CN111127171A - Order data processing method, device, equipment and computer readable storage medium - Google Patents
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Abstract
The invention discloses an order data processing method, a device, equipment and a computer readable storage medium, wherein the method comprises the following steps: when the execution time of a preset timing task is reached, reading order data generated in the execution period of the preset timing task; classifying the order data to generate commodity type information; and determining a data source corresponding to each commodity type information according to a preset corresponding relation between the data source and the type, and sharing each commodity type information to the corresponding data source. The order data are classified and processed through the preset timing task, the required information of each commodity type is automatically obtained, and statistical classification of service personnel is avoided; meanwhile, according to the preset corresponding relation representing various commodities and sources thereof, the commodity type information is shared, batch distribution of various commodities is realized, and the distribution efficiency is improved.
Description
Technical Field
The present invention relates to the field of internet technologies, and in particular, to a method, an apparatus, a device, and a computer-readable storage medium for processing order data.
Background
The development of the internet technology brings great convenience to the life of people, more and more people tend to shop through an internet platform, and the rapid development of internet shopping is promoted. Currently, internet shopping usually adopts a purchasing mode of allocating goods according to needs, a purchasing direction places an order at a third party registered on an internet shopping platform to generate a shopping order, and the third party allocates goods to a supplier according to needs according to the shopping order so as to avoid overstock of goods caused by too many allocation goods.
However, in the current market, the third-party service personnel counts the information of the goods to be distributed, the types, the quantity and the like, and under the condition that the types of the goods to be distributed are more, the goods to be distributed need to be classified and counted according to different suppliers, so that the consumed labor cost is high, and the goods distribution efficiency is low.
Disclosure of Invention
The invention mainly aims to provide an order data processing method, an order data processing device, order data processing equipment and a computer readable storage medium, and aims to solve the technical problems of low goods allocation efficiency and high labor cost caused by statistical goods allocation performed by a third-party service staff in the prior art.
In order to achieve the above object, the present invention provides an order data processing method, including the steps of:
when the execution time of a preset timing task is reached, reading order data generated in the execution period of the preset timing task;
classifying the order data to generate commodity type information;
and determining a data source corresponding to each commodity type information according to a preset corresponding relation between the data source and the type, and sharing each commodity type information to the corresponding data source.
Optionally, the step of classifying each order data to generate article type information includes:
reading the type code of each order data, classifying each order data according to each type code, and generating a commodity type group;
and determining attribute information of each of the commodity type groups according to the attribute code corresponding to each of the commodity type groups, and determining the attribute information of each of the commodity type groups as the commodity type information.
Optionally, the step of determining a data source corresponding to each of the commodity type information according to a preset correspondence between a data source and a type includes:
comparing each commodity type information with the corresponding relation, and searching a data source corresponding to each commodity type information in the corresponding relation to serve as the data source corresponding to each commodity type information.
Optionally, the step of determining a data source corresponding to each of the article type information is followed by:
displaying a data source corresponding to each of the commodity type information;
the step of sharing each of the commodity type information to the corresponding data source includes:
and receiving a sharing instruction sent by each displayed data source, and sharing each commodity type information to the corresponding data source according to the sharing instruction.
Optionally, the step of displaying the data source corresponding to each of the article type information includes:
receiving modification instructions sent by all the displayed data sources, and determining target data sources in all the displayed data sources according to the modification instructions;
and skipping a modification interface corresponding to the target data source to modify the target data source.
Optionally, the step of sharing each piece of commodity type information to the corresponding data source includes:
and reading the sharing time of each commodity type information, and updating each displayed data source according to each sharing time.
Optionally, the step of sharing each piece of commodity type information to the corresponding data source includes:
when a batch export instruction is received, reading time information in the export instruction;
screening the historically shared commodity type information according to the time information, and determining target type information corresponding to the time information;
and adding each target type information into a preset format file to generate a target file export.
Further, to achieve the above object, the present invention also provides an order data processing apparatus, including:
the reading module is used for reading order data generated in the execution period of a preset timing task when the execution time of the preset timing task is reached;
the classification module is used for classifying the order data to generate commodity type information;
and the sharing module is used for determining a data source corresponding to each commodity type information according to a preset corresponding relation between the data source and the type, and sharing each commodity type information to the corresponding data source.
