Early warning method, device and equipment for order pushing abnormity and storage medium

Abstract

The invention discloses an order pushing abnormity early warning method, and the method comprises the steps: obtaining order pushing data, which is used for obtaining the pushing data of an electronic order in a logistics system; setting a time window, and querying the number of abnormal push orders in the time window; comparing the abnormal push order with an order at an order receiving place in the logistics system, and skipping if the order exists at the order receiving place; if not, recording the order number of the order; the abnormal push order supplementary grabbing module is used for grabbing the abnormal push order again through the abnormal push order supplementary grabbing script after the abnormal push order is recorded; and the monitoring and early warning module is used for monitoring the execution states of the abnormal push order and the script for supplementary grabbing of the abnormal push order in the time window, and sending early warning information to the logistics system. According to the invention, the missing order can be automatically detected and re-pushed, the problem of data redundancy caused by repeated pushing is avoided, the processing speed of the abnormal order is accelerated, and the efficiency of the business process is improved.

Description

Technical Field

[0001] The present invention relates to the technical field of logistics, and particularly to a warning method, device, equipment and storage medium for abnormal order pushing. Background Art

[0002] In the process of order data flow in the logistics order system, only order capture and pushing are performed. However, in this process, order flow loss often occurs. This kind of order loss situation can only be discovered by the background through operations such as looking up tables after the network points and customers feedback that the order cannot be found in the system, which seriously affects the order flow efficiency.

[0003] The reason for the order loss problem is that the order receiving interface will be coupled during the process of saving orders and capturing orders by the order script, resulting in orders not being captured; in addition, if the script execution is incorrect, the data format is not standardized, or the downstream interface has an exception, etc., the order will not be transferred.

[0004] In order to be able to capture the missing orders in the order pushing process in a timely manner and systematically monitor and warn the pushing of abnormal orders, it is necessary to invent a warning method, device, equipment and storage medium for abnormal order pushing. Summary of the Invention

[0005] The main purpose of the present invention is to solve the technical problem that in the prior art, it is impossible to capture the missing orders in the order pushing process in a timely manner and systematically monitor and warn the pushing of abnormal orders.

[0006] The first aspect of the present invention provides a warning method for abnormal order pushing, and the method includes: Obtain order pushing data, which is used to obtain the pushing data of electronic orders in the logistics system; Set a time window and query the number of abnormally pushed orders within this time window; Compare the abnormally pushed orders with the orders at the order receiving place in the logistics system. If the order already exists at the order receiving place, skip it; if not, record the order number of this order; Re-capture the abnormally pushed orders, which is used to re-capture the abnormally pushed orders through a re-capture abnormal push order script after recording the abnormally pushed orders; Monitor and warn, which is used to monitor the execution status of the abnormally pushed orders and the re-capture abnormal push order script within the time window and send a warning message to the logistics system.

[0007] Optionally, in the first implementation manner of the first aspect of the present invention, the obtaining order pushing data, which is used to obtain the pushing data of electronic orders in the logistics system, includes: Obtain the pushing data of electronic orders through the logistics system interface; Parsing the push data of the electronic order and extracting the order number of the electronic order; Compare the parsed order number with the existing order data in the logistics system. If the order number already exists, update the order number of the order; If the order number does not exist, the pushed data is stored in the logistics system as a new order record.

[0008] Optionally, in a second implementation of the first aspect of the present invention, setting a time window and querying the number of abnormally pushed orders within the time window includes: Set a time window, the time window includes a start time and an end time; Query the abnormal push orders within the time window through SQL statements; Count the number of abnormal push orders within the time window; Preset a fluctuation range threshold for abnormal push orders to determine whether the number of abnormal orders within the time window exceeds the normal fluctuation range; If the number of abnormal orders within the time window exceeds the normal fluctuation range, the time period corresponding to the time window is marked as a high-risk omission interval.

