Redis6 note02 configuration file, publish and subscribe, new data type, jedis operation

Redis Configuration file details

Units Company

Configure size units , Some basic units of measurement are defined at the beginning , Only support bytes, I won't support it bit

Case insensitive

INCLUDES contain

Network related configuration

NETWORK Next , The default is as follows , Indicates that only local access requests can be accepted

Without writing , Unlimited acceptance of any ip Address access , The address of your application server must be written in the production environment ; The server needs remote access , So you need to comment it out

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If open protected-mode, Then there's no setting bind ip And without a password ,Redis Only local responses are allowed

Change it to no

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Port number

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tcp-backlog

Set up tcp Of backlog,backlog It's actually a connection queue ,backlog The sum of the queues = Three handshake queues not completed + Three handshake queues completed

In a high concurrency environment you need a high backlog Value to avoid slow client connection problems

Be careful Linux The kernel will reduce this value to /proc/sys/net/core/somaxconn Value (128), So we need to confirm the increase /proc/sys/net/core/somaxconn and /proc/sys/net/ipv4/tcp_max_syn_backlog(128) Two values to achieve the desired effect

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timeout

Timeout period of no operation after connection , You need to reconnect after timeout ,0 It means never time out

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tcp-keepalive

Check whether the current connection is still in operation ( Alive ) Time interval of

General Universal

daemonize

Is it a background process , Set to yes, Daemon , Background start

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pidfile

Deposit pid The location of the file , Each instance produces a different pid file

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loglevle

The level of logging

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logfile

Log file output path

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databases

Set the default number of libraries 16, Default database 0, have access to select<did> The command specifies the database on the connection id

SECURITY Security

Set the password , The default is not set

Access password view , Set up

Set the password in the command , It's just temporary . restart redis The server , The password is restored

Permanent settings , You need to set... In the configuration file

LIMITS Limit

maxclients

Set up redis How many clients can I connect to at the same time

By default 10000 A client

If this limit is reached ,redis New connection requests will be rejected , And send... To these connection requesters "max number of clients reached" In response to

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maxmemory

It is suggested that , otherwise , Fill up the memory , Causing server downtime

Set up redis The amount of memory that can be used , Once the memory usage limit is reached ,redis Will attempt to remove internal data , Remove the rule by maxmemory-policy To specify the .

If redis Can't remove data in memory according to removal rules , Or set up “ It is not allowed to remove ”, that redis An error message will be returned for the instructions that need to apply for memory , such as SET,LPUSH etc. .

But for instructions without memory request , It will still respond normally , such as GET etc. . If your redis It is the Lord. redis( Description from redis), When setting the upper memory limit , You need to leave some memory space in the system for the synchronous queue cache , Only if you set up “ Do not remove ” Under the circumstances , I don't have to think about it .

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maxmemory-policy

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maxmemory-samples

Set the number of samples ,LRU Algorithm and minimum TTL Algorithms are not exact algorithms , It's an estimate , So you can set the sample size ,redis By default, so many key Not selected LRU the

General Settings 3-7 The number of , The smaller the value, the less accurate the sample is , But the performance consumption is small .

Publish and subscribe

What is publish and subscribe

Redis Publish subscribe (pub/sub) It's a message communication mode ： sender (pub) Send a message , subscriber (sub) receive messages .

Redis Clients can subscribe to any number of channels .

Publish and subscribe command line implementation

Open a client subscription channel1

Open another client to channel1 Release the news hello

return 1 Is the number of subscribers

Open the first client to see the sent message

Redis6 New data types

Bitmaps

Modern computers use binary ( position ) As the basic unit of information ,1 Characters equal to 8 position , for example “abc” Strings are created by 3 Byte composition , But it is actually represented in binary when stored in the computer ,“abc“ Respectively corresponding ASCII The codes are 97,98,99, The corresponding binaries are 01100001,01100010 and 01100011 Here's the picture

Reasonable use of operation bits can effectively improve memory utilization and development efficiency .

