使用Redis作为维表输入的Flink示例代码

下面是一个使用Redis作为维表输入的Flink示例代码：

import org.apache.flink.api.common.functions.RichFlatMapFunction;
import org.apache.flink.api.common.state.MapState;
import org.apache.flink.api.common.state.MapStateDescriptor;
import org.apache.flink.api.common.typeinfo.TypeInformation;
import org.apache.flink.api.java.tuple.Tuple2;
import org.apache.flink.configuration.Configuration;
import org.apache.flink.streaming.api.datastream.BroadcastStream;
import org.apache.flink.streaming.api.environment.StreamExecutionEnvironment;
import org.apache.flink.streaming.api.functions.co.BroadcastProcessFunction;
import org.apache.flink.streaming.api.functions.source.SourceFunction;
import org.apache.flink.util.Collector;
import redis.clients.jedis.Jedis;
import redis.clients.jedis.JedisPool;
import redis.clients.jedis.JedisPoolConfig;

public class RedisLookupExample {
    public static void main(String[] args) throws Exception {
        StreamExecutionEnvironment env = StreamExecutionEnvironment.getExecutionEnvironment();

        // 创建维表数据源
        RedisTableSource tableSource = new RedisTableSource("localhost", 6379);
        // 从维表数据源中获取维表数据流
        BroadcastStream<Tuple2<String, String>> broadcastStream = env.addSource(tableSource)
                .broadcast(new MapStateDescriptor<>("redis-table", TypeInformation.of(String.class), TypeInformation.of(String.class)));

        // 创建主数据源
        SourceFunction<String> mainSource = new MainDataSource();

        // 连接主数据源和维表数据流
        env.addSource(mainSource)
                .connect(broadcastStream)
                .process(new RedisLookupProcessFunction())
                .print();

        env.execute("Redis Lookup Example");
    }

    // Redis作为维表数据源
    public static class RedisTableSource implements SourceFunction<Tuple2<String, String>> {
        private final String host;
        private final int port;
        private volatile boolean running;

        public RedisTableSource(String host, int port) {
            this.host = host;
            this.port = port;
        }

        @Override
        public void run(SourceContext<Tuple2<String, String>> ctx) throws Exception {
            running = true;

            // 创建JedisPool连接池
            JedisPoolConfig config = new JedisPoolConfig();
            JedisPool jedisPool = new JedisPool(config, host, port);
            Jedis jedis = jedisPool.getResource();

            // 从Redis读取维表数据，并发送到下游
            while (running) {
                // 读取维表数据
                // 示例中假设维表的键和值都是字符串类型
                // 可根据实际情况进行修改
                Map<String, String> redisData = jedis.hgetAll("your-redis-table");

                // 发送维表数据到下游
                for (Map.Entry<String, String> entry : redisData.entrySet()) {
                    ctx.collect(new Tuple2<>(entry.getKey(), entry.getValue()));
                }

                // 每隔一段时间读取一次维表数据
                Thread.sleep(5000);
            }
        }

        @Override
        public void cancel() {
            running = false;
        }
    }

    // 主数据源示例
    public static class MainDataSource implements SourceFunction<String> {
        private volatile boolean running;

        @Override
        public void run(SourceContext<String> ctx) throws Exception {
            running = true;

            // 生成主数据源数据
            // 示例中使用固定的数据源，可根据实际情况进行修改
            String[] data = {"

key1", "key2", "key3", "key4"};

            int i = 0;
            while (running && i < data.length) {
                ctx.collect(data[i]);
                i++;
                Thread.sleep(1000);
            }
        }

        @Override
        public void cancel() {
            running = false;
        }
    }

    // 使用Redis进行维表查询的ProcessFunction
    public static class RedisLookupProcessFunction extends BroadcastProcessFunction<String, Tuple2<String, String>, String> {
        private transient MapState<String, String> redisTable;

        @Override
        public void open(Configuration parameters) throws Exception {
            super.open(parameters);

            // 初始化维表状态
            MapStateDescriptor<String, String> descriptor = new MapStateDescriptor<>(
                    "redis-table",
                    TypeInformation.of(String.class),
                    TypeInformation.of(String.class)
            );
            redisTable = getRuntimeContext().getMapState(descriptor);
        }

        @Override
        public void processElement(String value, ReadOnlyContext ctx, Collector<String> out) throws Exception {
            // 从维表状态中查找对应的值
            String lookupValue = redisTable.get(value);

            // 输出查询结果
            if (lookupValue != null) {
                out.collect("Key: " + value + ", Value: " + lookupValue);
            } else {
                out.collect("Key: " + value + ", Value: Not Found");
            }
        }

        @Override
        public void processBroadcastElement(Tuple2<String, String> value, Context ctx, Collector<String> out) throws Exception {
            // 更新维表状态
            redisTable.put(value.f0, value.f1);
        }
    }
}

上述示例代码中，演示了如何使用Redis作为维表的输入。RedisTableSource实现了SourceFunction接口，从Redis中读取维表数据并发送到下游。MainDataSource是主数据源的示例，它生成主数据流。RedisLookupProcessFunction是处理函数，通过维表状态查询主数据流中的键对应的值，并将结果发送到下游。

在主函数中，首先创建了维表数据源RedisTableSource，然后通过BroadcastStream将维表数据流广播给主数据源。然后连接主数据源和维表数据流，通过RedisLookupProcessFunction进行维表查询，并打印结果。

这个示例中，维表的键和值都是字符串类型，你可以根据实际情况进行修改。同时，需要根据你的Redis部署情况配置RedisTableSource中的连接信息（host和port）。