scala – 在Spark Structured Streaming中外连接两个数据集(不是DataFrame)

2019年7月28日 300次阅读

我有一些代码将两个流式DataFrames和输出连接到控制台.

val dataFrame1 =
  df1Input.withWatermark("timestamp", "40 seconds").as("A")

val dataFrame2 =
  df2Input.withWatermark("timestamp", "40 seconds").as("B")

val finalDF: DataFrame = dataFrame1.join(dataFrame2,
      expr(
        "A.id = B.id" +
          " AND " +
          "B.timestamp >= A.timestamp " +
          " AND " +
          "B.timestamp <= A.timestamp + interval 1 hour")
      , joinType = "leftOuter")
finalDF.writeStream.format("console").start().awaitTermination()

我现在想要的是重构这部分以使用数据集,所以我可以进行一些编译时检查.

所以我尝试的非常简单：

val finalDS: Dataset[(A,B)] = dataFrame1.as[A].joinWith(dataFrame2.as[B],
      expr(
        "A.id = B.id" +
          " AND " +
          "B.timestamp >= A.timestamp " +
          " AND " +
          "B.timestamp <= A.timestamp + interval 1 hour")
      , joinType = "leftOuter")
finalDS.writeStream.format("console").start().awaitTermination()

但是,这会产生以下错误：

org.apache.spark.sql.AnalysisException: Stream-stream outer join between two streaming DataFrame/Datasets is not supported without a watermark in the join keys, or a watermark on the nullable side and an appropriate range condition;;

如您所见,连接代码没有改变,因此两侧都有水印和范围条件.唯一的变化是使用数据集API而不是DataFrame.

另外,当我使用内连接时它很好：

val finalDS: Dataset[(A,B)] = dataFrame1.as[A].joinWith(dataFrame2.as[B],
          expr(
            "A.id = B.id" +
              " AND " +
              "B.timestamp >= A.timestamp " +
              " AND " +
              "B.timestamp <= A.timestamp + interval 1 hour")
          )
    finalDS.writeStream.format("console").start().awaitTermination()

有谁知道这怎么可能发生？

最佳答案 好吧,当你使用joinWith方法而不是join时,你依赖于不同的实现,看起来这个实现不支持leftOuter join用于流式数据集.

您可以查看官方文档的outer joins with watermarking部分.方法join不使用joinWith.请注意,结果类型将是DataFrame.这意味着您很可能必须手动映射字段

val finalDS = dataFrame1.as[A].join(dataFrame2.as[B],
    expr(
      "A.key = B.key" +
        " AND " +
        "B.timestamp >= A.timestamp " +
        " AND " +
        "B.timestamp <= A.timestamp + interval 1 hour"),
    joinType = "leftOuter").select(/* useful fields */).as[C]
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