redisTemplate.opsForValue().set(K key, V value, Duration timeout)

对于这个问题，`redisTemplate.opsForValue().set(K key, V value, Duration timeout)`是Redis Template提供的一个方法，用于在Redis中设置一个键值对，并指定键的过期时间。

具体参数说明如下：
- `K key`: 键的类型
- `V value`: 值的类型
- `Duration timeout`: 键的过期时间

通过调用该方法，你可以将指定的键值对存储在Redis中，并设置键的过期时间。这样，在指定的过期时间之后，Redis会自动删除该键值对。

相关问题

Spring Boot+Mybatis Plus 使用Redis实现二级缓存具体步骤以及代码

非常感谢您的提问。以下是 Spring Boot Mybatis Plus 使用 Redis 实现二级缓存的具体步骤和代码：

1. 首先，在 pom.xml 文件中添加 Redis 相关依赖：

<dependency>
    <groupId>org.springframework.boot</groupId>
    <artifactId>spring-boot-starter-data-redis</artifactId>
</dependency>
<dependency>
    <groupId>com.baomidou</groupId>
    <artifactId>mybatis-plus-boot-starter</artifactId>
    <version>3.4.0</version>
</dependency>

2. 在 application.properties 文件中添加 Redis 相关配置：

spring.redis.host=127.0.0.1
spring.redis.port=6379
spring.redis.database=0
spring.redis.password=
spring.redis.timeout=3000
spring.redis.jedis.pool.max-active=8
spring.redis.jedis.pool.max-wait=-1
spring.redis.jedis.pool.max-idle=8
spring.redis.jedis.pool.min-idle=0

3. 在 Mybatis Plus 的配置文件中开启二级缓存，并配置 Redis 缓存：

@Configuration
@MapperScan("com.example.mapper")
public class MybatisPlusConfig {

    @Bean
    public ConfigurationCustomizer configurationCustomizer() {
        return new ConfigurationCustomizer() {
            @Override
            public void customize(Configuration configuration) {
                // 开启二级缓存
                configuration.setCacheEnabled(true);
                // 配置 Redis 缓存
                RedisCacheConfiguration redisCacheConfiguration = RedisCacheConfiguration.defaultCacheConfig()
                        .entryTtl(Duration.ofMinutes(30)); // 设置缓存过期时间为 30 分钟
                configuration.addCache(new RedisCache("mybatis-plus", new RedisCacheWriter() {
                    @Override
                    public void put(String key, byte[] value) {
                        redisTemplate().opsForValue().set(key, value, Duration.ofMinutes(30));
                    }

                    @Override
                    public byte[] get(String key) {
                        return redisTemplate().opsForValue().get(key);
                    }

                    @Override
                    public void put(String key, byte[] value, long time, TimeUnit unit) {
                        redisTemplate().opsForValue().set(key, value, Duration.ofMillis(unit.toMillis(time)));
                    }

                    @Override
                    public void delete(String key) {
                        redisTemplate().delete(key);
                    }

                    @Override
                    public void clean() {
                        redisTemplate().getConnectionFactory().getConnection().flushDb();
                    }

                    @Override
                    public long size() {
                        return redisTemplate().getConnectionFactory().getConnection().dbSize();
                    }
                }, redisCacheConfiguration));
            }
        };
    }

    @Bean
    public RedisTemplate<String, Object> redisTemplate() {
        RedisTemplate<String, Object> redisTemplate = new RedisTemplate<>();
        redisTemplate.setConnectionFactory(redisConnectionFactory());
        redisTemplate.setKeySerializer(new StringRedisSerializer());
        redisTemplate.setValueSerializer(new JdkSerializationRedisSerializer());
        redisTemplate.setHashKeySerializer(new StringRedisSerializer());
        redisTemplate.setHashValueSerializer(new JdkSerializationRedisSerializer());
        return redisTemplate;
    }

    @Bean
    public RedisConnectionFactory redisConnectionFactory() {
        LettuceConnectionFactory lettuceConnectionFactory = new LettuceConnectionFactory();
        lettuceConnectionFactory.setHostName("127.0.0.1");
        lettuceConnectionFactory.setPort(6379);
        lettuceConnectionFactory.setPassword("");
        lettuceConnectionFactory.setDatabase(0);
        return lettuceConnectionFactory;
    }
}

4. 在需要使用二级缓存的 Mapper 中添加 @CacheNamespace 注解：

@CacheNamespace(implementation = MybatisRedisCache.class, eviction = MybatisRedisCache.class)
public interface UserMapper extends BaseMapper<User> {
    // ...
}

5. 最后，实现 MybatisRedisCache 类，继承自 RedisCache，重写 clear 方法：

public class MybatisRedisCache extends RedisCache {

    public MybatisRedisCache(String name, RedisCacheWriter cacheWriter, RedisCacheConfiguration configuration) {
        super(name, cacheWriter, configuration);
    }

    @Override
    public void clear() {
        RedisConnection connection = Objects.requireNonNull(getRedisCacheWriter().getRedisConnectionFactory().getConnection());
        connection.flushDb();
        connection.close();
    }
}

以上就是 Spring Boot Mybatis Plus 使用 Redis 实现二级缓存的具体步骤和代码。希望能对您有所帮助！

bin/kafka-consumer-groups.sh --bootstrap-server localhost:9092 --describe --group test 用java实现

