java.io.NotSerializableException在星火下面

Question

代码启用检查点流：

def main(args: Array[String]) { 
    val sc = new SparkContext 
    val sec = Seconds(3) 
    val ssc = new StreamingContext(sc, sec) 
    ssc.checkpoint("./checkpoint") 
    val rdd = ssc.sparkContext.parallelize(Seq("a","b","c")) 
    val inputDStream = new ConstantInputDStream(ssc, rdd) 

    inputDStream.transform(rdd => { 
     val buf = ListBuffer[String]() 
     buf += "1" 
     buf += "2" 
     buf += "3" 
     val other_rdd = ssc.sparkContext.parallelize(buf) // create a new rdd 
     rdd.union(other_rdd) 
    }).print() 

    ssc.start() 
    ssc.awaitTermination() 
} 

，并抛出异常：

java.io.NotSerializableException: DStream checkpointing has been enabled but the DStreams with their functions are not serializable 
org.apache.spark.streaming.StreamingContext 
Serialization stack: 
    - object not serializable (class: org.apache.spark.streaming.StreamingContext, value: org.apache.spark.streaming.StreamingContext@5626e185) 
    - field (class: com.mirrtalk.Test$$anonfun$main$1, name: ssc$1, type: class org.apache.spark.streaming.StreamingContext) 
    - object (class com.mirrtalk.Test$$anonfun$main$1, <function1>) 
    - field (class: org.apache.spark.streaming.dstream.DStream$$anonfun$transform$1$$anonfun$apply$21, name: cleanedF$2, type: interface scala.Function1) 
    - object (class org.apache.spark.streaming.dstream.DStream$$anonfun$transform$1$$anonfun$apply$21, <function2>) 
    - field (class: org.apache.spark.streaming.dstream.DStream$$anonfun$transform$2$$anonfun$5, name: cleanedF$3, type: interface scala.Function2) 
    - object (class org.apache.spark.streaming.dstream.DStream$$anonfun$transform$2$$anonfun$5, <function2>) 
    - field (class: org.apache.spark.streaming.dstream.TransformedDStream, name: transformFunc, type: interface scala.Function2) 

当我删除代码ssc.checkpoint（ “./检查点”），该应用程序可以正常工作，但我需要启用检查点。

如何解决这个问题时启用检查点？

Answer 1

您可以将上下文初始化和配置任务外main：

object App { 
    val sc = new SparkContext(new SparkConf().setAppName("foo").setMaster("local")) 
    val sec = Seconds(3) 
    val ssc = new StreamingContext(sc, sec) 
    ssc.checkpoint("./checkpoint") // enable checkpoint 

    def main(args: Array[String]) { 
    val rdd = ssc.sparkContext.parallelize(Seq("a", "b", "c")) 
    val inputDStream = new ConstantInputDStream(ssc, rdd) 

    inputDStream.transform(rdd => { 
     val buf = ListBuffer[String]() 
     buf += "1" 
     buf += "2" 
     buf += "3" 
     val other_rdd = ssc.sparkContext.parallelize(buf) 
     rdd.union(other_rdd) // I want to union other RDD 
    }).print() 

    ssc.start() 
    ssc.awaitTermination() 
    } 
}