[0009] Optionally, in a third implementation of the first aspect of the present invention, comparing the abnormal push order with the order at the order receiving place in the logistics system, and if the order already exists at the order receiving place, skipping it; if not, recording the order number of the order, includes: Traversing the abnormal push order list, and comparing the abnormal push orders with the orders received in the logistics system one by one; If there is an order matching the current abnormal push order in the order receiving place in the logistics system, the abnormal push order will be skipped; If there is no order matching the current abnormal push order at the order receiving location in the logistics system, the order number of the abnormal push order is recorded and an abnormal order record is generated.

[0010] Optionally, in a fourth implementation of the first aspect of the present invention, the method of re-capturing the abnormal push order is used to re-capture the abnormal push order through a script for re-capturing the abnormal push order after recording the abnormal push order, and includes: After recording the abnormal push order, trigger the execution of the script for capturing the abnormal push order; The re-crawl script initiates a re-crawl request to the order push system based on the recorded abnormal push order number; If the re - scraping is successful, compare the scraped order data with the order data in the logistics system to ensure data consistency; if the re - scraping fails, record the information of failed supplementary scraping and update the status of the abnormally pushed order for supplementary scraping as failed.

[0011] Optionally, in the fifth implementation manner of the first aspect of the present invention, the monitoring and early warning are used to monitor the execution status of abnormally pushed orders and the script for supplementary scraping of abnormally pushed orders within a time window, and send early warning information to the logistics system, including: Set up a monitoring module for real - time monitoring of the number of abnormally pushed orders and the execution status of the script for supplementary scraping of abnormally pushed orders within a time window; The monitoring module obtains the statistical information of abnormally pushed orders and the execution log of the supplementary scraping script through a scheduled task or an event - triggering mechanism; If the monitoring module detects that the number of abnormally pushed orders within the time window exceeds a preset threshold or the supplementary scraping script fails to execute, trigger the early warning mechanism; The early warning mechanism sends early warning information to the logistics system.

[0012] Optionally, in the sixth implementation manner of the first aspect of the present invention, the method further includes: Collect the characteristic data of abnormally pushed orders in history; Use the characteristic data and the emergency level label as a training set to train a decision tree classification model; When an abnormally pushed order appears, extract the corresponding characteristic data of the order, input it into the trained decision tree classification model, and output the early warning emergency level classification of the order; Send early warning information of different levels according to the early warning emergency level classification output by the decision tree classification model.

[0013] The second aspect of the present invention provides an early warning device for abnormal order pushing, including: An order push data acquisition module for acquiring the push data of electronic orders in the logistics system; A query module for setting a time window and querying the number of abnormally pushed orders within the time window; A comparison and recording module for comparing the abnormally pushed order with the order at the order receiving place in the logistics system. If the order already exists at the order receiving place, skip it; if not, record the order number of the order; A supplementary scraping of abnormally pushed orders module for re - scraping the abnormally pushed order through a script for supplementary scraping of abnormally pushed orders after recording the abnormally pushed order; A monitoring and early warning module for monitoring the execution status of abnormally pushed orders and the script for supplementary scraping of abnormally pushed orders within a time window, and sending early warning information to the logistics system.

[0014] In the third aspect of the present invention, a computer device is provided. The computer device includes a memory and at least one processor, and instructions are stored in the memory; The at least one processor invokes the instructions in the memory to cause the computer device to execute the early warning method for abnormal order push as described above.

[0015] In the fourth aspect of the present invention, a computer-readable storage medium is provided, on which a computer program is stored. The computer program is loaded by a processor to execute the early warning method for abnormal order push as described above.

