Multi-index cache big data overtemperature judgment algorithm in logistics temperature control industry

Abstract

The invention discloses a multi-index cache big data overtemperature judgment algorithm in the logistics temperature control industry, and relates to the technical field of big data architectures. Themethod comprises the steps: arranging a data index processor on the level of a database, carrying out data cutting on the database, and establishing a logic index; using a configurable cache timing processor to carry out logic caching on data within variable time; dividing the existing data cache and the newly added data cache, removing the newly added data from the newly added data item set andadding the newly added data into the existing data item set after one logic operation is executed, transmitting the data to the data middle station for induction and arrangement, and performing persistence operation on the generated over-temperature data. According to the method, existing applications are simply deployed, server resources are fully utilized, data operation is effectively reduced,the query performance is remarkably improved in big data query application of the logistics temperature control industry, the operation performance and expandability of a monitoring system are improved, and the application prospect is wide.

Description

technical field [0001] The invention relates to the technical field of big data architecture, in particular to a multi-index cache big data over-temperature judging algorithm in the logistics temperature control industry. Background technique [0002] At present, more than 90% of multinational pharmaceutical companies have conducted business and established production plants in China, and China is gradually becoming the world's second largest pharmaceutical market player. With the improvement of the level of medical security, temperature-sensitive drugs such as biomedicine and vaccines have increasingly strict requirements on cold chain logistics, and the total market demand for pharmaceutical cold chain logistics has exceeded 10 billion yuan. Despite this, China still lacks a complete and efficient cold chain distribution system for pharmaceutical products. The vast territory, extreme climate under various terrain conditions, and inefficient transportation systems across ci...

AI Technical Summary

Problems solved by technology

Compared with the big data architectures on the market, small and medium-sized enterprises may not be suitable for using such heavy-duty big data architectures. Instead, they are more inclined to design their own architectures. However, due to the uneven development level, the architecture level is not high.

The architecture purchased by many enterprises is a direct storage architecture. There is no data segmentation. All data exists in a logical structure, such as a data table. The characteristics of big data are large quantities and low value density. Putting so much data together At this time, even adding an index key to the database will not help, because the amount of data has exceeded the range that the database can bear, so the query efficiency is extremely low, which limits the speed at which the system can judge data overheating, and there is no way to meet the requirements of real-time monitoring. need

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