SparkContext和StreamingContext可以在同一程序中共存吗? [英] Can SparkContext and StreamingContext co-exist in the same program?

问题描述

我正在尝试建立一个Sparkstreaming代码，该代码从Kafka服务器读取行，但使用另一个本地文件中编写的规则对其进行处理.我正在为流数据创建streamingContext，并为其他应用所有其他spark功能(例如字符串操作，读取本地文件等)的sparkContext创建

I am trying to set up a Sparkstreaming code which reads line from the Kafka server but processes it using rules written in another local file. I am creating streamingContext for the streaming data and sparkContext for other applying all other spark features - like string manipulation, reading local files etc

val sparkConf = new SparkConf().setMaster("local[*]").setAppName("ReadLine")
val ssc = new StreamingContext(sparkConf, Seconds(15))
ssc.checkpoint("checkpoint")

    val topicMap = topics.split(",").map((_, numThreads.toInt)).toMap
    val lines = KafkaUtils.createStream(ssc, zkQuorum, group, topicMap).map(_._2)
    val sentence = lines.toString

    val conf = new SparkConf().setAppName("Bi Gram").setMaster("local[2]")
    val sc = new SparkContext(conf)
    val stringRDD = sc.parallelize(Array(sentence))

但这会引发以下错误

Exception in thread "main" org.apache.spark.SparkException: Only one SparkContext may be running in this JVM (see SPARK-2243). To ignore this error, set spark.driver.allowMultipleContexts = true. The currently running SparkContext was created at:
org.apache.spark.SparkContext.<init>(SparkContext.scala:82)
org.apache.spark.streaming.StreamingContext$.createNewSparkContext(StreamingContext.scala:874)
org.apache.spark.streaming.StreamingContext.<init>(StreamingContext.scala:81)

推荐答案

一个应用程序只能有一个SparkContext. StreamingContext在SparkContext上创建.只需使用SparkContext创建ssc StreamingContext

One application can only have ONE SparkContext. StreamingContext is created on SparkContext. Just need to create ssc StreamingContext using SparkContext

val sc = new SparkContext(conf)
val ssc = new StreamingContext(sc, Seconds(15))

如果使用以下构造函数.

If using the following constructor.

StreamingContext(conf: SparkConf, batchDuration: Duration)

它在内部创建另一个SparkContext

this(StreamingContext.createNewSparkContext(conf), null, batchDuration)

SparkContext可以通过

ssc.sparkContext

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