CN110807654A - Commodity supply and sale price difference calculation method and system - Google Patents
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Abstract
The invention discloses a method and a system for calculating the supply and sale price difference of commodities.A movable price record import module receives a movable price record of a certain batch of commodities in a specified date range; the paid sales order extraction module is used for extracting the paid sales orders of the batch of commodities; the sales order matching module is used for matching the date range specified by the activity settlement price record with the payment time of the paid sales order record; the sales order screening module is used for extracting the orders entering the data stabilization period and matching the orders entering the data stabilization period with the sales orders in the date specified by the activity settlement price record; the supply price query module is used for querying the supply price corresponding to the sales order; and the difference calculating module is used for calculating the supply and sale difference by combining the activity price record, the extracted sales order information and the supply price information according to the difference calculating rule of each platform. The invention improves the execution efficiency and precision.
Description
Technical Field
The invention relates to the field of information processing, in particular to a commodity supply and sale price difference calculating method and a commodity supply and sale price difference calculating system.
Background
When the e-commerce company calculates the supply and sale price difference of the brand products, the sale attribute price and the supply attribute price of the order are required to be derived from the e-commerce platform and the e-commerce company, and because the sale attribute price and the supply attribute price of the order in different time periods can change, price information of different platforms in different time periods is required to be obtained when the price difference is calculated, and the screening and calculating process is complicated. In addition, a plurality of shops are generally arranged on each platform, and each shop generates a plurality of orders including payment orders, refund orders, invalid orders and the like, so that the data volume is extremely large. At present, price information of different platforms, different times and different attributes is obtained in a manual mode to carry out price difference calculation, execution efficiency is low, and errors are prone to occurring.
Disclosure of Invention
The invention aims to provide a commodity supply and sale price difference calculating method and a commodity supply and sale price difference calculating system.
The technical solution for realizing the purpose of the invention is as follows: a multi-store commodity spread calculating method comprises the following steps:
receiving the activity price record of a certain batch of commodities in a specified date range;
extracting paid sales orders of the batch of commodities;
matching the date range specified by the activity settlement price record with the payment time of the paid sales order record, and extracting the sales orders in the date specified by the activity settlement price record;
extracting an order entering a data stabilization period, matching the order entering the data stabilization period with a sales order in a date specified by the activity settlement price record, and deleting the order with refund;
and inquiring the supply price corresponding to the sales order, and combining the difference calculation rules of each platform to calculate the supply and sale difference.
In one embodiment, the imported activity price records of a certain batch of commodities are received, multi-day batch data processing is adopted, the time period from the starting time to the ending time is decomposed according to days, single-day price records are generated in batches and stored in a warehouse, and if the price records of the current day already exist, the latest price is used for covering the existing records.
In one embodiment, the drawing of the paid sales order for the batch of goods is performed periodically or aperiodically, and the time period for the query of the sales order record is related to the usage of the spread calculation.
In one embodiment, the paid sales orders for the batch of goods are extracted and synchronized to the big data platform for offline data processing.
In one embodiment, sales orders within the specified date of the active settlement price record are extracted and stored in a data table to be synchronized for later use.
In one embodiment, the data stabilization period, that is, the data change is basically completed, the refund action has occurred, the corresponding voucher has been generated and stored, and is determined according to the refund and return rule of each platform.
In one embodiment, the order entering the data stabilization period is matched with the sales order in the specified date of the active settlement price record, the order number and the sub-order number of the paid order are matched with the original order number and the atomic order number of the refund order by considering the relationship between the common payment order and the refund order, and the data of the refund order are deleted and stored in a data table to be synchronized for subsequent use.
In one embodiment, after an order for refund is deleted, order data is synchronized into the database from the data table to be synchronized, and the order data is stored into each partition in the database order table according to the date in the payment date as the partition dimension.
In one embodiment, the method further comprises a process of storing the price difference information, and when the data storage exceeds the set time, the historical data is archived, and full-text retrieval service or archived data downloading service is provided.
A multi-store item spread computing system, comprising: the system comprises an activity price record importing module, a paid sales order extracting module, a sales order matching module, a sales order screening module, a supply price inquiring module and a difference calculating module, wherein:
the activity price record importing module is used for receiving activity price records of a certain batch of commodities in a specified date range;
the paid sales order extracting module is used for extracting paid sales orders of the batch of commodities;
the sales order matching module is used for matching the date range specified by the activity settlement price record with the payment time of the paid sales order record and extracting the sales orders in the date specified by the activity settlement price record;
the sales order screening module is used for extracting orders entering a data stabilization period, matching the orders entering the data stabilization period with the sales orders in the appointed date of the activity settlement price record, and deleting the orders with refunds;
the supply price query module is used for querying a supply price corresponding to the sales order;
and the price difference calculation module is used for calculating the supply and sale price difference by combining the activity price record, the extracted sales order information and the supply price information according to the price difference calculation rule of each platform.