Further, to achieve the above object, the present invention also provides an order data processing device, which includes a memory, a processor and an order data processing program stored on the memory and executable on the processor, wherein the order data processing program, when executed by the processor, implements the steps of the order data processing method as described above.
Further, to achieve the above object, the present invention also provides a computer readable storage medium having stored thereon an order data processing program, which when executed by a processor, implements the steps of the order data processing method as described above.
The order data processing method of the invention presets a preset timing task and an execution time thereof for order data processing, and when the execution time is reached, reads order data generated in the execution period of the preset timing task for classification processing, and generates commodity type information of a required commodity represented by each order data; and determining a data source corresponding to each commodity type information for sharing according to a preset corresponding relation between the data source and the type, wherein the data source corresponding to each commodity type information is a source of the commodity represented by each commodity type information. Therefore, the order data are classified and processed through the preset timing task, the required type information of each commodity is automatically obtained, and statistical classification of service personnel is avoided; meanwhile, according to the preset corresponding relation representing various commodities and sources thereof, the commodity type information is shared, batch distribution of various commodities is realized, and the distribution efficiency is improved.
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FIG. 1 is a schematic diagram of a hardware operating environment of an order data processing apparatus according to an embodiment of the present invention;
FIG. 2 is a flowchart illustrating a first embodiment of an order data processing method according to the present invention;
FIG. 3 is a functional block diagram of an order data processing apparatus according to a preferred embodiment of the present invention.
The implementation, functional features and advantages of the objects of the present invention will be further explained with reference to the accompanying drawings.
Detailed Description
It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.
The invention provides order data processing equipment, and referring to fig. 1, fig. 1 is a schematic structural diagram of an equipment hardware operating environment according to an embodiment of the order data processing equipment of the invention.
As shown in fig. 1, the order data processing apparatus may include: a processor 1001, such as a CPU, a communication bus 1002, a user interface 1003, a network interface 1004, and a memory 1005. Wherein a communication bus 1002 is used to enable connective communication between these components. The user interface 1003 may include a Display screen (Display), an input unit such as a Keyboard (Keyboard), and the optional user interface 1003 may also include a standard wired interface, a wireless interface. The network interface 1004 may optionally include a standard wired interface, a wireless interface (e.g., WI-FI interface). The memory 1005 may be a high-speed RAM memory or a non-volatile memory (e.g., a magnetic disk memory). The memory 1005 may alternatively be a memory device separate from the processor 1001 described above.
Those skilled in the art will appreciate that the hardware configuration of the order data processing apparatus shown in fig. 1 does not constitute a limitation of the order data processing apparatus, and may include more or less components than those shown, or combine some of the components, or a different arrangement of components.
As shown in fig. 1, a memory 1005, which is a kind of computer-readable storage medium, may include therein an operating system, a network communication module, a user interface module, and an order data processing program. The operating system is a program for managing and controlling order data processing equipment and software resources and supports the running of a network communication module, a user interface module, an order data processing program and other programs or software; the network communication module is used to manage and control the network interface 1004; the user interface module is used to manage and control the user interface 1003.
In the hardware structure of the order data processing device shown in fig. 1, the network interface 1004 is mainly used for connecting to a background server and performing data communication with the background server; the user interface 1003 is mainly used for connecting a client (user side) and performing data communication with the client; the processor 1001 may call the order data handler stored in the memory 1005 and perform the following operations:
when the execution time of a preset timing task is reached, reading order data generated in the execution period of the preset timing task;
classifying the order data to generate commodity type information;
and determining a data source corresponding to each commodity type information according to a preset corresponding relation between the data source and the type, and sharing each commodity type information to the corresponding data source.
Further, the step of classifying each of the order data to generate article type information includes:
reading the type code of each order data, classifying each order data according to each type code, and generating a commodity type group;
and determining attribute information of each of the commodity type groups according to the attribute code corresponding to each of the commodity type groups, and determining the attribute information of each of the commodity type groups as the commodity type information.
Further, the step of determining a data source corresponding to each of the commodity type information according to a preset correspondence between a data source and a type includes:
comparing each commodity type information with the corresponding relation, and searching a data source corresponding to each commodity type information in the corresponding relation to serve as the data source corresponding to each commodity type information.
Further, after the step of determining the data source corresponding to each of the commodity type information, the processor 1001 may call an order data processing program stored in the memory 1005, and perform the following operations:
displaying a data source corresponding to each of the commodity type information;
the step of sharing each of the commodity type information to the corresponding data source includes:
and receiving a sharing instruction sent by each displayed data source, and sharing each commodity type information to the corresponding data source according to the sharing instruction.
