search
HomeDatabaseRedisExample analysis of Redis caching problem

1. Application of Redis cache

In our actual business scenarios, Redis is generally used in conjunction with other databases to reduce the pressure on back-end databases, such as relational databases. Used with database MySQL.

Redis will cache frequently queried data in MySQL, such as hotspot data, so that when users come to access, they do not need to go to MySQL. Instead of querying, the cached data in Redis is directly obtained, thereby reducing the reading pressure on the back-end database.

If the data queried by the user is not available in Redis, the user's query request will be transferred to the MySQL database. When MySQL returns the data to the client, the data will be cached in Redis at the same time., so that when the user reads again, the data can be obtained directly from Redis. The flow chart is as follows:

Example analysis of Redis caching problem

When using Redis as a cache database, we will inevitably face three common caching problems

  • Cache Penetration

  • Cache Penetration

  • Cache Avalanche

2. Cache Penetration

2.1 Introduction

Cache penetration means that when the user queries a certain data, the data does not exist in Redis, that is, the cache does not hit. At this time, the query request will be transferred to the persistence layer database MySQL, and it is found that the data does not exist in MySQL either. , MySQL can only return an empty object, indicating that the query failed. If there are many such requests, or users use such requests to conduct malicious attacks, it will put great pressure on the MySQL database and even collapse. This phenomenon is called cache penetration.

Example analysis of Redis caching problem

2.2 Solution

Cache empty objects

When MySQL When an empty object is returned, Redis caches the object and sets an expiration time for it. When the user initiates the same request again, an empty object will be obtained from the cache. The user's request is blocked in the cache layer, thus protecting the back-end database. However, this approach There are also some problems. Although the request cannot enter MSQL, this strategy will occupy Redis cache space.

Example analysis of Redis caching problem

Bloom filter

First store all keys of hotspot data that users may access In the Bloom filter (also called cache preheating) , when a user makes a request, it will first go through the Bloom filter. The Bloom filter will determine whether the requested key exists . If If it does not exist, then the request will be rejected directly, otherwise the query will continue to be executed, first go to the cache to query, if the cache does not exist, then go to the database to query. Compared with the first method, using the Bloom filter method is more efficient and practical. The process diagram is as follows:

Example analysis of Redis caching problem

Cache preheating is the process of loading relevant data into the Redis cache system in advance before the system starts. . This avoids loading data when the user requests it.

2.3 Comparison of solutions

Both solutions can solve the problem of cache penetration, but their usage scenarios are different:

Cache empty objects: suitable for scenarios where the number of keys for empty data is limited and the probability of repeated key requests is high.


Bloom filter: suitable for scenarios where the keys of empty data are different and the probability of repeated key requests is low.

3. Cache breakdown

3.1 Introduction

Cache breakdown means that the data queried by the user does not exist in the cache , but it exists in the back-end database. The reason for this phenomenon is generally caused by the expiration of the key in the cache. For example, a hot data key receives a large number of concurrent accesses all the time. If the key suddenly fails at a certain moment, a large number of concurrent requests will enter the back-end database, causing its pressure to increase instantly. This phenomenon is called cache breakdown.

3.2 Solution

Change the expiration time

Set hotspot data to never expire.

Distributed lock

Adopt the distributed lock method to redesign the use of cache. The process is as follows:

  • Locking: When we query data through key, we first query the cache. If not, we lock it through distributed lock. The first process to obtain the lock Enter the back-end database query and buffer the query results to Redis.

  • Unlocking: When other processes find that the lock is occupied by a certain process, they enter the waiting state. After unlocking, other processes access the cached key in turn. .

Example analysis of Redis caching problem

##3.3 Comparison of solutions

Never expires: This solution does not set the real As for the expiration time, there are actually no series of hazards caused by hot keys, but there will be data inconsistencies, and the code complexity will increase.

Mutex lock: This solution is relatively simple, but there are certain hidden dangers. If there is a problem in the cache building process or it takes a long time, there may be deadlock and thread pool blocking. Risky, but this method can better reduce the back-end storage load and achieve better consistency.

4. Cache avalanche

4.1 Introduction

Cache avalanche means that a large number of keys in the cache expire at the same time, and at this time the data The number of visits is very large, which leads to a sudden increase in pressure on the back-end database and may even cause it to crash. This phenomenon is called a cache avalanche. It is different from cache breakdown. Cache breakdown occurs when a certain hot key suddenly expires when the amount of concurrency is particularly large, while cache avalanche occurs when a large number of keys expire at the same time, so they are not of the same order of magnitude at all.

Example analysis of Redis caching problem

4.2 Solution

Handling expiration

In order to reduce cache breakdown and avalanche problems caused by a large number of keys expiring at the same time, a strategy of never expiring hotspot data can be adopted, which is similar to cache avalanche. In addition, in order to prevent keys from expiring at the same time, you can set a random expiration time for them.

redis high availability

One Redis may hang due to an avalanche, so you can add a few more Redis, build a cluster, if one hangs up, the others can continue to work.

The above is the detailed content of Example analysis of Redis caching problem. For more information, please follow other related articles on the PHP Chinese website!

