CN114818002A - Data processing method, device and medium - Google Patents
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Abstract
The method is applied to a block chain prediction machine, the block chain prediction machine is in communication connection with a local block chain network and an external block chain network, a market price trading event is subscribed to the local block chain network, when the market price trading event is obtained, a trading inquiry request is sent to a target trading node corresponding to the market price trading event, and after trading information is confirmed, the local block chain network is called back so that the local block chain network can update user data. Compared with a third-party exchange, the data related to the user transaction process is maintained and decentralized by using the local block link network, so that the safety of the data is improved, and the risk of tampering the data is effectively reduced; on the other hand, the blockchain prediction machine can interact with an external blockchain network, and the external blockchain network comprises various transaction nodes, so that cross-chain data interaction can be realized.
Description
Technical Field
The present application relates to the field of block chaining technologies, and in particular, to a data processing method, apparatus, and medium.
Background
With the development of technology, more and more fields relate to digital asset transactions, for example, transactions of different kinds of assets by two users, and because of the related asset changes, security is the most basic requirement.
The traditional transaction recording and maintaining mode among users is completed through a third-party exchange, due to lack of supervision of the third-party exchange, asset transaction of the users completely depends on the strength and the reputation of the third-party exchange, and once the third-party exchange has data tampering, fraud, even money collection running and other behaviors, inestimable loss is caused to the users.
It follows that how to maintain the security of data involved in transactions between users is a problem that those skilled in the art are demanding to solve.
Disclosure of Invention
The application aims to provide a data processing method for maintaining the security of data involved in user transactions. In addition, the purpose of this application still provides a data processing device and computer storage medium.
In order to solve the above technical problem, the present application provides a data processing method applied to a block chain prediction machine, including:
establishing a communication connection with a local blockchain network and an external blockchain network, wherein the external blockchain network comprises a plurality of transaction nodes;
subscribing to a market trading event to the local blockchain network; the market price trading event is generated after trading requests of two wallet clients are matched and the local block chain network matches the trading requests of the two wallet clients;
when a market price trading event created by the local block chain network is acquired, sending a trading inquiry request containing the market price trading event to a target trading node corresponding to the market price trading event; wherein, the number of the target trading nodes is two;
and after the confirmed transaction information sent by the target transaction node is acquired, sending the confirmed transaction information to the local blockchain network so as to facilitate the local blockchain network to update user data.
Preferably, the market trading event includes an address of the target trading node, a hang order trading address, a market trading address, hang order trading data and market trading data;
the sending of the transaction query request including the market trading event to the target trading node corresponding to the market trading event includes:
analyzing the address of the target trading node contained in the market trading event;
obtaining a target client according to the address of the target transaction node;
and sending a query trading request containing the market trading event to the target trading node through the target client.
Preferably, the market transaction event further includes a transaction hash value, the transaction hash value is an address of the target transaction node, the hang ticket transaction address, and the market transaction address, and the hang ticket transaction data and the market transaction data are obtained through hash operation.
Preferably, the sending the confirmation transaction information to the local blockchain network to facilitate the local blockchain network to update user data comprises:
and sending trade successful transaction information, the hang list transaction address and the market price transaction address to the local blockchain network, wherein the hang list transaction data and the market price transaction data are convenient for the local blockchain network to update user data.
Preferably, the wallet client is a hierarchical deterministic wallet client.
Preferably, the plurality of transaction nodes comprises any combination of a transaction node for transaction BTC, a transaction node for transaction ETH, a transaction node for transaction EOS, a transaction node for transaction LTC.
In order to solve the above technical problem, the present application further provides a data processing method, which is applied to a local block chain network, and the method includes:
establishing a communication connection with a blockchain predictive machine, wherein the blockchain predictive machine is also in communication connection with an external blockchain network, and the external blockchain network comprises a plurality of transaction nodes;
receiving a subscription of the block chain prediction machine to a market price trading event; the market price trading event is generated after trading requests of two wallet clients are matched and matched;
when the transaction requests of the two wallet clients are matched and the transaction requests of the two wallet clients are matched, creating the market price transaction event so that the blockchain predictor sends a transaction query request containing the market price transaction event to a target transaction node corresponding to the market price transaction event; wherein, the number of the target trading nodes is two;
and obtaining the confirmed transaction information returned by the blockchain prediction machine after obtaining the confirmed transaction information sent by the target transaction node, and updating user data.
