An order message processing method, device, equipment and medium
By using a pre-set stress testing tool to determine random dates and random strings during order testing, the problems of high concurrency and accurate data entry in order testing were solved, and efficient order message processing was achieved.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Patents(China)
- Current Assignee / Owner
- 杭州右文网络科技有限公司
- Filing Date
- 2023-02-20
- Publication Date
- 2026-05-12
AI Technical Summary
During order testing, existing technologies struggle to handle high-concurrency message sending and accurate order storage, resulting in high data verification costs.
By using a pre-set stress testing tool, a random date and random string are determined for the order message. Based on these random values, a time variable value and a random number are determined and stored as variables in the order message body. The message is then sent to the consumer to achieve high concurrency and accurate data storage.
It enables high-concurrency processing and accurate data entry of order messages, reducing data verification costs.
Smart Images
Figure CN116166517B_ABST
Abstract
Description
Technical Field
[0001] This invention relates to the field of testing, and in particular to an order message processing method, apparatus, device, and medium. Background Technology
[0002] During order testing, testers often need a large amount of order data, but manually sending MQ (Message Queue) messages requires too much configuration information and cannot quickly achieve high concurrency. Secondly, when placing an order, it is difficult for testers to know the location of the order in the database after the MQ message is sent, which increases the data verification cost during subsequent data verification.
[0003] Therefore, improving message sending efficiency and achieving accurate order placement during order testing are problems that need to be solved in this field. Summary of the Invention
[0004] In view of this, the purpose of this invention is to provide an order message processing method, apparatus, device, and medium that can guarantee high concurrency of order message sources and achieve accurate order storage in the subsequent database. The specific solution is as follows:
[0005] Firstly, this application discloses an order message processing method, including:
[0006] The random date and random string corresponding to the order message are determined using a preset stress testing tool; the order message is an MQ message sent by the producer in the preset message subscription tool.
[0007] The time variable value corresponding to the order message is determined based on the random date, and the random number corresponding to the order message is determined based on the random string;
[0008] The time variable value and the random number are stored as variables in the message body of the order message, and the order message is sent to the consumer so that the consumer can consume the order message and place it in the target table of the target database; wherein, the target database is determined based on the time variable value, and the target table in the target database is determined based on the random number.
[0009] Optionally, the step of using a preset stress testing tool to determine the random date and random string corresponding to the order message; the MQ message sent by the producer in the preset message subscription tool for the order message includes:
[0010] The random date and random string corresponding to the order message are determined using Jemter; the order message is an MQ message sent by a producer in Kafka.
[0011] Optionally, before determining the random date and random string corresponding to the order message using a preset stress testing tool, the method further includes:
[0012] The custom Kafka address, message topic, and message sending data are packaged into a JAR file using a preset development tool, and the JAR file is then imported into a preset stress testing tool.
[0013] Optionally, before determining the random date and random string corresponding to the order message using a preset stress testing tool, the method further includes:
[0014] Define a Kafka producer object and add configuration information to the producer object;
[0015] Create a producer object and call the send method to send the order message using the producer object.
[0016] Optionally, the step of using a preset stress testing tool to determine the random date and random string corresponding to the order message includes:
[0017] The random date and random string corresponding to the order message are determined using the preset random generation method in the preset stress testing tool.
[0018] Optionally, determining the random number corresponding to the order message based on the random string includes:
[0019] The remainder result of the random string is determined using a hash modulo algorithm, and the remainder result is used as the random number corresponding to the order message.
[0020] Optionally, determining the time variable value corresponding to the order message based on the random date includes:
[0021] The time variable value corresponding to the order message is determined by using the random date according to a pre-set rule based on the month to which the order placement time in the order message belongs.
[0022] Secondly, this application discloses an order message processing apparatus, comprising:
[0023] The message processing module is used to determine the random date and random string corresponding to the order message using a preset stress testing tool; the order message is a MQ message sent by the producer in the preset message subscription tool;
[0024] The data determination module is used to determine the time variable value corresponding to the order message based on the random date, and to determine the random number corresponding to the order message based on the random string;
[0025] The message sending module is used to store the time variable value and the random number as variables in the message body of the order message, and send the order message to the consumer so that the consumer can consume the order message and place it in the target table of the target database; wherein, the target database is determined based on the time variable value, and the target table in the target database is determined based on the random number.