[0016] The early warning method for abnormal order push of the present invention can automatically detect and re-push missed orders, greatly reducing the delays caused by failed order processing; through comparison and screening, it ensures that orders are only processed once, avoiding data redundancy problems caused by repeated pushing; on the other hand, it also improves the consistency and accuracy of data, reducing the complexity of subsequent data analysis and processing; speeds up the processing speed of abnormal orders, and improves the efficiency of the overall business process. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] Figure 1 It is a flowchart of the early warning method for abnormal order push provided by an embodiment of the present invention; Figure 2 It is a flowchart of obtaining order push data in the early warning method for abnormal order push provided by an embodiment of the present invention; Figure 3 It is a flowchart of querying the number of abnormal orders in the early warning method for abnormal order push provided by an embodiment of the present invention; Figure 4 It is a flowchart of comparing and recording abnormal orders in the early warning method for abnormal order push provided by an embodiment of the present invention; Figure 5 It is a flowchart of re-catching abnormally pushed orders in the early warning method for abnormal order push provided by an embodiment of the present invention; Figure 6 It is a flowchart of monitoring and early warning in the early warning method for abnormal order push provided by an embodiment of the present invention; Figure 7 It is a schematic structural diagram of the early warning device for abnormal order push provided by an embodiment of the present invention; Figure 8 It is another schematic structural diagram of the early warning device for abnormal order push provided by an embodiment of the present invention; Figure 9 It is a schematic structural diagram of the electronic device provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0018] The present invention provides a warning method for abnormal order push. The method includes: obtaining order push data, which is used to obtain the push data of electronic orders in the logistics system; setting a time window and querying the number of abnormally pushed orders within this time window; comparing the abnormally pushed orders with the orders at the order receiving place in the logistics system. If the order already exists at the order receiving place, skip it; if not, record the order number of this order; supplement and capture abnormally pushed orders, which is used to re-capture the abnormally pushed orders through a supplement and capture abnormally pushed orders script after recording the abnormally pushed orders; monitor and give warnings, which is used to monitor the execution status of the abnormally pushed orders and the supplement and capture abnormally pushed orders script within the time window and send warning messages to the logistics system.

[0019] The warning method for abnormal order push of the present invention can automatically detect and supplement and push the missing orders, greatly reducing the delay caused by order processing failures; through comparison and screening, it ensures that the order is only processed once, avoiding the data redundancy problem caused by repeated pushing; on the other hand, it also improves the consistency and accuracy of the data, reducing the complexity of subsequent data analysis and processing; speeds up the processing speed of abnormal orders and improves the efficiency of the overall business process.

[0020] The terms "first", "second", "third", "fourth", etc. (if any) in the description and claims of the present invention and the above-mentioned drawings are used to distinguish similar objects and do not necessarily need to be used to describe a specific order or sequence. It should be understood that such used data can be interchanged under appropriate circumstances so that the embodiments described here can be implemented in an order other than those illustrated or described here. In addition, the term "comprising" or "having" and any variation thereof are intended to cover non-exclusive inclusion. For example, a process, method, system, product or device comprising a series of steps or units does not necessarily need to be limited to those steps or units clearly listed, but may include other steps or units not clearly listed or inherent to these processes, methods, products or devices.

[0021] For ease of understanding, the specific process of the embodiments of the present invention will be described below. Please refer to Figure 1 , the embodiments of the present invention provide a warning method for abnormal order push. The method includes: 101. Obtain order push data, which is used to obtain the push data of electronic orders in the logistics system; 102. Set a time window and query the number of abnormally pushed orders within this time window; 103. Compare the abnormally pushed orders with the orders at the order receiving place in the logistics system. If the order already exists at the order receiving place, skip it; if not, record the order number of this order; 104. Supplementary capture of exception push orders, which is used to recapture the exception push orders through the supplementary capture of exception push order script after recording the exception push orders; 105. Monitoring and early warning, which is used to monitor the execution status of the exception push orders and the supplementary capture of exception push order script within the time window, and send early warning information to the logistics system.

[0022] The early warning method for order push exceptions of the present invention can automatically detect and supplement the missing orders, greatly reducing the delays caused by order processing failures; through comparison and screening, it ensures that the orders are processed only once, avoiding the data redundancy problem caused by repeated pushing; on the other hand, it also improves the consistency and accuracy of the data, reduces the complexity of subsequent data analysis and processing; speeds up the processing speed of exception orders, and improves the efficiency of the overall business process.

[0023] Please refer to Figure 2 , in the second embodiment of the early warning method for order push exceptions in the embodiments of the present invention, on the basis of the above embodiments, the obtaining of order push data is used to obtain the push data of the electronic order in the logistics system, including: 201. Obtain the push data of the electronic order through the logistics system interface; 202. Analyze the push data of the electronic order and extract the order number of the electronic order; 203. Compare the parsed order number with the existing order data in the logistics system. If the order number already exists, update the order number of the order; 204. If the order number does not exist, store the push data as a new order record in the logistics system.