Redis Provides Bitmaps This ” data type ” It can realize the alignment operation

Bitmaps Itself is not a data type , It's actually a string (key-value), But it can operate on the bits of a string .

Bitmaps A separate set of commands is provided , So in Redis Use in Bitmaps It's not quite the same as using strings . You can put Bitmaps Think of it as an array of bits , Each unit of an array can only store 0 and 1, The subscript of the array is in Bitmaps It's called offset .

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Common commands

setbit key offset value： Set up Bitmaps The value of an offset in (0 or 1), Offset from 0 Start

example ： Whether each individual user has visited the website and stored in Bitmaps in , Record the user you visited as 1, Do not visit users remember to do 0, Use the offset as the user id.

Set the number of the key offset The value of a bit ( from 0 Count up ), Suppose there are now 20 Users ,userid=1,6,11,15,19 's users visited the site , Then the current Bitmaps The initialization result is shown in Figure

Users of many applications id With a specified number ( Such as ：10000) start , Direct users id and Bitmaps A certain amount of offset is bound to cause waste , The usual practice is to do it every time setbit The user will be id Subtract the specified number .

At first initialization Bitmaps when , If the offset is very large , The whole initialization process will be slow , It may cause Redis Blocking .

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getbit key offset： obtain Bitmaps The value of an offset in , The value corresponding to the nonexistent offset is 0

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bitcount key start end Statistics string from start byte To end The byte bit value is 1 The number of

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bitop and(or/not/xor) destkey key

bitop Is a consistent operation , It can do more than one Bitmaps Of and intersection ,or Combine ,not Not ,xor XOR operation and save the result in destkey in

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set and Bitmaps Comparison of

Obviously , Use in this case Bitmaps Can save a lot of memory space , In particular, the memory saved over time is still very considerable .

however Bitmaps It's not a panacea , Few independent visitors join the site every day , Then the comparison between the two is shown in the table below , Obviously , Use at this time Bitmaps Not really , Because most of the bits are 0.

HyperLogLog

At work , We often encounter statistical related functional requirements , For example, statistics of website page visits , have access to Redis Of incr,incrby Make it easy .

But like UV(UniqueVistor, Independent visitor ), Independent IP Count , How to solve the problem of searching the number of records and other problems that need to be overlapped ？ The problem of finding the number of non repeating elements in a set is called the cardinality problem .

There are many solutions to the cardinality problem ：

1、 The data is stored in Mysql In the table , Use distinct count Calculate the number of non duplicates

2、 Use Redis Provided hash,set,bitmaps And other data structures

The results of the above scheme are accurate , But as the data grows , Resulting in more and more occupied space , It is impractical for very large data sets

Whether it can reduce a certain accuracy to balance the storage space ？Redis Launched HyperLogLog

Redis HyperLogLog It's an algorithm for cardinality statistics ,HyperLogLog The advantages of , When the number or volume of input elements is very, very large , The space needed to calculate the cardinality is always fixed , And it's very small

stay Redis Inside , Every HyperLogLog Keys only cost 12KB Memory , So we can calculate the proximity 2^64 Cardinality of different elements . This is the same as calculating the cardinality , The more elements you consume, the more memory you consume in a collection .

however , because HyperLogLog Only the input elements will be used to calculate the cardinality , Instead of storing the input element itself , therefore HyperLogLog It can't be like a collection , Return the various elements of the input .

What is the cardinality ？

Like data sets {1,3,5,7,5,7,8}, So the cardinality set of this dataset is {1,3,5,7,8}, base ( Number of non repeating elements ) by 5. Cardinality estimation is within the range of acceptable error , Fast base calculation .

