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Use redis' sorted set to make weekly hot Reviews
2022-06-25 01:15:00 【Java confidant_】
Click on the official account , Practical technical articles Know in time 
General idea
Thought analysis
Do weekly hot discussion , Cache should be used to do , If you check the library directly , It puts pressure on the database . If you do it with a cache , use Redis It's more appropriate to cache .
# utilize Redsi add to Data command
# day:1 Refer to 1 When no. post:1 The first article added 10 comments .
# Back 6 post:2 refer to stay 1 The second part of No. 2 added 6 comments
zadd day:1 10 post:1 6 post:2
zadd day:2 10 post:1 6 post:2
zadd day:3 10 post:1 6 post:2
....
zadd day:8 10 post:1 6 post:2
# That's it 7 A record of days The above command can help us record 7 Number of all comments in days . But it hasn't helped us figure out who is the most commented . see Redis Of sorted set An ordered set has a command that can help us achieve this function .
This command can help us achieve union , We just have to take 7 You can find out by combining the comments of days .
# Redis command
# It means union, put this 7 Days of Put it in a new collection The new set is week:rank In this way, there will be our... In this new collection
#7 Days of records
union week:rank 7 day:1...day:8Redis Command practice to see
Local command line test
127.0.0.1:6379> ping
PONG
127.0.0.1:6379> zadd day:1 10 post:1
(integer) 1
127.0.0.1:6379> zadd day:2 10 post:1
(integer) 1
127.0.0.1:6379> zadd day:3 10 post:1
(integer) 1
127.0.0.1:6379> zadd day:1 5 post:2
(integer) 1
127.0.0.1:6379> zadd day:2 5 post:2
(integer) 1
127.0.0.1:6379> zadd day:3 5 post:2
(integer) 1
127.0.0.1:6379> keys *
1) "day:1"
2) "day:2"
3) "day:3" View the leaderboard command of the day ZRevrange
127.0.0.1:6379> zrevrange day:1 0 -1 withscores
1) "post:1"
2) "10"
3) "post:2"
4) "5"
127.0.0.1:6379>Weekly review leaderboard records . Because I only have three days , So I just wrote it 3 Days of
127.0.0.1:6379> zrevrange week:rank 0 -1 withscores
1) "post:1"
2) "30"
3) "post:2"
4) "15"
127.0.0.1:6379> The above record is correct . The above commands can help us simply realize our idea , Here's how to do it in code . There's a small one on it bug Is that when day:1 This day may appear, but it can't be over directly . May increase one by one , At this time, you should use the auto increment command to solve this problem .
# When +1 When -1 It's when you When you add a comment, add 1 When you delete, subtract 1
ZINCRBY day:1 10 post:1Code to implement
Current front end style , In this case, we need to start this function at the beginning of the project
@Component
// Realization Start class , also Contextual servlect
public class ContextStartup implements ApplicationRunner, ServletContextAware {
// Inject categoryService
@Autowired
IMCategoryService categoryService;
ServletContext servletContext;
// Inject post The service class
@Autowired
IMPostService postService;
@Override
public void run(ApplicationArguments args) throws Exception {
// Call the method of full query
List<MCategory> list = categoryService.list(new QueryWrapper<MCategory>().eq("status", 0));
servletContext.setAttribute("List", list);
// Call the method of weekly hot review
postService.initweek();
}
@Override
public void setServletContext(ServletContext servletContext) {
this.servletContext = servletContext;
}
}Service serviceimpl class
General idea
obtain 7 Articles published within days
Initialize the total reading of the article
Cache the basic information of the article （id, title , comments , author ID ）
In this way, we can avoid searching the database . You can use our cache directly .