[0024] The embodiments of the present invention ensure the uniqueness of each order number in the logistics system through the comparison and update mechanism, avoiding data chaos caused by duplicate or conflicting order numbers. This helps to maintain the consistency and accuracy of the data; the automated comparison and update process reduces the possibility of human operation errors and improves the reliability and stability of the system.

[0025] Please refer to Figure 3 , in the third embodiment of the early warning method for order push exceptions in the embodiments of the present invention, the setting of the time window and the query of the number of exception push orders within the time window include: 301. Set the time window, and the time window includes a start time and an end time; In some embodiments, a sliding time window with a fixed duration is set, which slides on the time axis of the order data at a fixed time interval.

[0026] 302. Query the exception push orders within the time window through SQL statements; 303. Count the number of abnormal push orders within the time window; 304. Preset a fluctuation range threshold of abnormal pushed orders to determine whether the number of abnormal orders within the time window exceeds the normal fluctuation range; 305. If the number of abnormal orders within the time window exceeds the normal fluctuation range, mark the time period corresponding to the time window as a high-risk omission interval.

[0027] The embodiment of the present invention sets fluctuation range thresholds and performs real-time monitoring, which enables logistics companies to take preventive measures in advance to avoid greater losses; marking high-risk omission intervals can help managers quickly identify specific time periods and possible problem areas, making it easier to concentrate resources for investigation and resolution.

[0028] See also Figure 4 , the fourth embodiment of the method for warning of abnormal order push in the embodiment of the present invention, the abnormal push order is compared with the order at the order receiving place in the logistics system, if the order already exists at the order receiving place, it is skipped; if not, the order number of the order is recorded, including: 401. Traverse the abnormal push order list and compare the abnormal push orders with the orders received in the logistics system one by one; 402. If there is an order matching the current abnormal push order at the order receiving location in the logistics system, the abnormal push order is skipped; 403. If there is no order matching the current abnormal push order at the order receiving location in the logistics system, the order number of the abnormal push order is recorded and an abnormal order record is generated.

[0029] The embodiment of the present invention directly skips the orders that already exist in the logistics system, quickly identifies and processes newly emerged abnormal orders, saves unnecessary processing time, improves the response speed and processing capacity of the system, is suitable for large-scale order processing, and can significantly improve overall work efficiency; it provides customers with accurate information updates more quickly, and enhances customer trust and service experience.

[0030] See also Figure 5 In the fifth embodiment of the method for early warning of abnormal order push in the embodiment of the present invention, the method for re-capturing abnormal push orders is used to re-capture abnormal push orders through a script for re-capturing abnormal push orders after recording abnormal push orders, and includes: 501. After recording the abnormal push order, trigger the execution of the script for capturing the abnormal push order; 502. The re-capture script sends a re-capture request to the order push system according to the recorded abnormal push order number; 503. If the re-capture is successful, compare the captured order data with the order data in the logistics system to ensure data consistency; 504. If the re-capture fails, record the information of failed re-capture and update the status of the exception push order to failed re-capture.

[0031] In the embodiment of the present invention, by re-capturing and comparing the order data, it is ensured that the data in the logistics system is consistent with the data in the order push system; the operation errors and customer complaints caused by data inconsistency are reduced; even if the initial push fails or there are omissions, the re-capture mechanism can effectively reduce the risk of data loss and ensure that all orders can be correctly processed; the process of quickly identifying and re-capturing abnormal orders greatly shortens the order processing time and improves the overall work efficiency.