A computer device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, the processor implementing the following steps when executing the computer program:
receiving the activity price record of a certain batch of commodities in a specified date range;
extracting paid sales orders of the batch of commodities;
matching the date range specified by the activity settlement price record with the payment time of the paid sales order record, and extracting the sales orders in the date specified by the activity settlement price record;
extracting an order entering a data stabilization period, matching the order entering the data stabilization period with a sales order in a date specified by the activity settlement price record, and deleting the order with refund;
and inquiring the supply price corresponding to the sales order, and calculating the supply and sale price difference by combining the price difference calculation rule of each platform, the activity price record and the extracted sales order.
A computer-readable storage medium, on which a computer program is stored which, when executed by a processor, carries out the steps of:
receiving the activity price record of a certain batch of commodities in a specified date range;
extracting paid sales orders of the batch of commodities;
matching the date range specified by the activity settlement price record with the payment time of the paid sales order record, and extracting the sales orders in the date specified by the activity settlement price record;
extracting an order entering a data stabilization period, matching the order entering the data stabilization period with a sales order in a date specified by the activity settlement price record, and deleting the order with refund;
and inquiring the supply price corresponding to the sales order, and calculating the supply and sale price difference by combining the price difference calculation rule of each platform, the activity price record and the extracted sales order.
Compared with the prior art, the invention has the following remarkable advantages: the method and the system of the invention acquire the price information of different platforms, different time and different attributes by an automatic means to calculate the difference price, thereby improving the execution efficiency and precision.
Drawings
FIG. 1 is a flow chart of a method for calculating a difference between supply and sale prices of commodities according to the present invention.
FIG. 2 is a thread diagram of the calculation of the commodity supply and marketing spread in accordance with the present invention.
FIG. 3 is a schematic diagram of the calculation of the price difference between the supply and the sale of the commodities according to the invention.
Fig. 4 is a schematic structural diagram of the commodity supply and sale spread calculation system of the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the present application more apparent, the present application is described in further detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the present application and are not intended to limit the present application.
The invention discloses a spread calculation method, which relates to a user side system, a spread calculation system and an e-commerce platform system. The spread calculation is to calculate the supply and sale spread by the sales attribute price and the supply attribute price, wherein the sales attribute price includes the actual amount of money to be paid, the activity settlement price, etc., the spread calculation is applied for different purposes, and the used sales attribute price may be different. The actual money amount is generally obtained from an e-commerce platform system, and can be inquired by extracting an e-commerce platform order; the activity settlement price is set by the user side and can be imported from the user side system. The supply attribute price comes from the user side and can be inquired from a price management module such as a price service center of a user side system and the like. Because the data volume of the difference calculation is large, and the difference calculation generally aims at the financial accounting stage, the order offline screening and matching can be performed by using a big data platform, and then the data is synchronized to the difference calculation system, so as to improve the efficiency of data processing, and the specific architecture is shown in fig. 1.
The user side system, the spread computing system, the e-commerce platform system and the like cooperate with each other to jointly complete the calculation of the commodity supply and sale spread, and the specific process is shown in fig. 2-3.
Step 1, receiving activity price records of a certain batch of commodities in a specified date range;
the spread calculating system receives the activity price record of a certain batch of goods imported by the user foreground as the parameter data for calculating the spread, and in some embodiments, the imported activity price record includes information such as a goods code, an activity settlement price, a start time, an end time and the like, and other parameters can be adopted according to needs.
Regarding the import operation, a plurality of days of batch data processing may be performed according to the set data cycle. The specific implementation can adopt the following modes: and after receiving the data, decomposing the time period from the starting time to the ending time according to days, generating single-day price records in batches, and storing the records in a warehouse. At this time, if the price record of the current day already exists, the latest price is used to cover the existing record, and the activity settlement price in the same data cycle is guaranteed to be the latest data.
