Uncaught Exception Handling in Spark

问题

I am working on a Java based Spark Streaming application which responds to messages that come through a Kafka topic. For each message, the application does some processing, and writes back the results to a different Kafka topic.

Sometimes due to unexpected data related issues, the code that operates on RDDs might fail and throw an exception. When that happens, I would like to have a generic handler that could take necessary action and drop a message to an error topic. Right now, these exceptions are written in Spark's log by Spark itself.

What is the best approach to do this, instead of writing try-catch blocks for every code block that work on RDDs?

回答1:

You could write a generic function that does this. You only need to wrap it around RDD actions since those are the only ones that can throw Spark exceptions (transformers like .map and .filter are lazy executed by actions).

(Assuming this is in Scala) You could maybe even try something with implicits. Make a class that holds an RDD and handles the error. Here a sketch of what that might look like:

implicit class FailSafeRDD[T](rdd: RDD[T]) {
  def failsafeAction[U](fn: RDD[T] => U): Try[U] = Try {
    fn(rdd)
  }
}

You could add error topic messaging into failsafeAction or anything you want to do every time on failure. And then usage might be like:

val rdd = ??? // Some rdd you already have
val resultOrException = rdd.failsafeAction { r => r.count() }

Besides this though, I imagine the "best" approach is somewhat subjective to application needs.

回答2:

I think you could also implement this with a try catch =>

dstream.foreachRDD { case rdd: RDD[String] => 
    rdd.foreach { case string: String => 
      try {
        val kafkaProducer = ...
        val msg = ...
        kafkaProducer.send(msg)
      } catch {
        case d: DataException=>
          val kafkaErrorProducer = ...
          val errorMsg = ...
          kafkaErrorProducer.send(errorMsg )
        case t: Throwable =>
          //further error handling
      }
   }
}

来源：https://stackoverflow.com/questions/33262363/uncaught-exception-handling-in-spark