Second-level cache data processing method and system, processor, and storage medium

Abstract

The invention relates to the technical field of data management, and particularly provides a second-level cache data processing method, an application end operates a cache service of a second-level cache server through a second-level cache client interface, the second-level cache server comprises a Socket pipeline monitoring service and a cache service based on a memory and a disk. A specified socket port is monitored and a corresponding signal is applied to a cache service; when the second-level cache client side and the second-level cache server side are in Socket pipeline service communication, a second-level cache data signal interface requesting server side operation sends a data signal of server side cache operation by an application side to the server side for processing. Compared with the prior art, the invention has the advantages that when the database dictionary data is used as the cache data, the old cache can be reset based on the single data query operation, and the invalid dictionary cache data can be effectively cleared and updated within the acceptable delay.

Description

technical field [0001] The invention relates to the technical field of data management, and specifically provides a secondary cache data processing method. Background technique [0002] In the tax industry, with the development and use of various information systems such as the "Golden Tax Phase III", VAT invoice management system, and personal tax management system, as well as the deep integration of people's living consumption and Internet technology, the internal taxation system has Data, third-party data from other departments, and Internet tax-related data have exploded. In order to effectively store, manage and apply these big tax data and improve tax governance, tax systems across the country have introduced various big data component technologies such as Hive, Hbase, and Kudu. [0003] With the componentization of big data ETL, many ETL functions have been implemented to allow users to connect and configure the ETL process in the interface by dragging and dropping. ...

AI Technical Summary

Problems solved by technology

[0005] Problem 1: When the existing technology caches the database query results, the deleted data in the database cannot be captured, resulting in the retention of the discarded data. When the cache query is matched, the outdated cache is matched, which affects the quality of business data.

[0006] Problem 2: When the existing technology uses the cache component, it cannot remove the invalid cache in time, which affects the use of other business components

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