.
  • the block data recorded on the blockchain can include the following transaction information:
  • the data synchronization layer 308 of the data center can synchronize the block data of the blockchain to a local database based on a preset synchronization strategy (such as the above-mentioned real-time mode or offline mode or a combination of real-time and offline modes).
  • the information analysis layer 304 is used for Analyze the synchronized block data, for example, using a house lease contract analysis model.
  • the information analysis layer 304 can also perform some preprocessing on the parsed data, such as data sorting or merging, data desensitization, or encryption and decryption.
  • the data center after processing by the information analysis layer, the data center can get the following data:
  • the parsed house lease contract data can be stored in the underlying data source layer 310 in JSON format.
  • the underlying data source layer can use a standard relational database form or a non-relational database form.
  • the information parsing layer 304 of the data center can also use the index field parsing rules to parse the rent payment transaction submitted by the tenant, for example, using the index data fields "txhash” and "pay_channel” (Note: different pay_channels describe this data center
  • index data fields "txhash” and "pay_channel” Note: different pay_channels describe this data center
  • "pay_amount” parses the above transactions to obtain the following data as shown in Table 1:
  • Txhash Pay-channel Pay-amount Tx11 10001 999 Tx21 10002 888 ... ... ...
  • Table 1 Data parsed by the data center according to the index field parsing rules
  • the above parsed data can be stored in the underlying data source layer 310, and in order to further facilitate the retrieval and management of the rent payment transaction by the data center, the data center can also generate a query index for the above data, and based on the generated query index and The mapping relationship between the corresponding block data creates an index table (shown in Table 2 below) and stores it in the business index layer 306 of the data center.
  • the business index layer 306 may also store a mapping relationship table between each data index related to the above-mentioned house lease contract information and the storage location of the above-mentioned data in the underlying data source layer 310.
  • Table 2 House rental business rent payment index table held by the data center's business index layer 306
  • the external interface layer 302 of the data center 30 can use the form of RESTFUL API to interact with the upper layer data, thereby providing data services in the form of URLs, and compatible with multilingual platforms (C #, Python, C ++, JAVA ).
  • the upper-layer application can send a data query request to the data center 30 to query the lease contract details of the house No. 0001 in the format of a URL.
  • the data center 30 learns the contract from its business index layer 306
  • the storage location of the data involved in the details is in the underlying data source layer 310, and the data involved in the contract details data request instruction is obtained from the underlying data source layer 310, the above data is organized in JSON format, and the above data is returned to the Target application:
  • the returned data content can include:
  • the above-mentioned data processing method applied to the data center 30 interfacing with the blockchain can conveniently provide data services for upper-layer applications in various business scenarios by establishing a data storage structure in the local database of the data center 30 that is more suitable for upper-layer applications. , Solved the bottleneck problem encountered in the promotion and development of blockchain technology.
  • the embodiments of the present specification also provide a data processing device based on a blockchain.
  • the device can be implemented by software, or by hardware or a combination of software and hardware.
  • software implementation as an example, as a device in a logical sense, it is formed by reading a corresponding computer program instruction into a memory through a CPU (Central Process Unit) of a device where the device is located.
  • CPU Central Process Unit
  • the equipment where the data processing device is located usually includes other hardware such as a chip for wireless signal transmission and reception, and / or for network communication Function board and other hardware.
  • FIG. 4 shows a blockchain-based data processing device 40 provided in this specification; a data center that is applied to the blockchain and includes:
  • a synchronization unit 402 which synchronizes the block data on the blockchain to a local database
  • the receiving unit 404 receives a data use request sent by a target application
  • the processing unit 406 in response to the data use request, queries the requested data corresponding to the data use request in the local database, and returns the requested data to the target application.
  • the synchronization unit 402 is further configured to:
  • the block data of the latest block is synchronized to the local database based on the enabled timing task.
  • the synchronization unit 402 is further configured to:
  • the parsed block data is stored in the local database according to a preset storage format.
  • the parsing rule is a plug-in parsing rule.
  • the parsing rule includes one or more of a business scenario parsing rule, a data filtering rule, and a preset index field parsing rule.
  • the preset storage format includes a JSON format.
  • the synchronization unit 402 is further configured to:
  • Generate a query index for the parsed block data create an index table based on the mapping relationship between the generated query index and the corresponding block data, and save it locally.
  • the device embodiments described above are only schematic, and the units described as separate components may or may not be physically separated, and the components displayed as units may or may not be physical modules, that is, may be located in One place, or can be distributed to multiple network modules. Some or all of the units or modules can be selected according to actual needs to achieve the purpose of the solution in this specification. Those of ordinary skill in the art can understand and implement without creative efforts.