In order to solve the above technical problem, the present application further provides a data processing method applied to a block chain prediction machine, where the data processing method includes:
the communication module is used for establishing communication connection with a local blockchain network and an external blockchain network, wherein the external blockchain network comprises a plurality of transaction nodes;
the subscription module is used for subscribing market transaction events to the local block chain network; the market price trading event is generated after trading requests of two wallet clients are matched and the local block chain network matches the trading requests of the two wallet clients;
the system comprises a first sending unit, a second sending unit and a third sending unit, wherein the first sending unit is used for sending a transaction query request containing a market price transaction event to a target transaction node corresponding to the market price transaction event when the market price transaction event created by the local block chain network is obtained; wherein, the number of the target trading nodes is two;
and the second sending unit is used for sending the confirmed transaction information to the local blockchain network after the confirmed transaction information sent by the target transaction node is obtained so as to facilitate the local blockchain network to update user data.
In order to solve the above technical problem, the present application further provides a data processing apparatus, including a memory for storing a computer program;
a processor for implementing the steps of the data processing method as described when executing the computer program.
In order to solve the above technical problem, the present application further provides a computer-readable storage medium, on which a computer program is stored, and the computer program, when executed by a processor, implements the steps of the data processing method as described above.
The data processing method provided by the application is applied to a blockchain prediction machine, the blockchain prediction machine establishes communication connection with a local blockchain network and an external blockchain network, subscribes a market price transaction event to the local blockchain network, sends a transaction query request to a target transaction node corresponding to the market price transaction event when the market price transaction event is acquired, and calls back the local blockchain network after transaction information is acquired so as to facilitate the local blockchain network to update user data. Compared with a third-party exchange, the data related to the user transaction process is maintained and decentralized by using the local block link network, so that the safety of the data is improved, and the risk of tampering the data is effectively reduced; on the other hand, the blockchain prediction machine can interact with an external blockchain network, and the external blockchain network comprises various transaction nodes, so that cross-chain data interaction can be realized.
In addition, the data processing method, the data processing device and the computer storage medium applied to the local blockchain network provided by the application correspond to the method, and the effect is the same as the effect.
Drawings
In order to more clearly illustrate the embodiments of the present application, the drawings needed for the embodiments will be briefly described below, and it is obvious that the drawings in the following description are only some embodiments of the present application, and that other drawings can be obtained by those skilled in the art without inventive effort.
Fig. 1 is a system structure diagram of a block chain according to an embodiment of the present disclosure;
fig. 2 is a flowchart of a data processing method according to an embodiment of the present application;
fig. 3 is a flowchart of another data processing method provided in the embodiment of the present application;
fig. 4 is a block diagram of a data processing apparatus according to an embodiment of the present application;
fig. 5 is a block diagram of another data processing apparatus according to an embodiment of the present application.
Detailed Description
The technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application, and it is obvious that the described embodiments are only some embodiments of the present application, and not all embodiments. All other embodiments obtained by a person of ordinary skill in the art based on the embodiments in the present application without any creative effort belong to the protection scope of the present application.
The core of the application is to provide a data processing method, a device and a medium. The data processing method provided by the application is suitable for the application scenario shown in fig. 1. Fig. 1 is a system structure diagram of a block chain according to an embodiment of the present disclosure. As shown in fig. 1, the system comprises one or more user terminals 1, a local blockchain network 2, a blockchain oracle machine 3 and a server 4.
The user terminal 1 may be a mobile terminal such as a notebook computer, a desktop computer, and a mobile phone, and is configured to perform communication connection with an external blockchain network, and a wallet client is installed thereon, so as to implement a transaction of a user. The external blockchain network comprises a plurality of transaction nodes, wherein the transaction nodes can comprise transaction nodes (BTC nodes for short) for transaction of Bitcoin (BTC), transaction nodes (ETH nodes for short) for transaction of EtherFang (ETH), transaction nodes (EOS nodes for short) for transaction of grapefruit coin (EOS), and transaction nodes (LTC nodes for short) for transaction of Laitexin (LTC). The user can log in through the wallet client, and inquire the transaction depth, the disc opening, the K line, the transaction history and the like in the local block chain network 2 through the server 4, and can also recharge or cash up and the like through the wallet client and the transaction node in the external block chain network.