Further, after the step of displaying the data sources corresponding to the respective commodity type information, the processor 1001 may call the order data processing program stored in the memory 1005, and perform the following operations:
receiving modification instructions sent by all the displayed data sources, and determining target data sources in all the displayed data sources according to the modification instructions;
and skipping a modification interface corresponding to the target data source to modify the target data source.
Further, after the step of sharing the information of each commodity type to the corresponding data source, the processor 1001 may call an order data processing program stored in the memory 1005, and perform the following operations:
and reading the sharing time of each commodity type information, and updating each displayed data source according to each sharing time.
Further, after the step of sharing the information of each commodity type to the corresponding data source, the processor 1001 may call an order data processing program stored in the memory 1005, and perform the following operations:
when a batch export instruction is received, reading time information in the export instruction;
screening the historically shared commodity type information according to the time information, and determining target type information corresponding to the time information;
and adding each target type information into a preset format file to generate a target file export.
The specific implementation of the order data processing device of the present invention is substantially the same as the following embodiments of the order data processing method, and is not described herein again.
The invention also provides an order data processing method.
Referring to fig. 2, fig. 2 is a flowchart illustrating a first embodiment of an order data processing method according to the present invention.
While a logical order is shown in the flow chart, in some cases, the steps shown or described may be performed in an order different than that shown or described herein. Specifically, the order data processing method in this embodiment includes:
step S10, when the execution time of the preset timing task is reached, reading order data generated in the execution period of the preset timing task;
the order data processing method in the embodiment is applied to the server, and is suitable for performing classification statistical processing on order data through the server so as to classify commodities in the order data, share classified commodity type information to a data source corresponding to each type of commodity, and perform batch distribution. The system comprises a server, a third party terminal and a server, wherein the server is connected with the third party terminal formed by an internet shopping platform, the third party is a user or an enterprise for realizing the requirement of buying goods from a supplier by a buyer, and the third party terminal is a terminal which is used for displaying a buyer shopping request received by the server by the user or the enterprise and distributing goods to the supplier through the server according to the shopping requirement; the mobile phone can be a mobile phone, and can also be intelligent equipment such as a tablet personal computer.
Further, the buyer initiates a shopping demand to a third party to perform ordering operation. When receiving order placing information corresponding to the order placing operation, the server generates order placing information into order placing information; at least comprises the attributes of the size, color, quantity and the like of the goods purchased by the buyer for placing an order, and the recipient information such as the recipient address, the recipient contact phone and the like. And sending the order information to a third-party terminal for display so as to represent the status of the currently received order. Meanwhile, data representing the commodity attributes in the order information is used as order data, a preset timing task for processing the order data is preset in the server, the preset timing task comprises an execution period and execution time, and the execution period and the execution time are preset according to requirements. If the server receives a lot of order information, a short execution period may be set, for example, one day is used as one execution period, and the execution time is a certain time point in one day, for example, six pm every day. If the order information received by the server is less, a relatively long execution period may be set, for example, two days are used as one execution period, and the execution time is a certain time point in the next day, for example, six pm in the next day.
Furthermore, when the execution time of the preset task is detected, the server reads the order data generated in the execution period of the preset task so as to process the order data of the order information newly generated in the execution period and avoid repeated processing of the order data generated in the past execution period. The server records the generation time of each order information in the process of generating the order information from the order information of the buyer, so that the order data can be read according to the generation time. And if the generation time of certain order information is not in the current execution cycle, not reading the order data in the order information. In addition, the order information can be arranged according to the sequence of the generation time, the generation time of each order information is detected one by one, once the generation time of a certain order information is detected not to be in the current execution cycle, the generation time of the order information arranged behind is not detected, and the order data of each order information arranged ahead is taken as the order data generated in the current execution cycle for reading operation.
