What data structure is used for redis cache?

Redis cache supports a variety of data structures, including: strings, hash tables, lists, sets, sorted sets, geospatial data types, HyperLogLog, and bitmaps. Each data structure is optimized for specific application scenarios, improving the performance and efficiency of Redis caching.

Data structures used in Redis cache

Redis is a popular in-memory caching system that can store different types of data, and provides specific data structures for each data type. The main data structures include:

1. String

• The most basic Redis data type, used to store ordinary text or binary data.
• Supports various string operations, such as splicing, comparison, and interception.

2. Hash table (Hash)

• stores the mapping relationship of key-value pairs, and can quickly find the value according to the key.
• Usually used to store user session information, configuration files, or other associated data that needs quick access.

3. List

• Stores an ordered collection of elements, and elements can be added or removed from the head or tail of the list.
• Can be used as a queue, task list or history.

4. Set

• Stores a collection of unique elements, which can quickly determine whether a specific element exists.
• Used to store unique identifiers, labels, or mutually exclusive collections.

5. Sorted Set

• Adds scores to the set, and the elements can be sorted based on the scores.
• Suitable for situations where elements need to be sorted based on scores or other metrics, such as leaderboards or priority queues.

6. Geospatial data type

• is used to store geographical location information and supports operations such as search and distance calculation.
• Can be used to build location-based services, such as map lookups or nearby place searches.

7. HyperLogLog

• An approximate count data structure used to estimate the number of unique elements in a large data set.
• Provides accurate estimates even when the data set is very large.

8. Bitmaps

• Stores a set of bit values, each bit represents a Boolean value.
• Used to efficiently track status information, collection membership, or filters.

According to different application scenarios, choosing the appropriate data structure can optimize the performance and efficiency of Redis cache.

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