  • the devices, units, and modules described in the foregoing embodiments may be specifically implemented by a computer chip or entity, or may be implemented by a product having a certain function.
  • a typical implementation device is a computer, and the specific form of the computer may be a personal computer, a laptop computer, a cellular phone, a camera phone, a smart phone, a personal digital assistant, a media player, a navigation device, an email sending and receiving device, and a game control Desk, tablet computer, wearable device, or a combination of any of these devices.
  • the embodiment of the present specification further provides a computer device, the computer device including a memory and a processor.
  • the memory stores a computer program that can be run by a processor.
  • the processor runs the stored computer program, the processor executes each step of the data center-based data processing method of the data center in the embodiment of the present specification.
  • each step of the data center's blockchain-based data processing method please refer to the previous content and will not be repeated.
  • the embodiments of the present specification also provide a computer-readable storage medium.
  • the storage medium stores computer programs. When these computer programs are run by a processor, the data in the embodiments of the present specification is executed.
  • Each step of the center's blockchain-based data processing method For a detailed description of each step of the data processing method based on the data center and the blockchain, please refer to the previous content and will not be repeated.
  • a computing device includes one or more processors (CPUs), input / output interfaces, network interfaces, and memory.
  • processors CPUs
  • input / output interfaces output interfaces
  • network interfaces network interfaces
  • memory volatile and non-volatile memory
  • Memory may include non-persistent memory, random access memory (RAM), and / or non-volatile memory in computer-readable media, such as read-only memory (ROM) or flash memory (flash RAM). Memory is an example of a computer-readable medium.
  • RAM random access memory
  • ROM read-only memory
  • flash RAM flash memory