Step S20, classifying each of the order data to generate commodity type information;
further, according to the commodities represented by the order information, the order data from the orders are classified, the order data representing the same commodity are classified into one class, meanwhile, the commodities with the same size and color in the same class of commodities are classified again according to the size and the color of the commodity, and the commodity type information is generated. If the order data D1 is a computer with a model B1 of A1, the order data D2 is a computer with a model B2 of A1, the order data D3 is a computer with a model B2 of A1, and the order data D4 is a mobile phone with a model C of A2; when classifying, firstly, the order data D1, D2 and D3 of the A1 brand computer are classified into a type of W1, the order data D4 of the A2 brand mobile phone is classified into a type of W2, then the W1 is classified according to the computer attributes, the D1 and the D3 are classified into a type, and finally, commodity type information representing that 2 computers of A1 brand and B1 model, 1 computer of A1 brand and B2 model and 1 mobile phone of A2 brand and C model are purchased is generated.
It should be noted that the commodities represented by the order data are distinguished by type codes, that is, different types of commodities have different type codes, and the type codes exist in the order data; therefore, order data representing the same commodity can be classified into one class through the type code, and commodity type information is generated through classification. Specifically, the step of classifying each order data and generating the commodity type information includes:
step S21, reading the type code of each order data, classifying each order data according to each type code, and generating a commodity type group;
step S22 is a step of determining attribute information of each of the product type groups based on the attribute code corresponding to each of the product type groups, and determining the attribute information of each of the product type groups as the product type information.
Further, the type codes carried by the order data are read, the order data are classified according to the type codes carried by the order data, the order data with the same type codes are classified into one type, and a plurality of commodity type groups corresponding to various commodities are generated. The commodity type represented by the order data is consistent with the quantity of the commodity type groups, one commodity type group corresponds to one class of commodities, and the order data in the same commodity type group represents the same class of commodities.
Understandably, the same type of merchandise has different attributes, as if the same style of clothing had different sizes or colors, etc. Therefore, although the order data in the same commodity type group represents the same type of commodity, the attributes of the commodities contained in the same type of commodity are different, if the order data W1 in a certain commodity data group corresponds to the large size of green clothes, and the order data W2 in the certain commodity data group corresponds to the small size of yellow clothes. In order to accurately classify and process order data, accurate goods allocation is realized; after classifying the order data into each commodity type group, each commodity type group continues to be classified. Specifically, various attribute identifications of commodities represented by individual order data in the commodity type group are read and arranged according to a preset format to generate an attribute code of the order data in the commodity type group. As for the above order data W1, if the attribute of green clothes is identified as f1, the attribute of large size is identified as f2, and the preset format is such that the color attribute is arranged before the size, the generated attribute is encoded as f1f 2. And after each order data in the commodity type data group generates respective attribute code, determining each attribute code as the attribute code corresponding to the commodity type group. And determining attribute information of the commodity type group according to the corresponding attribute codes, and reflecting different attributes of the same type of commodities in the commodity type group and the required quantity of various types of attribute commodities. After each commodity type group determines the corresponding attribute information in this way, that is, the attribute information of each commodity type group is determined as the commodity type information obtained by classifying the order data, and the commodity types required by each order in the execution cycle, and different attributes and the quantity of each type of commodity are reflected.
Step S30, determining a data source corresponding to each of the commodity type information according to a preset correspondence between data sources and types, and sharing each of the commodity type information to the corresponding data source.
Furthermore, the server is preset with a corresponding relation between the data source and the type, wherein the data source is a commodity source party, the type is a commodity type, and the corresponding relation between the data source and the type represents the source of various commodities distributed by the third party. After determining the type of the commodity required in the execution cycle and the attribute and quantity thereof, the data source corresponding to each commodity type information, namely the source of each required commodity can be determined according to the corresponding relationship. And sharing the commodity type information to the corresponding data source to inform the commodity types, attributes and quantity required by various commodity sources, so as to realize batch distribution of order data in the execution period. The step of determining the data source corresponding to each commodity type information according to the corresponding relation between the preset data source and the type comprises the following steps:
step S31, comparing each of the commodity type information with the corresponding relationship, and searching a data source corresponding to each of the commodity type information in the corresponding relationship as a data source corresponding to each of the commodity type information.
Furthermore, in the process of determining the data source corresponding to each commodity type information according to the corresponding relationship, the commodity type information in one commodity type group is read first, and is compared with the type in the corresponding relationship, the target type corresponding to the corresponding relationship in the corresponding relationship is searched, and then the data source corresponding to the target type in the corresponding relationship is determined as the data source corresponding to the commodity type information in the corresponding relationship. And after the data source corresponding to the corresponding relation is found in each commodity type group, obtaining the data source corresponding to each commodity type information.