[0026] Thirdly, this application discloses an electronic device, including:
[0027] Memory, used to store computer programs;
[0028] A processor is used to execute the computer program to implement the aforementioned order message processing method.
[0029] Fourthly, this application discloses a computer storage medium for storing a computer program; wherein, when the computer program is executed by a processor, it implements the steps of the aforementioned disclosed order message processing method.
[0030] This application first uses a preset stress testing tool to determine the random date and random string corresponding to the order message; the order message is an MQ message sent by a producer in a preset message subscription tool; based on the random date, a time variable value corresponding to the order message is determined, and based on the random string, a random number corresponding to the order message is determined; the time variable value and the random number are stored as variables in the message body of the order message, and the order message is sent to the consumer so that the consumer can consume the order message and place it in the target table of the target database; wherein, the target database is determined based on the time variable value, and the target table in the target database is determined based on the random number. In this way, after obtaining the MQ message produced by the producer, this invention uses a preset stress testing tool to determine the random date and random string corresponding to the order message, determines the time variable value and random number based on the random date and random string, and stores the time variable value and random number as variables in the message body of the order message. Subsequently, when performing order entry into the database, the order can be accurately entered into the database based on the time variable value and the random number. This invention utilizes the producer's production of order messages to ensure the acquisition of a large number of order messages. At the same time, the method of this invention can complete high-concurrency processing of order entry and ensure accurate order entry, reducing data verification costs. Attached Figure Description
[0031] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on the provided drawings without creative effort.
[0032] Figure 1 A flowchart of an order message processing method provided in this application;
[0033] Figure 2 A flowchart illustrating a specific order message processing method provided in this application;
[0034] Figure 3 A schematic diagram of an order message processing device provided in this application;
[0035] Figure 4 This application provides a structural diagram of an electronic device. Detailed Implementation
[0036] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.
[0037] In existing technologies, testers often need large amounts of order data during order testing. However, manually sending MQ messages requires too much configuration information and cannot quickly achieve high concurrency. Secondly, when placing an order, testers often find it difficult to know the order's location in the database after the MQ message is sent, increasing data verification costs later. This application guarantees high concurrency for order message sources and ensures accurate order storage in the database.
[0038] This invention discloses an order message processing method, see [link to relevant documentation]. Figure 1 The method includes:
[0039] Step S11: Use a preset stress test tool to determine the random date and random string corresponding to the order message.
[0040] In this embodiment, the order message is an MQ message sent by a producer in a preset message subscription tool. The preset stress testing tool is preferably Jemter, and the preset message subscription tool is preferably Kafka. In a specific implementation, using a producer in Kafka to produce and send MQ messages in JSON (JavaScript Object Notation) format ensures high concurrency of the data source and eliminates the need for manually writing JSON-formatted order messages, thus guaranteeing efficient message generation. In this specific implementation, batch MQ messages can be obtained, and Jemter can be used to determine the random date and random string corresponding to each order message in the batch MQ messages.
[0041] In a specific implementation of this embodiment, before determining the random date and random string corresponding to the order message using a preset stress testing tool, the process may further include: using a preset development tool to package a custom Kafka address, message topic, and the sending data in the message into a Jar file, and then importing the Jar file into the preset stress testing tool. Preferably, the preset development tool is IDEA. That is, during the testing process of this embodiment, we need to simulate a third-party platform pushing a large number of order messages via MQ. To ensure high-quality, non-repeating MQ messages, we encapsulate the producer sending MQ messages into a Jar file usable by Jemter using the IDEA tool, and reference it in Jemter. It can be understood that by extending Jemter through referencing the Jar file in this invention, high-concurrency order processing can be achieved.