  • Computer-readable media includes permanent and non-persistent, removable and non-removable media.
  • Information storage can be accomplished by any method or technology.
  • Information may be computer-readable instructions, data structures, modules of a program, or other data.
  • Examples of computer storage media include, but are not limited to, phase change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), and read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technologies, read-only disc read-only memory (CD-ROM), digital versatile disc (DVD) or other optical storage, Magnetic tape cartridges, magnetic tape storage or other magnetic storage devices or any other non-transmitting medium may be used to store information that can be accessed by a computing device.
  • computer-readable media does not include temporary computer-readable media, such as modulated data signals and carrier waves.
  • the embodiments of the present specification may be provided as a method, a system, or a computer program product. Therefore, the embodiments of the present specification may take the form of an entirely hardware embodiment, an entirely software embodiment, or an embodiment combining software and hardware aspects. Moreover, the embodiments of the present specification may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code. .

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Abstract

一种基于区块链的数据处理方法和装置，应用于与所述区块链对接的数据中心，包括：将所述区块链上的区块数据同步至本地数据库；接收目标应用发送的数据使用请求；响应于所述数据使用请求，在所述本地数据库中查询与所述数据使用请求对应的被请求数据，并将所述被请求数据返回所述目标应用。

Description

基于区块链的数据处理方法和装置 技术领域
本说明书涉及网络通信技术领域，尤其涉及一种基于区块链的数据处理方法和装置。
背景技术
区块链技术，也被称之为分布式账本技术，是一种由若干台计算设备共同参与“记账”，共同维护一份完整的分布式数据库的新兴技术。在当前区块链环境下,链上数据存在严重的难以识别,统计,分析的问题。造成这一问题的主要原因是区块链以分布式形式存储数据的过程中,通常以全局唯一的Hash编码做为区块之间的父子血缘连接。区块中包含的数据信息无法与Hash编码建立连接,区块数据内部的数据也无法建立联系，因此区块链是一种低效且昂贵的存储数据的方式。区块链数据存储结构导致链上存储的数据很难被上层应用程序使用,给区块链技术推广发展造成很大的瓶颈。
发明内容
针对以上提出的问题，本说明书提供了一种基于区块链的数据处理方法，应用于与所述区块链对接的数据中心，包括：
将所述区块链上的区块数据同步至本地数据库；
接收目标应用发送的数据使用请求；
响应于所述数据使用请求，在所述本地数据库中查询与所述数据使用请求对应的被请求数据，并将所述被请求数据返回所述目标应用。
更优的，所述将所述区块链上的区块数据同步至本地数据库，包括：
实时监控所述区块链上的区块高度；
当监控到所述区块链上的区块高度发生变化时，基于启用的定时任务将最新区块的区块数据同步至本地数据库。
更优的，所述将所述区块链上的区块数据同步至本地数据库，包括：
根据预设的解析规则解析所述区块数据；
将解析得到的区块数据按照预设的存储格式存储于所述本地数据库。
更优的，所述解析规则为插件化的解析规则。
更优的，所述解析规则包括业务场景解析规则、数据过滤规则、预设索引字段解析规则中的一种或多种。
更优的，所述预设的存储格式包括JSON格式。