In addition, considering that a certain type of commodity may correspond to multiple sources, namely, the corresponding relationship between the data source and the type, there may be a case where one type corresponds to multiple data sources; if a computer of a certain type is available from both suppliers a and B, the computer of the type corresponds to two data sources. Therefore, in the process of determining the data source corresponding to each commodity type information according to the corresponding relation, the situation that the same commodity type information corresponds to a plurality of data sources needs to be processed. Specifically, after the target type is found in the corresponding relationship according to the commodity type information, if the target type corresponds to a plurality of data sources in the corresponding relationship, the data source corresponding to the commodity type information in the corresponding relationship is determined according to the number of times of the data source shared before the commodity type information. If the target type corresponds to the data sources P1 and P2 in the corresponding relationship, if the number of sharing times of the commodity type information to the data source P1 before is 3, and the number of sharing times of the commodity type information to the data source P2 is 2, the data source P1 is determined to be the data source corresponding to the commodity type information. In addition, a latest sharing data source mechanism may be set, that is, in a case where the target type corresponds to a plurality of data sources, a data source to which the commodity type information is most recently shared is determined as a data source corresponding to the latest sharing data source. Under the condition that one type corresponds to a plurality of data sources, the data source required to be shared by the commodity type information is determined through the most sharing times or the most recently shared data source, and the accuracy of determining the data source corresponding to the commodity type information is facilitated.
The order data processing method of the invention presets a preset timing task and an execution time thereof for order data processing, and when the execution time is reached, reads order data generated in the execution period of the preset timing task for classification processing, and generates commodity type information of a required commodity represented by each order data; and determining a data source corresponding to each commodity type information for sharing according to a preset corresponding relation between the data source and the type, wherein the data source corresponding to each commodity type information is a source of the commodity represented by each commodity type information. Therefore, the order data are classified and processed through the preset timing task, the required type information of each commodity is automatically obtained, and statistical classification of service personnel is avoided; meanwhile, according to the preset corresponding relation representing various commodities and sources thereof, the commodity type information is shared, batch distribution of various commodities is realized, and the distribution efficiency is improved.
Further, a second embodiment of the order data processing method of the present invention is provided.
The second embodiment of the order data processing method differs from the first embodiment of the order data processing method in that the step of determining a data source corresponding to each of the commodity type information includes, after the step of:
step S32 of displaying a data source corresponding to each of the commodity type information;
the step of sharing each of the commodity type information to the corresponding data source includes:
step S33, receiving a sharing instruction sent by each displayed data source, and sharing each piece of commodity type information to the corresponding data source according to the sharing instruction.
The implementation shares the determined data sources corresponding to the commodity type information in a mode selected by a third party. Specifically, after the data sources corresponding to the commodity type information are determined according to the corresponding relationship, the data sources and the commodity type information needing to be shared to the data sources are displayed on a display device of a third-party terminal so as to be selectively shared by a third party. Each commodity type information and the corresponding data source are provided with a sharing button, and a third party triggers the sharing button to send a sharing instruction. And when the server receives the sharing instruction generated based on the displayed data sources, the server shares the commodity type information associated with the button to the data source corresponding to the button.
Understandably, the data source corresponding to each commodity type information determined by the corresponding relation may not be the data source required by the third party, i.e. the required commodity source; at this time, the present embodiment is provided with a modification mechanism for the data source corresponding to the commodity type information. Specifically, the step of displaying the data source corresponding to each item type information includes:
step S34, receiving modification instructions sent by each displayed data source, and determining target data sources in each displayed data source according to the modification instructions;
and step S35, jumping to a modification interface corresponding to the target data source to modify the target data source.
Further, the modification mode of the embodiment may be a real-time modification operation during sharing, or a setting operation before sharing. The setting operation before sharing is substantially to update the corresponding relation between the data source and the type, and more data sources are set for the type to serve as commodity source parties. For real-time modification, besides the sharing button, each commodity type information and the data source corresponding to each commodity type information are also provided with a modification button. And triggering a modification button before triggering the sharing button, and sending a modification instruction to the server, so that the data source corresponding to the commodity type information can be modified. And when receiving the modification instruction, the server determines the data source to which the modification is directed according to the data source identifier carried in the modification instruction, and determines the data source as a target data source in all the displayed data sources. And then jumping to a modification interface preset aiming at the target data source so as to reselect and set the commodity source party. And inputting the required data source into an input box of the modification interface, and triggering a confirmation modification button which is used for initiating a confirmation modification request to the server in the modification interface. When the server receives the modification confirmation request, the target data source is modified into the data source input through the input box and displayed, so that the target commodity type information associated with the target data source is shared through the modified data source. And then, a corresponding relation is formed between the modified data source and the target commodity type information, namely, the corresponding relation is updated, so that the commodity type information can be conveniently shared through the updated corresponding relation, and the requirements of the user on the commodity source side can be better met.