[0032] Please refer to Figure 6 , the sixth embodiment of the early warning method for abnormal order push in the embodiment of the present invention, the monitoring and early warning are used to monitor the execution status of abnormal push orders and the script for re-capturing abnormal push orders within a time window, and send early warning information to the logistics system, including: 601. Set up a monitoring module to monitor the number of abnormal push orders and the execution status of the script for re-capturing abnormal push orders within a time window in real time; 602. The monitoring module obtains the statistical information of abnormal push orders and the execution log of the re-capture script through a scheduled task or an event trigger mechanism; 603. If the monitoring module detects that the number of abnormal push orders within the time window exceeds a preset threshold, or the re-capture script fails to execute, trigger the early warning mechanism; 604. The early warning mechanism sends early warning information to the logistics system.

[0033] In the embodiment of the present invention, by monitoring the number of abnormal orders and the execution status of the re-capture script in real time, potential problems can be discovered in time to ensure the stable operation of the system; when it is detected that the number of abnormal orders exceeds the preset threshold or the re-capture script fails to execute, the early warning mechanism is immediately triggered.

[0034] In some embodiments, the method further includes Collect the characteristic data of abnormal push orders in history; Use the characteristic data and the urgency label as a training set to train a decision tree classification model; When an abnormal push order appears, extract the corresponding characteristic data of the order, input it into the trained decision tree classification model, and output the early warning urgency classification of the order; Send early warning information of different levels according to the early warning urgency classification output by the decision tree classification model.

[0035] By using a decision tree classification model to classify abnormal orders, it is possible to accurately evaluate the risk level of each order based on its characteristic data; it can more precisely identify which orders need to be processed first, thereby optimizing resource allocation; flexibly adjust business processes and resource allocation strategies according to different warning levels to ensure that there are sufficient resources to handle emergencies at critical moments.

[0036] The above described the warning method for abnormal order push in the embodiments of the present invention. Next, the warning device for abnormal order push in the embodiments of the present invention will be described. Please refer to Figure 7 One embodiment of the warning device for abnormal order push in the embodiments of the present invention includes: An order push data acquisition module 701, configured to acquire the push data of electronic orders in the logistics system; A query module 702, configured to set a time window and query the number of abnormally pushed orders within this time window; A comparison and recording module 703, configured to compare the abnormally pushed orders with the orders at the order receiving place in the logistics system. If the order already exists at the order receiving place, skip it; if not, record the order number of this order; An abnormal push order re-capture module 704, configured to, after recording the abnormally pushed orders, re-capture the abnormally pushed orders through an abnormally pushed order re-capture script; A monitoring and warning module 705, configured to monitor the execution status of the abnormally pushed orders and the abnormally pushed order re-capture script within the time window, and send a warning message to the logistics system.

[0037] The warning device for abnormal order push of the present invention can automatically detect and re-push missed orders, greatly reducing the delays caused by failed order processing; through comparison and screening, it ensures that an order is only processed once, avoiding data redundancy problems caused by repeated pushes; on the other hand, it also improves the consistency and accuracy of data, reducing the complexity of subsequent data analysis and processing; speeds up the processing speed of abnormal orders and improves the efficiency of the overall business process.

[0038] Please refer to Figure 8 Another embodiment of the warning device for abnormal order push in the embodiments of the present invention includes: An order push data acquisition module 701, configured to acquire the push data of electronic orders in the logistics system; In some embodiments, the order push data acquisition module 701 includes: An interface connection unit 7011, configured to acquire the push data of electronic orders through a logistics system interface; An extraction unit 7012, configured to parse the push data of the electronic orders and extract the order numbers of the electronic orders; The first comparison and update unit 7013 is used to compare the parsed order number with the existing order data in the logistics system. If the order number already exists, update the order number of this order; If the order number does not exist, store the push data as a new order record in the logistics system.

[0039] Through the comparison and update mechanism in the embodiments of the present invention, it is ensured that each order number is unique in the logistics system, avoiding data chaos caused by duplicate or conflicting order numbers. This helps to maintain data consistency and accuracy; the automated comparison and update process reduces the possibility of human operation errors and improves the reliability and stability of the system.

[0040] The query module 702 is used to set a time window and query the number of abnormally pushed orders within this time window; In some embodiments, the query module 702 includes: The time window unit 7021 sets the time window, and the time window includes a start time and an end time; In some embodiments, a sliding time window with a fixed duration is set to slide on the time axis of the order data at a fixed time interval.

