Data processing method and device, storage medium and electronic equipment

Abstract

The embodiment of the invention provides a data processing method and device, a storage medium and electronic equipment, and the method comprises the steps: obtaining a plurality of pieces of market information data for carrying out financial transactions; splitting the multiple pieces of market information data to obtain a contract data set, a coding time data set and an encrypted transaction data set; performing parallel analysis processing on the contract data set, the coding time data set and the encrypted transaction data set, screening from the contract data set to obtain at least one piece of target contract data of the target user, and decoding the coding time data in the coding time data set to obtain actual time data, decrypting the encrypted transaction data in the encrypted transaction data group to obtain a transaction value; and splicing the target contract data and the actual time data and the transaction value corresponding to the target contract data to obtain analyzed target market data. The analysis efficiency of the market data is improved, so that longer transaction decision time can be provided for the user.

Description

Technical Field

[0001] The embodiments of the present application relate to the field of data processing technology, and in particular, to a data processing method, device, storage medium and electronic device. Background Art

[0002] Market data is a financial tool in the financial market, which is used to buy, sell, trade or settle financial assets under specific time and conditions. By analyzing market data, the changes and trends of various asset prices in the financial market can be studied and analyzed to help trading users make trading decisions.

[0003] In the trading scenario, the exchange will send all market data to users in the form of multicast. During the receiving process, users need to parse the market data and make trading decisions based on the parsing results. However, the current parsing process has a long delay. Summary of the invention

[0004] In view of this, embodiments of the present application provide a data processing method, device, storage medium, and electronic device to at least partially solve the above problems.

[0005] According to a first aspect of an embodiment of the present application, a data processing method is provided, comprising: obtaining multiple market data for conducting financial transactions, the market data comprising contract data, coded time data and encrypted transaction data; splitting the multiple market data to obtain a contract data group, a coded time data group and an encrypted transaction data group respectively; performing parallel parsing processing on the contract data group, the coded time data group and the encrypted transaction data group, screening at least one target contract data of a target user from the contract data group, decoding the coded time data in the coded time data group to obtain actual time data, and decrypting the encrypted transaction data in the encrypted transaction data group to obtain a transaction value; and splicing the target contract data and the actual time data and transaction value corresponding to the target contract data to obtain parsed target market data.

[0006] According to a second aspect of an embodiment of the present application, a data processing device is provided, comprising: an acquisition module, used to acquire multiple market data for conducting financial transactions, the market data comprising contract data, coded time data and encrypted transaction data; a splitting module, used to split the multiple market data to obtain a contract data group, a coded time data group and an encrypted transaction data group respectively; a parsing module, used to perform parallel parsing processing on the contract data group, the coded time data group and the encrypted transaction data group, screen out at least one target contract data of a target user from the contract data group, decode the coded time data in the coded time data group to obtain actual time data, and decrypt the encrypted transaction data in the encrypted transaction data group to obtain a transaction value; a splicing module, used to splice the target contract data and the actual time data and transaction value corresponding to the target contract data to obtain parsed target market data.

[0007] According to a third aspect of an embodiment of the present application, a computer storage medium is provided, on which a computer program is stored. When the program is executed by a processor, the method described in the first aspect is implemented.

[0008] According to the fourth aspect of an embodiment of the present application, there is provided an electronic device, including a processor, a memory, a communication interface and a communication bus, wherein the processor, the memory and the communication interface communicate with each other through the communication bus; the memory is used to store at least one executable instruction, and the executable instruction enables the processor to perform an operation corresponding to the method described in the first aspect.

[0009] The embodiment of the present application provides a data processing method, device, storage medium and electronic device, wherein the data processing method includes: obtaining multiple market data for financial transactions, the market data including contract data, coded time data and encrypted transaction data; splitting the multiple market data to obtain contract data group, coded time data group and encrypted transaction data group respectively; performing parallel parsing processing on the contract data group, coded time data group and encrypted transaction data group, screening at least one target contract data of the target user from the contract data group, decoding the coded time data in the coded time data group to obtain the actual time data, and decrypting the encrypted transaction data in the encrypted transaction data group to obtain the transaction value; splicing the target contract data and the actual time data and transaction value corresponding to the target contract data to obtain the parsed target market data. The present application accelerates the data parsing speed and improves the parsing efficiency of the market data by performing parallel parsing processing on the contract data, coded time data and encrypted transaction data in the market data, thereby providing users with a longer transaction decision time. BRIEF DESCRIPTION OF THE DRAWINGS

[0010] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments recorded in the embodiments of the present application. For ordinary technicians in this field, other drawings can also be obtained based on these drawings.

