我有一个简单的scala-seq，我把它转换成Dataframe进行测试有没有类似的方法把scala-seq转换成dstream？
我需要一个从scala seq生成的简单流来进行简单的测试

val spark = SparkSession
      .builder()
      .master("local")
      .getOrCreate()

    import spark.implicits._

    val df1 = Seq(
      ("1", "sri", "2020-01-01"),
      ("1", "hari", "2020-01-02")
    ).toDF("restaurant_id", "customer_name", "visit_date")

    val df2 = Seq(
      ("1", "sri", "2020-01-01")
    ).toDF("restaurant_id", "customer_name", "visit_date")

    df1.registerTempTable("tabl1")
    df2.registerTempTable("tabl2")

    spark
      .sql(
        "select a.*,b.* from tabl1 as a left join tabl2 as b " +
          "on a.restaurant_id=b.restaurant_id and a.visit_date=b.visit_date")
      .show()

    spark
      .sql(
        "select a.*,b.* from tabl1 as a left join tabl2 as b " +
          "on a.restaurant_id=b.restaurant_id and a.visit_date=b.visit_date where b.visit_date is null")
      .show()

Dataframeoutput:-

+-------------+-------------+----------+-------------+-------------+----------+
|restaurant_id|customer_name|visit_date|restaurant_id|customer_name|visit_date|
+-------------+-------------+----------+-------------+-------------+----------+
|            1|          sri|2020-01-01|            1|          sri|2020-01-01|
|            1|         hari|2020-01-02|         null|         null|      null|
+-------------+-------------+----------+-------------+-------------+----------+
+-------------+-------------+----------+-------------+-------------+----------+
|restaurant_id|customer_name|visit_date|restaurant_id|customer_name|visit_date|
+-------------+-------------+----------+-------------+-------------+----------+
|            1|         hari|2020-01-02|         null|         null|      null|
+-------------+-------------+----------+-------------+-------------+----------+

谢谢，斯里