CN115130953A

CN115130953A - Community group purchase server ordering method, device, equipment and storage medium

Info

Publication number: CN115130953A
Application number: CN202210675531.5A
Authority: CN
Inventors: 马晓君
Original assignee: Shanghai Yucan Information Technology Co ltd
Current assignee: Shanghai Yucan Information Technology Co ltd
Priority date: 2022-06-15
Filing date: 2022-06-15
Publication date: 2022-09-30

Abstract

The invention provides a method, a device, equipment and a storage medium for ordering a community group purchase server, wherein the method for ordering the community group purchase server comprises the following steps: determining a server for ordering the user based on the current delivery address of the user; providing an automatic selection of delivery time among the options for delivery time in response to the determined compliance of the server with the set congestion condition; and responding to a payment request of the user based on the current receiving address, wherein the delivery time is the automatic delivery time, so that the determined server receives the payment request of the user for the current order, the determined server judges whether delivery capacity exists in a delivery station corresponding to the receiving address, and if the delivery capacity exists, the order corresponding to the payment request is confirmed. According to the method and the device, the phenomenon that a large number of users place orders at the same time to cause overhigh load of the server is avoided, and therefore after the users select the expected delivery time and pay the order, the order placing failure that the delivery time is unavailable is achieved, and the order placing experience of the users is improved.

Description

Community group purchase server ordering method, device, equipment and storage medium

Technical Field

The invention relates to the field of computer application, in particular to a method, a device, equipment and a storage medium for ordering by a community group purchase server.

Background

The community group buying is an internet online and offline shopping consumption behavior of a resident group in a real residential community, and is a regional, small, popular, local and networked group buying form depending on the real community.

In a community group purchase scene, when a user places an order, the user needs to select expected delivery time first and then select a payment mode to pay. However, when a large number of users select payment at the same time, the server may be crowded, and when the users select the delivery time and pay again, the delivery time is often unavailable, which eventually results in a failure of ordering by the users, and the user experience is very low.

The situation can be effectively relieved by the server capacity expansion mode, but the frequency of the occurrence of the too high load is low, the utilization rate of the capacity expansion is low, and the cost is too high.

Therefore, how to avoid the situation that the ordering fails when a large number of users order at the same time and the server load is too high, so that the users select the expected delivery time and pay when ordering, and the delivery time is unavailable, is a technical problem to be solved in the field.

Disclosure of Invention

In order to overcome the defects of the related technologies, the invention provides a method, a device, equipment and a storage medium for ordering by a community group purchase server, so that the phenomenon that the server load is too high due to the fact that a large number of users order at the same time is avoided, and therefore, after the users select the expected delivery time and pay, the ordering fails when the delivery time is unavailable, and the ordering experience of the users is improved.

According to one aspect of the invention, a method for ordering by a community group purchase server is provided, which comprises the following steps:

determining a server for ordering the user based on the current delivery address of the user;

providing an automatic selection of delivery time in the option of delivery time in response to the determined server meeting the set congestion condition;

and responding to a payment request of the user based on the current receiving address, wherein the delivery time is the automatic delivery time, so that the determined server receives the payment request of the user for the current order, the determined server judges whether delivery capacity exists in a delivery station corresponding to the receiving address, and if the delivery capacity exists, the order corresponding to the payment request is confirmed.

In some embodiments of the application, the setting of the congestion condition comprises one or more of the following congestion conditions:

the determined real-time load of the server is greater than a set load threshold;

the determined number of active users of the server is greater than a set number threshold;

the time difference between the current time and the determined server commodity sale time and/or capacity opening time is less than a first set time period threshold.

In some embodiments of the present application, the active users include:

currently operating users of the community group-buying user terminal; and/or

A user having generated a communication interaction with the determined server within a second set time period threshold.

In some embodiments of the present application, the providing for automatically selecting a delivery time among the options of delivery times includes:

canceling the option of the original time of the delivery time, and automatically selecting the delivery time as the automatically selected delivery time; or

Options for the delivery time include an original time and an automatically selected delivery time.

In some embodiments of the present application, the determining, by the server, whether the delivery capacity exists at the delivery station corresponding to the shipping address further includes:

in response to the order placing time of the user, within a third set time period threshold after the determined server meets the set congestion condition, the determined server judges whether the corresponding distribution station has distribution capacity according to whether the current accumulated sheet amount of the distribution station meets the set total sheet amount,

if the current accumulated single quantity of the distribution stations meets the set total single quantity, the corresponding distribution stations do not have distribution transport capacity; and if the current accumulated single quantity of the distribution stations is less than the set total single quantity, the corresponding distribution stations have distribution transport capacity.