The local block chain network 2 comprises a plurality of block chain nodes 20, the block chain nodes 20 jointly complete storage of data of users, a decentralized transaction mode is achieved without relying on a third-party exchange, the safety problem of a transaction process can be effectively solved, the transaction process is completely conducted on the block chain, decentralized and anonymous, and the effects of higher safety and smaller tampering risk are achieved.
The blockchain prediction machine 3 can write information outside the blockchain into the blockchain, complete the intercommunication of the blockchain and real world data, and allow the determined blockchain to react to the uncertain external world. Through the blockchain prediction machine 3, whether the transaction on other blockchains is valid can be determined, and a transaction query request can be sent to other blockchains.
And the server 4 is connected with the local block chain network 2, analyzes the transaction in the block chain network, and generates transaction depth, a transaction port, K lines, transaction history and the like.
In order that those skilled in the art will better understand the disclosure, the following detailed description will be given with reference to the accompanying drawings. Fig. 2 is a flowchart of a data processing method according to an embodiment of the present application. As shown in fig. 2, the method is applied to a block chain prediction machine, and includes the following steps:
s10: communication connections are established with a local blockchain network and an external blockchain network, wherein the external blockchain network comprises a plurality of transaction nodes.
The function of the local blockchain network is to record data interaction involved in user transaction process, for example, after user transaction, account balance is updated.
Typically, decentralized exchanges are based on a particular blockchain platform, and can only trade certain types of digital assets, e.g., IDEX is ETH-based and can only trade tokens issued at Etherns; as another example, NewDEX is EOS-based, and tokens issued on an EOS can only be traded. Although cross-chaining techniques are continuously developed, the decentralized exchange does not support cross-chaining asset transactions, such as BTC and ETH transactions. The various transaction nodes in the external blockchain network include BTC nodes, ETH nodes, EOS nodes, and LTC nodes. Each transaction node is provided with a corresponding client for inquiring after the block chain prediction machine is logged in.
S11: and subscribing the market trading event to the local blockchain network.
The block chain prediction machine subscribes market trading events of the local block chain network in advance, and once the market trading events occur on the local block chain network, the block chain prediction machine can acquire the events. The market price trading event is generated after the trading requests of the two wallet clients are matched and the local block chain network matches the trading requests of the two wallet clients.
The market trading process of the user is as follows:
1) the user A initiates a bill hanging transaction to a local block chain network through a wallet client, and the parameters are as follows: trade pair ETH/BTC, price 0.0250, quantity 1 BTC;
2) processing a user A hang-up transaction at a certain block chain link point in the local block chain network, and marking the user A hang-up transaction as a temporary non-transaction;
3) user B initiates market price trading to the local blockchain network through the wallet client, and the parameters are as follows: for ETH/BTC, the price is the optimal price, and the quantity is 100 ETH;
4) and processing the market price transaction of the user B at a certain block chain link point in the local block chain network, finding that a BTC (Business to Board) hang bill is available, and matching the business. And (3) a bargaining result: bargaining price: 0.0250, traffic 1BTC (40 ETH).
5) The local blockchain network creates a market trading event. Typically, the market trading event includes an address of the target trading node, a hang-order trading address, a market trading address, hang-order trading data, and market trading data.
S12: and when a market trading event created by the local block chain network is acquired, sending a trading query request containing the market trading event to a target trading node corresponding to the market trading event.
It should be noted that, in the present embodiment, there are two target trading nodes, and in the above market trading process as an example, the ETH node and the BTC node are the target trading nodes. And when the block chain prediction machine acquires the market price trading event, sending a trading query request to the corresponding target trading node. Since the market trading event includes the address of the target trading node, the blockchain oracle can acquire the target trading node. And the target transaction node confirms whether the transaction is successful according to the data in the request, and sends confirmation transaction information to the block chain prediction machine under the condition of successful transaction.
S13: and after the confirmed transaction information sent by the target transaction node is acquired, the confirmed transaction information is sent to the local blockchain network so as to facilitate the local blockchain network to update the user data.
And after receiving the confirmed transaction information, the block chain prediction machine calls back block chain link points in the local block chain network, sends the information to the node, and the node adjusts the balance of the user, so that the user data is updated, and after the updated data is linked, all the nodes in the local block chain network can be obtained. For example, after the block link point obtains the confirmed transaction information, the updated user data is that the BTC balance of the user a is decreased by 1BTC, and the ETH balance of the user a is increased by 40 ETH; the BTC balance of the B user is increased by 1BTC, and the ETH balance of the B user is decreased by 40 ETH.
