Redis common interview questions

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redis lock

 String isLock = jedis.set(lockKey, userId, "NX", "PX", 6 * 1000);
 Copy code 

jedis Of set Commands can have complex parameters , Through these parameters, the atomic distributed lock command can be realized

jedis.set(lockName, "", "NX", "PX", expireTime);

Copy code, code analysis

redis Of set Commands can carry complex parameters , The first one is locked key, The second is value, The client that can store the lock ID, Check whether the current client has obtained the lock , The value of the third parameter NX/XX, Fourth parameter EX|PX, The fifth is time

NX: If it doesn't exist, set this key XX: If it exists, set this key

EX: The unit is in seconds ,PX: The unit is millisecond

Redis What are the advantages and disadvantages

advantage

• Excellent reading and writing performance , Redis The speed at which you can read is 110000 Time /s, The speed of writing is 81000 Time /s.
• Support data persistence , Support AOF and RDB Two ways to persist .
• Support transactions ,Redis All operations of are atomic , meanwhile Redis It also supports atomic execution after several operations are combined .
• Rich data structure , In addition to supporting string Type of value Support in addition hash、set、zset、list And so on .
• Support master-slave replication , The host will automatically synchronize the data to the slave , Can be read-write separation .

shortcoming

• Database capacity is limited by physical memory , Cannot be used as high-performance read-write of massive data , therefore Redis Suitable scenarios are mainly limited to high-performance operations and operations with small amount of data .
• Redis No automatic fault tolerance and recovery functions , The downtime of the host and slave will lead to the failure of the front-end read and write requests , You need to wait for the machine to restart or manually switch the front end IP To recover .
• Host down , Before the outage, some data could not be synchronized to the slave in time , Switch IP After that, the problem of data inconsistency will be introduced , Reduced system availability .
• Redis Difficult to support online capacity expansion , When the cluster capacity reaches the upper limit, online capacity expansion will become very complex . To avoid this problem , The operation and maintenance personnel must ensure enough space when the system is online , This is a great waste of resources .

Redis Why so soon?

1、 Completely based on memory , Most requests are purely memory operations , Very fast . Data is in memory , Be similar to HashMap,HashMap The advantage is the time complexity of both the lookup and the operation O(1);

2、 The data structure is simple , It's also easy to manipulate data ,Redis The data structure in is specially designed ;

3、 Using single thread , Unnecessary context switches and race conditions are avoided , There is also no switching consumption caused by multiple processes or multiple threads CPU, You don't have to worry about locks , There is no lock release operation , There is no performance penalty due to possible deadlocks ;

4、 Using multiple channels I/O Reuse model , Non blocking IO;

5、 Using the underlying model is different , The underlying implementation and application protocols for communicating with clients are different between them ,Redis Build it yourself VM Mechanism , Because the normal system calls system functions , It's a waste of time moving and requesting ;

data type

Redis There are mainly 5 Type of data , Include String,List,Set,Zset,Hash, Meet most of the use requirements

Redis What is the persistence mechanism of ？ Advantages and disadvantages of each ？

Redis There are two persistence mechanisms RDB（ Default ） and AOF Mechanism :

RDB： yes Redis DataBase Abbreviated snapshot

RDB yes Redis Default persistence method . Save the memory data to the hard disk in the form of snapshot according to a certain time , The corresponding generated data file is dump.rdb. Through... In the configuration file save Parameter to define the period of the snapshot .

advantage ：

1、 Only one file dump.rdb, Easy persistence . 2、 Good disaster tolerance , A file can be saved to a safe disk . 3、 Maximize performance ,fork Sub process to complete the write operation , Let the main process continue processing commands , So it is IO Maximize . Use a single child process for persistence , The main process will not do anything IO operation , To ensure the redis A high performance 4. When the data set is large , Than AOF It's more efficient to start . shortcoming ：

1、 Data security is low .RDB It's persistence at intervals , If between persistence redis failure , There will be data loss . So this way is more suitable when the data requirements are not rigorous ) 2、AOF（Append-only file) Persistence mode ： Means all command line records to redis Command please The format of the protocol is fully persistent ) Save as aof file .

AOF： Persistence

AOF Persistence ( namely Append Only File Persistence ), Will be Redis Each write command executed is recorded in a separate log file , When restarting Redis It will recover the data from the persistent log again .

