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This article introduces the relevant knowledge of "how to optimize the massive data of Redis Set". In the operation of actual cases, many people will encounter such a dilemma, so let the editor lead you to learn how to deal with these situations. I hope you can read it carefully and be able to achieve something!

Project data business architecture diagram

In order to realize the function of removing weight [counting the number of ships in grid time], the redis Set structure is adopted. The data is valid for 2 days. Due to the huge amount of data, redis down is dropped in the test environment.

First, flushdb is used to clear the data.

The storage code is as follows: convert ship MMSI to String- > byte []

So that each MMSI [9 bits] takes up 9 bytes of memory.

Optimize the data structure:

It only takes 4 bytes to convert Integer to byte [].

So now for 200 million redisKey, it will save at least the memory size as follows:

200 million * (9-4) = 1 billion bytes

It will save at least nearly 1G of memory. If an average of 10 MMSI is stored in a KEY, it saves nearly 10 gigabytes of memory.

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