[0011] Figure 1 A schematic diagram of an exemplary system for a data processing method applicable to an exemplary embodiment of the present application;

[0012] Figure 2 is a flowchart of a data processing method according to an exemplary embodiment of the present application;

[0013] Figure 3 is a structural block diagram of a data processing device according to an exemplary embodiment of the present application;

[0014] Figure 4 It is a schematic structural diagram of an electronic device according to an exemplary embodiment of the present application. DETAILED DESCRIPTION

[0015] In order to enable those skilled in the art to better understand the technical solutions in the embodiments of the present application, the technical solutions in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. All other embodiments obtained by ordinary technicians in this field based on the embodiments in the embodiments of the present application should fall within the scope of protection of the embodiments of the present application.

[0016] Before describing the data processing method of the embodiment of the present application, the application scenario of the data processing method is briefly described to facilitate understanding.

[0017] Reference Figure 1 , Figure 1 The present invention is a schematic diagram of an exemplary system for a data processing method suitable for an exemplary embodiment of the present application.

[0018] An exemplary system of this embodiment may include a server, a communication network and multiple hosts. For example, in a financial transaction scenario, the server is the exchange party and the host is the user party. All market data are sent to multiple users' hosts in the form of multicast through the exchange's server. Each user's host can be coupled to an acceleration card to assist the host in data processing through the acceleration card.

[0019] The host may include any suitable type of device. For example, in some embodiments, the host may include a mobile device, a tablet computer, a laptop computer, a desktop computer, and / or any other suitable type of device.

[0020] The communication network can be any suitable combination of one or more wired and / or wireless networks. For example, the communication network can include any one or more of the following: the Internet, intranet, wide area network (Wide Area Network, WAN), local area network (Local Area Network, LAN), wireless network, digital subscriber line (Digital Subscriber Line, DSL) network, frame relay network, asynchronous transfer mode (Asynchronous Transfer Mode, ATM) network, virtual private network (Virtual Private Network, VPN) and / or any other suitable communication network. The main frame can be connected to the communication network by one or more communication links (for example, communication link), and the communication network can be linked to the server via one or more communication links (for example, communication link). The communication link can be any communication link suitable for transmitting data between the main frame and the server, such as a network link, a dial-up link, a wireless link, a hard-wired link, any other suitable communication link or any suitable combination of such links.

[0021] The accelerator card can be a dedicated data processor DPU. DPU (Data Processing Unit) is a new generation of computing chip that is data-centric, I / O intensive, and uses software-defined technology to support infrastructure resource layer virtualization. It has the capabilities of improving computing system efficiency, reducing the total cost of ownership of the overall system, improving data processing performance, and reducing performance losses of other computing chips.

[0022] The accelerator card can be plugged into the host through the PCIE slot to connect the accelerator card to the host. PCIE refers to PCI-Express, a bus and interface standard. The accelerator card and the host can transmit data through PCIE.

[0023] The data processing method of this embodiment can be used in the aforementioned host or accelerator card, and this embodiment does not limit this. When the data processing method of this embodiment is applied to the accelerator card, it can save the computing resources of the user's host and improve the data processing efficiency.

[0024] When users receive market data, they need to parse the market data so as to make trading decisions based on the parsing results. However, the current parsing process has a long delay. In view of this, the embodiments of the present application provide a data processing method, device, storage medium and electronic device to solve the above technical problems.

[0025] Reference Figure 2, shows a flow chart of steps of a data processing method according to an exemplary embodiment of the present application. As shown in the figure, this embodiment mainly includes the following steps:

[0026] S202: Acquire a plurality of market data for conducting financial transactions.