When both modes are on at the same time , Data recovery Redis Preference will be given AOF recovery .

advantage ：

1、 Data security ,aof Persistence can be configured appendfsync attribute , Yes always, Every time Command operations are recorded as aof Once in the file . 2、 adopt append Mode write file , Even if the server goes down , Can pass redis-check-aof Tools for data consistency . 3、AOF The mechanism rewrite Pattern .AOF The document was not rewrite Before （ When the file is too large, the command Do merge rewrite ）, You can delete some of these commands （ For example, misoperation flushall）) shortcoming ：

1、AOF File than RDB The file is big , And the recovery speed is slow . 2、 When the data set is large , Than rdb Low starting efficiency . What are the advantages and disadvantages ？

AOF File than RDB High update frequency , priority of use AOF Restore data . AOF Than RDB Safer and bigger RDB Performance ratio AOF good If both have priority loading AOF

Cache avalanche 、 Cache penetration 、 Cache preheating 、 Cache update 、 Cache degradation and other issues

Cache avalanche We can simply understand it as ： Due to the original cache failure , Period before new cache ( for example ： We set up the cache with the same expiration time , Large cache expiration occurs at the same time ), All requests that should have access to the cache are going to query the database , And for databases CPU And memory , Serious will cause database downtime . Thus a series of chain reactions are formed , Cause the whole system to crash . terms of settlement ： Most system designers consider locking （ The most solutions ） Or the way of queue ensures that there will not be a large number of threads reading and writing to the database at one time , So as to avoid a large number of concurrent requests falling on the underlying storage system in case of failure . There is also a simple solution to spread the cache failure time .

Two 、 Cache penetration Cache penetration refers to user query data , There is no , Naturally, there won't be . This leads to user queries when , Could not find... In cache , Every time I have to go to the database and check it again , Then return to empty （ Equivalent to two useless queries ）. In this way, the request bypasses the cache and directly queries the database , This is also a frequently raised cache hit rate problem . terms of settlement ; The most common is the use of bloon filter , Hash all possible data to a large enough bitmap in , A certain nonexistent data will be bitmap Intercept , Thus, the query pressure on the underlying storage system is avoided . There's also a simpler and rougher way , If the data returned by a query is empty （ Whether the data doesn't exist , Or a system failure ）, We still cache this empty result , But its expiration time will be very short , Up to five minutes . The default values set directly are stored in the cache , In this way, the second access to the buffer has a value , Instead of continuing to access the database , This method is the simplest and rudest . 5TB Our hard disk is full of data , Please write an algorithm to arrange the data . If these data are some 32bit How to deal with the size of data ？ If it is 64bit What about ？

The use of space has reached an extreme , That's it Bitmap And the bloon filter (Bloom Filter). Bitmap： A typical example is a hash table The disadvantage is that ,Bitmap Only... Can be recorded for each element 1bit Information , If you want to complete additional functions , I'm afraid we have to sacrifice more space 、 Time has come to complete .

The bloon filter （ recommend ） That is to introduce k(k>1)k(k>1) Independent hash functions , Make sure that in a given space 、 Under the rate of miscalculation , Complete the process of element weight determination . Its advantage is that the space efficiency and query time are far more than the general algorithm , The disadvantage is that it has certain error recognition rate and deletion difficulty . Bloom-Filter The core idea of the algorithm is to use multiple different Hash Function to solve “ Conflict ”. Hash There is a conflict （ Collision ） The problem of , Use the same Hash Two of them URL The value of may be the same . To reduce conflict , We can introduce more Hash, If you go through one of them Hash Value we get that an element is not in the set , Then the element must not be in the collection . Only in all Hash The function tells us that when the element is in the collection , To determine that the element exists in the collection . This is Bloom-Filter The basic idea of . Bloom-Filter It is generally used to determine whether an element exists in a large set of data . Be reminded to add ： The difference between cache penetration and cache breakdown Cache breakdown ： It means a key Very hot , Constantly carrying big concurrency , Large concurrent centralized access to this point , When this key At the moment of failure , Continuous large concurrency breaks through the cache , Request data directly . Solution ; During a visit to key Before , use SETNX（set if not exists） To set up another short term key To lock in the present key The interview of , Delete the short term after the visit key. increase ： Give me a case that our company deals with ： Background dual camera token,token Save a copy to redis, Make sure the system is in token When expired, there is only one thread to get token; There are two machines in the online environment , Therefore, distributed lock is used to implement .