具有三向连接的Spark结构化流的水印

Che*_*ovP 5 scala apache-spark spark-structured-streaming

我有3个数据流:foo,barbaz.

LEFT OUTER JOIN在以下链中加入这些流是必要的:foo -> bar -> baz.

这是尝试使用内置流模拟这些rate流:

val rateStream = session.readStream
  .format("rate")
  .option("rowsPerSecond", 5)
  .option("numPartitions", 1)
  .load()

val fooStream = rateStream
  .select(col("value").as("fooId"), col("timestamp").as("fooTime"))

val barStream = rateStream
  .where(rand() < 0.5) // Introduce misses for ease of debugging
  .select(col("value").as("barId"), col("timestamp").as("barTime"))

val bazStream = rateStream
  .where(rand() < 0.5) // Introduce misses for ease of debugging
  .select(col("value").as("bazId"), col("timestamp").as("bazTime"))
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这是将这些流连接在一起的第一种方法,假设潜在的延迟foo,bar并且baz很小(〜5 seconds):

val foobarStream = fooStream
  .withWatermark("fooTime", "5 seconds")
  .join(
    barStream.withWatermark("barTime", "5 seconds"),
    expr("""
       barId = fooId AND
       fooTime >= barTime AND
       fooTime <= barTime + interval 5 seconds
           """),
    joinType = "leftOuter"
  )

val foobarbazQuery = foobarStream
  .join(
    bazStream.withWatermark("bazTime", "5 seconds"),
    expr("""
      bazId = fooId AND
      bazTime >= fooTime AND
      bazTime <= fooTime + interval 5 seconds
         """),
    joinType = "leftOuter")
  .writeStream
  .format("console")
  .start()
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通过上面的设置,我能够观察以下数据元组:

  • (some_foo, some_bar, some_baz)
  • (some_foo, some_bar, null)

但仍然缺少(some_foo, null, some_baz)(some_foo, null, null).

任何想法,如何正确配置水印,以获得所有组合?

更新:

在添加额外的水印后,foobarStream令人惊讶的是barTime:

val foobarbazQuery = foobarStream
  .withWatermark("barTime", "1 minute")
  .join(/* ... */)`
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我能够得到这个(some_foo, null, some_baz)组合,但仍然缺少(some_foo, null, null)......

Jun*_*Lim 4

我留下一些信息仅供参考。

链接流-流连接无法正常工作,因为 Spark 仅支持全局水印(而不是运算符水印),这可能会导致连接之间的中间输出丢失。

Apache Spark 社区不久前就指出并讨论了这个问题。以下是更多详细信息的链接: https://lists.apache.org/thread.html/cc6489a19316e7382661d305fabd8c21915e5faf6a928b4869ac2b4a@%3Cdev.spark.apache.org%3E

(免责声明:我是发起该邮件线程的作者。)