Do Union
I need a Redis Tool class of , I found it on the Internet , I didn't write it . There's a lot of stuff on the Internet . Just use it directly
package com.example.springbootblog.util;
import org.springframework.beans.factory.annotation.Autowired;
import org.springframework.data.redis.core.RedisTemplate;
import org.springframework.data.redis.core.ZSetOperations;
import org.springframework.stereotype.Component;
import org.springframework.util.CollectionUtils;
import java.util.Collection;
import java.util.List;
import java.util.Map;
import java.util.Set;
import java.util.concurrent.TimeUnit;
@Component
public class RedisUtil {
@Autowired
private RedisTemplate redisTemplate;
/**
* Specify cache expiration time
*
* @param key key
* @param time Time ( second )
* @return
*/
public boolean expire(String key, long time) {
try {
if (time > 0) {
redisTemplate.expire(key, time, TimeUnit.SECONDS);
}
return true;
} catch (Exception e) {
e.printStackTrace();
return false;
}
}
/**
* according to key Get expiration time
*
* @param key key Not for null
* @return Time ( second ) return 0 Stands for permanent validity
*/
public long getExpire(String key) {
return redisTemplate.getExpire(key, TimeUnit.SECONDS);
}
/**
* Judge key Whether there is
*
* @param key key
* @return true There is false non-existent
*/
public boolean hasKey(String key) {
try {
return redisTemplate.hasKey(key);
} catch (Exception e) {
e.printStackTrace();
return false;
}
}
/**
* Delete cache
*
* @param key You can pass a value Or more
*/
@SuppressWarnings("unchecked")
public void del(String... key) {
if (key != null && key.length > 0) {
if (key.length == 1) {
redisTemplate.delete(key[0]);
} else {
redisTemplate.delete(CollectionUtils.arrayToList(key));
}
}
}
//============================String=============================
/**
* Normal cache fetch
*
* @param key key
* @return value
*/
public Object get(String key) {
return key == null ? null : redisTemplate.opsForValue().get(key);
}
/**
* Normal cache put in
*
* @param key key
* @param value value
* @return true success false Failure
*/
public boolean set(String key, Object value) {
try {
redisTemplate.opsForValue().set(key, value);
return true;
} catch (Exception e) {
e.printStackTrace();
return false;
}
}
/**
* The normal cache is put in and set the time
*
* @param key key
* @param value value
* @param time Time ( second ) time Be greater than 0 If time Less than or equal to 0 Will be set indefinitely
* @return true success false Failure
*/
public boolean set(String key, Object value, long time) {
try {
if (time > 0) {
redisTemplate.opsForValue().set(key, value, time, TimeUnit.SECONDS);
} else {
set(key, value);
}
return true;
} catch (Exception e) {
e.printStackTrace();
return false;
}
}
/**
* Increasing
*
* @param key key
* @param delta How much more should I add ( Greater than 0)
* @return
*/
public long incr(String key, long delta) {
if (delta < 0) {
throw new RuntimeException(" The increment factor must be greater than 0");
}
return redisTemplate.opsForValue().increment(key, delta);
}
/**
* Decline
*
* @param key key
* @param delta To cut it down a few ( Less than 0)
* @return
*/
public long decr(String key, long delta) {
if (delta < 0) {
throw new RuntimeException(" The decline factor must be greater than 0");
}
return redisTemplate.opsForValue().increment(key, -delta);
}
//================================Map=================================
/**
* HashGet
*
* @param key key Not for null
* @param item term Not for null
* @return value
*/
public Object hget(String key, String item) {
return redisTemplate.opsForHash().get(key, item);
}
/**
* obtain hashKey All the corresponding key values
*
* @param key key
* @return Corresponding multiple key values
*/
public Map<Object, Object> hmget(String key) {
return redisTemplate.opsForHash().entries(key);
}
/**
* HashSet
*
* @param key key
* @param map Corresponding to multiple key values
* @return true success false Failure
*/
public boolean hmset(String key, Map<String, Object> map) {
try {
redisTemplate.opsForHash().putAll(key, map);
return true;
} catch (Exception e) {
e.printStackTrace();
return false;