[0042] In this embodiment, before determining the random date and random string corresponding to the order message using a preset stress testing tool, the process may further include: defining a Kafka producer object and adding configuration information to the producer object; creating the producer object and calling the `send` method to send the order message using the producer object. When creating the producer object, we can configure IP (Intellectual Property) address, key, value, and other configuration information. Correspondingly, when the producer subsequently produces order messages, the sent key and value can be serialized into corresponding byte arrays. In a specific implementation, the order message produced by the producer is in JSON format, and the `send` method is called to publish it after generating the JSON format order message.
[0043] Through the above steps, this invention can achieve high concurrency in sending MQ messages by generating a custom MQ JAR file and providing it to the jetter for reference.
[0044] In this embodiment, determining the random date and random string corresponding to the order message using a preset stress testing tool may include: determining the random date and random string corresponding to the order message using a preset random generation method in the preset stress testing tool. In a specific implementation, the preset random generation method in this embodiment may be the RandomString method. Users can predefine the character length of the subsequently generated random string and random date in the RandomString method of Jemter, thus generating a random string and random date of a specified length.
[0045] Step S12: Determine the time variable value corresponding to the order message based on the random date, and determine the random number corresponding to the order message based on the random string.
[0046] In this step, the time variable value corresponding to the order message is determined based on the random date, and the random number corresponding to the order message is determined based on the random string. The time variable value and the random number correspond to the database and the data table in the database when the order is subsequently entered into the warehouse. In the future, when the order is entered into the warehouse, the order can be accurately entered into the warehouse based on the time variable value and the random number.
[0047] In addition, in this embodiment, after obtaining the batch of MQ messages, the corresponding random number and time variable value can be determined based on the random string and random time of each message to achieve high-concurrency message processing.
[0048] Step S13: Store the time variable value and the random number as variables in the message body of the order message, and send the order message to the consumer so that the consumer can consume the order message and place it in the target table of the target database; wherein, the target database is determined based on the time variable value, and the target table in the target database is determined based on the random number.
[0049] In this embodiment, the number of threads can be set to store the time variable value and the random number as variables in the value field of the message body in the order message. The order can then fall into the target database corresponding to the time variable value and accurately fall into the data table corresponding to the random number in the target database.
[0050] In this embodiment, a preset stress testing tool is first used to determine the random date and random string corresponding to the order message. The order message is an MQ message sent by a producer in a preset message subscription tool. A time variable value corresponding to the order message is determined based on the random date, and a random number corresponding to the order message is determined based on the random string. The time variable value and the random number are stored as variables in the message body of the order message, and the order message is sent to the consumer so that the consumer can consume the order message and place it in the target table of the target database. The target database is determined based on the time variable value, and the target table in the target database is determined based on the random number. Thus, after obtaining the MQ message produced by the producer, this invention uses a preset stress testing tool to determine the random date and random string corresponding to the order message, determines the time variable value and random number based on the random date and random string, and stores the time variable value and random number as variables in the message body of the order message. Subsequently, when performing order entry into the database, the order can be accurately entered into the database based on the time variable value and the random number. In this embodiment, the method of using producers to generate order messages can ensure the acquisition of a large number of order messages. At the same time, the method of the present invention can complete high-concurrency processing of order entry and ensure accurate order entry, reducing data verification costs.
[0051] Figure 2 A flowchart illustrating a specific order message processing method provided in this application embodiment. See also... Figure 2 As shown, the method includes:
[0052] Step S21: Use Jemter to determine the random date and random string corresponding to the order message; the order message is an MQ message sent by the producer in Kafka.
[0053] For a more detailed description of the process of step S21, please refer to the relevant content disclosed in the foregoing embodiments, which will not be repeated here.
[0054] Step S22: Using the random date, determine the time variable value corresponding to the order message according to the pre-set rule of determining the random date of the order message based on the month to which the order placement time in the order message belongs, and use the hash modulo algorithm to determine the modulo result of the random string, and determine the modulo result as the random number corresponding to the order message.