In some embodiments of the present application, the third set time period threshold is preset, or is determined according to a determined duration that the server switches from meeting the set congestion condition to meeting the set idle-time condition.

In some embodiments of the present application, the determined server accumulates the current order of the user to the current accumulated amount of the delivery station within a fourth set time period threshold after the user completes the payment operation of the current order, and the fourth set time period threshold is preset or determined according to the third set time period threshold.

In some embodiments of the present application, after the fifth setting of the time period threshold after the user completes the payment operation of the current order, the method further includes:

the determined server calculates a distribution route according to a plurality of orders of the distribution station; and

the determined server allocates delivery times for the orders according to the calculated delivery routes and order placement order,

wherein the fifth set time period threshold is greater than or equal to a fourth set time period threshold.

In some embodiments of the present application, the fifth set time period threshold is preset or determined according to the third set time period threshold.

According to another aspect of the present application, there is provided a group purchase server ordering apparatus for a community, including:

the server determining module is used for determining a server for ordering the user based on the current delivery address of the user;

an automatic delivery time selection providing module, which is used for responding to the determined server meeting the set congestion condition and providing automatic delivery time selection in the delivery time option;

and the payment determining module is used for responding to a payment request of the user based on the current receiving address, and the delivery time is the automatic delivery time selection, so that the determined server receives the payment request of the user to the current order, the determined server judges whether the delivery station corresponding to the receiving address has delivery capacity, and if the delivery capacity exists, the order corresponding to the payment request is confirmed.

According to still another aspect of the present invention, there is also provided an electronic apparatus, including: a processor; a storage medium having stored thereon a computer program which, when executed by the processor, performs the steps as described above.

According to yet another aspect of the present invention, there is also provided a storage medium having stored thereon a computer program which, when executed by a processor, performs the steps as described above.

Compared with the prior art, the invention has the advantages that:

when the server for ordering is crowded, the automatic selection of the delivery time is provided in the option of the required operation delivery time when the user orders, so that when the user orders based on the current receiving address and the delivery time is the automatic selection of the delivery time, the determined server can directly judge the corresponding delivery station according to the receiving address to judge the delivery capacity and the payment operation of the current order, and the judgment of the delivery capacity based on the delivery time is not required to be distinguished. Therefore, the problem that a large number of users place orders at the same time to cause overhigh load of the server is avoided, and therefore the order placing failure that the delivery time is unavailable is avoided after the users select the expected delivery time and pay when placing the orders, and the order placing experience of the users is improved.

Drawings

The above and other features and advantages of the present invention will become more apparent by describing in detail exemplary embodiments thereof with reference to the attached drawings.

Fig. 1 shows a flow chart of a community group purchase server ordering method according to an embodiment of the invention.

FIG. 2 illustrates an ordering interface diagram of a community group purchase platform, according to an embodiment of the invention.

Fig. 3 shows a flow diagram for a server determining dispatch capacity in accordance with an embodiment of the invention.

Fig. 4 is a flowchart illustrating the updating of the delivery capacity by the server after the successful payment of the order made by the user according to the embodiment of the present invention.

Fig. 5 shows a flowchart of a server calculating a delivery path and a delivery time according to an embodiment of the present invention.

Fig. 6 is a block diagram illustrating an ordering apparatus of a community group purchase server according to an embodiment of the present invention.

Fig. 7 schematically illustrates a computer-readable storage medium in an exemplary embodiment of the invention.

Fig. 8 schematically illustrates an electronic device in an exemplary embodiment of the invention.

Detailed Description

Example embodiments will now be described more fully with reference to the accompanying drawings. Example embodiments may, however, be embodied in many different forms and should not be construed as limited to the examples set forth herein; rather, these embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the concept of example embodiments to those skilled in the art. The described features, structures, or characteristics may be combined in any suitable manner in one or more embodiments.

Furthermore, the drawings are merely schematic illustrations of the invention and are not necessarily drawn to scale. The same reference numerals in the drawings denote the same or similar parts, and a repetitive description thereof will be omitted. Some of the block diagrams shown in the figures are functional entities and do not necessarily correspond to physically or logically separate entities. These functional entities may be implemented in the form of software, or in one or more hardware modules or integrated circuits, or in different networks and/or processor devices and/or microcontroller devices.

The flow charts shown in the drawings are merely illustrative and do not necessarily include all of the steps. For example, some steps may be decomposed, some steps may be combined or partially combined, and thus, the actual execution order may be changed according to the actual situation.

Fig. 1 shows a flowchart of a community group purchase server ordering method according to an embodiment of the present invention. The order placing method of the community group purchase server comprises the following steps:

step S110: and determining a server for ordering the user based on the current delivery address of the user.