更优的，所述将所述区块链上的区块数据同步至本地数据库，还包括：
为解析得到的区块数据生成查询索引，基于生成的查询索引与对应的区块数据之间的映射关系创建索引表，并在本地保存。
相应地，本说明书还提供一种基于区块链的数据处理装置，应用于与所述区块链对接的数据中心，包括：
同步单元，将所述区块链上的区块数据同步至本地数据库；
接收单元，接收目标应用发送的数据使用请求；
处理单元，响应于所述数据使用请求，在所述本地数据库中查询与所述数据使用请求对应的被请求数据，并将所述被请求数据返回所述目标应用。
更优的，所述同步单元进一步用于：
实时监控所述区块链上的区块高度；
当监控到所述区块链上的区块高度发生变化时，基于启用的定时任务将最新区块的区块数据同步至本地数据库。
更优的，所述同步单元进一步用于：
根据预设的解析规则解析所述区块数据；
将解析得到的区块数据按照预设的存储格式存储于所述本地数据库。
更优的，所述解析规则为插件化的解析规则。
更优的，所述解析规则包括业务场景解析规则、数据过滤规则、预设索引字段解析规则中的一种或多种。
更优的，所述预设的存储格式包括JSON格式。
更优的，所述同步单元进一步用于：
为解析得到的区块数据生成查询索引，基于生成的查询索引与对应的区块数据之间的映射关系创建索引表，并在本地保存。
相应地，本说明书还提供了一种计算机设备，包括：存储器和处理器；所述存储器上存储有可由处理器运行的计算机程序；所述处理器运行所述计算机程序时，执行如上述基于区块链的数据处理方法所述的步骤。
相应地，本说明书还提供了一种计算机可读存储介质，其上存储有计算机程序，所述计算机程序被处理器运行时，执行如上述基于区块链的数据处理方法所述的步骤。
应用本说明书所提供的基于区块链的数据处理方法、装置、计算机设备和计算机可读存储介质，在区块链与其上层应用(即目标应用)之间构建一数据中心，该数据中心同步区块链的区块数据至本地数据库，数据中心可基于本地数据库的数据存储方式和数据检索方式，为目标应用提供更加便捷的数据处理方法，克服了区块链中的数据使用不便的缺陷。
附图说明
图1为本说明书一示例性实施例提供的区块链系统、上层应用及数据中心的连接架构图；
图2为本说明书一示例性实施例提供的一种基于区块链的数据处理方法的流程图；
图3为本说明书一示例性实施例提供的数据中心的架构示意图；
图4为本说明书一示例性实施例提供的一种基于区块链的数据处理装置的示意图；
图5为运行本说明书所提供的基于区块链的数据处理方法或装置实施例的一种硬件结构图。
具体实施方式
“区块链”，具体可指一个各节点通过共识机制达成的、具有分布式数据存储结构的P2P网络系统，该区块链内的数据分布在时间上相连的一个个“区块(block)”之内，后一区块包含前一区块的数据摘要，且根据具体的共识机制(如POW、POS、DPOS或PBFT等)的不同，达成全部或部分节点的数据全备份。本领域的技术人员熟知，由于区块链系统在相应共识机制下运行，已收录至区块链数据库内的数据很难再被更改，例如采用Pow共识的区块链，至少需要全网51％算力的攻击才有可能篡改已有数据， 因此区块链系统有着其他中心化数据库系统所无法比拟的保证数据安全、防更改的特性。区块内的数据通常以交易(transaction)的形式被收录，各个交易之间并无建立联系，且各交易无法从内容上与区块的数据摘要建立联系(而仅仅从数学上如默克尔树法建立联系)，由于缺乏对区块内数据或交易内数据统一的分析统计及索引机制，区块链内的数据很难被区块链的上层应用使用。
为解决如上所述的问题，图1示意了本说明书一示意性实施例提供的基于区块链的数据处理方法的流程图，该方法应用于与所述区块链对接的数据中心，包括：
步骤102，将所述区块链上的区块数据同步至本地数据库；
步骤104，接收目标应用发送的数据使用请求；
步骤106，响应于所述数据使用请求，在所述本地数据库中查询与所述数据使用请求对应的被请求数据，并将所述被请求数据返回所述目标应用。
本说明书实施例所述的“上层应用”或“目标应用”是指构建于所述区块链的分布式数据存储架构上的应用程序，可利用区块链的共识机制、分布式数据库、或可自动执行的智能合约等机制特性为该应用程序具体的业务实现(比如，租房业务、车辆调度业务、保险理赔业务、信用服务、医疗服务等)提供数据服务。本说明书实施例所述的数据中心是指既与所述区块链通信连接(可作为上述区块链的一个节点设备)，又与区块链的目标应用(又可称为上层应用)通信连接的数据处理设备。
图2示意了本说明书一实施例提供的区块链系统、上层应用及数据中心的连接架构图，所述数据中心既与所述区块链系统连接，又与所述区块链的上层应用DAPP(Decentralized Application)连接，且该上层应用也与所述区块链系统通信联系以便上层应用将其产生的业务数据直接写入区块链的分布式数据库。通过在区块链系统与其上层应用DAPP之间设置一数据中心，将区块链的区块数据同步至数据中心的本地数据库，利用数据中心为上层应用的数据使用请求提供被请求数据。由于数据中心可以对其本地数据库内所存储的数据进行解析、格式更改、移动位置等操作，不再受限于区块链的区块数据不能被更改(如存储格式或存储位置)且数据之间关联性差造成的数据使用不便的特性，该数据中心的构建可更加便捷地为区块链的上层应用提供数据服务。上述区块数据可包括区块内全部交易数据、区块内的交易摘要数据、区块的摘要数据等数据内容的一种或多种，可根据数据中心或其上层应用的具体的业务需求而设定。而且，本领域的技术人员应知，上述实施例所述的数据中心可为多个上层应用提供数据服务，在本发 明中不作限定。