[0055] In this embodiment, when determining the time variable value, it is preferable to use a rule that determines the random date of the order message based on the month to which the order placement time belongs in the order message. Specifically, the month of the order placement time in the order message can be determined and stored in a preset variable `time`. In a specific implementation, the time variable value takes on 12 values corresponding to each of the 12 months. When batch processing MQ messages, classification can be achieved by extracting dates. For example, the time variable value of order messages with order placement times between 2022-10-01 and 2022-10-31 can be determined as 10 and stored in the variable `time`.
[0056] In this embodiment, a hash modulo algorithm is preferably used to determine the random number. Specifically, the hash modulo algorithm is used to obtain the remainder result, which consists of eight values corresponding to 0 to 7.
[0057] In a specific implementation, after determining the time variable value and the random number, the time variable value and the random number can be combined according to a pre-set order number combination method, and the combined data can be used as the order number of the order message, which facilitates subsequent data verification.
[0058] Through the above steps, this invention utilizes order placement time to partition the database and generates an eight-part hash table. By batch generating random numbers and using a hash remainder algorithm to obtain a fixed remainder combination of the random numbers, the order is accurately placed into the database.
[0059] Step S23: Store the time variable value and the random number as variables in the message body of the order message, and send the order message to the consumer so that the consumer can consume the order message and place it in the target table of the target database; wherein, the target database is determined based on the time variable value, and the target table in the target database is determined based on the random number.
[0060] In this step, after an order message is consumed by a consumer, the order is placed in the target database corresponding to the time variable value, and then precisely into the data table corresponding to the random number within that target database. Specifically, in the actual database placement operation, orders can be placed into 8 data tables across 12 databases based on different time variable values and random numbers within their respective message bodies, achieving accurate order placement under high concurrency conditions.
[0061] This embodiment proposes using a pre-set rule to determine the random date of the order message based on the month to which the order placement time belongs, thereby determining the time variable value corresponding to the order message. A hash modulo algorithm is then used to determine the remainder of the random string, and this remainder is used as the random number corresponding to the order message. When an order is stored in the database, it can be accurately stored in 8 tables across 12 databases based on the different time variable values and random numbers within each message body. This achieves accurate order storage under high concurrency, reducing data verification costs.
[0062] See Figure 3 As shown in the figure, this application discloses an order message processing device, which may specifically include:
[0063] Message processing module 11 is used to determine the random date and random string corresponding to the order message using a preset stress testing tool; the order message is a MQ message sent by the producer in the preset message subscription tool;
[0064] The data determination module 12 is used to determine the time variable value corresponding to the order message based on the random date, and to determine the random number corresponding to the order message based on the random string;
[0065] The message sending module 13 is used to store the time variable value and the random number as variables in the message body of the order message, and send the order message to the consumer so that the consumer can consume the order message and place it in the target table of the target database; wherein, the target database is determined based on the time variable value, and the target table in the target database is determined based on the random number.
[0066] In this embodiment, a preset stress testing tool is first used to determine the random date and random string corresponding to the order message. The order message is an MQ message sent by a producer in a preset message subscription tool. A time variable value corresponding to the order message is determined based on the random date, and a random number corresponding to the order message is determined based on the random string. The time variable value and the random number are stored as variables in the message body of the order message, and the order message is sent to the consumer so that the consumer can consume the order message and place it in the target table of the target database. The target database is determined based on the time variable value, and the target table in the target database is determined based on the random number. Thus, after obtaining the MQ message produced by the producer, this invention uses a preset stress testing tool to determine the random date and random string corresponding to the order message, determines the time variable value and random number based on the random date and random string, and stores the time variable value and random number as variables in the message body of the order message. Subsequently, when performing order entry into the database, the order can be accurately entered into the database based on the time variable value and the random number. In this embodiment, the production of order messages by the producer can ensure the acquisition of a large number of order messages. At the same time, the method of the present invention can complete high-concurrency processing of order entry and ensure accurate order entry.
[0067] In some specific embodiments, the message processing module 11 includes:
[0068] The message processing unit is used to determine the random date and random string corresponding to the order message using Jemter; the order message is an MQ message sent by a producer in Kafka.