Specifically, the number of servers used for ordering for the user is plural, so that a server cluster or a distributed server is formed. Each server may be responsible for performing ordering operations for users in different areas. In some embodiments, the regions may be pre-divided, so that the server for performing the ordering operation is determined for the user according to the region where the receiving address of the user is located. In other embodiments, each server may be responsible for one or more distribution stations, and thus the server that performs the order placing operation for the user is determined based on the distribution range of which distribution station the user's current shipping address is in.

Step S120: in response to a determination that the server meets the set congestion condition, providing for automatic selection of a delivery time among options for delivery time.

Specifically, whether the server meets the set congestion condition or not can be determined based on real-time monitoring of the server, so that whether the server needs to flexibly adjust congestion processing or not is conveniently achieved, and the original community group purchase shopping experience of a user is guaranteed when the server is not congested. For example, when the real-time load of the server is greater than a set load threshold, it may be determined that the server meets the congestion condition. For another example, when the number of active users of the server is greater than a set number threshold, it may be determined that the server meets the congestion condition. The active users may include users currently operating the community group-buying user terminal (the users currently operating the community group-buying user terminal may not yet have made communication with the determined server, but belong to candidate users that are about to make communication with the determined server). Active users may also include users that have generated communication interactions with the determined server within a second set time period threshold (background users). Therefore, the probability that the server is overloaded is higher as the number of active users is larger, and therefore, whether the server meets the congestion condition or not can be determined by the number of active users.

Further, in some embodiments, due to the limitation of the capacity condition or the quantity condition of the goods, the community group buying platform may set the goods selling time and/or the capacity opening time, and when the goods selling time and/or the capacity opening time is reached, the server is often overloaded, so that congestion is generated. In such an embodiment, the number of load/active users of the server may not be monitored in real time, and it is only necessary to determine whether the server meets the congestion condition through time matching. Further, some advance may be set for the server to ensure that the server is ready for congestion processing and adjusts when the current time reaches the commodity selling time and/or the transportation capacity opening time, and at this time, the congestion condition may be set such that a time difference between the current time and the determined commodity selling time and/or the transportation capacity opening time of the server is smaller than a first set time period threshold (advance). For example, when the merchandise selling time is 8 am and the first set time period is 15 minutes, the server meets the congestion condition from 7 am to 45 am.

In some embodiments, when the determined server is in congestion, the original time of the delivery time may be deselected and the delivery time may be automatically selected as the automatically selected delivery time. In this embodiment, only the option of automatically selecting the delivery time exists in the delivery time, and the user cannot select other delivery time periods, so that the efficiency of ordering operation performed by the server is higher and the required load is lower.

In other embodiments, the options for the delivery time include an original time and an automatically selected delivery time. In this embodiment, the delivery time is automatically selected as a default option of the delivery time, so that a user who does not have a requirement for the delivery time period may not need to select the delivery time, on one hand, the ordering efficiency of the user is improved, and on the other hand, the ordering operation executed by the server based on the automatically selected delivery time is more efficient and requires less load. In this embodiment, the user may still switch the automatically selected delivery time to the delivery time period he or she desires in order to provide convenient service to the user who needs to receive the delivery in a particular time period.

Step S130: and responding to a payment request of the user based on the current receiving address, wherein the delivery time is the automatic delivery time, so that the determined server receives the payment request of the user for the current order, the determined server judges whether delivery capacity exists in a delivery station corresponding to the receiving address, and if the delivery capacity exists, the order corresponding to the payment request is confirmed.

In particular, the order interface 200 of the user may refer to fig. 2 (fig. 2 is merely illustrative, and the order interface of the present application is not limited thereto). When the server performing the order placing operation associated with the shipping address of the user meets the congestion condition, the delivery time may be automatically set to the option of "automatically selecting the delivery time" when the user places an order, and when the user selects the immediate payment control at the interface 200, a payment request is sent to the determined server. And after receiving the payment request, the determined server finds the distribution station corresponding to the receiving address and judges whether the distribution station has distribution transport capacity or not, so that whether the payment service is called or not is determined based on the distribution transport capacity, and ordering of the user is completed. In other embodiments, the user completes the payment operation of the order in step S130, and the determined server confirms whether the order paid by the user is valid according to the capacity. If capacity is insufficient, the partial order may be invalidated (cancel the partial order).

Specifically, the delivery capacity in step S130 may be the delivery unit amount of the delivery station. The delivery order amount can be obtained by, for example, the number of deliverers at the delivery station and the calculation of the historical delivery order amount. Further, the delivery capacity can also be planned by the delivery path of the placed order, the weight of the goods and the volume of the goods; and comprehensively calculating and determining the number of distribution personnel and the number of distribution transportation tools of the distribution station.