[0027] Exemplarily, the market data includes contract data, encoded time data and encrypted transaction data. Among them, the contract data may include a contract number, a contract string, etc. The multiple contract data may include one or more target contract data of the target user, and the target contract data may be the contract data subscribed by the target user. The encoded time data may be obtained by encoding the sending time of the market data, such as Ascll encoding. The encrypted transaction data may be obtained by encrypting the transaction value.

[0028] In some optional embodiments, obtaining multiple market data for conducting financial transactions includes: obtaining a target market data packet, the target market data packet including a target sequence number and multiple market data; if the target sequence number of the target market data packet is greater than a preset sequence number, and the difference between the target sequence number and the preset sequence number is less than a preset threshold, then outputting multiple market data.

[0029] Exemplarily, the preset sequence number may be the maximum sequence number of the market data package stored locally, and the preset threshold value may be flexibly set by a person skilled in the art according to actual conditions, such as 1000, and this embodiment does not limit this. After receiving the target market data package, it is determined whether the target sequence number of the target market data package is greater than the preset sequence number, and the difference between the target sequence number and the preset sequence number is less than the preset threshold value. If so, the target market data package is output to obtain multiple market data.

[0030] In this embodiment, by judging the received target market data packet, the accuracy of the received market data can be guaranteed, and the reception of erroneous data that affects subsequent processing can be avoided.

[0031] In some optional embodiments, obtaining a target market data packet includes: receiving multiple market data packets, the market data packets including sequence numbers; and determining a market data packet with a largest sequence number among the multiple market data packets as a target market data packet.

[0032] Exemplarily, taking the data processing method of the present embodiment applied to an accelerator card as an example, one or more data receiving ports can be set on the accelerator card, and each data receiving port can be enabled by configuring an enable flag. When receiving market data, if only one data receiving port can receive data, the market data packet received by the data receiving port is used as the target market data packet. If multiple data receiving ports can receive market data packets at the same time, that is, the accelerator card can receive multiple market data packets, wherein the content of each market data packet is the same. In this regard, in order to reduce the subsequent data processing amount, when receiving multiple market data packets, the serial numbers in the market data packets can be compared, and the market data packet with the largest serial number can be determined as the target market data packet.

[0033] In this embodiment, when multiple market data packets are received, the market data packet with the largest serial number in the multiple market data packets is determined as the target market data packet by comparing the serial numbers in the market data packets, thereby ensuring that the received market data packet is the latest data. In addition, by screening the multiple market data packets, data redundancy can be reduced, the amount of computation for subsequent data processing can be reduced, and data processing efficiency can be improved.

[0034] In some optional embodiments, after receiving multiple market data packets, the method of this embodiment also includes: filtering the multiple market data packets according to preset filtering conditions to obtain at least one filtered market data packet, and the preset filtering conditions include the target data packet type, target data length and target identification information of the market data packet.

[0035] Exemplarily, when receiving multiple market data packets, the multiple market data packets can also be screened according to preset screening conditions to determine whether the data packet type of the market data packet is the target data packet type, whether the data length of the market data packet reaches the target data length, and whether the market data packet contains target identification information, etc. The target data packet type can include an IPV4 data packet and a UDP data packet, and the target identification information can include a market data flag.

[0036] In this embodiment, multiple market data packets are screened by preset screening conditions, so that invalid data packets can be screened out, thereby improving the accuracy of receiving data packets.

[0037] S204, splitting the multiple market data to obtain a contract data group, a coding time data group and an encrypted transaction data group respectively.

[0038] Exemplarily, the contract data, coded time data and encrypted transaction data in each market data are split, and all the contract data obtained by splitting are divided into contract data groups, all the coded time data obtained by splitting are divided into coded time data groups, and all the encrypted transaction data obtained by splitting are divided into encrypted transaction data groups. The contract data, coded time data and encrypted transaction data split from each market data can carry the same identifier for subsequent splicing.