[0069] In some specific embodiments, the order message processing device further includes:
[0070] The data packaging unit is used to package a custom Kafka address, message topic, and sent data in the message into a Jar file using a preset development tool, and then introduce the Jar file into a preset stress testing tool.
[0071] In some specific embodiments, the order message processing device further includes:
[0072] The information configuration unit is used to define Kafka producer objects and add configuration information to the producer objects;
[0073] The object creation unit is used to create a producer object and call the send method to send an order message using the producer object.
[0074] In some specific embodiments, the message processing module 11 includes:
[0075] The method application unit is used to determine the random date and random string corresponding to the order message using a preset random generation method in a preset stress testing tool.
[0076] In some specific embodiments, the data determination module 12 includes:
[0077] The algorithm application unit is used to determine the remainder result of the random string using a hash modulo algorithm, and to determine the remainder result as the random number corresponding to the order message.
[0078] In some specific embodiments, the data determination module 12 includes:
[0079] The rule application unit is used to determine the time variable value corresponding to the order message by using the random date according to a pre-set rule based on the month to which the order placement time in the order message belongs.
[0080] Furthermore, embodiments of this application also disclose an electronic device, Figure 4 This is a structural diagram of an electronic device 20 according to an exemplary embodiment. The content of the diagram should not be construed as limiting the scope of use of this application.
[0081] Figure 4 This is a schematic diagram of the structure of an electronic device 20 provided in an embodiment of this application. Specifically, the electronic device 20 may include: at least one processor 21, at least one memory 22, a power supply 23, a display screen 24, an input / output interface 25, a communication interface 26, and a communication bus 27. The memory 22 stores a computer program, which is loaded and executed by the processor 21 to implement the relevant steps in the order message processing method disclosed in any of the foregoing embodiments. Furthermore, the electronic device 20 in this embodiment may specifically be an electronic computer.
[0082] In this embodiment, the power supply 23 is used to provide operating voltage for each hardware device on the electronic device 20; the communication interface 26 can create a data transmission channel between the electronic device 20 and external devices, and the communication protocol it follows can be any communication protocol applicable to the technical solution of this application, and is not specifically limited here; the input / output interface 25 is used to acquire external input data or output data to the outside world, and its specific interface type can be selected according to specific application needs, and is not specifically limited here.
[0083] Furthermore, the memory 22, as a carrier for resource storage, can be a read-only memory, random access memory, disk, or optical disk, etc. The resources stored on it can include an operating system 221, computer programs 222, and virtual machine data 223, etc. The virtual machine data 223 can include various types of data. The storage method can be temporary storage or permanent storage.
[0084] The operating system 221 is used to manage and control the various hardware devices on the electronic device 20 and the computer program 222, which may be Windows Server, Netware, Unix, Linux, etc. In addition to including a computer program capable of performing the order message processing method executed by the electronic device 20 as disclosed in any of the foregoing embodiments, the computer program 222 may further include a computer program capable of performing other specific tasks.
[0085] Furthermore, this application also discloses a computer-readable storage medium, which includes random access memory (RAM), main memory, read-only memory (ROM), electrically programmable ROM, electrically erasable programmable ROM, registers, hard disks, magnetic disks, optical disks, or any other form of storage medium known in the art. When the computer program is executed by a processor, it implements the aforementioned disclosed order message processing method. Specific steps of this method can be found in the corresponding content disclosed in the foregoing embodiments, and will not be repeated here.
[0086] The various embodiments in this specification are described in a progressive manner, with each embodiment focusing on its differences from other embodiments. Similar or identical parts between embodiments can be referred to interchangeably. For the apparatuses disclosed in the embodiments, since they correspond to the methods disclosed in the embodiments, the descriptions are relatively simple; relevant parts can be referred to the method section. Those skilled in the art will further recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, computer software, or a combination of both. To clearly illustrate the interchangeability of hardware and software, the composition and steps of each example have been generally described in terms of function in the foregoing description. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementations should not be considered beyond the scope of this application.