Specifically, the delivery time of the community group purchase is generally updated in units of days (the current day or the next day), and in a normal state of the server, the user may select a specific time period within one day as the delivery time. For example, the user may be provided with 6:00-8: 00; 8:00-10: 00; 10:00-12: 00; 12:00-14: 00; 14:00-16: 00; 16:00-18: 00; 18:00-20: 00; delivery time option of 20:00-22:00 (inventory may be checked 22: 00-6: 00 of the next day, delivery is suspended). The server allocates the capacity of the distribution station to each distribution time period. When a user requests a payment order, the server determines whether the delivery time period still has transport capacity according to the delivery time period selected by the user, if yes, the payment service is called, if not, the user fails to place an order, the server recalculates the current time period still having transport capacity and provides the time period for the user to select, and the user places an order again after selecting and sends a payment request to the server. Therefore, on one hand, after the service receives the payment request of the user, the service needs to inquire the current transport capacity condition corresponding to the distribution time period, and then can execute transport capacity judgment; on the other hand, since the capacity of the distribution station is distributed to a plurality of time slots, the distribution capacity of each distribution time slot is small, so that when the number of people selecting the distribution time slot is too large, the situation of crowding is more likely to occur, and the probability of ordering failure is high; on the other hand, after the ordering failure of the user, other distribution time periods are selected for ordering again, so that the payment request received by the server is further increased, and the load pressure of the server is higher.

By setting the automatic selection of the distribution time period, when a user payment request is received, the transportation capacity condition of the corresponding distribution time period does not need to be inquired, and the inquiry steps are reduced; the distribution transport capacity of the distribution station is integrated, the probability of order placing failure of a user is reduced, and the order placing experience of the user is improved; in addition, when the order placing fails, the delivery station is indicated to have insufficient transport capacity on the day, so that the user does not place the order again, the payment requests to be received by the server are not increased, and the load pressure of the server is reduced.

In a variation of the present application, in addition to providing the user with an option of automatically selecting the delivery time, the division interval of the plurality of time periods of the delivery time may be adjusted in real time according to the degree of congestion of the server. The more congested the server, the longer the time interval between delivery time divisions. In a specific implementation, congestion parameters can be set for the server, and when the congestion parameters (such as load parameters of CPU utilization and/or the number of active people) reach a congestion condition, an option of automatically selecting delivery time is provided for a user; when the congestion parameter does not satisfy the congestion condition, the larger the congestion parameter is, the longer the time interval between the delivery times to be provided is. For example, the congestion parameter is the CPU utilization of the server, and a plurality of sections may be set for the CPU utilization of the server, for example, the CPU utilization is lower than 60%; 60% -75%; 75% -90%; greater than 90%. When the CPU utilization rate is lower than 60%, the distribution time can be divided according to the time interval of one hour (such as 6:00-7: 00; 7:00-8:00, and the like); when the CPU utilization rate is 60% -75%, the distribution time can be divided into two hours (such as 6:00-8: 00; 8:00-10:00, and so on); when the CPU utilization rate is 75% -90%, the distribution time can be divided according to the time interval of four hours (such as 6:00-10: 00; 10:00-14: 00; and so on); when the CPU usage is greater than 90%, the user is provided with the option of automatically selecting the delivery time. The longer the time interval of distribution time division is, the more the capacity of the same distribution time period is, and the smaller the load pressure of the server is, so that the load pressure of the server can be relieved by adjusting the time interval of distribution time division in a staged real-time manner, and meanwhile, users and commodities which have requirements on the receiving time are taken into consideration, and the shopping experience of group shopping of the user community is improved.

In some embodiments, when the server is in a crowded state (for example, the commodity is placed in a 8-point opening mode, the server is in a crowded state from the 8-point), the background may delay a set time period (for example, 5 to 10 minutes) for order settlement, and when the order settlement is performed, the number of users placing the order and the delivery route may be counted in sequence at each set time interval (for example, 10 seconds to 20 seconds), and it is determined whether or not the capacity currently exists based on the counting result, and if the capacity is sufficient, the number of users placing the order and the delivery route may be continuously calculated at the next set time interval; if the transport capacity is insufficient, judging whether the transport capacity exists according to the order number of the user placing the order at the next set time interval in a mode of accumulating the order quantity, and if the transport capacity is sufficient, continuously judging whether the transport capacity exists according to the order number of the user placing the order at the next set time interval; if the capacity is insufficient, the order is randomly confirmed for the person who places the order at the current set time interval, or the order of the user with less order placing times and the order of the limited confirmation special type (such as fresh food) are preferably selected, which is not limited in the present application.