在本说明书中所描述的交易(transfer)，是指用户通过区块链的客户端创建，并需要最终发布至区块链的分布式数据库中的一笔数据。其中，区块链中的交易，存在狭义的交易以及广义的交易之分。狭义的交易是指用户向区块链发布的一笔价值转移；例如，在传统的比特币区块链网络中，交易可以是用户在区块链中发起的一笔转账。而广义的交易是指用户向区块链发布的一笔具有业务意图的业务数据；例如，运营方可以基于实际的业务需求搭建一个联盟链，依托于联盟链部署一些与价值转移无关的其它类型的在线业务(比如，贷款申请、租房业务、车辆调度业务、保险理赔业务、信用服务、医疗服务等)，而在这类联盟链中，交易可以是用户在联盟链中发布的一笔具有业务意图的业务消息或者业务请求。本说明书不限定该“交易”的表现形式，可根据本说明书所述的区块链的业务性质具体而定。
另外，在本说明书所提供的实施例中，关于区块链与其目标应用(或上层应用)的通信方式可以有多种，例如，区块链可以与其上层应用直接连接，图2中所示的区块链的上层应用DAPP将其产生的业务数据直接写入区块链中；本说明书不限于此，例如，该上层应用DAPP还可将其产生的业务数据先发送至数据中心进行预处理，或过滤处理等操作，再将应上链的数据发送至区块链中，从而进一步节约区块链的数据占用空间。
在图1所提供的基于区块链的数据处理方法的实施例中，步骤102——将所述区块链上的区块数据同步至本地数据库与步骤104——接收目标应用发送的数据使用请求的先后顺序并不是唯一限定的。该数据中心可根据预设的同步规则先行将区块链的最新区块数据同步至本地数据库，再接收目标应用发送的数据使用请求以在本地数据库中处理该数据使用请求；也可以先接收目标应用发送的数据使用请求，再进行区块数据的同步，而且如果先行接收到的数据使用请求中包含与该数据使用请求相关或应获取的区块高度列表，该数据中心可选择性同步该区块高度列表中包含的区块高度的区块数据，而省去获取所述区块链的全部区块的区块数据，从而进一步节约数据中心的存储空间，提高数据中心计算机资源的使用效率。
上述的数据中心将区块链的最新数据同步至本地数据库的具体实现方式也可以有多种。在一示出的实施例中，数据中心与区块链保持实时获取模式，即数据中心实时向区块链系统获取最新区块，每当区块链系统内有新的区块被广播收录，数据中心可立刻将该新的区块同步至本地数据库。上述数据中心实时将区块链上的区块数据同步至本地数据库的方式，不易出现数据延迟,但由于数据中心需实时保持下载区块数据的状态，而区 块链上的区块并非实时增加高度，因此对数据中心计算资源存在浪费。
在另一示出的实施例中，数据中心可选择离线定时获取的模式同步区块链上的区块数据，即数据中心启用定时获取任务，每隔一段预设的时间段从区块链上获取新增的区块数据，并将获取到的新增的区块数据同步至本地数据库。相比于上述数据中心对区块链的区块数据的实时获取模式，离线定时获取的模式增加了数据中心的计算机资源的有效利用率，但数据中心由于并不能准确获知区块高度增加的时间而存在所获数据延迟的缺点，甚至由于数据中心并不知晓所同步区块的详情，其定时获取的区块数据也许并不是数据中心为其目标应用提供数据服务所需的数据，而增加了对计算机资源的浪费。
基于以上所述的数据中心将区块链上的区块数据同步至本地数据库的方式，本说明书还提供了一种实施方式以结合上述两种数据同步方式的优势，即数据中心可实时监听所述区块链上的区块高度；当监控到所述区块链上的区块高度发生变化时，再基于启用的定时任务将最新区块的区块数据同步至本地数据库。
由于实时监听所需的计算机资源远小于实时获取区块链上新增区块的区块数据所需的计算机资源，数据中心采用该种实施方式同步区块链上的区块数据，明显增加了计算机资源的有效利用率。
基于监听到的区块链上的区块高度增加情况，数据中心可配置具体的定时任务将最新区块的区块数据同步至本地数据库；通过配置该定时任务，数据中心可控制其获取到的区块数据的延迟时间，对于数据时效性要求较高的区块给予获取频率较高的定时任务，对于数据时效性要求不高的区块给予获取频率较低的定时任务，从而更加合理的利用数据中心的计算机资源；而且，由于数据中心应为其上层应用提供数据服务，该服务所需的数据可能存在某些特定的区块中，数据中心可在监听到这些特定的区块后，再通过启用的定时任务来获取特定区块，从而进一步控制所需数据的延迟时间，并增加计算机资源的利用率。
在本说明书提供了又一实施例中，为了更加方便地为目标应用提供数据使用服务，数据中心将区块链上的区块数据同步至本地数据库的过程，还包括：根据预设的解析规则解析所述区块数据，将解析得到的区块数据按照预设的存储格式存储于本地数据库，本地数据库可为标准关系型数据库(例如:Rds)或非关系型存储(例如:HBase)，在本说明书中不作限定。
具体说来，上述解析规则可根据区块链系统所收录的数据内容类型或目标应用的具 体业务进行设置，包括业务场景解析规则、数据过滤规则、或预设索引字段解析规则等规则中的一种或多种。以房屋租赁场景为例，上述区块链收录了不同节点或节点客户端发来的房屋租赁合同交易、房租押金缴纳交易、房租缴纳交易等多种内容或类型的交易，用于为房屋租赁的全过程进行区块链存证，当然，本领域技术人员应知，上述区块链还可用于收录其他业务场景的存证信息交易，各种业务场景下产生的交易都被混合收录在该区块链的区块内，区块链并未按照交易的业务类型对所有的交易进行相应的归类及存储。该区块链上构建有一用于房屋租赁管理的上层应用，需要从该区块链内获取与房屋租赁业务相关的各类数据信息，为方便上述的数据信息获取，本实施例所提供的数据中心可对从区块链上获取的区块信息进行解析，将解析所得的房屋租赁管理相关的信息存储于本地数据库，以供上述用于房租租赁管理的上层应用随时调用。