[0039] S206. Perform parallel parsing processing on the contract data group, the coded time data group and the encrypted transaction data group, filter out at least one target contract data of the target user from the contract data group, decode the coded time data in the coded time data group to obtain the actual time data, and decrypt the encrypted transaction data in the encrypted transaction data group to obtain the transaction value.

[0040] Exemplarily, the contract data group, the coded time data group, and the encrypted transaction data group can be parsed and processed in parallel, the contract data in the contract data group can be calculated according to the pre-acquired target hash function to obtain the hash value corresponding to each contract data, and then the target contract data can be screened from the contract data group according to the contract data, the hash value, and the pre-acquired target hash list of the target user. The coded time data in the coded time data group can be decoded to obtain the actual time data, such as the time value. The encrypted transaction data in the encrypted transaction data group can be decrypted according to the pre-configured key to obtain the transaction value, which can be a floating point number.

[0041] In some optional embodiments, at least one target contract data of a target user is screened from a contract data group, including: calculating the contract data in the contract data group according to a pre-acquired target hash function to obtain a hash value corresponding to each contract data; the hash value corresponding to each contract data includes at least one target hash value corresponding to at least one target contract data, and at least one target hash value is different; determining the target contract data in the contract data group according to the contract data, the hash value and a pre-acquired target hash list, the target hash list including multiple target contract data and target hash values ​​corresponding to the target contract data.

[0042] Exemplarily, a hash function is a function that maps input data of any length to output data of a fixed length. A target hash function may be pre-constructed, and the target hash function may be:

[0043] Hash (s) =s0+s1*p+s2*p 2 +…+s n-1 *p n-1 mod m

[0044] Among them, si Represents the i+1th character in the contract data, i=0,1,2…n-1; p is the coefficient, and m is the size of the hash table mapped by the target hash function.

[0045] By calculating multiple contract data separately through the target hash function, the hash value corresponding to each contract data can be obtained. For example, if the contract data includes the string HO2310-C-2500, the calculated hash value is 816d; if the contract data includes the string HO2310-P-2450, the calculated hash value is c160.

[0046] The target hash function is used to calculate multiple contract data respectively to obtain multiple corresponding hash values. Since the multiple contract data include one or more target contract data, the multiple hash values ​​include one or more target hash values. When the multiple contract data include multiple target contract data, the multiple target hash values ​​corresponding to the multiple target contract data are all different, that is, the target hash function is used to calculate the multiple target contract data respectively, and the corresponding multiple different target hash values ​​can be obtained. Here, when the target hash function is used to calculate multiple contract data, it can be ensured that there is no hash conflict when calculating multiple target contract data, that is, the multiple target hash values ​​obtained are different, thereby avoiding hash conflicts for multiple target contract data in the subsequent processing process and improving data processing efficiency.

[0047] Finally, multiple hash values ​​can be matched one by one with the target hash value in the target hash list. If the match is successful, it means that the contract data corresponding to the hash value is the target contract data. Furthermore, the contract data corresponding to the successfully matched hash value can be matched with the target contract data in the target hash table. If the match is successful, it means that the contract data corresponding to the hash value is the target contract data.

[0048] In an optional implementation, the pre-acquired target hash function is obtained in the following manner: based on all target contract data of the target user and a preset coefficient set, the preset hash function is iteratively calculated to determine the target coefficient from the preset coefficient set; based on the target coefficient and the preset hash function, the target hash function is determined; wherein, by calculating all target contract data of the target user through the target hash function, all target hash values ​​obtained are different.

[0049] Exemplarily, the preset coefficient set may be a list including multiple p values, and the p value list may be 20,000 prime numbers starting from 3. The preset hash function is the above-mentioned pre-constructed hash function, in which the coefficient is not determined. By iteratively enumerating the p values ​​in the p value list, the hash values ​​of all target contract data are calculated respectively: when a hash conflict occurs, the iteration of the p value of this round is stopped, the next p value is selected, and so on, until a p value without hash conflict is found. The specific process is as follows: select a coefficient p value from the preset coefficient set and substitute it into the preset hash function, initialize the contract list and hash table containing all target contract data of the target user, and calculate the target contract data in the contract list one by one. During the calculation process, if a hash conflict occurs, that is, the target hash values ​​corresponding to the two target contract data are the same, then select a coefficient p value from the preset coefficient set again, and calculate the target contract data in the contract list one by one again, and repeat the above process until the target coefficient p value is found, so that all the calculated target hash values ​​are different. Substituting the target coefficient into the preset hash function, the target hash function can be obtained.