Further, within a certain time threshold after the user completes payment, the user's access request to the community group purchase platform may be prohibited to further reduce the server load.

In the method for ordering by the community group purchase server, when the server for ordering the order for the user is crowded, the automatic selection of the delivery time is provided in the options of the delivery time required by the user for ordering, so that when the user orders the order based on the current receiving address and the delivery time is the automatic selection of the delivery time, the determined server can directly judge the corresponding delivery station according to the receiving address to judge the delivery capacity and the payment operation of the current order without distinguishing the delivery time and executing the judgment of the delivery capacity based on the delivery time. Therefore, the problem that a server load is too high due to the fact that a large number of users place orders at the same time is avoided, and therefore the order placing failure that the delivery time is unavailable is achieved after the users select the expected delivery time and pay when placing orders, and the order placing experience of the users is improved.

Referring now to fig. 3, fig. 3 illustrates a flow diagram for a server determining dispatch capacity in accordance with an embodiment of the present invention. Fig. 3 shows the following steps:

step S311: the determined server receives a payment request of a user.

Step S312: and in response to the order placing time of the user, within a third set time interval threshold after the determined server meets the set congestion condition, the determined server judges whether the corresponding distribution station has distribution capacity according to whether the current accumulated amount of the distribution station meets the set total amount of the orders.

If the current accumulated single quantity of the distribution stations meets the set total single quantity, the corresponding distribution stations do not have distribution capacity; and if the current accumulated single quantity of the distribution stations is less than the set total single quantity, the corresponding distribution stations have distribution capacity.

Specifically, the set total units may be a predicted total delivery unit of the delivery station. The estimated total delivery unit quantity can be obtained by calculation according to historical delivery data of the delivery stations. For example, the average daily delivery volume of the delivery stations may be calculated from historical delivery data of the delivery stations, and the average daily delivery volume may be used as the estimated delivery volume. The present application is not limited thereto, and the calculated daily average delivery volume may be adjusted in consideration of changes in the number of people and changes in time (working days, holidays, sales promotion days, etc.). In other embodiments, the number of people at the distribution station, the transport, the date, etc. may also be input into the trained artificial intelligence model to predict the estimated total number of deliveries for the distribution station. The artificial intelligence model may be trained using historical distribution data for distribution stations.

Specifically, the current accumulated amount of the order may be determined according to the accumulated order of the current order, which may be specifically referred to the description of fig. 4 and fig. 4, and is not described herein again.

Specifically, the calculation power required for determining the transportation power based on the single volume comparison is smaller than that for performing the route planning and the distribution time based on the order in real time, and thus, the transportation power determination method with the smaller calculation power can be used during the period in which the server is crowded by setting the third set time period threshold value, so that the server load can be reduced. Thus, the third set time period threshold may be set in advance. For example, the third set time period threshold may be set as needed, or may be determined according to the historical congestion time period of the server. In some variations, the congestion status of the server may be monitored in real time, and when the server is still congested, a less computationally intensive capacity determination may be used. The present application can implement more variations, which are not described herein.

Step S313: and in response to the delivery capacity of the delivery station, invoking a payment service to execute the payment operation of the current order.

Referring now to fig. 4, fig. 4 is a flow chart illustrating the updating of shipping capacity by the server after a successful order placement payment is made by the user according to an embodiment of the present invention. Fig. 4 shows the steps after step S313:

step S314: and in response to the user completing the payment operation of the current order, the determined server accumulates the current order of the user to the current accumulated order quantity of the delivery station, and the determined server does not calculate a delivery route for the current order within a fourth set time period threshold after the user completes the payment operation of the current order.

Specifically, in order to match the statistics of the sheet amount of the server, when the user completes the payment operation of the current order, the order may be accumulated to the current accumulated sheet amount of the delivery station, and the delivery route is not calculated for the current order. And after the user finishes the payment operation of the current order within a fourth set time period, calculating a distribution route for the order of the user so as to reduce the load of the server in a crowded time period.

Specifically, the fourth set time period threshold may be set in advance. For example, it may be set to half an hour, 1 hour, etc., as needed. The fourth set time period threshold may also be determined from the third set time period threshold. For example, the fourth time period threshold may be equal to the third time period threshold. The current time may be subtracted from the time of the third time period threshold after the server congestion as the fourth time period threshold. Further variations that may be implemented by the present application are not described herein.

Referring now to fig. 5, fig. 5 illustrates a flow chart for a server to calculate delivery paths and delivery times, according to an embodiment of the invention. Fig. 5 shows the following steps:

step S315: and after the user finishes the payment operation of the current order and a fifth set time period threshold value, the determined server calculates a distribution route according to a plurality of orders of the distribution station.