The data processing method provided by the embodiment is applied to a blockchain predictor, which establishes communication connection with a local blockchain network and an external blockchain network, subscribes a market price transaction event to the local blockchain network, sends a transaction query request to a target transaction node corresponding to the market price transaction event when the market price transaction event is acquired, and calls back the local blockchain network after transaction confirmation information is acquired so as to facilitate the local blockchain network to update user data. Compared with a third-party exchange, the data related to the user transaction process is maintained and decentralized by using the local block link network, so that the safety of the data is improved, and the risk of tampering the data is effectively reduced; on the other hand, the blockchain prediction machine can interact with an external blockchain network, and the external blockchain network comprises various transaction nodes, so that cross-chain data interaction can be realized.
On the basis of the above embodiment, the market trading event includes the address of the target trading node, the hang order trading address, the market trading address, the hang order trading data, and the market trading data. On this basis, sending a transaction query request including a market trading event to a target trading node corresponding to the market trading event includes:
analyzing the address of a target trading node contained in the market trading event;
obtaining a target client according to the address of the target transaction node;
and sending a query transaction request containing market price transaction events to the target transaction node through the target client.
The block chain prediction machine mainly obtains the address of the target trading node, so that the address of the target trading node is only needed to be analyzed from the market trading event, and the efficiency is improved. In this embodiment, the data structure of the market transaction event is not limited, so the positions of the hang-order transaction data and the market transaction data in the data packet are not limited to the address of the target transaction node, the hang-order transaction address, and the market transaction address.
In other embodiments, the blockchain preplan may also parse out other parameters in the market trading event, such as the hang ticket trade address, the market trading address, the hang ticket trade data, and the market trading data, in order to mark which market trading event is. However, if the data is not processed, the data storage capacity is large, and the data is not convenient to store and search, so further, the market price transaction event further includes a transaction hash value, the transaction hash value is the address of the target transaction node, the coupon transaction address and the market price transaction address, and the coupon transaction data and the market price transaction data are obtained through hash operation. It is understood that the type of hash operation is not limited, and may be MD4, MD5, SHS, etc. The transaction hash value is data with a fixed length and can uniquely represent one data, namely uniquely represent a market transaction event, so that the transaction hash value can mark which market transaction event is, and after the block chain prediction machine obtains the confirmed transaction information, the confirmed transaction information is sent to the corresponding block chain link point, so that the block chain link point can quickly find the corresponding user data for updating.
On the basis of the above embodiment, sending confirmation transaction information to the local blockchain network to facilitate the local blockchain network to update the user data includes:
and sending trade success information, a hang-up trade address and a market price trade address to the local blockchain network, and hanging-up trade data and market price trade data so as to facilitate the local blockchain network to update the user data.
The confirmation transaction information in this embodiment represents that the target transaction node receives the transaction request of the user and responds. When the amount of data is large, the data of the local blockchain network is updated very frequently, so that the blockchain network needs to store a large amount of data and consume large resources. In view of this problem, in this embodiment, the confirmed transaction information includes transaction success information, a hang-order transaction address, a market price transaction address, hang-order transaction data, and market price transaction data, so that the local blockchain network does not need to store the hang-order transaction address and the market price transaction address, and the hang-order transaction data and the market price transaction data can obtain the user account, thereby updating the user data.
In the above embodiments, the type of the Wallet client is not limited, and the Wallet client in this embodiment is a hierarchical deterministic Wallet (HD Wallet) client. It can be understood that HD Wallet is a deterministic Wallet conforming to the rules of BIP-32, BIP-39, BIP44, and is characterized in that all currencies are managed by one private key, and the three rules are supported by the main currencies, so that HD Wallet can be easily backed up. A problem with conventional wallets is that a wallet may hold a stack of key addresses, each address having a number of bits of money. Thus, when backing up a wallet, all keys need to be backed up. But if a new address is generated later you need to be backed up once again. In fact, a backup is needed each time a new address is generated. HD Wallet allows the creation of massive numbers of subkeys from one master (root) key. This means that once the master key is controlled, all the subkeys can be generated, the master and subkeys forming a tree structure. There is no need to frequently backup wallets, only once at the time of wallet creation, and all subkeys can be subsequently recreated from the master key.