[0041] The query unit 7022 is used to query the abnormally pushed orders within the time window through an SQL statement; The statistics unit 7023 is used to count the number of abnormally pushed orders within the time window; The judgment unit 7024 presets a fluctuation range threshold for abnormally pushed orders and judges whether the number of abnormal orders within the time window exceeds the normal fluctuation range; The marking unit 7025 is used to mark the time period corresponding to the time window as a high-risk omission interval if the number of abnormal orders within the time window exceeds the normal fluctuation range.

[0042] Through setting the fluctuation range threshold and performing real-time monitoring in the embodiments of the present invention, it enables logistics enterprises to take preventive measures in advance to avoid greater losses; marking the high-risk omission interval can help managers quickly identify specific time periods and possible problem areas, facilitating the concentration of resources for investigation and solution.

[0043] The comparison and recording module 703 is used to compare the abnormally pushed orders with the orders at the order receiving place in the logistics system. If the order already exists at the order receiving place, skip it; if not, record the order number of this order; In some embodiments, the comparison and recording module 703 includes: The traversal comparison unit 7031 is used to traverse the abnormal push order list and compare each abnormal push order with the orders at the order receiving location in the logistics system one by one; The recording unit 7032 is used to skip the abnormal push order if there is already a matching order at the order receiving location in the logistics system; if there is no matching order at the order receiving location in the logistics system for the current abnormal push order, record the order number of the abnormal push order and generate an abnormal order record.

[0044] The embodiment of the present invention directly skips the orders that already exist in the logistics system, quickly identifies and processes newly emerging abnormal orders, saves unnecessary processing time, improves the response speed and processing capacity of the system, is suitable for large-scale order processing, and can significantly improve the overall work efficiency; provides accurate information updates to customers faster, enhancing customers' trust and service experience.

[0045] The abnormal push order re-capture module 704 is used to re-capture the abnormal push order through the abnormal push order re-capture script after recording the abnormal push order; In some embodiments, the abnormal push order re-capture module 704 includes: The trigger unit 7041 is used to trigger the execution of the abnormal push order re-capture script after recording the abnormal push order; The re-capture unit 7042 is used for the re-capture script to initiate a re-capture request to the order push system according to the recorded order number of the abnormal push order; The second comparison and update unit 7043 is used to compare the captured order data with the order data in the logistics system to ensure data consistency if the re-capture is successful; if the re-capture fails, record the re-capture failure information and update the status of the abnormal push order to re-capture failure.

[0046] The embodiment of the present invention ensures the consistency of the data in the logistics system and the data in the order push system by re-capturing and comparing the order data; reduces operation errors and customer complaints caused by data inconsistency; even if the initial push fails or there are omissions, the re-capture mechanism can effectively reduce the risk of data loss and ensure that all orders are correctly processed; the process of quickly identifying and re-capturing abnormal orders greatly shortens the order processing time and improves the overall work efficiency.

[0047] The monitoring and warning module 705 is used to monitor the execution status of the abnormal push order and the abnormal push order re-capture script within the time window and send a warning message to the logistics system.

[0048] In some embodiments, the monitoring and warning module 705 includes: The monitoring unit 7051 is used to set up a monitoring module for real-time monitoring of the number of abnormally pushed orders within a time window and the execution status of the script for capturing abnormally pushed orders again; The acquisition unit 7052 is used for the monitoring module to obtain the statistical information of abnormally pushed orders and the execution log of the capturing script through a scheduled task or an event trigger mechanism; The warning trigger unit 7053 is used to trigger a warning mechanism if the monitoring module detects that the number of abnormally pushed orders within a time window exceeds a preset threshold or the capturing script fails to execute; the warning mechanism sends warning information to the logistics system.

[0049] In the embodiment of the present invention, by real-time monitoring of the number of abnormal orders and the execution status of the capturing script, potential problems can be discovered in a timely manner to ensure the stable operation of the system; when it is detected that the number of abnormal orders exceeds the preset threshold or the capturing script fails to execute, the warning mechanism is immediately triggered.