Specifically, orders with closer shipping addresses may be assigned to the same dispenser for delivery, and a delivery route may be calculated for the dispenser based on the assigned orders. Other distribution route algorithms may be employed in the present application and are not described herein.

Step S316: the determined server allocates delivery times for the orders according to the calculated delivery routes and order placement order.

Specifically, the fifth set time period threshold value is equal to or greater than the fourth set time period threshold value. Further, the fifth set time period threshold may be set in advance. The fifth set time period threshold may also be determined in accordance with the third set time period threshold. For example, the fifth time period threshold may be equal to the third time period threshold (or the sum of the third time period threshold and a buffer time period). The time difference between the current time and the time after the server is congested subtracted from the time of the third time period threshold (or the sum of the time difference and a buffer time period) may be used as the fifth time period threshold.

Therefore, when the server is not crowded, the distribution route is calculated and the distribution time is distributed for each order, so that the user can know the expected distribution time and the distribution condition of the order.

Further, considering that after the capacity has been allocated, there are still users who have failed to place orders to continue to try to place orders, therefore, the system may not allocate or select the distribution time in the background within a certain time after the user payment is completed through the above-mentioned embodiments of fig. 3 to 5, and only calculate the total amount of the corresponding distribution stations; after reaching the fifth time period threshold, the background starts calculating the delivery route again and calculates and prompts the delivery time according to the route and the order placing sequence. At this time, there may be a surplus in the capacity due to the volume and weight of the distribution route and the order, and in this case, the released capacity may be pushed to the user after the capacity calculation work is completed. Specifically, when the capacity is released, a capacity release prompt can be sent to the user who has failed to place an order, so that the user can know the capacity release condition and place an order again.

In some embodiments of the present application, when the server is in a crowded state, if the ordered goods are out of stock and there is currently transportation capacity, the user may not confirm the ordered goods any more, and the payment request is directly invoked. Therefore, the order determining operation and order confirming time of the user can be reduced, the order placing efficiency is improved conveniently, the probability of order failure is reduced, and the frequency of sending the payment request to the server by the user for placing the order again is also reduced.

The above are merely a plurality of specific implementation manners of the community group purchase server ordering method of the present invention, and each implementation manner may be implemented independently or in combination, and the present invention is not limited thereto. Furthermore, the flow charts of the present invention are merely schematic, the execution sequence between the steps is not limited thereto, and the steps can be split, combined, exchanged sequentially, or executed synchronously or asynchronously in other ways within the protection scope of the present invention.

Referring now to fig. 6, fig. 6 is a block diagram illustrating an ordering apparatus of a community group purchase server according to an embodiment of the present invention. The community group purchase server ordering apparatus 400 includes a server determination module 410, an automatically selected delivery time providing module 420, and a payment determination module 430.

The server determining module 410 is configured to determine a server for ordering the user based on the current shipping address of the user;

the automatic delivery time selection providing module 420 is used for providing automatic delivery time selection in the option of the delivery time in response to the fact that the determined server meets the set congestion condition;

the payment determining module 430 is configured to, in response to a payment request of the user based on the current receiving address, enable the determined server to receive the payment request of the user for the current order when the delivery time is the automatic delivery time, so that the determined server determines whether delivery capacity exists at a delivery station corresponding to the receiving address, and if the delivery capacity exists, confirm the order corresponding to the payment request.

In the ordering device of the community group purchase server, when the ordering server for the user is crowded, the delivery time is automatically selected from options of the delivery time required by the user for ordering, so that when the user orders based on the current receiving address and the delivery time is automatically selected, the determined server can directly judge the corresponding delivery station according to the receiving address to judge the delivery capacity and pay the current order without distinguishing the delivery time and executing the judgment of the delivery capacity based on the delivery time. Therefore, the problem that a server load is too high due to the fact that a large number of users place orders at the same time is avoided, and therefore the order placing failure that the delivery time is unavailable is achieved after the users select the expected delivery time and pay when placing orders, and the order placing experience of the users is improved.

Fig. 6 is a schematic diagram illustrating the community group purchase server ordering apparatus 400 provided by the present invention, and the splitting, merging and adding of modules are within the scope of the present invention without departing from the concept of the present invention. The ordering apparatus 400 of the community group purchase server provided by the present invention can be implemented by software, hardware, firmware, plug-in and any combination thereof, which is not limited thereto.