}
}
/**
* HashSet And set the time
*
* @param key key
* @param map Corresponding to multiple key values
* @param time Time ( second )
* @return true success false Failure
*/
public boolean hmset(String key, Map<String, Object> map, long time) {
try {
redisTemplate.opsForHash().putAll(key, map);
if (time > 0) {
expire(key, time);
}
return true;
} catch (Exception e) {
e.printStackTrace();
return false;
}
}
/**
* To a piece of hash Put data in the table , If it doesn't exist, it will create
*
* @param key key
* @param item term
* @param value value
* @return true success false Failure
*/
public boolean hset(String key, String item, Object value) {
try {
redisTemplate.opsForHash().put(key, item, value);
return true;
} catch (Exception e) {
e.printStackTrace();
return false;
}
}
/**
* To a piece of hash Put data in the table , If it doesn't exist, it will create
*
* @param key key
* @param item term
* @param value value
* @param time Time ( second ) Be careful : If there is already hash Watch has time , This will replace the original time
* @return true success false Failure
*/
public boolean hset(String key, String item, Object value, long time) {
try {
redisTemplate.opsForHash().put(key, item, value);
if (time > 0) {
expire(key, time);
}
return true;
} catch (Exception e) {
e.printStackTrace();
return false;
}
}
/**
* Delete hash The values in the table
*
* @param key key Not for null
* @param item term Can make multiple Not for null
*/
public void hdel(String key, Object... item) {
redisTemplate.opsForHash().delete(key, item);
}
/**
* Judge hash Whether there is a value of this item in the table
*
* @param key key Not for null
* @param item term Not for null
* @return true There is false non-existent
*/
public boolean hHasKey(String key, String item) {
return redisTemplate.opsForHash().hasKey(key, item);
}
/**
* hash Increasing If it doesn't exist , It creates a And return the added value to
*
* @param key key
* @param item term
* @param by How much more should I add ( Greater than 0)
* @return
*/
public double hincr(String key, String item, double by) {
return redisTemplate.opsForHash().increment(key, item, by);
}
/**
* hash Decline
*
* @param key key
* @param item term
* @param by Remember less ( Less than 0)
* @return
*/
public double hdecr(String key, String item, double by) {
return redisTemplate.opsForHash().increment(key, item, -by);
}
//============================set=============================
/**
* according to key obtain Set All the values in
*
* @param key key
* @return
*/
public Set<Object> sGet(String key) {
try {
return redisTemplate.opsForSet().members(key);
} catch (Exception e) {
e.printStackTrace();
return null;
}
}
/**
* according to value From a set Query in , Whether there is
*
* @param key key
* @param value value
* @return true There is false non-existent
*/
public boolean sHasKey(String key, Object value) {
try {
return redisTemplate.opsForSet().isMember(key, value);
} catch (Exception e) {
e.printStackTrace();
return false;
}
}
/**
* Put data into set cache
*
* @param key key
* @param values value It can be more than one
* @return The number of successes
*/
public long sSet(String key, Object... values) {
try {
return redisTemplate.opsForSet().add(key, values);
} catch (Exception e) {
e.printStackTrace();
return 0;
}
}
/**
* take set Data is put into the cache
*
* @param key key
* @param time Time ( second )
* @param values value It can be more than one
* @return The number of successes
*/
public long sSetAndTime(String key, long time, Object... values) {
try {
Long count = redisTemplate.opsForSet().add(key, values);
if (time > 0) expire(key, time);
return count;
} catch (Exception e) {
e.printStackTrace();
return 0;
}
}
/**
* obtain set The length of the cache
*
* @param key key
* @return
*/
public long sGetSetSize(String key) {
try {
return redisTemplate.opsForSet().size(key);
} catch (Exception e) {
e.printStackTrace();
return 0;
}
}
/**
* The removal value is value Of
*
* @param key key
* @param values value It can be more than one
* @return Number of removed
*/
public long setRemove(String key, Object... values) {
try {