你可以使用 Kafka 的 Java API 来实现这个命令，具体实现如下：

import org.apache.kafka.clients.admin.AdminClient;
import org.apache.kafka.clients.admin.AdminClientConfig;
import org.apache.kafka.clients.admin.ConsumerGroupDescription;
import org.apache.kafka.clients.admin.ConsumerGroupListing;
import org.apache.kafka.clients.admin.ListConsumerGroupOffsetsResult;
import org.apache.kafka.clients.admin.ListConsumerGroupsResult;
import org.apache.kafka.clients.admin.ListOffsetsResult;
import org.apache.kafka.clients.admin.OffsetSpec;
import org.apache.kafka.clients.admin.TopicDescription;
import org.apache.kafka.clients.consumer.ConsumerConfig;
import org.apache.kafka.clients.consumer.KafkaConsumer;
import org.apache.kafka.common.TopicPartition;
import org.apache.kafka.common.serialization.StringDeserializer;

import java.time.Duration;
import java.util.Collections;
import java.util.Map;
import java.util.Properties;
import java.util.Set;
import java.util.concurrent.ExecutionException;

public class KafkaConsumerGroups {

    public static void main(String[] args) throws ExecutionException, InterruptedException {
        Properties adminProps = new Properties();
        adminProps.put(AdminClientConfig.BOOTSTRAP_SERVERS_CONFIG, "localhost:9092");
        AdminClient adminClient = AdminClient.create(adminProps);

        // List Consumer Groups
        ListConsumerGroupsResult consumerGroupsResult = adminClient.listConsumerGroups();
        Set<ConsumerGroupListing> consumerGroups = consumerGroupsResult.all().get();
        for (ConsumerGroupListing group : consumerGroups) {
            System.out.println("Consumer Group: " + group.groupId());
            // Describe Consumer Group
            ConsumerGroupDescription consumerGroupDescription = adminClient.describeConsumerGroups(Collections.singleton(group.groupId())).all().get().get(group.groupId());
            System.out.println("State: " + consumerGroupDescription.state());
            System.out.println("Coordinator: " + consumerGroupDescription.coordinator().toString());
            System.out.println("Members: " + consumerGroupDescription.members().size());
            System.out.println("Topic Partitions:");
            Map<String, TopicDescription> topicDescriptions = adminClient.describeTopics(consumerGroupDescription.members().stream().map(member -> member.assignment().topicPartitions().iterator().next().topic()).distinct().toArray(String[]::new)).all().get();
            for (TopicDescription topicDescription : topicDescriptions.values()) {
                for (TopicPartition partition : topicDescription.partitions()) {
                    System.out.println("\t" + topicDescription.name() + "-" + partition.partition() + ": " + consumerGroupDescription.assignment().partitionsForTopic(topicDescription.name()).contains(partition));
                }
            }

            // List Consumer Group Offsets
            ListConsumerGroupOffsetsResult consumerGroupOffsetsResult = adminClient.listConsumerGroupOffsets(group.groupId());
            Map<TopicPartition, Long> consumerGroupOffsets = consumerGroupOffsetsResult.partitionsToOffsetAndMetadata().get();
            System.out.println("Consumer Group Offsets:");
            for (Map.Entry<TopicPartition, Long> entry : consumerGroupOffsets.entrySet()) {
                System.out.println("\t" + entry.getKey().topic() + "-" + entry.getKey().partition() + ": " + entry.getValue());
            }

            // List Latest Offsets
            Properties consumerProps = new Properties();
            consumerProps.put(ConsumerConfig.BOOTSTRAP_SERVERS_CONFIG, "localhost:9092");
            consumerProps.put(ConsumerConfig.ENABLE_AUTO_COMMIT_CONFIG, "false");
            consumerProps.put(ConsumerConfig.GROUP_ID_CONFIG, group.groupId());
            consumerProps.put(ConsumerConfig.KEY_DESERIALIZER_CLASS_CONFIG, StringDeserializer.class);
            consumerProps.put(ConsumerConfig.VALUE_DESERIALIZER_CLASS_CONFIG, StringDeserializer.class);
            KafkaConsumer<String, String> consumer = new KafkaConsumer<>(consumerProps);
            Map<TopicPartition, Long> latestOffsets = consumer.endOffsets(consumerGroupOffsets.keySet(), Duration.ofSeconds(5));
            System.out.println("Latest Offsets:");
            for (Map.Entry<TopicPartition, Long> entry : latestOffsets.entrySet()) {
                System.out.println("\t" + entry.getKey().topic() + "-" + entry.getKey().partition() + ": " + entry.getValue());
            }

            // List Earliest Offsets
            Map<TopicPartition, Long> earliestOffsets = consumer.beginningOffsets(consumerGroupOffsets.keySet(), Duration.ofSeconds(5));
            System.out.println("Earliest Offsets:");
            for (Map.Entry<TopicPartition, Long> entry : earliestOffsets.entrySet()) {
                System.out.println("\t" + entry.getKey().topic() + "-" + entry.getKey().partition() + ": " + entry.getValue());
            }
        }
    }
}

这个程序使用 Kafka 的 AdminClient 来获取消费者组信息、消费者组偏移量以及主题分区的最早和最新偏移量。你可以根据自己的需求修改程序，例如只获取特定的消费者组信息等。