[0050] In some embodiments, the method further includes, Collecting the characteristic data of abnormally pushed orders in history; Using the characteristic data and the urgency label as a training set to train a decision tree classification model; When an abnormally pushed order appears, extracting the corresponding characteristic data of the order and inputting it into the trained decision tree classification model to output the warning urgency classification of the order; Sending warning information of different levels according to the warning urgency classification output by the decision tree classification model.

[0051] By classifying abnormal orders using a decision tree classification model, the risk level of each order can be accurately evaluated according to its characteristic data; it is possible to more precisely identify which orders need to be processed preferentially, thereby optimizing resource allocation; flexibly adjusting business processes and resource allocation strategies according to different warning levels to ensure that there are sufficient resources to cope with emergencies at critical moments.

[0052] Above Figure 7 And Figure 8 The warning method for abnormal order pushing in the embodiment of the present invention is described in detail from the perspective of modular functional entities. Next, the electronic device in the embodiment of the present invention will be described in detail from the perspective of hardware processing.

[0053] Figure 9It is a schematic structural diagram of an electronic device provided by an embodiment of the present invention. The electronic device 800 may vary greatly due to different configurations or performances, and may include one or more processors (central processing units, CPUs) 810 (for example, one or more processors) and a memory 820, and one or more storage media 830 (for example, one or more mass storage devices) for storing application programs 833 or data 832. Among them, the memory 820 and the storage media 830 may be transient storage or persistent storage. The program stored in the storage media 830 may include one or more upper modules for vehicle allocation in the distribution center (not shown in the figure), and each module may include a series of instruction operations on the electronic device 800. Further, the processor 810 may be set to communicate with the storage media 830 and execute a series of instruction operations in the storage media 830 on the electronic device 800.

[0054] The electronic device 800 may further include one or more power supplies 840, one or more wired or wireless network interfaces 850, one or more input / output interfaces 850, and / or one or more operating systems 831, such as Windows Serve, Mac OS X, Unix, Linux, FreeBSD, and so on. Those skilled in the art can understand that Figure 9 The shown structure of the electronic device does not constitute a limitation on the electronic device, and may include more or fewer components than shown in the figure, or combine some components, or have different component arrangements.

[0055] The present invention also provides a computer-readable storage medium. The computer-readable storage medium may be a non-volatile computer-readable storage medium, and may also be a volatile computer-readable storage medium. Instructions are stored in the computer-readable storage medium. When the instructions run on a computer, the computer is caused to execute the steps of the vehicle allocation method in the distribution center.

[0056] Those skilled in the art can clearly understand that for the convenience and brevity of description, the specific working processes of the above-described system or device and unit can refer to the corresponding processes in the foregoing method embodiments, and will not be described herein again.

[0057] When the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on such an understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. The computer software product is stored in a storage medium and includes several instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the methods described in various embodiments of the present invention. The foregoing storage medium includes: various media such as a USB flash drive, a mobile hard disk, a read-only memory (ROM), a random access memory (RAM), a magnetic disk, or an optical disc that can store program codes.

[0058] As described above, the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art should understand that they can still modify the technical solutions described in the foregoing embodiments, or perform equivalent replacements for some of the technical features; and these modifications or replacements do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of various embodiments of the present invention.

Claims

1. A warning method for abnormal order push, characterized in that, The method comprises: Obtain order push data, which is used to obtain push data of electronic orders in the logistics system; Set a time window and query the number of abnormally pushed orders within the time window; Compare the abnormal push order with the order at the receiving order in the logistics system. If the order already exists at the receiving order, skip it; if not, record the order number. Recapture abnormal push orders, which is used to recapture abnormal push orders after recording them through the script for recapture abnormal push orders; Monitoring and early warning are used to monitor the execution status of abnormal push orders and catch abnormal push order scripts within the time window, and send early warning information to the logistics system.

2. The early warning method for abnormal order push according to claim 1, characterized in that, The method of obtaining order push data is used to obtain push data of electronic orders in the logistics system, and includes: Obtain push data of electronic orders through the logistics system interface; Parsing the push data of the electronic order and extracting the order number of the electronic order; Compare the parsed order number with the existing order data in the logistics system. If the order number already exists, update the order number of the order; If the order number does not exist, the pushed data is stored in the logistics system as a new order record.