具体地，数据中心可设置一房屋租赁业务数据模型(例如Schema模板)，使用该数据模型解析区块数据，并将相应的数据填写入数据模型中。例如，该房屋租赁业务数据模型可包括房屋租赁合同号、房屋租赁人ID、房屋承租人ID、房屋地址、租金押金、租金、租赁期限等内容，通过逐个解析区块内的交易内容数据，即可将相应的数据信息填入该模型之中，并按照本地数据库的数据文本保存类型，如JSON格式，存储于本地数据库。上述数据解析过程还可使用一些过滤规则，如特定公钥规则、或滤掉黑名单公钥规则，选择特定公钥发布的交易进行数据解析、或不对隶属于黑名单的公钥发布的交易进行数据解析，从而过滤掉脏数据以节约计算机资源；也可使用分类规则，对区块内的交易进行分类，过滤掉不属房屋租赁业务的交易，从而只针对目标业务进行数据解析。具体的解析过程中还可使用预设索引字段解析规则，在本例中，设置“租赁合同编号”、“房屋面积”、“承租人身份证号”等上层应用所需的业务索引字段，对同步的区块数据逐个解析。
值得注意的是，上述按各种解析规则进行解析的过程可以被设置为插件化的可执行程序，从而针对不同的业务场景，灵活运用各种解析规则，或灵活运用各种解析规则的组合，提高数据解析处理的效率。另外，上述解析过程中还可包括对数据的验签、加密或解密、脱敏等操作，在此不做赘述。
根据上述各种解析规则生成的数据通常为Key-Value格式，如租赁合同编号-1234567，承租人身份证号-1XXXXXXXXXXX等，为方便数据中心对上述存储数据的检索查询，在本说明书提供的又一实施例中，数据中心可以为上述解析所得的数据生成查询索引，基于生成的查询索引与对应的区块数据之间的映射关系创建索引表，并在上述本地数据 库保存。以下本说明书对在房屋租赁业务中数据中心可实现的各种功能做出说明。
图3示意了可为房屋租赁管理的上层应用提供数据处理服务的数据中心30的架构，该数据中心30可划分为对外接口层302、信息解析层304、业务索引层306、数据同步层308、底层数据源层310等多层架构，对上层应用提供交易信息数据检索、统计、分析等多种数据处理操作。值得注意的是，上述多层架构仅仅是基于数据中心可执行的数据处理功能而概括性地人为划分，上述各层之间并无特定的分界，且本说明书所提供的数据中心所能实现的功能也可不限于此。
区块链上收录的区块数据可包括以下交易信息：
交易00：{txhash:tx00,contract No.:12345678,housecode:0001,land lord:A,tenant name:B and C}
交易01：{txhash:tx01,contract No.:12345678,deposit：500，month rent for B:999,month rent for C:888}
交易11：{txhash:tx11，contract No.:12345678housecode:0001pay_channel:10001 pay_amount:999}
交易21：{txhash:tx21，contract No.:12345678housecode:0001pay_channel:10002 pay_amount:888}
……
该数据中心的数据同步层308可基于预设的同步策略(如上述的实时模式或离线模式或实时与离线结合模式)将区块链的区块数据同步至本地数据库，信息解析层304用于对上述已同步的区块数据进行解析，例如使用房屋租赁合同解析模型，另外，信息解析层304还可对解析后的数据进行一些预处理，如数据的排序或合并，数据脱敏或加解密等；在本例中，经过信息解析层的处理，数据中心可得到如下数据：
{contract No.:12345678,
housecode:0001,
land lord:A,
tenant name:B and C}
deposit：500，
month rent for B:999,
month rent for C:888}
上述解析所得的房屋租赁合同数据可以JSON格式被保存在底层数据源层310中，底层数据源层可使用标准的关系型数据库形式，也可为非关系型数据库形式。
类似地，数据中心的信息解析层304还可利用索引字段解析规则，对承租人提交的房租支付交易进行解析，例如使用索引数据字段“txhash”“pay_channel”(注：不同的pay_channel说明本数据中心可同步获取不同的区块链或同一区块链的不同子链中的区块数据)“pay_amount”解析上述交易，以获得如表1所示的如下数据：
Txhash Pay-channel Pay-amount
Tx11 10001 999
Tx21 10002 888
…… …… ……
表1数据中心根据索引字段解析规则解析所得的数据
上述解析所得的数据可被保存至底层数据源层310内，而且为进一步方便数据中心对上述房租支付交易的检索及管理，数据中心还可为上述数据生成查询索引，并基于生成的查询索引与对应的区块数据之间的映射关系创建索引表(如下表2所示)，并将其保存在数据中心的业务索引层306。类似的，该业务索引层306也可存有与上述房屋租赁合同信息相关的各数据索引与上述各数据在底层数据源层310的存储位置的映射关系表。
