Detailed introduction and application scenarios of the five data structures of Redis

Redis is a very popular open source in-memory database that uses key-value pairs to store data and supports a variety of data structures. Redis provides five main data structures: string, hash, list, set and ordered set. This article will introduce the characteristics and application scenarios of each data structure in detail.

1. String

String is one of the most basic data structures supported by Redis. It can store any type of data, including numbers, text and binary data, etc. . The operations supported by the string data structure include setting, getting, deleting and modifying.

Commonly used string operations:

(1) SET key value: Set the key value pair

(2) GET key: Get the value corresponding to the key

(3) DEL key: Delete key-value pair

(4) INCR key: Add 1 to the value corresponding to the key

(5) DECR key: Decrease the value corresponding to the key by 1

String data structures have a wide range of application scenarios, including cached data, counters, calculators, etc.

2. Hash

A hash is a collection of key-value pairs, where each key corresponds to a value. The key in a hash key-value pair is always a string, and the value can be a string, number, or other hash table.

Commonly used hash operations:

(1) HSET key field value: Assign a value to the field in the hash table

(2) HGET key field: Get the hash The value of the table field

(3) HDEL key field1 [field2]: Delete one or more fields in the hash table

(4) HINCRBY key field increment: Increment the hash table Field plus a value

The application scenarios of the hash data structure include storing objects, user data, product attributes, etc.

3. List

A list is a list of strings sorted in insertion order. Elements can be inserted or deleted at the beginning or end of the list. List data structures support operations including insertion, deletion, slicing, retrieval, and search.

Commonly used list operations:

(1) LPUSH key value: Insert a value into the head of the list

(2) RPUSH key value: Insert a value To the end of the list

(3)LPOP key: Remove an element from the list and return it

(4)RPOP key: Remove the last element from the list and return it

(5) LINDEX key index: Get the element with the specified index in the list

The application scenarios of the list data structure include message queue, task queue, news list, recently used items, etc.

4. Collection

A collection is an unordered collection of strings that does not allow duplicate elements. Redis provides many set operations, including add, delete, union, intersection and difference.

Commonly used collection operations:

(1) SADD key member: Add an element to the collection

(2) SREM key member: Delete an element from the collection

(3) SMEMBERS key: Get all elements in the set

(4) SUNION key1 key2: Get the union of two sets

(5) SINTER key1 key2: Obtain the intersection of two collections

Application scenarios of collection data structures include friend lists, hobbies, etc.

5. Ordered set

An ordered set is an ordered set of strings. Each element has a score, arranged from small to large according to the score. Sorted sets are often used in scenarios where rankings need to be based on scores.

Commonly used ordered set operations:

(1) ZADD key score member: Add an element to the ordered set

(2) ZRANK key member: Get The ranking of an element in the ordered set

(3) ZSCORE key member: Get the score of an element in the ordered set

(4) ZRANGE key start stop [WITHSCORES]: Get the ordered set Elements within the specified range in

The application scenarios of the ordered set data structure include business scenarios such as rankings that need to be sorted according to scores.

Summary

Redis supports a variety of data structures. These data structures can not only solve data problems in different scenarios, but also provide flexibility and performance optimization. When choosing which data structure to use, you need to choose based on the needs of the scenario. For example, ordered sets that need to quickly query elements are suitable for using ordered set data structures, and task queues that need to be sorted according to insertion order are suitable for using list data structures.

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