Flink中的DataStream和DataSet有什么区别？请解释其概念和用途。

import org.apache.flink.api.java.tuple.Tuple2;
import org.apache.flink.streaming.api.datastream.DataStream;
import org.apache.flink.streaming.api.environment.StreamExecutionEnvironment;
import org.apache.flink.streaming.api.windowing.time.Time;
public class PurchaseBehaviorAnalysis {
    public static void main(String[] args) throws Exception {
        // 创建流处理环境
        StreamExecutionEnvironment env = StreamExecutionEnvironment.getExecutionEnvironment();
        // 创建DataStream，从Kafka中接收购买行为数据流
        DataStream<PurchaseEvent> purchaseStream = env.addSource(new KafkaSource<>());
        // 使用DataStream进行实时购买金额统计
        DataStream<Tuple2<String, Double>> purchaseAmountStream = purchaseStream
                .keyBy(PurchaseEvent::getUserId)
                .timeWindow(Time.minutes(10))
                .sum("amount");
        // 使用DataStream进行实时推荐
        DataStream<Recommendation> recommendationStream = purchaseAmountStream
                .filter(tuple -> tuple.f1 > 100) // 过滤购买总金额大于100的用户
                .map(tuple -> new Recommendation(tuple.f0, "Recommended Product"));
        // 打印实时推荐结果
        recommendationStream.print();
        // 执行流处理任务
        env.execute("Purchase Behavior Analysis");
    }
}
class PurchaseEvent {
    private String userId;
    private double amount;
    // 省略构造函数、getter和setter
}
class Recommendation {
    private String userId;
    private String productId;
    // 省略构造函数、getter和setter
}