需求说明
需要实现一个检索功能，需要查询到最近所有的所有热词，自定需求为所有一个月内检索数量最多的10个热词；这里使用Redis的内存数据库功能，其中Redis的ZSet格式提供的功能完全贴合该需求；
后台服务使用SpringBoot实现，由于不想起多余的服务，所以从maven上找了一个可内嵌如SpringBoot的Redis服务。
SpringBoot整合内嵌Redis
pom文件添加，虽然下面这个包两三年没更新了，但亲测可放心使用
<dependency>
<groupId>com.github.kstyrc</groupId>
<artifactId>embedded-redis</artifactId>
<version>0.6</version>
</dependency>
application.xml配置
spring:
redis:
host: localhost
port: 6379
Redis配置类
package cn.com.casic.thinkdata.configuration;
import org.springframework.beans.factory.annotation.Autowired;
import org.springframework.context.annotation.Bean;
import org.springframework.context.annotation.Configuration;
import org.springframework.data.redis.connection.RedisConnectionFactory;
import org.springframework.data.redis.core.HashOperations;
import org.springframework.data.redis.core.ListOperations;
import org.springframework.data.redis.core.RedisTemplate;
import org.springframework.data.redis.core.SetOperations;
import org.springframework.data.redis.core.ValueOperations;
import org.springframework.data.redis.core.ZSetOperations;
import org.springframework.data.redis.serializer.JdkSerializationRedisSerializer;
import org.springframework.data.redis.serializer.StringRedisSerializer;
@Configuration
public class RedisConfig {
/**
* 注入 RedisConnectionFactory
*/
@Autowired
RedisConnectionFactory redisConnectionFactory;
/**
* 存储key值和评分值
*
* @return
*/
@Bean
public RedisTemplate<String, Object> redisKeyDb() {
RedisTemplate<String, Object> redisTemplate = new RedisTemplate<>();
initDomainRedisTemplate(redisTemplate, redisConnectionFactory);
return redisTemplate;
}
/**
* 设置数据存入 redis 的序列化方式
*
* @param redisTemplate
* @param factory
*/
private void initDomainRedisTemplate(RedisTemplate<String, Object> redisTemplate, RedisConnectionFactory factory) {
redisTemplate.setKeySerializer(new StringRedisSerializer());
redisTemplate.setHashKeySerializer(new StringRedisSerializer());
redisTemplate.setHashValueSerializer(new JdkSerializationRedisSerializer());
redisTemplate.setValueSerializer(new JdkSerializationRedisSerializer());
redisTemplate.setConnectionFactory(factory);
}
/**
* 实例化 HashOperations 对象,可以使用 Hash 类型操作
*
* @param redisTemplate
* @return
*/
@Bean
public HashOperations<String, String, Object> hashOperations(RedisTemplate<String, Object> redisTemplate) {
return redisTemplate.opsForHash();
}
/**
* 实例化 ValueOperations 对象,可以使用 String 操作
*
* @param redisTemplate
* @return
*/
@Bean
public ValueOperations<String, Object> valueOperations(RedisTemplate<String, Object> redisTemplate) {
return redisTemplate.opsForValue();
}
/**
* 实例化 ListOperations 对象,可以使用 List 操作
*
* @param redisTemplate
* @return
*/
@Bean
public ListOperations<String, Object> listOperations(RedisTemplate<String, Object> redisTemplate) {
return redisTemplate.opsForList();
}
/**
* 实例化 SetOperations 对象,可以使用 Set 操作
*
* @param redisTemplate
* @return
*/
@Bean
public SetOperations<String, Object> setOperations(RedisTemplate<String, Object> redisTemplate) {
return redisTemplate.opsForSet();
}
/**
* 实例化 ZSetOperations 对象,可以使用 ZSet 操作
*
* @param redisTemplate
* @return
*/
@Bean
public ZSetOperations<String, Object> zSetOperations(RedisTemplate<String, Object> redisTemplate) {
return redisTemplate.opsForZSet();
}
}
热词实现思路
由于热词同时需要兼顾 【检索次数】和【检索时间】两个维度，所以在Redis中同时需要维护【检索次数】和【检索时间】两种数据；
存储【检索次数】数据时，使用redis的ZSet结构，该结构可自动支持数据按分数排序；
redis的service类
package cn.com.casic.thinkdata.service.impl;
import cn.com.casic.thinkdata.service.HotWordService;
import com.google.common.util.concurrent.*;
import lombok.extern.slf4j.Slf4j;
import org.apache.commons.lang3.StringUtils;
import org.springframework.data.redis.core.RedisTemplate;
import org.springframework.data.redis.core.ValueOperations;
import org.springframework.scheduling.annotation.EnableScheduling;
import org.springframework.scheduling.annotation.Scheduled;
import org.springframework.stereotype.Service;
import javax.annotation.Resource;
import java.util.Set;
import java.util.concurrent.*;
@Service
@Slf4j
@EnableScheduling
public class HotWordServiceImpl implements HotWordService {
ListeningExecutorService executorService = MoreExecutors.listeningDecorator(Executors.newFixedThreadPool(1));
@Resource(name = "redisKeyDb")
private RedisTemplate<String, Object> redisKeyDb;
@Override
public void addHotWord(String hotWord) throws Exception {
if (StringUtils.isEmpty(hotWord))
return;
Long now = System.currentTimeMillis(); //记录热词的日期
redisKeyDb.opsForZSet().incrementScore("hotWord", hotWord, 1); // 加入排序set
redisKeyDb.opsForValue().set(hotWord, now); // 记录时间
}
@Override
public Set<Object> getHotWord(int topN) throws Exception {
Set<Object> sets = redisKeyDb.opsForZSet()
.reverseRangeByScore("hotWord", 0, Integer.MAX_VALUE, 0, topN);
return sets;
}
@Override
@Scheduled(cron = "0 0 1 * * ?")
public Boolean clearHotWordOutTime() throws Exception {
ListenableFuture<Boolean> future = executorService.submit(new Callable<Boolean>() {
@Override
public Boolean call() throws Exception {
Long now = System.currentTimeMillis();
ValueOperations<String, Object> wordTime = redisKeyDb.opsForValue();
Set<Object> sets = redisKeyDb.opsForZSet().reverseRange("hotWord", 0, Integer.MAX_VALUE);
for (Object set : sets) {
String word = String.valueOf(set);
Long time = Long.valueOf(String.valueOf(wordTime.get(word)));
if ((now - time) > 2592000000L) { // 找到1个月未操作的数据
redisKeyDb.opsForZSet().remove("hotWord", word);
redisKeyDb.opsForValue().getOperations().delete(word);
}
}
return true;
}
});
Futures.addCallback(future, new FutureCallback<Boolean>() {
@Override
public void onSuccess(Boolean v) {
log.info("@HotWord: clear redis data for hot word month ago successfully");
}
@Override
public void onFailure(Throwable throwable) {
log.info("@HotWord: fail to clear redis data for hot word, message is {}", throwable.getMessage());
}
});
return true;
}
}
为了节约内存使用，使用SpringBoot提供的定时调度功能，每天凌晨1点自动清除一个月前的数据，同时为了清理时不影响其他功能，需要通过线程后台调度，使用ListenableFuture监测执行完毕时，写日志，用于监察记录
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