[0050] In this implementation, the preset hash function is iteratively calculated based on all the target contract data of the target user and the preset coefficient set, and the target coefficient is determined from the preset coefficient set; the target hash function is determined based on the target coefficient and the preset hash function, which can ensure that when the target hash function is used to calculate multiple target contract data of the target user, there is no hash conflict, that is, the multiple target hash values ​​obtained are different, thereby avoiding hash conflicts for multiple target contract data in the subsequent processing process and improving data processing efficiency. In addition, the coefficients of the target hash function have been calculated in advance, so they can be directly applied without calculating the coefficients of the target hash function during operation, reducing the amount of calculation during the operation process and reducing processing delays.

[0051] In some optional embodiments, target contract data in a contract data group is determined based on contract data, hash values, and a pre-acquired target hash list, including: matching multiple hash values ​​with multiple target hash values ​​in a pre-acquired target hash list respectively; determining whether there is an identical first hash value among multiple first hash values ​​that have successfully matched; if there is no identical first hash value, determining the contract data corresponding to the first hash value as the target contract data.

[0052] Exemplarily, after obtaining multiple hash values ​​by calculating using the target hash function, the multiple hash values ​​are respectively matched with the multiple target hash values ​​in the pre-acquired target hash list to obtain multiple successfully matched first hash values; further, it can be determined whether there is an identical first hash value among the multiple successfully matched first hash values. If there is no identical first hash value, the contract data corresponding to the first hash value can be directly determined as the target contract data.

[0053] Since there is no hash conflict in the target hash value calculated by the target hash function for the target contract data, there may be a hash conflict between the hash value corresponding to the non-target contract data in multiple contract data and the hash value corresponding to the target contract data. In this implementation, by determining whether there is an identical first hash value among the multiple first hash values ​​that have successfully matched, if there is no identical first hash value, the contract data corresponding to the first hash value is determined as the target contract data, thereby avoiding hash conflicts caused by the above situation and further avoiding misjudgment of the target contract data due to hash conflicts.

[0054] In some optional embodiments, the method of this embodiment also includes: if there is an identical first hash value, comparing the contract data corresponding to the identical first hash value that has been successfully matched with the target contract data corresponding to the target hash value; and determining the contract data in the identical first hash value that is consistent with the target contract data as the target contract data.

[0055] Exemplarily, if the same first hash value exists among multiple first hash values ​​that are successfully matched, that is, there is a hash conflict between the hash value corresponding to the non-target contract data in the contract data and the hash value corresponding to the target contract data, the contract data corresponding to the same first hash value that is successfully matched can be further compared with the target contract data corresponding to the target hash value, and the contract data that is consistent with the target contract data in the same first hash value is determined as the target contract data. Here, the contract data can include a contract string and a contract number. During the comparison process, the contract strings can be compared to see if they are consistent. For example, the first hash values ​​corresponding to the contract strings HO2310-P-2500 and HO2310-P-2475 are both 0x247a, and the target contract string corresponding to the target hash value 0x247a is HO2310-P-2500. After comparison, it can be determined that the contract data containing the contract string HO2310-P-2500 is the target contract data. Furthermore, the contract numbers may be compared to see if they are consistent. When the contract number and the contract character string in the contract data are both compared to be consistent, the contract data is determined to be the target contract data.

[0056] In the present embodiment, when a hash conflict occurs between the hash value corresponding to the non-target contract data in the contract data and the hash value corresponding to the target contract data, the contract data corresponding to the same first hash value that has been successfully matched can be further compared with the target contract data corresponding to the target hash value, and then the contract data with the same first hash value that is consistent with the target contract data can be determined as the target contract data, thereby avoiding hash conflicts caused by the above situation and further avoiding misjudgment of the target contract data due to hash conflicts; in addition, only comparing the contract data corresponding to the same first hash value with the target contract data corresponding to the target hash value can reduce the amount of data processed, improve data processing efficiency, and reduce data processing delay.