Long count = redisTemplate.opsForSet().remove(key, values);
return count;
} catch (Exception e) {
e.printStackTrace();
return 0;
}
}
//===============================list=================================
/**
* obtain list The contents of the cache
*
* @param key key
* @param start Start
* @param end end 0 To -1 For all values
* @return
*/
public List<Object> lGet(String key, long start, long end) {
try {
return redisTemplate.opsForList().range(key, start, end);
} catch (Exception e) {
e.printStackTrace();
return null;
}
}
/**
* obtain list The length of the cache
*
* @param key key
* @return
*/
public long lGetListSize(String key) {
try {
return redisTemplate.opsForList().size(key);
} catch (Exception e) {
e.printStackTrace();
return 0;
}
}
/**
* Through the index obtain list The value in
*
* @param key key
* @param index Indexes index>=0 when , 0 Header ,1 The second element , By analogy ;index<0 when ,-1, Tail ,-2 The next to last element , By analogy
* @return
*/
public Object lGetIndex(String key, long index) {
try {
return redisTemplate.opsForList().index(key, index);
} catch (Exception e) {
e.printStackTrace();
return null;
}
}
/**
* take list Put into cache
*
* @param key key
* @param value value
* @return
*/
public boolean lSet(String key, Object value) {
try {
redisTemplate.opsForList().rightPush(key, value);
return true;
} catch (Exception e) {
e.printStackTrace();
return false;
}
}
/**
* take list Put into cache
*
* @param key key
* @param value value
* @param time Time ( second )
* @return
*/
public boolean lSet(String key, Object value, long time) {
try {
redisTemplate.opsForList().rightPush(key, value);
if (time > 0) expire(key, time);
return true;
} catch (Exception e) {
e.printStackTrace();
return false;
}
}
/**
* take list Put into cache
*
* @param key key
* @param value value
* @return
*/
public boolean lSet(String key, List<Object> value) {
try {
redisTemplate.opsForList().rightPushAll(key, value);
return true;
} catch (Exception e) {
e.printStackTrace();
return false;
}
}
/**
* take list Put into cache
*
* @param key key
* @param value value
* @param time Time ( second )
* @return
*/
public boolean lSet(String key, List<Object> value, long time) {
try {
redisTemplate.opsForList().rightPushAll(key, value);
if (time > 0) expire(key, time);
return true;
} catch (Exception e) {
e.printStackTrace();
return false;
}
}
/**
* Modify according to the index list A piece of data in
*
* @param key key
* @param index Indexes
* @param value value
* @return
*/
public boolean lUpdateIndex(String key, long index, Object value) {
try {
redisTemplate.opsForList().set(key, index, value);
return true;
} catch (Exception e) {
e.printStackTrace();
return false;
}
}
/**
* remove N The values are value
*
* @param key key
* @param count How many removed
* @param value value
* @return Number of removed
*/
public long lRemove(String key, long count, Object value) {
try {
Long remove = redisTemplate.opsForList().remove(key, count, value);
return remove;
} catch (Exception e) {
e.printStackTrace();
return 0;
}
}
//================ Ordered set sort set===================
/**
* Orderly set Additive elements
*
* @param key
* @param value
* @param score
* @return
*/
public boolean zSet(String key, Object value, double score) {
return redisTemplate.opsForZSet().add(key, value, score);
}
public long batchZSet(String key, Set<ZSetOperations.TypedTuple> typles) {
return redisTemplate.opsForZSet().add(key, typles);
}
public void zIncrementScore(String key, Object value, long delta) {
redisTemplate.opsForZSet().incrementScore(key, value, delta);
}
public void zUnionAndStore(String key, Collection otherKeys, String destKey) {
redisTemplate.opsForZSet().unionAndStore(key, otherKeys, destKey);
}
/**
* obtain zset Number
* @param key
* @param value
* @return
*/
public long getZsetScore(String key, Object value) {
Double score = redisTemplate.opsForZSet().score(key, value);
if(score==null){
return 0;
}else{
return score.longValue();
}
}
/**
* Get ordered set key Member of the member Ranking .
* The members of the ordered set press score The value is decreasing ( From big to small ) Sort .
