写作时间：2019-12-01
Spring Boot: 2.1 ,JDK: 1.8, IDE: IntelliJ IDEA

1. 说明

响应式编程操作Redis，Lettuce能够支持Reactive方式。
Spring Data Redis 中主要的支持：

ReactiveRedisConnection
ReactiveRedisConnectionFactory
ReactiveRedisTemplate
opsForXxx()

响应式编程的概念请参考：
第三十篇：SpringBoot Reactor响应式编程介绍
 第三十一篇：SpringBoot Reactor响应式编程实战一。
在这里插入图片描述

2. Docker 启动Redis

查看历史上启动过的Redis进程

% docker ps -a
CONTAINER ID        IMAGE               COMMAND                  CREATED             STATUS                      PORTS                      NAMES
8eb8d32453bb        redis               "docker-entrypoint.s…"   2 months ago        Up 19 minutes               0.0.0.0:6379->6379/tcp     redis

启动Redis进程

% docker start redis
redis

启动Redis客户端, 查看所有的keys，目前是空的。

% docker exec -it redis redis-cli
127.0.0.1:6379> keys *
(empty list or set)

详细解释可以参考：
第廿三篇：SpringBoot之Docker入门
 第三十二篇：Redis Docker入门

3. 工程建立

参照教程【SpringBoot 2.1 | 第一篇：构建第一个SpringBoot工程】新建一个Spring Boot项目，名字叫RPCClient，在目录src/main/java/resources 下找到配置文件application.properties，重命名为application.yml。

Spring Boot 版本选择2.1.10，依赖勾选Developer Tools > Lombok.
SQL > Spring Data JDBC, H2 Database
NoSQL > Spring Data Reactive Redis
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4. application.yml配置文件

spring:
  redis:
    host: "localhost"

5. 数据库建表和初始化数据

在 application.yml的同级目录，创建文件schema.sql

drop table t_coffee if exists;

create table t_coffee (
    id bigint auto_increment,
    create_time timestamp,
    update_time timestamp,
    name varchar(255),
    price bigint,
    primary key (id)
);

在 application.yml的同级目录，创建文件data.sql

insert into t_coffee (name, price, create_time, update_time) values ('espresso', 2000, now(), now());
insert into t_coffee (name, price, create_time, update_time) values ('latte', 2500, now(), now());
insert into t_coffee (name, price, create_time, update_time) values ('capuccino', 2500, now(), now());
insert into t_coffee (name, price, create_time, update_time) values ('mocha', 3000, now(), now());
insert into t_coffee (name, price, create_time, update_time) values ('macchiato', 3000, now(), now());

6. 创建Model

com.zgpeace.reactive.Coffee

package com.zgpeace.reactive;

import lombok.AllArgsConstructor;
import lombok.Builder;
import lombok.Data;
import lombok.NoArgsConstructor;

@Data
@Builder
@NoArgsConstructor
@AllArgsConstructor
public class Coffee {
  private Long id;
  private String name;
  private Long price;
}

7. Controller

package com.zgpeace.reactive;

import lombok.extern.slf4j.Slf4j;
import org.springframework.beans.factory.annotation.Autowired;
import org.springframework.boot.ApplicationArguments;
import org.springframework.boot.ApplicationRunner;
import org.springframework.boot.SpringApplication;
import org.springframework.boot.autoconfigure.SpringBootApplication;
import org.springframework.context.annotation.Bean;
import org.springframework.data.redis.connection.ReactiveRedisConnectionFactory;
import org.springframework.data.redis.core.ReactiveHashOperations;
import org.springframework.data.redis.core.ReactiveStringRedisTemplate;
import org.springframework.jdbc.core.JdbcTemplate;
import reactor.core.publisher.Flux;
import reactor.core.publisher.Mono;
import reactor.core.scheduler.Schedulers;

import java.time.Duration;
import java.util.List;
import java.util.concurrent.CountDownLatch;

@SpringBootApplication
@Slf4j
public class ReactiveApplication  implements ApplicationRunner {
  private static final String KEY = "COFFEE_MENU";

  @Autowired
  private JdbcTemplate jdbcTemplate;
  @Autowired
  private ReactiveStringRedisTemplate redisTemplate;

  public static void main(String[] args) {
    SpringApplication.run(ReactiveApplication.class, args);
  }

  @Bean
  ReactiveStringRedisTemplate reactiveRedisTemplate(ReactiveRedisConnectionFactory factory) {
    return new ReactiveStringRedisTemplate(factory);
  }