[0057] S208: splice the target contract data and the actual time data and transaction value corresponding to the target contract data to obtain the parsed target market data.

[0058] Exemplarily, based on the target contract data, the actual time data and transaction values ​​corresponding to the target contract data are screened out from all the actual time data and transaction values ​​obtained, and then the target contract data and the actual time data and transaction values ​​corresponding to the target contract data are spliced ​​to obtain the parsed target market data.

[0059] This embodiment splits multiple market data to obtain contract data groups, coded time data groups and encrypted transaction data groups respectively; performs parallel parsing processing on the contract data groups, coded time data groups and encrypted transaction data groups, selects at least one target contract data of the target user from the contract data group, decodes the coded time data in the coded time data group to obtain the actual time data, and decrypts the encrypted transaction data in the encrypted transaction data group to obtain the transaction value; splices the target contract data and the actual time data and transaction value corresponding to the target contract data to obtain the parsed target market data. This application speeds up the data parsing speed and improves the parsing efficiency of the market data by performing parallel parsing processing on the contract data, coded time data and encrypted transaction data in the market data, thereby providing users with a longer transaction decision time.

[0060] Reference Figure 3 , shows a structural block diagram of a data processing device according to an exemplary embodiment of the present application.

[0061] The data processing device of this embodiment includes an acquisition module 302, a splitting module 304, a parsing module 306 and a splicing module 308. The acquisition module 302 is used to acquire multiple market data for financial transactions, the market data including contract data, coded time data and encrypted transaction data; the splitting module 304 is used to split the multiple market data to obtain a contract data group, a coded time data group and an encrypted transaction data group respectively; the parsing module 306 is used to perform parallel parsing processing on the contract data group, the coded time data group and the encrypted transaction data group, screen at least one target contract data of the target user from the contract data group, decode the coded time data in the coded time data group to obtain the actual time data, and decrypt the encrypted transaction data in the encrypted transaction data group to obtain the transaction value; the splicing module 308 is used to splice the target contract data and the actual time data and transaction value corresponding to the target contract data to obtain the parsed target market data.

[0062] In some optional embodiments, the acquisition module 302 is also used to: acquire a target market data packet, the target market data packet including a target serial number and multiple market data; if the target serial number of the target market data packet is greater than a preset serial number, and the difference between the target serial number and the preset serial number is less than a preset threshold, then output multiple market data.

[0063] In some optional embodiments, the acquisition module 302 is further used to: receive multiple market data packets, the market data packets including sequence numbers; and determine the market data packet with the largest sequence number among the multiple market data packets as the target market data packet.

[0064] In some optional embodiments, the acquisition module 302 is further used to filter multiple market data packets according to preset filtering conditions to obtain at least one filtered market data packet, wherein the preset filtering conditions include the target data packet type, target data length and target identification information of the market data packet.

[0065] In some optional embodiments, the parsing module 306 is also used to: calculate the contract data in the contract data group according to a pre-acquired target hash function to obtain a hash value corresponding to each contract data; the hash value corresponding to each contract data includes at least one target hash value corresponding to at least one target contract data, and at least one target hash value is different; determine the target contract data in the contract data group according to the contract data, the hash value and a pre-acquired target hash list, the target hash list including multiple target contract data and target hash values ​​corresponding to the target contract data.

[0066] In some optional embodiments, the parsing module 306 is also used to: respectively match multiple hash values ​​with multiple target hash values ​​in a pre-acquired target hash list; determine whether there is an identical first hash value among the multiple first hash values ​​that successfully match; if there is no identical first hash value, determine the contract data corresponding to the first hash value as the target contract data.

[0067] In some optional embodiments, the parsing module 306 is also used to: if there is an identical first hash value, compare the contract data corresponding to the identical first hash value that has been successfully matched with the target contract data corresponding to the target hash value; and determine the contract data in the identical first hash value that is consistent with the target contract data as the target contract data.