COLUMN_NAME COLUMN_VALUE TXHASH
pay_channel 10001 tx11
pay_channel 10002 tx21
pay_amount 999 tx11
pay_amount 888 tx21
…… …… ……
表2数据中心的业务索引层306保存的房屋租赁业务房租缴纳索引表
数据中心30的对外接口层302可采用RESTFUL API的形式与上层数据进行交互，从而以url方式提供数据服务,并兼容多语言平台(C#,Python,C++,JAVA...)。在本例中，上层应用可以URL的格式向该数据中心30发送查询0001号房屋的租赁合同详情的数据查询请求，数据中心30在解析上述请求指令后，从其业务索引层306中获知该合同详情所涉及的数据在底层数据源层310的存储位置，并从底层数据源层310中获取上述合同详情数据请求指令所涉及的数据，以JSON格式组织上述数据，并将上述数据返回 至所述目标应用：
例如，以按照JSON格式组织数据为例，返回的数据内容可包括：
{“content”:{
contract No.:12345678,
housecode:0001,
land lord:A,
tenant name:B and C}
deposit：500，
month rent for B:999,
month rent for C:888，
url：http://asassa.com}}
上述应用于与区块链对接的数据中心30的数据处理方法，通过在数据中心30的本地数据库建立更适宜上层应用使用的数据存储结构，方便地为各种业务场景下的上层应用提供数据服务，解决了区块链技术推广发展所遇到的瓶颈问题。
与上述流程实现对应，本说明书的实施例还提供了一种基于区块链的数据处理装置。该装置可以通过软件实现，也可以通过硬件或者软硬件结合的方式实现。以软件实现为例，作为逻辑意义上的装置，是通过所在设备的CPU(Central Process Unit，中央处理器)将对应的计算机程序指令读取到内存中运行形成的。从硬件层面而言，除了图5所示的CPU、内存以及存储器之外，该数据处理装置所在的设备通常还包括用于进行无线信号收发的芯片等其他硬件，和/或用于实现网络通信功能的板卡等其他硬件。
图4所示为本说明书所提供的一种基于区块链的数据处理装置40；应用于与所述区块链对接的数据中心，包括：
同步单元402，将所述区块链上的区块数据同步至本地数据库；
接收单元404，接收目标应用发送的数据使用请求；
处理单元406，响应于所述数据使用请求，在所述本地数据库中查询与所述数据使用请求对应的被请求数据，并将所述被请求数据返回所述目标应用。
更优地，所述同步单元402进一步用于：
实时监控所述区块链上的区块高度；
当监控到所述区块链上的区块高度发生变化时，基于启用的定时任务将最新区块的区块数据同步至本地数据库。
更优地，所述同步单元402进一步用于：
根据预设的解析规则解析所述区块数据；
将解析得到的区块数据按照预设的存储格式存储于所述本地数据库。
更优地，所述解析规则为插件化的解析规则。
更优地，所述解析规则包括业务场景解析规则、数据过滤规则、预设索引字段解析规则中的一种或多种。
更优地，所述预设的存储格式包括JSON格式。
更优地，所述同步单元402进一步用于：
为解析得到的区块数据生成查询索引，基于生成的查询索引与对应的区块数据之间的映射关系创建索引表，并在本地保存。
上述装置中各个单元的功能和作用的实现过程具体详见上述方法中对应步骤的实现过程，相关之处参见方法实施例的部分说明即可，在此不再赘述。
以上所描述的装置实施例仅仅是示意性的，其中所述作为分离部件说明的单元可以是或者也可以不是物理上分开的，作为单元显示的部件可以是或者也可以不是物理模块，即可以位于一个地方，或者也可以分布到多个网络模块上。可以根据实际的需要选择其中的部分或者全部单元或模块来实现本说明书方案的目的。本领域普通技术人员在不付出创造性劳动的情况下，即可以理解并实施。
上述实施例阐明的装置、单元、模块，具体可以由计算机芯片或实体实现，或者由具有某种功能的产品来实现。一种典型的实现设备为计算机，计算机的具体形式可以是个人计算机、膝上型计算机、蜂窝电话、相机电话、智能电话、个人数字助理、媒体播放器、导航设备、电子邮件收发设备、游戏控制台、平板计算机、可穿戴设备或者这些设备中的任意几种设备的组合。
与上述方法实施例相对应，本说明书的实施例还提供了一种计算机设备，该计算机设备包括存储器和处理器。其中，存储器上存储有能够由处理器运行的计算机程序；处理器在运行存储的计算机程序时，执行本说明书实施例中数据中心基于区块链的数据处 理方法的各个步骤。对数据中心基于区块链的数据处理方法的各个步骤的详细描述请参见之前的内容，不再重复。
与上述方法实施例相对应，本说明书的实施例还提供了一种计算机可读存储介质，该存储介质上存储有计算机程序，这些计算机程序在被处理器运行时，执行本说明书实施例中数据中心基于区块链的数据处理方法的各个步骤。对基于数据中心基于区块链的数据处理方法的各个步骤的详细描述请参见之前的内容，不再重复。
以上所述仅为本说明书的较佳实施例而已，并不用以限制本说明书，凡在本说明书的精神和原则之内，所做的任何修改、等同替换、改进等，均应包含在本说明书保护的范围之内。