Statement
This article is reproduced at:亿速云. If there is any infringement, please contact admin@php.cn delete
Redis vs. SQL Databases: Key DifferencesRedis vs. SQL Databases: Key DifferencesApr 25, 2025 am 12:02 AM

The main difference between Redis and SQL databases is that Redis is an in-memory database, suitable for high performance and flexibility requirements; SQL database is a relational database, suitable for complex queries and data consistency requirements. Specifically, 1) Redis provides high-speed data access and caching services, supports multiple data types, suitable for caching and real-time data processing; 2) SQL database manages data through a table structure, supports complex queries and transaction processing, and is suitable for scenarios such as e-commerce and financial systems that require data consistency.

Redis: How It Acts as a Data Store and ServiceRedis: How It Acts as a Data Store and ServiceApr 24, 2025 am 12:08 AM

Redisactsasbothadatastoreandaservice.1)Asadatastore,itusesin-memorystorageforfastoperations,supportingvariousdatastructureslikekey-valuepairsandsortedsets.2)Asaservice,itprovidesfunctionalitieslikepub/submessagingandLuascriptingforcomplexoperationsan

Redis vs. Other Databases: A Comparative AnalysisRedis vs. Other Databases: A Comparative AnalysisApr 23, 2025 am 12:16 AM

Compared with other databases, Redis has the following unique advantages: 1) extremely fast speed, and read and write operations are usually at the microsecond level; 2) supports rich data structures and operations; 3) flexible usage scenarios such as caches, counters and publish subscriptions. When choosing Redis or other databases, it depends on the specific needs and scenarios. Redis performs well in high-performance and low-latency applications.

Redis's Role: Exploring the Data Storage and Management CapabilitiesRedis's Role: Exploring the Data Storage and Management CapabilitiesApr 22, 2025 am 12:10 AM

Redis plays a key role in data storage and management, and has become the core of modern applications through its multiple data structures and persistence mechanisms. 1) Redis supports data structures such as strings, lists, collections, ordered collections and hash tables, and is suitable for cache and complex business logic. 2) Through two persistence methods, RDB and AOF, Redis ensures reliable storage and rapid recovery of data.

Redis: Understanding NoSQL ConceptsRedis: Understanding NoSQL ConceptsApr 21, 2025 am 12:04 AM

Redis is a NoSQL database suitable for efficient storage and access of large-scale data. 1.Redis is an open source memory data structure storage system that supports multiple data structures. 2. It provides extremely fast read and write speeds, suitable for caching, session management, etc. 3.Redis supports persistence and ensures data security through RDB and AOF. 4. Usage examples include basic key-value pair operations and advanced collection deduplication functions. 5. Common errors include connection problems, data type mismatch and memory overflow, so you need to pay attention to debugging. 6. Performance optimization suggestions include selecting the appropriate data structure and setting up memory elimination strategies.

Redis: Real-World Use Cases and ExamplesRedis: Real-World Use Cases and ExamplesApr 20, 2025 am 12:06 AM

The applications of Redis in the real world include: 1. As a cache system, accelerate database query, 2. To store the session data of web applications, 3. To implement real-time rankings, 4. To simplify message delivery as a message queue. Redis's versatility and high performance make it shine in these scenarios.

Redis: Exploring Its Features and FunctionalityRedis: Exploring Its Features and FunctionalityApr 19, 2025 am 12:04 AM

Redis stands out because of its high speed, versatility and rich data structure. 1) Redis supports data structures such as strings, lists, collections, hashs and ordered collections. 2) It stores data through memory and supports RDB and AOF persistence. 3) Starting from Redis 6.0, multi-threaded I/O operations have been introduced, which has improved performance in high concurrency scenarios.

Is Redis a SQL or NoSQL Database? The Answer ExplainedIs Redis a SQL or NoSQL Database? The Answer ExplainedApr 18, 2025 am 12:11 AM

RedisisclassifiedasaNoSQLdatabasebecauseitusesakey-valuedatamodelinsteadofthetraditionalrelationaldatabasemodel.Itoffersspeedandflexibility,makingitidealforreal-timeapplicationsandcaching,butitmaynotbesuitableforscenariosrequiringstrictdataintegrityo

See all articles

Hot AI Tools

Undresser.AI Undress

Undresser.AI Undress

AI-powered app for creating realistic nude photos

AI Clothes Remover

AI Clothes Remover

Online AI tool for removing clothes from photos.

Undress AI Tool

Undress AI Tool

Undress images for free

Clothoff.io

Clothoff.io

AI clothes remover

Video Face Swap

Video Face Swap

Swap faces in any video effortlessly with our completely free AI face swap tool!

Hot Tools

SecLists

SecLists

SecLists is the ultimate security tester's companion. It is a collection of various types of lists that are frequently used during security assessments, all in one place. SecLists helps make security testing more efficient and productive by conveniently providing all the lists a security tester might need. List types include usernames, passwords, URLs, fuzzing payloads, sensitive data patterns, web shells, and more. The tester can simply pull this repository onto a new test machine and he will have access to every type of list he needs.

Dreamweaver CS6

Dreamweaver CS6

Visual web development tools

SAP NetWeaver Server Adapter for Eclipse

SAP NetWeaver Server Adapter for Eclipse

Integrate Eclipse with SAP NetWeaver application server.

SublimeText3 Linux new version

SublimeText3 Linux new version

SublimeText3 Linux latest version

SublimeText3 Mac version

SublimeText3 Mac version

God-level code editing software (SublimeText3)