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This article analyzes "what are big data's two ways of dealing with it?" The content is detailed and easy to understand. Friends who are interested in "what are the two ways to deal with big data" can follow the editor's train of thought to read it slowly and deeply. I hope it will be helpful to everyone after reading. Let's follow the editor to learn more about "what are the two ways to deal with big data?"

Big data has two processing methods: memory-based streaming processing and hard disk-based storage processing.

Streaming is like building a sluice in front of passing data. The data flows through here, and as it passes through the floodgates, it is filtered, analyzed, discarded, and never used again.

Storage processing is to build a reservoir. The data is first put into the storage pool and stored, and then into the storage tank when needed, where it is screened and analyzed to find the valuable content. In this process, because the water is still in the reservoir and has not been released, it can be used next time.

The data processing of the storage mode can be repeated, used again and again. However, because of the mechanical characteristics of the hard disk itself, the processing speed is slow and the speed is not high. However, there are still some optimization measures for hard drives.

Streaming processing because the data processing process is carried out in memory, and the memory processing performance is several orders of magnitude of the hard disk, so its processing speed is much higher than the storage mode. But also because the data resides in memory, the characteristic of memory is power-off and can only be used at one time. So flow processing is usually disposable, such as sanitary napkins.

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