在一个典型的配置中，计算设备包括一个或多个处理器(CPU)、输入/输出接口、网络接口和内存。
内存可能包括计算机可读介质中的非永久性存储器，随机存取存储器(RAM)和/或非易失性内存等形式，如只读存储器(ROM)或闪存(flash RAM)。内存是计算机可读介质的示例。
计算机可读介质包括永久性和非永久性、可移动和非可移动媒体可以由任何方法或技术来实现信息存储。信息可以是计算机可读指令、数据结构、程序的模块或其他数据。
计算机的存储介质的例子包括，但不限于相变内存(PRAM)、静态随机存取存储器(SRAM)、动态随机存取存储器(DRAM)、其他类型的随机存取存储器(RAM)、只读存储器(ROM)、电可擦除可编程只读存储器(EEPROM)、快闪记忆体或其他内存技术、只读光盘只读存储器(CD-ROM)、数字多功能光盘(DVD)或其他光学存储、磁盒式磁带，磁带磁磁盘存储或其他磁性存储设备或任何其他非传输介质，可用于存储可以被计算设备访问的信息。按照本文中的界定，计算机可读介质不包括暂存电脑可读媒体(transitory media)，如调制的数据信号和载波。
还需要说明的是，术语“包括”、“包含”或者其任何其他变体意在涵盖非排他性的包含，从而使得包括一系列要素的过程、方法、商品或者设备不仅包括那些要素，而且还包括没有明确列出的其他要素，或者是还包括为这种过程、方法、商品或者设备所固有的要素。在没有更多限制的情况下，由语句“包括一个……”限定的要素，并不排除在包括所述要素的过程、方法、商品或者设备中还存在另外的相同要素。
本领域技术人员应明白，本说明书的实施例可提供为方法、系统或计算机程序产品。 因此，本说明书的实施例可采用完全硬件实施例、完全软件实施例或结合软件和硬件方面的实施例的形式。而且，本说明书的实施例可采用在一个或多个其中包含有计算机可用程序代码的计算机可用存储介质(包括但不限于磁盘存储器、CD-ROM、光学存储器等)上实施的计算机程序产品的形式。

Claims (16)

  1. 一种基于区块链的数据处理方法，应用于与所述区块链对接的数据中心，包括：
    将所述区块链上的区块数据同步至本地数据库；
    接收目标应用发送的数据使用请求；
    响应于所述数据使用请求，在所述本地数据库中查询与所述数据使用请求对应的被请求数据，并将所述被请求数据返回所述目标应用。
  2. 根据权利要求1所述的方法，所述将所述区块链上的区块数据同步至本地数据库，包括：
    实时监听所述区块链上的区块高度；
    当监听到所述区块链上的区块高度发生变化时，基于启用的定时任务将最新区块的区块数据同步至本地数据库。
  3. 根据权利要求1或2所述的方法，所述将所述区块链上的区块数据同步至本地数据库，包括：
    根据预设的解析规则解析所述区块数据；
    将解析得到的区块数据按照预设的存储格式存储于所述本地数据库。
  4. 根据权利要求3所述的方法，所述解析规则为插件化的解析规则。
  5. 根据权利要求3所述的方法，所述解析规则包括业务场景解析规则、数据过滤规则、预设索引字段解析规则中的一种或多种。
  6. 根据权利要求3所述的方法，所述预设的存储格式包括JSON格式。
  7. 根据权利要求3所述的方法，所述将所述区块链上的区块数据同步至本地数据库，还包括：
    为解析得到的区块数据生成查询索引，基于生成的查询索引与对应的区块数据之间的映射关系创建索引表，并在上述本地数据库保存。
  8. 一种基于区块链的数据处理装臵，应用于与所述区块链对接的数据中心，包括：
    同步单元，将所述区块链上的区块数据同步至本地数据库；
    接收单元，接收目标应用发送的数据使用请求；
    处理单元，响应于所述数据使用请求，在所述本地数据库中查询与所述数据使用请求对应的被请求数据，并将所述被请求数据返回所述目标应用。
  9. 根据权利要求8所述的装臵，所述同步单元进一步：
    实时监控所述区块链上的区块高度；
    当监控到所述区块链上的区块高度发生变化时，基于启用的定时任务将最新区块的 区块数据同步至本地数据库。
  10. 根据权利要求8或9所述的装臵，所述同步单元进一步：
    根据预设的解析规则解析所述区块数据；
    将解析得到的区块数据按照预设的存储格式存储于所述本地数据库。
  11. 根据权利要求10所述的装臵，所述解析规则为插件化的解析规则。
  12. 根据权利要求10所述的装臵，所述解析规则包括业务场景解析规则、数据过滤规则、预设索引字段解析规则中的一种或多种。
  13. 根据权利要求10所述的装臵，所述预设的存储格式包括JSON格式。
  14. 根据权利要求10所述的装臵，所述同步单元进一步：
    为解析得到的区块数据生成查询索引，基于生成的查询索引与对应的区块数据之间的映射关系创建索引表，并在本地保存。
  15. 一种计算机设备，包括：存储器和处理器；所述存储器上存储有可由处理器运行的计算机程序；所述处理器运行所述计算机程序时，执行如权利要求1到7任意一项所述的步骤。
  16. 一种计算机可读存储介质，其上存储有计算机程序，所述计算机程序被处理器运行时，执行如权利要求1到7任意一项所述的步骤。
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