22-05-26 Xi'an interview question (01) preparation

I. Copy of object ： Deep copy and light copy

An object exists 2 There are two types of properties , One is basic data type , One is the reference of instance object

Shallow copy refers to ： Copy the value of the basic data type and the reference address of the instance object , It will not copy the object pointed to by a reference object , That is, the objects that are copied out , Internal reference attributes refer to objects in the same heap in memory .

Deep copy ： Copy the value of the basic data type and the object pointed to by the reference address of the instance object , Both will copy . Deeply copied objects , The internal reference attribute points to an object in the same heap no longer as the object pointed to before copying

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II. thread deadlock

Conditions to be satisfied by the lock

1. A resource can only be used by one thread at a time
2. A thread is blocking waiting for a resource , Do not release occupied resources
3. A thread has obtained resources , Before use , Can't be forcibly deprived of

Deadlock is to add a necessary condition to the lock

4. A number of threads form end-to-end loops waiting for resource relationships

How to avoid deadlock in the development process ？

Pay attention to the locking sequence , Ensure that each thread locks in the same order

Pay attention to the locking time limit , Set a timeout for the lock

Pay attention to deadlock checking , It's a preventive mechanism , Ensure that deadlocks are discovered and resolved at the first time

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III.redis Eliminate key The algorithm of LRU and LFU difference

LRU Algorithm （ Least recently used ,recently）：

Eliminate data that has not been accessed for a long time , Take the latest visit time as a reference

LFU Algorithm （ The least used ,frequently）

Eliminate the data that has been accessed the least in recent time , Take the number of times as a reference

In most cases, we can use LRU Strategy , When there is a large amount of hotspot cache data ,LFU Better .

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IV. Why use caching

cache purpose ： High performance 、 High concurrency .

High performance ： Suppose there are many read requests , Then directly put the results of the query in the cache , Just read the cache directly later ！

High concurrency ： The concurrency of a single cache is mysql Dozens of times of single machine . Cache is memory driven , Memory naturally supports high concurrency .

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V： How to ensure the data consistency between cache and database ？

Serialization ensures that no inconsistencies will occur , But it will also cause the throughput of the system to be greatly reduced .

 Cache Aside Pattern

• When reading , Read cache first , If there is no cache , Reading database , Then take out the data and put it into the cache , Return response at the same time .
• When it's updated , Update the database first , Then delete the cache .

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VI  What is? Redis The avalanche of 、 Penetration and breakdown ？

Cache avalanche and penetration , The two biggest problems in caching , Or it doesn't show up , When it does, it's fatal

Cache avalanche ： The cache machine went down unexpectedly . The cache is down , here 1 second 5000 Requests all drop to database , Database can't bear it , It will call the police , And then I hung up

Cache penetration ： database id It's from 1 At the beginning , As a result, the request from the hacker id All negative numbers . In this case , Not in cache , Request every time “ View cache in nothing ”, Direct query database . The cache penetration in this malicious attack scenario will directly kill the database .

Cache breakdown ： That is to say, some key Very hot , Very frequent visits , Centralized high concurrent access , When this key At the moment of failure , A large number of requests break down the cache , Direct request database , It's like making a hole in a barrier .