Redis is an open source, in-memory data structure storage system that can be used as a database, cache, and message broker. Redis supports multiple types of data structures, including Strings, Hashes, Lists, Sets, Sorted Sets, Bitmaps, and HyperLogLogs ) and geo-spatial indexes with radius queries. Below we will analyze these data types in detail.
String (String)
String is the simplest data type of Redis and is binary safe. This means that a Redis string can contain any type of data, such as a jpeg image or a serialized object. The string type is the most basic data type of Redis. It can be understood as a key-value storage system like Memcached. The maximum storage capacity is 512MB.
Hashes Redis
hashes are mappings between string fields and string values. Therefore, they are used to represent objects. For example, you could use a hash to store a user's name, age, and address. In Redis, each hash can store more than 400 million key-value pairs.
Lists
Redis lists are simple lists of strings, sorted in insertion order. You can add an element to the head (left) or tail (right) of the list. This data type is suitable for storing multiple related values, such as a user's status updates in a social network. The maximum length of a list is 429 million elements.
Sets
Redis sets are unordered collections of strings. It is implemented through HashTable, so the complexity of adding, deleting, and searching is O(1). The main function of a collection is to add, delete, and determine whether elements exist. Moreover, the elements in the collection are unique and there will be no duplication.
Sorted Sets
Redis ordered sets, like sets, are also collections of strings, and they are ordered at the same time. Each element is associated with a score of type double. Redis uses scores to sort the members of the collection from small to large. The main feature of an ordered set is that you can add, delete, and update members, as well as get a list of members based on score ranges or members.
Bitmaps Bitmaps
are not actually a special data type, but a usage pattern of strings. Through bitmaps, we can operate on the bits of strings, which makes bitmaps very useful in certain types of counting, such as counting user activity or counting online users.
HyperLogLogs
HyperLogLog is an algorithm used to complete cardinality statistics. The so-called cardinality statistics is to count the number of non-repeating elements. HyperLogLog can accept multiple elements as input and gives a cardinality estimate of the number of input elements. Although the accuracy of HyperLogLog will be lost in order to maintain memory usage, it only needs to use a fixed and fairly small space.
Geo-spatial indexes with radius queries The
geo-spatial index of Redis is a special data type that allows you to store relevant geo-spatial data (such as latitude and longitude information) into Redis, and then perform Various operations based on geographical location, such as calculating the distance between two points, obtaining elements within a specified radius, etc.
The above are the main data types of Redis. Each data type has its specific usage scenarios. Understanding these data types and how to use them in practice is key to mastering Redis.