Step 2, extracting the paid sales orders of the batch of commodities;
the spread calculation system may query the sales order records of the corresponding batches of goods in a specific time period from the e-commerce platform system at regular or irregular time, and in some embodiments, the registered sales order records include actual payment price, payment time, goods code, and the like, and other parameters may also be adopted as needed.
The specific time period may also vary according to scene changes due to different uses of the spread calculation. For example, when the method is applied to a monthly subsidy scene, all order records with dates less than or equal to the current day and more than or equal to the date before the appointed number of compensation days are inquired.
After the query, the query result can be synchronized to the big data platform to wait for the next off-line data processing. If real-time processing is needed, the query result can be directly used for subsequent order matching operation.
Step 3, matching the date range specified by the activity settlement price record with the payment time of the paid sales order record, and extracting the sales orders in the date specified by the activity settlement price record;
in some embodiments, the big data platform matches the date range specified by the activity settlement price record with the payment time of the paid order, and after the sales order data in the time period is extracted, the sales order data is stored in a data table to be synchronized according to a specified format, such as { commodity code, sales time, activity settlement price, and actual payment price }, for subsequent use, or other parameters may be adopted as needed to specify other formats. This process may also be an online process, although the process will be performed at the spread computing system.
Step 4, extracting the order entering the data stabilization period, matching the order entering the data stabilization period with the sales order in the specified date of the activity settlement price record, and deleting the order with refund;
within a date range specified by the activity settlement price record, partial orders in the E-commerce platform system may enter a data stabilization period, namely, data change is basically completed, a refund action has occurred, a corresponding voucher has been generated and stored, the longest time period may exceed 40 days, the refund and return rules of each platform are determined, the item is a configuration item, and a relatively long date is taken according to the reconciliation rule.
Considering the relation between the common payment order and the refund order, namely the hierarchical relation of the order, the order can be extracted and stored in a big data platform, the order number and the sub-order number of the paid order are used to be matched with the original order number and the atomic order number of the refund order, and the refund order data in the time range are pulled out and stored in a data table to be synchronized for subsequent use. The principle of matching may vary for different e-commerce platform systems. Likewise, if online, the process is performed at the spread computing system.
In some embodiments, after all orders are pulled, the spread computing system synchronizes the order data from the data table to be synchronized into the database, and stores the order data into each partition in the order table of the database as a partition dimension according to the date in the payment date, so that the subsequent query efficiency is improved.
And 5, inquiring supply prices corresponding to the sales orders, and calculating supply and sale prices according to the price difference calculation rules of the platforms, the activity price records and the extracted sales orders.
And after receiving the difference price calculation command or reaching the calculation period, inquiring the supply price corresponding to the sales order from the price center, and writing back the supply price to the order information. The query conditions of the supply prices are related to the user side, some supply prices are different at different supply places, and some supply prices are unified nationwide. After the supply price corresponding to the order is obtained, the difference calculation rule of each platform is selected, the difference calculation is carried out by combining the supply price, the movable settlement price and the actual payment price, and the difference data is updated to the order information.
And 6, after the data is stored for a certain time, archiving the historical data, and providing full-text retrieval service or archived data downloading service to reduce the storage pressure of the database and improve the reading and writing performance of the database. This process may be added selectively.
The commodity supply and sale price difference computing system for implementing the method comprises an active price record importing module, a paid sales order extracting module, a sales order matching module, a sales order screening module, a supply price inquiring module and a price difference computing module, as shown in fig. 4, wherein:
the activity price record importing module is used for receiving activity price records of a certain batch of commodities in a specified date range. In some embodiments, the imported activity price record includes information such as a product code, an activity settlement price, a start time, an end time, and other parameters may be used as needed.
Regarding the import operation, a plurality of days of batch data processing may be performed according to the set data cycle. The specific implementation can adopt the following modes: and after receiving the data, decomposing the time period from the starting time to the ending time according to days, generating single-day price records in batches, and storing the records in a warehouse. At this time, if the price record of the current day already exists, the latest price is used to cover the existing record, and the activity settlement price in the same data cycle is guaranteed to be the latest data.
The paid sales order extracting module is used for extracting the paid sales orders of the batch of commodities, and generally, the sales order records of the corresponding batch of commodities in a specific time period are inquired from the e-commerce platform system at regular time or irregular time. In some embodiments, the registered sales order record includes the actual payment price, payment time, product code, etc., although other parameters may be used as desired.
The specific time period may also vary according to scene changes due to different uses of the spread calculation. For example, when the method is applied to a monthly subsidy scene, all order records with dates less than or equal to the current day and more than or equal to the date before the appointed number of compensation days are inquired.