[0087] The steps of the methods or algorithms described in conjunction with the embodiments disclosed herein can be implemented directly by hardware, a software module executed by a processor, or a combination of both. The software module can be located in random access memory (RAM), main memory, read-only memory (ROM), electrically programmable ROM, electrically erasable programmable ROM, registers, hard disk, removable disk, CD-ROM, or any other form of storage medium known in the art.
[0088] Finally, it should be noted that in this document, relational terms such as "first" and "second" are used only to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitations, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes said element.
[0089] The order message processing method, apparatus, device, and storage medium provided by the present invention have been described in detail above. Specific examples have been used to illustrate the principles and implementation methods of the present invention. The description of the above embodiments is only for the purpose of helping to understand the method and core ideas of the present invention. At the same time, for those skilled in the art, there will be changes in the specific implementation methods and application scope based on the ideas of the present invention. Therefore, the content of this specification should not be construed as a limitation of the present invention.
Claims
1. An order message processing method, characterized in that, include: Use a preset stress testing tool to determine the random date and random string corresponding to the order message; The order message is an MQ message sent by the producer in the preset message subscription tool; The time variable value corresponding to the order message is determined based on the random date, and the random number corresponding to the order message is determined based on the random string; The time variable value and the random number are stored as variables in the message body of the order message, and the order message is sent to the consumer so that the consumer can consume the order message and place it in the target table of the target database; wherein, the target database is determined based on the time variable value, and the target table in the target database is determined based on the random number; The step of determining the random number corresponding to the order message based on the random string includes: The remainder result of the random string is determined using a hash modulo algorithm, and the remainder result is used as the random number corresponding to the order message; The step of determining the time variable value corresponding to the order message based on the random date includes: The time variable value corresponding to the order message is determined by using the random date according to a pre-set rule based on the month to which the order placement time in the order message belongs.
2. The order message processing method according to claim 1, characterized in that, The method of using a preset stress testing tool to determine the random date and random string corresponding to the order message; the MQ messages sent by the producer in the preset message subscription tool for the order message include: The random date and random string corresponding to the order message are determined using Jemter; the order message is an MQ message sent by a producer in Kafka.
3. The order message processing method according to claim 2, characterized in that, Before determining the random date and random string corresponding to the order message using a preset stress testing tool, the process also includes: The custom Kafka address, message topic, and message sending data are packaged into a JAR file using a preset development tool, and the JAR file is then imported into a preset stress testing tool.
4. The order message processing method according to claim 1, characterized in that, Before determining the random date and random string corresponding to the order message using a preset stress testing tool, the process also includes: Define a Kafka producer object and add configuration information to the producer object; Create a producer object and call the send method to send the order message using the producer object.
5. The order message processing method according to claim 1, characterized in that, The step of using a preset stress testing tool to determine the random date and random string corresponding to the order message includes: The random date and random string corresponding to the order message are determined using the preset random generation method in the preset stress testing tool.
6. An order message processing device, characterized in that, include: The message processing module is used to determine the random date and random string corresponding to the order message using a preset stress testing tool; The order message preset message subscription tool sends MQ messages sent by the producer; The data determination module is used to determine the time variable value corresponding to the order message based on the random date, and to determine the random number corresponding to the order message based on the random string; The message sending module is used to store the time variable value and the random number as variables in the message body of the order message, and send the order message to the consumer so that the consumer can consume the order message and place it in the target table of the target database; wherein, the target database is determined based on the time variable value, and the target table in the target database is determined based on the random number; The data determination module includes: The algorithm application unit is used to determine the remainder result of the random string using a hash modulo algorithm, and to determine the remainder result as the random number corresponding to the order message; The data determination module includes: The rule application unit is used to determine the time variable value corresponding to the order message by using the random date according to a pre-set rule based on the month to which the order placement time in the order message belongs.
7. An electronic device, characterized in that, It includes a processor and a memory; wherein, when the processor executes a computer program stored in the memory, it implements the order message processing method as described in any one of claims 1 to 5.
8. A computer-readable storage medium, characterized in that, Used to store a computer program; wherein, when the computer program is executed by a processor, it implements the order message processing method as described in any one of claims 1 to 5.