In the above, the embodiments of the data processing method applied to the blockchain predictor are described in detail, and the present application also provides an embodiment of a data processing method applied to a local blockchain network. Fig. 3 is a flowchart of another data processing method according to an embodiment of the present application. As shown in fig. 3, the method includes:
s20: and establishing a communication connection with the blockchain prediction machine, wherein the blockchain prediction machine is also in communication connection with an external blockchain network, and the external blockchain network comprises various transaction nodes.
S21: receiving a subscription of the block chain prediction machine to a market price trading event; the market price trading event is generated after the trading requests of the two wallet clients are matched and matched.
S22: when the transaction requests of the two wallet clients are matched and the transaction requests of the two wallet clients are matched, creating a market price transaction event so that the block chain prediction machine can send a transaction query request containing the market price transaction event to a target transaction node corresponding to the market price transaction event; the number of the target transaction nodes is two.
S23: and obtaining the confirmed transaction information returned by the blockchain prediction machine after obtaining the confirmed transaction information sent by the target transaction node, and updating the user data.
Since the above detailed description is made on the embodiment of the data processing method applied to the blockchain predictor, the detailed description is omitted here, and for details, refer to the above.
The data processing method provided in this embodiment is applied to a local blockchain network, and is in communication connection with a blockchain predictor, and the blockchain predictor is also in communication connection with an external blockchain network. The local blockchain network receives a subscription of the blockchain predictive machine to a market trading event. When the block chain prediction machine acquires a market price trading event, a trading inquiry request is sent to a target trading node corresponding to the market price trading event, and after the confirmed trading information is acquired, the local block chain network is called back so that the local block chain network can update user data. Compared with a third-party exchange, the data related to the user transaction process is maintained and decentralized by using the local block link network, so that the safety of the data is improved, and the risk of tampering the data is effectively reduced; on the other hand, the blockchain prediction machine can interact with an external blockchain network, and the external blockchain network comprises various transaction nodes, so that cross-chain data interaction can be realized.
In the foregoing embodiments, detailed descriptions are given for data processing methods, and the present application also provides embodiments corresponding to the data processing apparatus. It should be noted that the present application describes the embodiments of the apparatus portion from two perspectives, one is based on the functional module, and the other is based on the hardware structure.
Fig. 4 is a structural diagram of a data processing apparatus according to an embodiment of the present application, and as shown in fig. 4, the apparatus is applied to a blockchain prediction machine based on the angle of a functional module, and includes:
the communication module 10 is configured to establish a communication connection with a local blockchain network and an external blockchain network, where the external blockchain network includes a plurality of transaction nodes.
A subscription module 11, configured to subscribe to a market trading event from a local blockchain network; the market price trading event is generated after the trading requests of the two wallet clients are matched and the local block chain network matches the trading requests of the two wallet clients.
The first sending unit 12 is configured to send a transaction query request including a market trading event to a target trading node corresponding to the market trading event when the market trading event created by the local blockchain network is acquired; the number of the target transaction nodes is two.
And the second sending unit 13 is configured to send the confirmed transaction information to the local blockchain network after the confirmed transaction information sent by the target transaction node is obtained, so that the local blockchain network can update the user data.
Since the embodiments of the apparatus portion and the method portion correspond to each other, please refer to the description of the embodiments of the method portion for the embodiments of the apparatus portion, which is not repeated here.
The data processing apparatus provided in this embodiment is applied to a blockchain predictor, which establishes a communication connection with a local blockchain network and an external blockchain network, subscribes a market price transaction event to the local blockchain network, sends a transaction query request to a target transaction node corresponding to the market price transaction event when the market price transaction event is acquired, and calls back the local blockchain network after acquiring confirmed transaction information so as to facilitate updating of user data by the local blockchain network. Compared with a third-party exchange, the data related to the user transaction process is maintained and decentralized by using the local block link network, so that the safety of the data is improved, and the risk of tampering the data is effectively reduced; on the other hand, the blockchain prediction machine can interact with an external blockchain network, and the external blockchain network comprises various transaction nodes, so that cross-chain data interaction can be realized.