The sales order matching module is used for matching the date range specified by the activity settlement price record with the payment time of the paid sales order record and extracting the sales orders in the date specified by the activity settlement price record. In some embodiments, after the sales order data in the time period is extracted, the sales order data is stored in a data table to be synchronized according to a specified format, such as { product code, sales time, activity settlement price, actual payment price }, for subsequent use, or other formats may be specified by using other parameters as needed.
The sales order screening module is used for extracting orders entering a data stabilization period, matching the orders entering the data stabilization period with the sales orders in the appointed date of the activity settlement price record, and deleting the orders with refunds. And the data stabilization period, namely the data change is basically completed, the refund behavior occurs, the corresponding voucher is generated and stored, the longest time period may exceed 40 days, the refund and refund behavior is determined according to refund and return rules of each platform, the refund and refund behavior is a configuration item, and a relatively long date is taken according to the reconciliation rule.
Considering the relationship between the normal payment order and the refund order, i.e., the hierarchical relationship of the orders, some embodiments extract the order, match the original order number and the atomic order number of the refund order with the order number and the sub-order number of the paid order, pull the refund order data within the time range, and store the refund order data in a data table to be synchronized for subsequent use. The principle of matching may vary for different e-commerce platform systems.
After all orders are pulled, in some embodiments, order data are synchronized into the database from the data table to be synchronized, and are stored into each partition in the database order table according to the date in the payment date as the partition dimension, so that subsequent query efficiency is improved conveniently.
The supply price query module is used for querying a supply price corresponding to the sales order. The query conditions of the supply prices are related to the user side, some supply prices are different at different supply places, and some supply prices are unified nationwide.
And the price difference calculation module is used for calculating the supply and sale price difference by combining the activity price record, the extracted sales order information and the supply price information according to the price difference calculation rule of each platform. After calculation, in some embodiments, the spread data is updated into the order information. When the data is stored for a certain time, some embodiments file the historical data, and provide full-text retrieval service or filing data downloading service to reduce the storage pressure of the database and improve the read-write performance of the database. This process can be selectively added as desired.
The present invention also provides a computer device, including a memory, a processor, and a computer program stored on the memory and executable on the processor, wherein the processor implements the following steps when executing the computer program:
receiving the activity price record of a certain batch of commodities in a specified date range;
extracting paid sales orders of the batch of commodities;
matching the date range specified by the activity settlement price record with the payment time of the paid sales order record, and extracting the sales orders in the date specified by the activity settlement price record;
extracting an order entering a data stabilization period, matching the order entering the data stabilization period with a sales order in a date specified by the activity settlement price record, and deleting the order with refund;
and inquiring the supply price corresponding to the sales order, and calculating the supply and sale price difference by combining the price difference calculation rule of each platform, the activity price record and the extracted sales order.
A computer-readable storage medium, on which a computer program is stored which, when executed by a processor, carries out the steps of:
receiving the activity price record of a certain batch of commodities in a specified date range;
extracting paid sales orders of the batch of commodities;
matching the date range specified by the activity settlement price record with the payment time of the paid sales order record, and extracting the sales orders in the date specified by the activity settlement price record;
extracting an order entering a data stabilization period, matching the order entering the data stabilization period with a sales order in a date specified by the activity settlement price record, and deleting the order with refund;
and inquiring the supply price corresponding to the sales order, and calculating the supply and sale price difference by combining the price difference calculation rule of each platform, the activity price record and the extracted sales order.
It will be understood by those skilled in the art that all or part of the processes of the methods of the embodiments described above can be implemented by hardware instructions of a computer program, which can be stored in a non-volatile computer-readable storage medium, and when executed, can include the processes of the embodiments of the methods described above. Any reference to memory, storage, database, or other medium used in the embodiments provided herein may include non-volatile and/or volatile memory, among others. Non-volatile memory can include read-only memory (ROM), Programmable ROM (PROM), Electrically Programmable ROM (EPROM), Electrically Erasable Programmable ROM (EEPROM), or flash memory. Volatile memory can include Random Access Memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in a variety of forms such as Static RAM (SRAM), Dynamic RAM (DRAM), Synchronous DRAM (SDRAM), Double Data Rate SDRAM (DDRSDRAM), Enhanced SDRAM (ESDRAM), Synchronous Link DRAM (SLDRAM), Rambus Direct RAM (RDRAM), direct bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM).