3. The early warning method for abnormal order push according to claim 2, wherein The setting of the time window and querying the number of abnormally pushed orders within the time window include: Set a time window, the time window includes a start time and an end time; Query the abnormal push orders within the time window through SQL statements; Count the number of abnormal push orders within the time window; Preset a fluctuation range threshold for abnormal push orders to determine whether the number of abnormal orders within the time window exceeds the normal fluctuation range; If the number of abnormal orders within the time window exceeds the normal fluctuation range, the time period corresponding to the time window is marked as a high-risk omission interval.

4. The early warning method for abnormal order push according to claim 3, characterized in that, The abnormal push order is compared with the order at the receiving order in the logistics system, and if the order already exists at the receiving order, it is skipped; If it does not exist, record the order number, including: Traversing the abnormal push order list, and comparing the abnormal push orders with the orders received in the logistics system one by one; If there is an order matching the current abnormal push order in the order receiving place in the logistics system, the abnormal push order will be skipped; If there is no order matching the current abnormal push order at the order receiving location in the logistics system, the order number of the abnormal push order is recorded and an abnormal order record is generated.

5. The early warning method for abnormal order push according to claim 4, wherein The method of re-capturing the abnormal push order is used to re-capture the abnormal push order through the script of re-capturing the abnormal push order after recording the abnormal push order, and includes: After recording the abnormal push order, trigger the execution of the script for capturing the abnormal push order; The re-crawl script initiates a re-crawl request to the order push system based on the recorded abnormal push order number; If the re-capture is successful, the captured order data will be compared with the order data in the logistics system to ensure data consistency; if the re-capture fails, the re-capture failure information will be recorded and the status of the abnormal push order will be updated to re-capture failure.

6. The early warning method for abnormal order push according to claim 3, wherein, The monitoring and warning are used to monitor the execution status of abnormal push orders and the script for re-catching abnormal push orders within a time window, and send warning messages to the logistics system, including: A monitoring module is set up to monitor the number of abnormal push orders and the execution status of the script for re-catching abnormal push orders in real time within the time window; The monitoring module obtains the statistical information of abnormal push orders and the execution log of the re-catching script through a scheduled task or an event trigger mechanism; If the monitoring module detects that the number of abnormal push orders within the time window exceeds the preset threshold or the re-catching script fails to execute, the warning mechanism is triggered; The warning mechanism sends warning messages to the logistics system.

7. The early warning method for abnormal order push according to claim 6, characterized in that, The method further includes: Collecting the characteristic data of abnormal push orders in history; Using the characteristic data and the urgency label as a training set to train a decision tree classification model; When an abnormal push order appears, extracting the corresponding characteristic data of the order and inputting it into the trained decision tree classification model to output the warning urgency classification of the order; Sending warning messages of different levels according to the warning urgency classification output by the decision tree classification model.

8. An early warning device for abnormal order push, characterized in that, Including: An order push data acquisition module for acquiring the push data of electronic orders in the logistics system; A query module for setting a time window and querying the number of abnormal push orders within the time window; A comparison and recording module for comparing the abnormal push order with the order at the order receiving place in the logistics system. If the order already exists at the order receiving place, it is skipped; if not, the order number of the order is recorded; A module for re-catching abnormal push orders, which is used to re-catch the abnormal push orders through a script for re-catching abnormal push orders after recording the abnormal push orders; A monitoring and warning module for monitoring the execution status of abnormal push orders and the script for re-catching abnormal push orders within the time window, and sending warning messages to the logistics system.

9. A computer device, characterized in that, The computer device includes a memory and at least one processor, and instructions are stored in the memory; The at least one processor invokes the instructions in the memory so that the computer device executes the warning method for abnormal order push according to any one of claims 1-7.

10. A computer-readable storage medium, characterized in that, A computer program is stored thereon, and the computer program is loaded by a processor to execute the warning method for abnormal order push according to any one of claims 1-7.

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