Furthermore, after the implementation shares the commodity type information with the respective corresponding data source, the state of the displayed commodity type information is changed into the shared state, and the shared state is correspondingly displayed with the respective shared data source so as to represent the data source shared by the commodity type information. And simultaneously reading the sharing time, and displaying the read sharing time, the shared commodity type information and the shared data source together so as to update the displayed data and represent the time of sharing the commodity type information to the corresponding data source.
According to the embodiment, the sharing operation and the modification operation are respectively realized by setting the sharing instruction and the modification instruction, so that the data source shared by the commodity type information is a commodity source side required, and the goods distribution requirement is better met.
Further, a third embodiment of the order data processing method of the present invention is provided.
The third embodiment of the order data processing method is different from the first or second embodiment of the order data processing method in that the step of sharing each item type information to the corresponding data source includes:
step S40, when receiving batch export instruction, reading the time information in the export instruction;
step S50, according to the time information, screening each commodity type information which is historically shared, and determining target type information corresponding to the time information;
step S60, adding each piece of target type information to a preset format file, and generating a target file export.
The embodiment is provided with a export backup mechanism for the shared commodity type information, so that the list of the goods is locally saved. Specifically, a batch export time selection button is arranged in a display interface for displaying the data source. When the server receives the batch export instruction triggered by the button, the time information in the batch export instruction is read to represent the time range of the commodity type information required to be exported. If the time selected by the time selection key is 1 month, it indicates that the derivation operation needs to be performed on the information of each commodity type shared in one month before the current time; if the selected time is 2 months, it is indicated that the derivation operation needs to be performed on each commodity type information shared in two months before the current time, and the specific time information is set according to the time selection key.
Further, screening the historically shared commodity type information according to the time information, reading the sharing time of the commodity type information, judging whether the sharing time of the commodity type information is within the time range represented by the time information one by one, if so, taking the commodity type information as target type information corresponding to the time information, and if not, taking the commodity type information as the commodity type information needing to be exported.
Furthermore, a preset format file, such as an Excel file or a word file, is preset. After finding out each target type information meeting the time information requirement, each target type information is added into a preset format file, and a target file export is generated, so that backup storage of each commodity type information shared in the time range represented by the time information is realized.
According to the embodiment, the backup mechanism of the shared commodity type information is arranged, so that the commodity type information is backed up and stored, the subsequent statistics and summarization of the commodity type information are facilitated, the checking and checking are facilitated, and the commodity type information is prevented from being lost.
The invention also provides an order data processing device.
Referring to fig. 3, fig. 3 is a functional module diagram of the order data processing apparatus according to the first embodiment of the present invention.
The order data processing apparatus includes:
the reading module 10 is configured to read order data generated in an execution period of a preset timing task when the execution time of the preset timing task is reached;
a classification module 20, configured to classify each of the order data to generate commodity type information;
the sharing module 30 is configured to determine a data source corresponding to each piece of commodity type information according to a preset correspondence between a data source and a type, and share each piece of commodity type information to the corresponding data source.
Further, the classification module 20 includes:
the classification unit is used for reading the type code of each order data, classifying each order data according to each type code and generating a commodity type group;
and the determining unit is used for determining the attribute information of each commodity type group according to the attribute code corresponding to each commodity type group, and determining the attribute information of each commodity type group as the commodity type information.
Further, the sharing module 30 includes:
and the searching unit is used for comparing each commodity type information with the corresponding relation, and searching a data source corresponding to each commodity type information in the corresponding relation to serve as the data source corresponding to each commodity type information.
Further, the sharing module 30 further includes:
a display unit for displaying a data source corresponding to each of the commodity type information;
and the sharing unit is used for receiving a sharing instruction sent by each displayed data source and sharing each commodity type information to the corresponding data source according to the sharing instruction.
Further, the sharing module 30 further includes:
the receiving unit is used for receiving modification instructions sent by all the displayed data sources and determining target data sources in all the displayed data sources according to the modification instructions;
and the modification unit is used for skipping a modification interface corresponding to the target data source so as to modify the target data source.