Fig. 5 is a structural diagram of another data processing apparatus according to an embodiment of the present application, and as shown in fig. 5, the data processing apparatus includes, in terms of a hardware structure: a memory 20 for storing a computer program; a processor 21 for implementing the steps of the data processing method as in the above embodiments when executing the computer program.
The data processing device provided by the embodiment may include, but is not limited to, a smart phone, a tablet computer, a notebook computer, or a desktop computer.
The processor 21 may include one or more processing cores, such as a 4-core processor, an 8-core processor, and the like. The processor 21 may be implemented in at least one hardware form of a DSP (Digital Signal Processing), an FPGA (Field-Programmable Gate Array), and a PLA (Programmable Logic Array). The processor 21 may also include a main processor and a coprocessor, where the main processor is a processor for Processing data in an awake state, and is also called a Central Processing Unit (CPU); a coprocessor is a low power processor for processing data in a standby state. In some embodiments, the processor 21 may be integrated with a GPU (Graphics Processing Unit), which is responsible for rendering and drawing the content required to be displayed on the display screen. In some embodiments, the processor 21 may further include an AI (Artificial Intelligence) processor for processing a calculation operation related to machine learning.
The memory 20 may include one or more computer-readable storage media, which may be non-transitory. Memory 20 may also include high speed random access memory, as well as non-volatile memory, such as one or more magnetic disk storage devices, flash memory storage devices. In this embodiment, the memory 20 is at least used for storing the following computer program 201, wherein after being loaded and executed by the processor 21, the computer program can implement the relevant steps of the data processing method disclosed in any of the foregoing embodiments. In addition, the resources stored in the memory 20 may also include an operating system 202, data 203, and the like, and the storage manner may be a transient storage manner or a permanent storage manner. Operating system 202 may include, among others, Windows, Unix, Linux, and the like. The data 203 may include, but is not limited to, the data referred to in the above embodiments.
In some embodiments, the data processing device may further include a display 22, an input/output interface 23, a communication interface 24, a power supply 25, and a communication bus 26.
Those skilled in the art will appreciate that the configuration shown in FIG. 5 does not constitute a limitation of the data processing apparatus and may include more or fewer components than those shown.
The data processing device provided by the embodiment of the application comprises a memory and a processor, and the processor can realize the steps described in the embodiment of the method when executing the program stored in the memory. Compared with a third-party exchange, the data related to the user transaction process is maintained and decentralized by using the local block chain network, so that the safety of the data is improved, and the risk of tampering the data is effectively reduced; on the other hand, the blockchain prediction machine can interact with an external blockchain network, and the external blockchain network comprises various transaction nodes, so that cross-chain data interaction can be realized.
Finally, the application also provides a corresponding embodiment of the computer readable storage medium. The computer-readable storage medium has stored thereon a computer program which, when being executed by a processor, carries out the steps as set forth in the above-mentioned method embodiments.
It is to be understood that if the method in the above embodiments is implemented in the form of software functional units and sold or used as a stand-alone product, it can be stored in a computer readable storage medium. Based on such understanding, the technical solutions of the present application may be embodied in the form of a software product, which is stored in a storage medium and executes all or part of the steps of the methods described in the embodiments of the present application, or all or part of the technical solutions. And the aforementioned storage medium includes: various media capable of storing program codes, such as a usb disk, a removable hard disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a magnetic disk, or an optical disk.
The data processing method, apparatus, and medium provided by the present application are described in detail above. The embodiments are described in a progressive manner in the specification, each embodiment focuses on differences from other embodiments, and the same and similar parts among the embodiments are referred to each other. The device disclosed by the embodiment corresponds to the method disclosed by the embodiment, so that the description is simple, and the relevant points can be referred to the method part for description. It should be noted that, for those skilled in the art, it is possible to make several improvements and modifications to the present application without departing from the principle of the present application, and such improvements and modifications also fall within the scope of the claims of the present application.
It is further noted that, in the present specification, relational terms such as first and second, and the like are used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. Also, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising an … …" does not exclude the presence of other identical elements in a process, method, article, or apparatus that comprises the element.