In an exemplary embodiment of the present invention, a computer-readable storage medium is further provided, on which a computer program is stored, which when executed by, for example, a processor, may implement the steps of the community group buying server ordering method in any of the above embodiments. In some possible embodiments, the various aspects of the present invention may also be implemented in the form of a program product comprising program code means for causing a terminal device to carry out the steps according to various exemplary embodiments of the present invention as described in the section of the community group buying server ordering method mentioned above in this description, when said program product is run on the terminal device.

Referring to fig. 7, a program product 700 for implementing the above method according to an embodiment of the present invention is described, which may employ a portable compact disc read only memory (CD-ROM) and include program code, and may be run on a terminal device, such as a personal computer. However, the program product of the present invention is not limited in this regard and, in the present document, a readable storage medium may be any tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device.

The program product may employ any combination of one or more readable media. The readable medium may be a readable signal medium or a readable storage medium. The readable storage medium may be, for example, but not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination of the foregoing. More specific examples (a non-exhaustive list) of the readable storage medium include: an electrical connection having one or more wires, a portable diskette, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.

The computer readable storage medium may include a propagated data signal with readable program code embodied therein, for example, in baseband or as part of a carrier wave. Such a propagated data signal may take many forms, including, but not limited to, electro-magnetic, optical, or any suitable combination thereof. A readable storage medium may also be any readable medium that is not a readable storage medium and that can communicate, propagate, or transport a program for use by or in connection with an instruction execution system, apparatus, or device. Program code embodied on a readable storage medium may be transmitted using any appropriate medium, including but not limited to wireless, wireline, optical fiber cable, RF, etc., or any suitable combination of the foregoing.

Program code for carrying out operations for aspects of the present invention may be written in any combination of one or more programming languages, including an object oriented programming language such as Java, C + + or the like and conventional procedural programming languages, such as the "C" programming language or similar programming languages. The program code may execute entirely on the tenant computing device, partly on the tenant device, as a stand-alone software package, partly on the tenant computing device and partly on a remote computing device, or entirely on the remote computing device or server. In the case of remote computing devices, the remote computing devices may be connected to the tenant computing device through any kind of network, including a Local Area Network (LAN) or a Wide Area Network (WAN), or may be connected to an external computing device (e.g., through the internet using an internet service provider).

In an exemplary embodiment of the invention, there is also provided an electronic device that may include a processor and a memory for storing executable instructions of the processor. Wherein the processor is configured to perform the steps of the community group purchase server ordering method in any of the above embodiments via execution of the executable instructions.

As will be appreciated by one skilled in the art, aspects of the present invention may be embodied as a system, method or program product. Thus, various aspects of the invention may be embodied in the form of: an entirely hardware embodiment, an entirely software embodiment (including firmware, microcode, etc.) or an embodiment combining hardware and software aspects that may all generally be referred to herein as a "circuit," module "or" system.

An electronic device 500 according to this embodiment of the invention is described below with reference to fig. 8. The electronic device 500 shown in fig. 8 is only an example, and should not bring any limitation to the functions and the scope of use of the embodiments of the present invention.

As shown in fig. 8, the electronic device 500 is embodied in the form of a general purpose computing device. The components of the electronic device 500 may include, but are not limited to: at least one processing unit 510, at least one memory unit 520, a bus 530 that couples various system components including the memory unit 520 and the processing unit 510, a display unit 540, and the like.

Wherein the storage unit stores program code, which can be executed by the processing unit 510, to cause the processing unit 510 to execute the steps according to various exemplary embodiments of the present invention described in the community group buying server ordering method section above in this specification. For example, the processing unit 510 may perform the steps as shown in fig. 1.

The memory unit 520 may include readable media in the form of volatile memory units, such as a random access memory unit (RAM)5201 and/or a cache memory unit 5202, and may further include a read-only memory unit (ROM) 5203.

The memory unit 520 may also include a program/utility 5204 having a set (at least one) of program modules 5205, such program modules 5205 including, but not limited to: an operating system, one or more application programs, other program modules, and program data, each of which or some combination thereof may comprise an implementation of a network environment.

Bus 530 may be one or more of any of several types of bus structures including a memory unit bus or memory unit controller, a peripheral bus, an accelerated graphics port, a processing unit, or a local bus using any of a variety of bus architectures.

The electronic device 500 may also communicate with one or more external devices 600 (e.g., keyboard, pointing device, bluetooth device, etc.), with one or more devices that enable a tenant to interact with the electronic device 500, and/or with any devices (e.g., router, modem, etc.) that enable the electronic device 500 to communicate with one or more other computing devices. Such communication may be through input/output (I/O) interfaces 550. Also, the electronic device 500 may communicate with one or more networks (e.g., a Local Area Network (LAN), a Wide Area Network (WAN) and/or a public network, such as the Internet) via the network adapter 560. The network adapter 560 may communicate with other modules of the electronic device 500 via the bus 530. It should be appreciated that although not shown in the figures, other hardware and/or software modules may be used in conjunction with the electronic device 500, including but not limited to: microcode, device drivers, redundant processing units, external disk drive arrays, RAID systems, tape drives, and data backup storage systems, to name a few.