Further, the sharing module 30 further includes:
and the updating unit is used for reading the sharing time of each commodity type information and updating each displayed data source according to each sharing time.
Further, the order data processing apparatus further includes:
the reading module is used for reading the time information in the export instruction when receiving the batch export instruction;
the screening module is used for screening the historically shared commodity type information according to the time information and determining target type information corresponding to the time information;
and the generating module is used for adding each target type information into a preset format file to generate a target file export.
The specific implementation of the device for guiding queuing of the present invention is basically the same as that of each embodiment of the method for guiding queuing, and is not described herein again.
In addition, the embodiment of the invention also provides a computer readable storage medium.
The computer readable storage medium has stored thereon an order data processing program which, when executed by a processor, implements the steps of the order data processing method as described above.
The specific implementation manner of the computer-readable storage medium of the present invention is substantially the same as that of the above-mentioned embodiments of the order data processing method, and is not described herein again.
The present invention is described in connection with the accompanying drawings, but the present invention is not limited to the above embodiments, which are only illustrative and not restrictive, and those skilled in the art can make various changes without departing from the spirit and scope of the invention as defined by the appended claims, and all changes that come within the meaning and range of equivalency of the specification and drawings that are obvious from the description and the attached claims are intended to be embraced therein.
Claims (10)
1. An order data processing method, characterized by comprising the steps of:
when the execution time of a preset timing task is reached, reading order data generated in the execution period of the preset timing task;
classifying the order data to generate commodity type information;
and determining a data source corresponding to each commodity type information according to a preset corresponding relation between the data source and the type, and sharing each commodity type information to the corresponding data source.
2. The order data processing method according to claim 1, wherein the step of classifying each of the order data to generate article type information comprises:
reading the type code of each order data, classifying each order data according to each type code, and generating a commodity type group;
and determining attribute information of each of the commodity type groups according to the attribute code corresponding to each of the commodity type groups, and determining the attribute information of each of the commodity type groups as the commodity type information.
3. The order data processing method according to claim 1, wherein the step of determining a data source corresponding to each of the commodity type information according to a preset correspondence between data sources and types includes:
comparing each commodity type information with the corresponding relation, and searching a data source corresponding to each commodity type information in the corresponding relation to serve as the data source corresponding to each commodity type information.
4. The order data processing method according to claim 1, wherein the step of determining a data source corresponding to each of the commodity type information is followed by:
displaying a data source corresponding to each of the commodity type information;
the step of sharing each of the commodity type information to the corresponding data source includes:
and receiving a sharing instruction sent by each displayed data source, and sharing each commodity type information to the corresponding data source according to the sharing instruction.
5. The order data processing method according to claim 4, wherein said step of displaying a data source corresponding to each of said article type information is followed by:
receiving modification instructions sent by all the displayed data sources, and determining target data sources in all the displayed data sources according to the modification instructions;
and skipping a modification interface corresponding to the target data source to modify the target data source.
6. The order data processing method according to claim 4, wherein the step of sharing each of the commodity type information to the corresponding data source is followed by:
and reading the sharing time of each commodity type information, and updating each displayed data source according to each sharing time.
7. The order data processing method according to any one of claims 1 to 6, wherein the step of sharing each of the commodity type information to the corresponding data source is followed by:
when a batch export instruction is received, reading time information in the export instruction;
screening the historically shared commodity type information according to the time information, and determining target type information corresponding to the time information;
and adding each target type information into a preset format file to generate a target file export.
8. An order data processing apparatus, characterized by comprising:
the reading module is used for reading order data generated in the execution period of a preset timing task when the execution time of the preset timing task is reached;
the classification module is used for classifying the order data to generate commodity type information;
and the sharing module is used for determining a data source corresponding to each commodity type information according to a preset corresponding relation between the data source and the type, and sharing each commodity type information to the corresponding data source.
9. An order data processing apparatus, characterized in that the order data processing apparatus comprises a memory, a processor and an order data processing program stored on the memory and executable on the processor, which when executed by the processor implements the steps of the order data processing method according to any one of claims 1 to 7.
10. A computer-readable storage medium, characterized in that the computer-readable storage medium has stored thereon an order data processing program which, when executed by a processor, implements the steps of the order data processing method according to any one of claims 1 to 7.
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