[0068] The data processing device of this embodiment is used to implement the corresponding data processing methods in the aforementioned multiple method embodiments, and has the beneficial effects of the corresponding method embodiments, which will not be described in detail here. In addition, the functional implementation of each module in the data processing device of this embodiment can refer to the description of the corresponding parts in the aforementioned method embodiments, which will not be described in detail here.

[0069] Reference Figure 4 , shows a schematic diagram of the structure of an electronic device according to an exemplary embodiment of the present application. The specific embodiment of the present invention does not limit the specific implementation of the electronic device.

[0070] like Figure 4 As shown, the electronic device may include: a processor (processor) 401 , a memory (memory) 403 , a communication bus 404 , and a communication interface (Communications Interface) 405 .

[0071] Wherein: the processor 401 , the memory 403 and the communication interface 405 communicate with each other via the communication bus 404 .

[0072] The communication interface 405 is used to communicate with other electronic devices or servers.

[0073] The processor 401 is used to execute the program 402, and specifically can execute the steps of any data processing method in the above embodiments.

[0074] Specifically, the program 402 may include program codes, which include computer operation instructions.

[0075] The processor 401 may be a central processing unit (CPU), or an application-specific integrated circuit (ASIC), or one or more integrated circuits configured to implement the embodiments of the present application. The one or more processors included in the smart device may be processors of the same type, such as one or more CPUs; or processors of different types, such as one or more CPUs and one or more ASICs.

[0076] The memory 403 is used to store the program 402. The memory 403 may include a high-speed RAM memory, and may also include a non-volatile memory (non-volatile memory), such as at least one disk memory.

[0077] The program 402 can be specifically used to enable the processor 401 to execute the steps of any data processing method described in the embodiment. The specific implementation of each step in the program 402 can refer to the corresponding description of the steps and units executed by any data processing method in the above steps, which will not be repeated here. Those skilled in the art can clearly understand that for the convenience and simplicity of description, the specific working process of the above-described devices and modules can refer to the corresponding process description in the aforementioned method embodiment.

[0078] An embodiment of the present application further provides a computer storage medium on which a computer program is stored. When the program is executed by a processor, the data processing method described in any one of the above-mentioned method embodiments is implemented.

[0079] An embodiment of the present application also provides a computer program product, including computer instructions, which instruct a computing device to execute operations corresponding to the data processing method described in any one of the above-mentioned multiple method embodiments.

[0080] It should be pointed out that, according to the needs of implementation, the various components / steps described in the embodiments of the present application can be split into more components / steps, or two or more components / steps or partial operations of components / steps can be combined into new components / steps to achieve the purpose of the embodiments of the present application.

[0081] The above-mentioned method according to the embodiment of the present application can be implemented in hardware, firmware, or implemented as software or computer code that can be stored in a recording medium (such as a CD ROM, RAM, floppy disk, hard disk or magneto-optical disk), or implemented as a computer code originally stored in a remote recording medium or a non-temporary machine-readable medium downloaded through a network and to be stored in a local recording medium, so that the method described herein can be stored in such software processing on a recording medium using a general-purpose computer, a special-purpose processor or programmable or special-purpose hardware (such as an ASIC or FPGA). It can be understood that a computer, a processor, a microprocessor controller or programmable hardware includes a storage component (e.g., RAM, ROM, flash memory, etc.) that can store or receive software or computer code, and when the software or computer code is accessed and executed by a computer, a processor or hardware, the method described herein is implemented. In addition, when a general-purpose computer accesses the code for implementing the method shown here, the execution of the code converts the general-purpose computer into a special-purpose computer for executing the method shown here.

[0082] Those of ordinary skill in the art will appreciate that the units and method steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of the embodiments of the present application.

[0083] The above implementation methods are only used to illustrate the embodiments of the present application, and are not limitations on the embodiments of the present application. Ordinary technicians in the relevant technical field can make various changes and modifications without departing from the spirit and scope of the embodiments of the present application. Therefore, all equivalent technical solutions also belong to the scope of the embodiments of the present application. The scope of patent protection of the embodiments of the present application should be limited by the claims.

