Apache Flink 是一个开源的流处理框架，它可以处理多个流。以下是一个示例代码，展示了如何处理三个流：

首先，我们需要导入必要的 Flink 库：

import org.apache.flink.api.common.functions.MapFunction;
import org.apache.flink.streaming.api.datastream.DataStream;
import org.apache.flink.streaming.api.environment.StreamExecutionEnvironment;

然后，我们创建一个 StreamExecutionEnvironment，并定义三个输入流：

StreamExecutionEnvironment env = StreamExecutionEnvironment.getExecutionEnvironment();

DataStream stream1 = env.fromElements("Hello", "World");
DataStream stream2 = env.fromElements("Flink", "Stream");
DataStream stream3 = env.fromElements("Processing", "Example");

接下来，我们可以对这三个流进行一些操作，比如将它们合并成一个流、对每个元素进行映射等：

DataStream mergedStream = stream1.union(stream2).union(stream3);

DataStream mappedStream = mergedStream.map(new MapFunction() {
    @Override
    public String map(String value) throws Exception {
        return value.toUpperCase();
    }
});

最后，我们可以将处理后的结果打印出来：

mappedStream.print();

env.execute("Processing Three Streams Example");

完整的示例代码如下：

import org.apache.flink.api.common.functions.MapFunction;
import org.apache.flink.streaming.api.datastream.DataStream;
import org.apache.flink.streaming.api.environment.StreamExecutionEnvironment;

public class ProcessThreeStreamsExample {

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

        DataStream stream1 = env.fromElements("Hello", "World");
        DataStream stream2 = env.fromElements("Flink", "Stream");
        DataStream stream3 = env.fromElements("Processing", "Example");

        DataStream mergedStream = stream1.union(stream2).union(stream3);

        DataStream mappedStream = mergedStream.map(new MapFunction() {
            @Override
            public String map(String value) throws Exception {
                return value.toUpperCase();
            }
        });

        mappedStream.print();

        env.execute("Processing Three Streams Example");
    }
}

运行该代码，你将会看到合并并映射后的结果被打印出来。