How redis caches paging data

We often need to cache data that needs paging in our projects. There are several ideas as follows. Let’s compare the advantages and disadvantages of each

## An idea:

Each page of data uses a key cache, and sets the expiration time respectively. It is initialized when the data is requested and is not in the cache. PageIndex and pageSize are used as part of the cache key, for example: (Recommended learning: Redis video tutorial)

key: cstm:list:${pageIndex}_${pageSize}

value: serialization (List)

Each page of data uses a key cache. When the data is updated, the data of all pages is actively updated. pageIndex and pageSize are used as part of the cache key, for example:

key: cstm:list:${pageIndex}_${pageSize}

value: serialization (List)

Use ordered sets to cache hotspot data, sort conditions as scores, and use the command [ZRANGE key start stop [WITHSCORES]] to achieve paging effects

key: cstm:zset:pageList

value: Serialization (Customer)

Analysis of advantages and disadvantages:

The first method: initialize between data addition and deletion Caching will cause data duplication or omission. For example: after the first page of data is cached, if there is new data, when the second page of data is cached, the cached data of the two pages will be duplicated

Second The first method: If the data is updated frequently, the cached data will be updated more frequently.

The third method: This method is relatively friendly. You need to maintain the cache while the data changes, and pay attention to trimming the list length

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