Expired data archiving method and device

Abstract

The invention relates to an expired data archiving method and device, and the method comprises the steps: extracting expired data in a business system, and temporarily storing the expired data in a preset transfer data table; deleting the expired data from the service system; and transferring the expired data in the transfer data table to a preset archiving database. According to the scheme, the expired data in the service system is deleted and archived, it is guaranteed that only effective data is stored in the service system, and therefore the data size stored in the service system is reduced, and system performance reduction caused by violent increase of the data size is avoided; the expired data is transferred into another archiving database, normal operation of a business system is not affected, and meanwhile historical data query service can be provided.

Description

technical field [0001] This application relates to the field of big data technology, and in particular to a method and device for archiving expired data. Background technique [0002] The e-commerce industry has a large amount of commodity SKUs (Stock Keeping Units, stock keeping units). At the same time, a large amount of price data is maintained every day, and the amount of accumulated data is huge. If the expired price data is not processed, the amount of price data in the price system will become larger and larger. Currently, data is stored in relational databases, which occupy more and more memory. At the same time, the performance of querying databases is getting lower and lower when the amount of data increases rapidly. [0003] And most of these price data are expired price data, which have no impact on users' real-time transactions; however, these expired price data cannot be deleted simply and rudely, because historical data still need to be used for business anal...

AI Technical Summary

Problems solved by technology

The current data is stored in the relational database, which will occupy more and more memory, and at the same time, the performance of querying the database will become lower and lower when the amount of data increases rapidly.

[0003] And most of these price data are expired price data, which have no impact on users' real-time transactions; however, these expired price data cannot be deleted simply and rudely, because historical data still need to be used for business analysis and reporting systems , indicator analysis and other business scenarios, as well as scenarios where users query historical prices

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