  @Override
  public void run(ApplicationArguments args) throws Exception {
    ReactiveHashOperations<String, String, String> hashOps = redisTemplate.opsForHash();
    CountDownLatch cdl = new CountDownLatch(1);

    List<Coffee> list = jdbcTemplate.query(
        "select * from t_coffee", (rs, i) ->
            Coffee.builder()
                .id(rs.getLong("id"))
                .name(rs.getString("name"))
                .price(rs.getLong("price"))
                .build()
    );

    Flux.fromIterable(list)
        .publishOn(Schedulers.single())
        .doOnComplete(() -> log.info("list ok"))
        .flatMap(c -> {
          log.info("try to put {},{}", c.getName(), c.getPrice());
          return hashOps.put(KEY, c.getName(), c.getPrice().toString());
        })
        .doOnComplete(() -> log.info("set ok"))
        .concatWith(redisTemplate.expire(KEY, Duration.ofMinutes(1)))
        .doOnComplete(() -> log.info("expire ok"))
        .onErrorResume(e -> {
          log.error("exception {}", e.getMessage());
          return Mono.just(false);
        })
        .subscribe(b -> log.info("Boolean: {}", b),
            e -> log.error("Exception {}", e.getMessage()),
            () -> cdl.countDown());
    log.info("Waiting");
    cdl.await();
  }
}

解析：

jdbcTemplate.query 查询数据库中数据，并组装为List
Flux.fromIterable(list)遍历列表
publishOn(Schedulers.single())在单线程中Publisher执行
flatMap 把数组存入redis
concatWith(redisTemplate.expire(KEY, Duration.ofMinutes(1))) 设置Redis数据过期时间为1分钟。
CountDownLatch 同步线程锁，一次只允许一个线程任务处理。

结果输出如下

Bootstrapping Spring Data repositories in DEFAULT mode.
[           main] .s.d.r.c.RepositoryConfigurationDelegate : Finished Spring Data repository scanning in 1ms. Found 0 repository interfaces.
[           main] com.zaxxer.hikari.HikariDataSource       : HikariPool-1 - Starting...
[           main] com.zaxxer.hikari.HikariDataSource       : HikariPool-1 - Start completed.
[           main] c.zgpeace.reactive.ReactiveApplication   : Started ReactiveApplication in 1.279 seconds (JVM running for 1.779)
[           main] c.zgpeace.reactive.ReactiveApplication   : Waiting
[       single-1] c.zgpeace.reactive.ReactiveApplication   : try to put espresso,2000
[       single-1] io.lettuce.core.EpollProvider            : Starting without optional epoll library
[       single-1] io.lettuce.core.KqueueProvider           : Starting without optional kqueue library
[       single-1] c.zgpeace.reactive.ReactiveApplication   : try to put latte,2500
[       single-1] c.zgpeace.reactive.ReactiveApplication   : try to put capuccino,2500
[       single-1] c.zgpeace.reactive.ReactiveApplication   : try to put mocha,3000
[       single-1] c.zgpeace.reactive.ReactiveApplication   : try to put macchiato,3000
[       single-1] c.zgpeace.reactive.ReactiveApplication   : list ok
[ioEventLoop-4-1] c.zgpeace.reactive.ReactiveApplication   : Boolean: true
[ioEventLoop-4-1] c.zgpeace.reactive.ReactiveApplication   : Boolean: true
[ioEventLoop-4-1] c.zgpeace.reactive.ReactiveApplication   : Boolean: true
[ioEventLoop-4-1] c.zgpeace.reactive.ReactiveApplication   : Boolean: true
[ioEventLoop-4-1] c.zgpeace.reactive.ReactiveApplication   : Boolean: true
[ioEventLoop-4-1] c.zgpeace.reactive.ReactiveApplication   : set ok
[ioEventLoop-4-1] c.zgpeace.reactive.ReactiveApplication   : Boolean: true
[ioEventLoop-4-1] c.zgpeace.reactive.ReactiveApplication   : expire ok
[       Thread-5] com.zaxxer.hikari.HikariDataSource       : HikariPool-1 - Shutdown initiated...
[       Thread-5] com.zaxxer.hikari.HikariDataSource       : HikariPool-1 - Shutdown completed.

8. 查看Redis数据

在Terminal中查看Redis数据

127.0.0.1:6379> keys *
1) "COFFEE_MENU"
127.0.0.1:6379> hgetall COFFEE_MENU
 1) "espresso"
 2) "2000"
 3) "latte"
 4) "2500"
 5) "capuccino"
 6) "2500"
 7) "mocha"
 8) "3000"
 9) "macchiato"
10) "3000"