* @param key
* @param start
* @param end
* @return
*/
public Set<ZSetOperations.TypedTuple> getZSetRank(String key, long start, long end) {
return redisTemplate.opsForZSet().reverseRangeWithScores(key, start, end);
}
}Code of implementation class
// The method of weekly hot review
@Override
public void initweek() {
// obtain 7 Day's article
List<MPost> posts = this.list(new QueryWrapper<MPost>().ge("created", DateUtil.lastWeek())
.select("id", "title", "user_id", "comment_count", "view_count", "created")
);// Get 7 Days ago and according to these queries , You don't need to query all
// Initialize the general comments of the article
for (MPost post : posts) {
// Set up key
String key = "day:rank:" + DateUtil.format(post.getCreated(), DatePattern.PURE_DATE_FORMAT);
// Number of comments cached
redisUtil.zSet(key, post.getId(), post.getCommentCount());
// Set auto expiration 7 Days overdue
long between = DateUtil.between(new Date(), post.getCreated(), DateUnit.DAY);
long expireTime = (7 - between) * 24 * 60 * 60; // It works Time
redisUtil.expire(key, expireTime);
// Cache some basic information of the article
this.hashCachePost(post, expireTime);
}
// Do Union
this.zunionAndStore();
}
/**
* The number of comments per week is combined
**/
private void zunionAndStore() {
String destkey = "day:rank:" + DateUtil.format(new Date(), DatePattern.PURE_DATE_FORMAT);
// Set new after union key
String newkey = "week:rank";
ArrayList<String> otherKeys = new ArrayList<>();
// Calculation 7 Days of
for (int i = -6; i < 0; i++) {
String temp = "day:rank:" + DateUtil.format(DateUtil.offsetDay(new Date(), i), DatePattern.PURE_DATE_FORMAT);
otherKeys.add(temp);
}
redisUtil.zUnionAndStore(destkey, otherKeys, newkey);
}
/**
* Article author
**/
private void hashCachePost(MPost post, long expireTime) {
// Set up key
String key = "rank:post:" + post.getId();
// Judge whether there is
boolean hasKey = redisUtil.hasKey(key);
if (!hasKey) {
// Just put it in the cache
redisUtil.hset(key, "post:id", post.getId(), expireTime);
redisUtil.hset(key, "post:title", post.getTitle(), expireTime);
redisUtil.hset(key, "post:commentCount", post.getCommentCount(), expireTime);
}
}
}In this way, we can convert our command line into code form . Then we can store the data of our database in the cache first .
effect
127.0.0.1:6379> keys *
1) "rank:post:4"
2) "week:rank"
3) "day:rank:20210724"
4) "rank:post:3"
5) "rank:post:2"
6) "day:rank:20210726"
# Look at the data after our union id by 3 There are 1 comments .
127.0.0.1:6379> zrevrange week:rank 0 -1 withscores
1) "3"
2) "1"
3) "2"
4) "1"
5) "4"
6) "0"
127.0.0.1:6379>In the database id by 3 There are 1 comments
There is really only one comment
The front end is displayed
The idea here is relatively simple , Just take our data out of the cache . With freemarker You can customize the label . I customized the label .
Hosttemplate
/**
* Hot discussion this week
*/
@Component
public class HotsTemplate extends TemplateDirective {
@Autowired
RedisUtil redisUtil;
@Override
public String getName() {
return "hots";
}
@Override
public void execute(DirectiveHandler handler) throws Exception {
// Set up key
String key ="week:rank";
Set<ZSetOperations.TypedTuple> zSetRank = redisUtil.getZSetRank(key, 0, 6);
ArrayList<Map> maps = new ArrayList<>();
// facilitate
for (ZSetOperations.TypedTuple typedTuple : zSetRank) {
// establish Map
HashMap<String, Object> map = new HashMap<>();
Object post_id = typedTuple.getValue();
String PostHashKey = "rank:post:" +post_id;
map.put("id",post_id);
map.put("title",redisUtil.hget(PostHashKey,"post:title"));
map.put("commentCount",typedTuple.getScore());
maps.add(map);
}
handler.put(RESULTS,maps).render();
}
} stay FreemarkerConfig We can use our custom tags by injecting the notes we wrote
@Configuration
public class FreemarkerConfig {
@Autowired
private freemarker.template.Configuration configuration;
@Autowired
PostsTemplate postsTemplate;
@Autowired
HotsTemplate hotsTemplate;
@PostConstruct
public void setUp() {
configuration.setSharedVariable("timeAgo", new TimeAgoMethod());
configuration.setSharedVariable("posts", postsTemplate);
configuration.setSharedVariable("hosts", hotsTemplate);
}
}Get the front page
effect
summary
When doing this function . Not comprehensive enough . Although it's finished , But it should be to get 7 Comments within days . I got 7 Day's article . Though it is a bug But I don't want to fix . be it so . Just use it now . It's the same thing . There will be time for problems. Let's change it . Tired , Ruthless code machines record code life .....
source ：blog.csdn.net/m0_46937429/article/
details/119172118
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