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command

pfadd key element...： Add specified elements to HyperLogLog in

After joining , When the cardinality changes, it returns 1, Otherwise return to 0

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pfcount key....： Calculation HLL The approximate cardinality of , Sure Calculate multiple HLL, use HLL Store daily UV, Calculate the usage of the week 7 Days of consolidation

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pfmerge destkey sourcekey1 sourcekey2.....： Put one or more HLL The merged results are stored in another HLL

Geospatial

Redis3.2 Added right to GED Type of support .GEO,Geographic, Abbreviation for geographic information . This type of , Is the two-dimensional coordinates of the element , On the map is latitude and longitude .redis Based on this type , Longitude and latitude settings are provided , Inquire about , Range queries , Distance inquiry , Longitude and latitude Hash And so on .

command

geoadd key longgitude latitude member...： Add location （ precision , dimension , name ）

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geopos key member： Get the coordinate value of the specified area

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geodist key member1 member2 [m|km|ft|mi]： Get the linear distance between two positions , Default meter

mi： miles ,ft： feet

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georadius key longitude latitude radius [m|km|ft|mi], With the given latitude and longitude as the center , Find the elements in a certain radius

Jedis operation Redis6

Connect Redis

establish maven engineering

add to Jedis The required depend on

        <dependency>
            <groupId>redis.clients</groupId>
            <artifactId>jedis</artifactId>
            <version>3.2.0</version>
        </dependency>

Java Connect Redis

It needs to be annotated first redis.conf in bind Below

close protected mode

see Linux System firewall status , Press q sign out

systemctl status firewalld

Turn off the firewall temporarily

systemctl stop firewalld

test

The return value is PONG The connection is successful

Test related operations

operation String type

operation list

operation set

operation hash

operation zset

One to one correspondence with command line commands .

Case study ： Verification Code ( Six digit random verification code , Two minutes expired , Three times a day for each mobile number )

public class JedisDemo {
    public static void main(String[] args) {
        // User tips 
        System.out.println(" Please enter your mobile phone number ");
        Scanner sc = new Scanner(System.in);
        String tel = sc.next();
        // Verify the number of times sent , Put the verification code in Redis
        verifyCode(tel);
        // The user enters the verification code 
        System.out.println(" Please enter the verification code received ");
        String code = sc.next();
        // Determine whether the verification code is correct 
        getRedisCode(tel, code);
    }

    // Generate verification code 
    public static String generateCode() {
        Random random = new Random();
        String code = "";
        for (int i = 0; i < 6; i++) {
            int rand = random.nextInt(10);
            code += rand;
        }
        return code;
    }

    // Each mobile phone can only send verification code three times a day , Put the verification code in Redis in 
    public static void verifyCode(String tel) {
        // establish Jedis object ,Redis Of the running server ip Address , Port number 
        Jedis jedis = new Jedis("192.168.199.129", 6379);
        // Splicing key
        // The number of times a cell phone sends key
        String countKey = "VerifyCode" + tel + ":count";
        // Verification Code key
        String codeKey = "VerifyCode" + tel + ":code";
        // Each mobile phone can only send three times at a time 
        String count = jedis.get(countKey);
        if (count == null) {
            // First send 
            jedis.setex(countKey, 24 * 60 * 60, "1");
        } else if (Integer.parseInt(count) <= 2) {
            // Send times plus 1
            jedis.incr(countKey);
        } else if (Integer.parseInt(count) > 2) {
            // Has been sent three times 
            System.out.println(" Sent more than three times ");
            jedis.close();
            return;
        }
        // Send verification code to redis In the middle 
        String code = generateCode();
        System.out.println(code);
        jedis.setex(codeKey, 120, code);
        jedis.close();
    }

    // Verification code verification 
    public static void getRedisCode(String tel, String code) {
        // Connect Redis
        Jedis jedis = new Jedis("192.168.199.129", 6379);
        // Verification Code key
        String codeKey = "VerifyCode" + tel + ":code";
        String redisCode = jedis.get(codeKey);
        // Judge 
        if (code.equals(redisCode)) {
            System.out.println(" Verify success ");
        } else {
            System.out.println(" Validation failed ");
        }
    }
}