Apache Flink 提供了多种选项来处理数据关联和缓存，以下是一些解决方法的示例代码：

1. 使用 Broadcast State（广播状态）：

// 创建广播状态描述符
MapStateDescriptor broadcastStateDescriptor = new MapStateDescriptor<>(
    "broadcast-state",
    BasicTypeInfo.STRING_TYPE_INFO,
    BasicTypeInfo.INT_TYPE_INFO
);

// 创建广播流
DataStream> broadcastStream = env.fromElements(
    new Tuple2<>("key1", 1),
    new Tuple2<>("key2", 2),
    new Tuple2<>("key3", 3)
);

// 将广播流广播到所有并行任务中
BroadcastStream> broadcast = broadcastStream.broadcast(broadcastStateDescriptor);

// 处理输入流并访问广播状态
DataStream> resultStream = inputStream
    .connect(broadcast)
    .process(new BroadcastProcessFunction<>(
        // 处理输入流的函数
        new ProcessFunction, Tuple2>() {
            @Override
            public void processElement(Tuple2 value, ReadOnlyContext ctx, Collector> out) throws Exception {
                // 访问广播状态
                ReadOnlyBroadcastState state = ctx.getBroadcastState(broadcastStateDescriptor);
                Integer broadcastValue = state.get(value.f0);
                if (broadcastValue != null) {
                    out.collect(new Tuple2<>(value.f0, value.f1 + broadcastValue));
                }
            }
        },
        // 处理广播流的函数
        new BroadcastProcessFunction, Tuple2, Tuple2>() {
            @Override
            public void processBroadcastElement(Tuple2 value, Context ctx, Collector> out) throws Exception {
                // 更新广播状态
                BroadcastState state = ctx.getBroadcastState(broadcastStateDescriptor);
                state.put(value.f0, value.f1);
            }
        }
    ));

2. 使用 CoProcessFunction（两个流的处理函数）：

// 创建第二个流的键控状态描述符
MapStateDescriptor cacheStateDescriptor = new MapStateDescriptor<>(
    "cache-state",
    BasicTypeInfo.STRING_TYPE_INFO,
    BasicTypeInfo.INT_TYPE_INFO
);

// 创建第二个流并将其作为广播流
BroadcastStream> broadcast = cacheStream
    .keyBy(tuple -> tuple.f0)
    .broadcast(cacheStateDescriptor);

// 处理输入流并访问广播状态
DataStream> resultStream = inputStream
    .connect(broadcast)
    .process(new KeyedCoProcessFunction, Tuple2, Tuple2>() {
        private MapState cacheState;

        @Override
        public void open(Configuration parameters) throws Exception {
            // 初始化键控状态
            cacheState = getRuntimeContext().getMapState(cacheStateDescriptor);
        }

        @Override
        public void processElement1(Tuple2 value, Context ctx, Collector> out) throws Exception {
            // 获取广播状态
            Integer broadcastValue = cacheState.get(value.f0);
            if (broadcastValue != null) {
                out.collect(new Tuple2<>(value.f0, value.f1 + broadcastValue));
            }
        }

        @Override
        public void processElement2(Tuple2 value, Context ctx, Collector> out) throws Exception {
            // 更新广播状态
            cacheState.put(value.f0, value.f1);
        }
    });

这些示例展示了如何使用广播状态和键控状态来处理数据关联和缓存。具体的使用方法取决于你的数据和业务需求。请根据你的实际情况选择适合的解决方案。