Claims

1. A data processing method, characterized in that: include: Acquiring a plurality of market data for conducting financial transactions, the market data comprising contract data, encoded time data, and encrypted transaction data; Splitting the plurality of market data to obtain a contract data group, a coding time data group and an encrypted transaction data group respectively; Performing parallel parsing processing on the contract data group, the coded time data group and the encrypted transaction data group, screening out at least one target contract data of a target user from the contract data group, decoding the coded time data in the coded time data group to obtain actual time data, and decrypting the encrypted transaction data in the encrypted transaction data group to obtain a transaction value; The target contract data and the actual time data and the transaction value corresponding to the target contract data are spliced ​​to obtain the parsed target market data.

2. The data processing method according to claim 1, characterized in that: The obtaining of a plurality of market data for conducting financial transactions includes: Acquire a target market data packet, wherein the target market data packet includes a target sequence number and a plurality of market data; If the target sequence number of the target market data packet is greater than a preset sequence number, and the difference between the target sequence number and the preset sequence number is less than a preset threshold, the plurality of market data are output.

3. The data processing method according to claim 2, characterized in that: The step of obtaining a target market data packet includes: receiving multiple market data packets, wherein the market data packets include sequence numbers; The market data packet with the largest sequence number among the multiple market data packets is determined as the target market data packet.

4. The data processing method according to claim 3, characterized in that: After receiving the multi-channel market data packets, the method further includes: The multiple market data packets are screened according to preset screening conditions to obtain at least one screened market data packet, wherein the preset screening conditions include a target data packet type, a target data length, and a target identification information of the market data packet.

5. The data processing method according to claim 1, characterized in that: The step of screening the contract data group to obtain at least one target contract data of the target user includes: The contract data in the contract data group are calculated according to the pre-acquired target hash function to obtain hash values ​​corresponding to each of the contract data; the hash values ​​corresponding to each of the contract data include at least one target hash value corresponding to the at least one target contract data, and the at least one target hash value is different; The target contract data in the contract data group is determined according to the contract data, the hash value and a pre-acquired target hash list, wherein the target hash list includes multiple target contract data and target hash values ​​corresponding to the target contract data.

6. The data processing method according to claim 2, characterized in that: The step of determining the target contract data in the contract data group according to the contract data, the hash value and the pre-acquired target hash list includes: Respectively matching the plurality of hash values ​​with a plurality of target hash values ​​in a pre-acquired target hash list; Determine whether there is an identical first hash value among the multiple first hash values ​​that successfully match; If the same first hash value does not exist, the contract data corresponding to the first hash value is determined as the target contract data.

7. The data processing method according to claim 3, characterized in that: The method further comprises: If there is an identical first hash value, the contract data corresponding to the identical first hash value that matches successfully is compared with the target contract data corresponding to the target hash value; The contract data among the same first hash values ​​that is consistent with the target contract data is determined as the target contract data.

8. A data processing device, characterized in that: include: An acquisition module, used to acquire a plurality of market data for conducting financial transactions, wherein the market data includes contract data, coded time data and encrypted transaction data; A splitting module, used to split the multiple market data to obtain a contract data group, a coding time data group and an encrypted transaction data group respectively; a parsing module, configured to perform parallel parsing processing on the contract data group, the coded time data group and the encrypted transaction data group, screen the contract data group to obtain at least one target contract data of the target user, decode the coded time data in the coded time data group to obtain the actual time data, and decrypt the encrypted transaction data in the encrypted transaction data group to obtain the transaction value; The splicing module is used to splice the target contract data and the actual time data and the transaction value corresponding to the target contract data to obtain the parsed target market data.

9. An electronic device, characterized in that: include: A processor, a memory, a communication interface and a communication bus, wherein the processor, the memory and the communication interface communicate with each other via the communication bus; The memory is used to store at least one executable instruction, and the executable instruction enables the processor to perform an operation corresponding to the method according to any one of claims 1 to 7.

10. A computer storage medium having a computer program stored thereon, characterized in that: When the program is executed by a processor, the method according to any one of claims 1 to 7 is implemented.

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