Through the above description of the embodiments, those skilled in the art will readily understand that the exemplary embodiments described herein may be implemented by software, or by software in combination with necessary hardware. Therefore, the technical solution according to the embodiment of the present invention may be embodied in the form of a software product, which may be stored in a non-volatile storage medium (which may be a CD-ROM, a usb disk, a removable hard disk, etc.) or on a network, and includes several instructions to enable a computing device (which may be a personal computer, a server, or a network device, etc.) to execute the above-mentioned community group purchase server ordering method according to the embodiment of the present invention.

Compared with the prior art, the invention has the advantages that:

when the server for ordering is crowded, the automatic selection of the delivery time is provided in the option of the required operation delivery time when the user orders, so that when the user orders based on the current receiving address and the delivery time is the automatic selection of the delivery time, the determined server can directly judge the corresponding delivery station according to the receiving address to judge the delivery capacity and the payment operation of the current order, and the judgment of the delivery capacity based on the delivery time is not required to be distinguished. Therefore, the problem that a server load is too high due to the fact that a large number of users place orders at the same time is avoided, and therefore the order placing failure that the delivery time is unavailable is achieved after the users select the expected delivery time and pay when placing orders, and the order placing experience of the users is improved.

Other embodiments of the invention will be apparent to those skilled in the art from consideration of the specification and practice of the invention disclosed herein. This application is intended to cover any variations, uses, or adaptations of the invention following, in general, the principles of the invention and including such departures from the present disclosure as come within known or customary practice within the art to which the invention pertains. It is intended that the specification and examples be considered as exemplary only, with a true scope and spirit of the invention being indicated by the following claims.

Claims

1. A method for ordering by a community group purchase server is characterized by comprising the following steps:

providing an automatic selection of delivery time among the options for delivery time in response to the determined compliance of the server with the set congestion condition;

2. The community group purchase server ordering method of claim 1, wherein said setting congestion conditions includes one or more of the following congestion conditions:

3. The community group purchase server ordering method according to claim 2, wherein said active users comprise:

currently operating users of the community group purchase user side; and/or

And generating a communication interaction with the determined server within a second set time period threshold.

4. The community group purchase server ordering method according to claim 1, wherein said providing an automatic selection of delivery time among the options for delivery time comprises:

an option to cancel the original time of the delivery time, automatically selecting the delivery time as an automatically selected delivery time; or alternatively

The options for the delivery time include the original time and the automatically selected delivery time.

5. The community group purchase server ordering method of claim 1, wherein said determining whether the delivery station corresponding to the shipping address has delivery capacity further comprises:

responding to the order placing time of the user, and within a third set time interval threshold after the determined server meets the set congestion condition, determining whether the corresponding distribution station has distribution capacity or not by the determined server according to whether the current accumulated amount of the distribution station meets the set total amount of the orders or not,

6. The method as claimed in claim 5, wherein the third predetermined time threshold is preset or determined according to a time period for the determined server to switch from meeting the predetermined congestion condition to meeting the predetermined idle condition.

7. The community group purchase server ordering method according to claim 5, wherein the determined server accumulates the current order of the user to the current accumulated amount of the delivery station within a fourth set time period threshold after the user completes the payment operation of the current order, and the fourth set time period threshold is preset or determined according to the third set time period threshold.

8. The community group purchase server ordering method of claim 7, wherein after a fifth set time period threshold after said user completes the payment operation for the current order, further comprising:

the determined server calculates a delivery route according to a plurality of orders of the delivery station; and

9. The community group purchase server ordering method according to claim 8, wherein said fifth set time period threshold is preset or determined according to said third set time period threshold.

10. A device for ordering by a community group purchase server is characterized by comprising:

and the payment determining module responds to a payment request of the user based on the current receiving address, and the delivery time is the automatic delivery time, so that the determined server receives the payment request of the user for the current order, the determined server judges whether the delivery station corresponding to the receiving address has delivery capacity, and if the delivery capacity exists, the order corresponding to the payment request is confirmed.

11. An electronic device, characterized in that the electronic device comprises:

a processor;

a memory having stored thereon a computer program that, when executed by the processor, performs:

the community group purchase server ordering method as claimed in any one of claims 1 to 9.

12. A storage medium having stored thereon a computer program which, when executed by a processor, performs: