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How to use Redis

Usage scenarios In my project, there is a function provided for Autocomplete, and the amount of data is probably tens of thousands. In this article, I use the example of name retrieval to illustrate. For the list, please click on the Demo from the author of Redis. Such a list is full of user names. For example, there is a user object in our system: publicClassUser{publicstringId{get;set;}publicstringName{get;set;}....publicstringUserHead{get;set;}} in the system A user's drop-down list is needed. Due to the large amount of data, it cannot be displayed all at once, so an Auto

Jun 03, 2023 pm 12:48 PM

redis

How to apply Redis stand-alone cache of SpringBoot caching mechanism

Redis stand-alone cache is the same as Ehcache. If Redis exists in the classpath and Redis has been configured, RedisCacheManager will be used as the cache provider by default. The steps for using Redis stand-alone cache are as follows: 1. Create a project, add cache dependencies, and create a SpringBoot project. Add spring-boot-starter-cache and Redis dependencies org.springframework.bootspring-boot-starter-cacheorg.springframework.bootspring-boot-

Jun 03, 2023 pm 12:41 PM

redisSpringBoot

How to solve the double-write consistency problem between Redis and MySQL

Double-write consistency between Redis and MySQL refers to how to ensure the data consistency between the two (the content is the same or as close as possible) in the scenario where the cache and the database are used to store data at the same time (mainly when there is high concurrency). Normal business process: There is no problem with reading. The key lies in the write (update) operation. This will cause several problems. Here, the database is updated first, and then the cache is operated. But for cache operations, should we update the cache or delete the cache? Or why not operate (delete, update) the cache first and then update the database? To sum up, should we operate the cache first and then the database, or should we operate the database first and then the cache? Let’s continue with these questions. First, let’s talk about the operation cache, which includes two types: update cache and delete.

Jun 03, 2023 pm 12:28 PM

MySQLredis

What causes Redis memory fragmentation and what is the principle of Pipeline?

Memory fragmentation How does memory fragmentation occur? Redis has its own internal memory allocator, the default is jemalloc, which manages the application and release of memory in order to improve the efficiency of memory usage. The memory allocator allocates memory according to a fixed size, not exactly according to the memory size requested by the program. For example, if the program applies for a 20-byte memory, the memory allocator will allocate a 32-byte memory space. This is done to reduce the number of allocations. Redis will apply for different sizes of memory space to store different types of data for different businesses. Since the memory is allocated according to a fixed size and will be larger than the actual requested memory, memory fragmentation will occur in this process. For example: Let’s use a high-speed rail carriage to illustrate. Suppose a car

Jun 03, 2023 pm 12:16 PM

redispipeline

What are the pitfalls of redis distributed locks?

1. Non-atomic operations use redis distributed locks. The first thing we think of may be the setNx command. if(jedis.setnx(lockKey,val)==1){jedis.expire(lockKey,timeout);} It’s easy, divide three times five by two, and we can write the code. This code can indeed lock successfully, but have you found any problems? The locking operation and the subsequent setting of the timeout are separate and are not atomic operations. If the lock is successful but the timeout setting fails, the lockKey will never expire. If in a high-concurrency scenario, a large number of lockKeys are successfully locked but will not fail, it may directly lead to redi failure.

Jun 03, 2023 pm 12:03 PM

redis

How Redis speeds up Spark

ApacheSpark has gradually become a model for the next generation of big data processing tools. By borrowing from open source algorithms and distributing processing tasks across clusters of compute nodes, Spark and Hadoop generation frameworks easily outperform both in the types of data analysis they can perform on a single platform and in the speed with which they can perform these tasks. over traditional frameworks. Spark uses memory to process data, making it significantly faster (up to 100 times faster) than disk-based Hadoop. But with a little help, Spark can run even faster. If you combine Spark with Redis (a popular in-memory data structure storage technology), you can once again significantly improve the performance of processing analysis tasks. This is due to Red

Jun 03, 2023 am 11:45 AM

redisspark

How SpringBoot customizes Redis to implement cache serialization

1. Customize RedisTemplate1.1, RedisAPI default serialization mechanism. The API-based Redis cache implementation uses the RedisTemplate template for data caching operations. Here, open the RedisTemplate class and view the source code information of the class. publicclassRedisTemplateextendsRedisAccessorimplementsRedisOperations, BeanClassLoaderAware{//Declare key, Various serialization methods of value, the initial value is empty @NullableprivateRedisSe

Jun 03, 2023 am 11:32 AM

redisSpringBoot

How to deploy and install Redis 6.2.0 using CentOS 7.5 source package

Install Redis6.2.0wgethttp://download.redis.io/releases/redis-6.2.0.tar.gzyum-yinstallgccautomakeautoconflibtoolmaketar-xzvfredis-6.2.0.tar.gz&&redis-6.2.0.tar.gzcdredis-6.2.0makecdsrcmakeinstallPREFIX= If zmalloc.h:50:31: fatal error occurs in /usr/local/redis: jemall

Jun 03, 2023 am 11:16 AM

redisCentOS

How to use the special data types of Redis

1. HyperLogLog cardinality statistics 1.1 What is cardinality? We can understand what cardinality statistics is directly through an example, such as the data set {1,2,3,3,5,5,}, then the cardinality set of this data set is {1,2,3,5}, the cardinality (non-repeating elements) is 4. That is to say, it is the number of non-repeating elements. 1.2 Benefits of using cardinality statistics Each HyperLogLog key only requires 12KB of memory to calculate the cardinality of nearly 2^64 different elements. This is in sharp contrast to a collection that consumes more memory when calculating cardinality. The more elements there are, the more memory is consumed. If you want to compare from a memory perspective, Hyperloglog is the first choice. 1.3 UV of application scenario web page (visited by one person

Jun 03, 2023 am 11:10 AM

redis

How SpringBoot integrates Redis to enable caching mechanism

A small demopom file integrating springboot+redis+mybatisplus 4.0.0com.wlientspringboot_mq_redis0.0.1-SNAPSHOTspringboot_mq_redisDemoprojectforSpringBoot1.8UTF-8UTF-82.3.7.RELEASEorg.springframework.bootspring-boot-starter-amqporg.springframework.bootspring-boot -starte

Jun 03, 2023 am 11:10 AM

redisSpringBoot

How to implement Redis read and write separation in go

Why do we need to understand the RESP protocol? Regarding this issue, I would like to explain through an example why we need to understand the RESP protocol when we write Redis middleware. The above code is a very simple TCP server written. We listen to port 8888, try to use redis-cli-p8888 to connect to the server, and then view the printed application layer messages. We try to execute this code and enter redis-cli-p8888 to connect. The message that the server we wrote gets the redis client is: *1$7COMMAND. The above is the content of the RESP protocol. So, if we want to write a Redis middleware, we need to understand it first.

Jun 03, 2023 am 11:08 AM

Goredis

Analysis of String data type examples in Redis

Overview: The string type is the most basic data storage type in Redis. It is binary safe in Redis, which means that this type can accept data in any format, such as JPEG image data or Json object description information. In Redis, the maximum data length that the string type Value can hold is 512M. Related command list: Command prototype time complexity command description return value APPENDO (1) If the Key already exists, the APPEND command appends the data of the parameter Value to the end of the existing Value. If the Key does not exist, the APPEND command will create a new Key/Value. The length of Value after appending. DECR

Jun 03, 2023 am 10:47 AM

redisstring

How to implement redis double linked list in python

Features of redis double linked list: len: O(1), get the length of the linked list head: O(1), the first node in the head tail: O(1) the first node in the tail acyclic: acyclic linked list void*: store any type data. (Dynamic language comes naturally) 2. Doubly linked list API interface creation/destruction/initialization: listCreatelistEmptylistRelease to add nodes/delete nodes: listAddNodeHeadlistAddNodeTaillistInsertNodelistDelNode implements iterator/forward/reverse traversal: listGetIteratorlistReleaseIte

Jun 03, 2023 am 10:26 AM

Pythonredis

What are the solutions for redis distributed ID?

Commonly used distributed ID solutions In distributed systems, it is very important to generate globally unique IDs, because in distributed systems, multiple nodes generating IDs at the same time may cause ID conflicts. The following introduces several commonly used distributed ID solutions. UUIDUUID (Universally Unique Identifier) is an identifier composed of 128 digits, which can guarantee global uniqueness because its generation algorithm is based on factors such as timestamp, node ID and so on. UUID can be generated using Java's own UUID class, as shown below: javaCopycodeimportjava.util.UUID;publicclassUuidGenerator{publicstat

Jun 03, 2023 am 10:14 AM

redisid