The technical features of the above embodiments can be arbitrarily combined, and for the sake of brevity, all possible combinations of the technical features in the above embodiments are not described, but should be considered as the scope of the present specification as long as there is no contradiction between the combinations of the technical features.
The above-mentioned embodiments only express several embodiments of the present application, and the description thereof is more specific and detailed, but not construed as limiting the scope of the invention. It should be noted that, for a person skilled in the art, several variations and modifications can be made without departing from the concept of the present application, which falls within the scope of protection of the present application. Therefore, the protection scope of the present patent shall be subject to the appended claims.
Claims (12)
1. A commodity supply and sale price difference calculation method is characterized by comprising the following steps:
receiving the activity price record of a certain batch of commodities in a specified date range;
extracting paid sales orders of the batch of commodities;
matching the date range specified by the activity settlement price record with the payment time of the paid sales order record, and extracting the sales orders in the date specified by the activity settlement price record;
extracting an order entering a data stabilization period, matching the order entering the data stabilization period with a sales order in a date specified by the activity settlement price record, and deleting the order with refund;
and inquiring the supply price corresponding to the sales order, and calculating the supply and sale price difference by combining the price difference calculation rule of each platform, the activity price record and the extracted sales order.
2. The method according to claim 1, wherein the method comprises receiving an activity price record of a certain batch of imported commodities, performing multi-day batch data processing, decomposing a time period from a start time to an end time by day, generating a single-day price record in batch and storing the single-day price record in a warehouse, and if the current-day price record exists, covering the existing record with the latest price.
3. The method of claim 1, wherein the drawing of the paid sales order for the batch of goods is performed periodically or aperiodically, and the time period for searching the sales order record is related to the purpose of the spread calculation.
4. The method as claimed in claim 1, wherein the paid sales orders of the batch of commodities are extracted and synchronized to a big data platform for offline data processing.
5. The method of claim 1, wherein the sales orders within the specified date of the active settlement price record are extracted and stored in a data table to be synchronized for subsequent use.
6. The method as claimed in claim 1, wherein the data stabilization period is a period in which data change is substantially completed, refund behavior has occurred, and corresponding voucher has been generated and stored, and is determined according to refund and return rules of each platform.
7. The method according to claim 1, wherein the order entering the data stabilization period is matched with the sales order within the specified date of the active settlement price record, the order number and the sub-order number of the paid order are matched with the original order number and the atomic order number of the refund order in consideration of the relationship between the general payment order and the refund order, and the refund order data is deleted and stored in a data table to be synchronized for subsequent use.
8. The method according to claim 1, wherein after the order for which the refund has occurred is deleted, the order data is synchronized into the database from the data table to be synchronized, and stored into each partition in the database order table as a partition dimension according to the date of the payment date.
9. The method of claim 1, further comprising a step of storing the price difference information, and when the data storage exceeds a predetermined time, archiving the historical data, and providing a full-text search service or an archived data download service.
10. A commodity supply and sale spread calculation system, comprising: the system comprises an activity price record importing module, a paid sales order extracting module, a sales order matching module, a sales order screening module, a supply price inquiring module and a difference calculating module, wherein:
the activity price record importing module is used for receiving activity price records of a certain batch of commodities in a specified date range;
the paid sales order extracting module is used for extracting paid sales orders of the batch of commodities;
the sales order matching module is used for matching the date range specified by the activity settlement price record with the payment time of the paid sales order record and extracting the sales orders in the date specified by the activity settlement price record;
the sales order screening module is used for extracting orders entering a data stabilization period, matching the orders entering the data stabilization period with the sales orders in the appointed date of the activity settlement price record, and deleting the orders with refunds;
the supply price query module is used for querying a supply price corresponding to the sales order;
and the price difference calculation module is used for calculating the supply and sale price difference by combining the activity price record, the extracted sales order information and the supply price information according to the price difference calculation rule of each platform.
11. A computer device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, characterized in that the steps of the method of any of claims 1 to 9 are implemented when the computer program is executed by the processor.
12. A computer-readable storage medium, on which a computer program is stored, which, when being executed by a processor, carries out the steps of the method of any one of claims 1 to 9.
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| CN112667645A (en) * | 2021-01-22 | 2021-04-16 | 北京天健源达科技股份有限公司 | Method for processing sent medicine record |
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| CN113592576A (en) * | 2021-06-18 | 2021-11-02 | 青岛海尔科技有限公司 | Order control method and device |
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