Claims (10)
1. A data processing method, applied to a blockchain predictor, the method comprising:
establishing a communication connection with a local blockchain network and an external blockchain network, wherein the external blockchain network comprises a plurality of transaction nodes;
subscribing to a market trading event to the local blockchain network; the market price trading event is generated after trading requests of two wallet clients are matched and the local block chain network matches the trading requests of the two wallet clients;
when a market price trading event created by the local block chain network is acquired, sending a trading inquiry request containing the market price trading event to a target trading node corresponding to the market price trading event; wherein, the number of the target trading nodes is two;
and after the confirmed transaction information sent by the target transaction node is acquired, sending the confirmed transaction information to the local blockchain network so as to facilitate the local blockchain network to update user data.
2. The data processing method according to claim 1, wherein the market trading event comprises an address of the target trading node, a hang order trading address, a market trading address, hang order trading data, and market trading data;
the sending of the transaction query request including the market trading event to the target trading node corresponding to the market trading event includes:
analyzing the address of the target trading node contained in the market trading event;
obtaining a target client according to the address of the target transaction node;
and sending a query trading request containing the market trading event to the target trading node through the target client.
3. The data processing method according to claim 2, wherein the market transaction event further includes a transaction hash value, the transaction hash value is an address of the target transaction node, the hang ticket transaction address, and the market transaction address, and the hang ticket transaction data and the market transaction data are obtained by a hash operation.
4. A data processing method according to claim 2 or 3, wherein said sending the confirmation transaction information to the local blockchain network to facilitate the local blockchain network to update user data comprises:
and sending trade successful transaction information, the hang list transaction address and the market price transaction address to the local blockchain network, wherein the hang list transaction data and the market price transaction data are convenient for the local blockchain network to update user data.
5. The data processing method of claim 1, wherein the wallet client is a hierarchical deterministic wallet client.
6. The data processing method of claim 1, wherein the plurality of transaction nodes comprises any combination of a transaction node for transacting BTC, a transaction node for transacting ETH, a transaction node for transacting EOS, and a transaction node for transacting LTC.
7. A data processing method, applied to a local blockchain network, the method comprising:
establishing a communication connection with a blockchain predictive machine, wherein the blockchain predictive machine is also in communication connection with an external blockchain network, and the external blockchain network comprises a plurality of transaction nodes;
receiving a subscription of the block chain prediction machine to a market price trading event; the market price trading event is generated after trading requests of two wallet clients are matched and matched;
when the trading requests of the two wallet clients are matched and the trading requests of the two wallet clients are matched, creating the market price trading event so that the blockchain predictor can send a trading query request containing the market price trading event to a target trading node corresponding to the market price trading event; wherein, the number of the target trading nodes is two;
and obtaining the confirmed transaction information returned by the blockchain prediction machine after obtaining the confirmed transaction information sent by the target transaction node, and updating user data.
8. A data processing method, applied to a block chain prediction machine, the apparatus comprising:
the communication module is used for establishing communication connection with a local blockchain network and an external blockchain network, wherein the external blockchain network comprises a plurality of transaction nodes;
the subscription module is used for subscribing market transaction events to the local block chain network; the market price trading event is generated after trading requests of two wallet clients are matched and the local block chain network matches the trading requests of the two wallet clients;
the system comprises a first sending unit, a second sending unit and a third sending unit, wherein the first sending unit is used for sending a transaction query request containing a market price transaction event to a target transaction node corresponding to the market price transaction event when the market price transaction event created by the local block chain network is obtained; wherein, the number of the target trading nodes is two;
and the second sending unit is used for sending the confirmed transaction information to the local blockchain network after the confirmed transaction information sent by the target transaction node is obtained so as to facilitate the local blockchain network to update user data.
9. A data processing apparatus comprising a memory for storing a computer program;
a processor for implementing the steps of the data processing method according to any one of claims 1 to 7 when executing the computer program.
10. A computer-readable storage medium, characterized in that a computer program is stored on the computer-readable storage medium, which computer program, when being executed by a processor, carries out the steps of the data processing method according to any one of claims 1 to 7.
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| CN116708464A (en) * | 2023-08-09 | 2023-09-05 | 杭州安碣信息安全科技有限公司 | De-centralized blockchain node connection management protocol method |
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| CN116708464A (en) * | 2023-08-09 | 2023-09-05 | 杭州安碣信息安全科技有限公司 | De-centralized blockchain node connection management protocol method |
| CN116708464B (en) * | 2023-08-09 | 2023-10-31 | 杭州安碣信息安全科技有限公司 | De-centralized blockchain node connection management protocol method |
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