我试着把数据从卡夫卡流出来
我用的是火花1.6.2和kafka 0.9.0.1和scala 2.11.8
当我使用基于接收器的方法(KafkaUtils.createStream())时,一切都很好,但是当我尝试这种没有接收器的直接方法时,一切都很好。
val kafkaStreams = KafkaUtils.createDirectStream[String, String, StringDecoder, StringDecoder](
ssc,
Map("group.id" -> "blah",
"auto.offset.reset" -> "smallest",
"metadata.broker.list" -> "127.0.0.1:9092",
"bootstrap.servers"-> "127.0.0.1:9092"),
Set("tweets")
)
我知道这个错误
Exception in thread "main" java.lang.ClassCastException: kafka.cluster.BrokerEndPoint cannot be cast to kafka.cluster.Broker
at org.apache.spark.streaming.kafka.KafkaCluster$$anonfun$2$$anonfun$3$$anonfun$apply$6$$anonfun$apply$7.apply(KafkaCluster.scala:90)
at scala.Option.map(Option.scala:146)
at org.apache.spark.streaming.kafka.KafkaCluster$$anonfun$2$$anonfun$3$$anonfun$apply$6.apply(KafkaCluster.scala:90)
at org.apache.spark.streaming.kafka.KafkaCluster$$anonfun$2$$anonfun$3$$anonfun$apply$6.apply(KafkaCluster.scala:87)
at scala.collection.TraversableLike$$anonfun$flatMap$1.apply(TraversableLike.scala:241)
at scala.collection.TraversableLike$$anonfun$flatMap$1.apply(TraversableLike.scala:241)
at scala.collection.IndexedSeqOptimized$class.foreach(IndexedSeqOptimized.scala:33)
at scala.collection.mutable.WrappedArray.foreach(WrappedArray.scala:35)
at scala.collection.TraversableLike$class.flatMap(TraversableLike.scala:241)
at scala.collection.AbstractTraversable.flatMap(Traversable.scala:104)
at org.apache.spark.streaming.kafka.KafkaCluster$$anonfun$2$$anonfun$3.apply(KafkaCluster.scala:87)
at org.apache.spark.streaming.kafka.KafkaCluster$$anonfun$2$$anonfun$3.apply(KafkaCluster.scala:86)
at scala.collection.TraversableLike$$anonfun$flatMap$1.apply(TraversableLike.scala:241)
at scala.collection.TraversableLike$$anonfun$flatMap$1.apply(TraversableLike.scala:241)
at scala.collection.immutable.Set$Set1.foreach(Set.scala:94)
at scala.collection.TraversableLike$class.flatMap(TraversableLike.scala:241)
at scala.collection.AbstractTraversable.flatMap(Traversable.scala:104)
at org.apache.spark.streaming.kafka.KafkaCluster$$anonfun$2.apply(KafkaCluster.scala:86)
at org.apache.spark.streaming.kafka.KafkaCluster$$anonfun$2.apply(KafkaCluster.scala:85)
at scala.util.Either$RightProjection.flatMap(Either.scala:522)
at org.apache.spark.streaming.kafka.KafkaCluster.findLeaders(KafkaCluster.scala:85)
at org.apache.spark.streaming.kafka.KafkaCluster.getLeaderOffsets(KafkaCluster.scala:179)
at org.apache.spark.streaming.kafka.KafkaCluster.getLeaderOffsets(KafkaCluster.scala:161)
at org.apache.spark.streaming.kafka.KafkaCluster.getEarliestLeaderOffsets(KafkaCluster.scala:155)
at org.apache.spark.streaming.kafka.KafkaUtils$$anonfun$5.apply(KafkaUtils.scala:213)
at org.apache.spark.streaming.kafka.KafkaUtils$$anonfun$5.apply(KafkaUtils.scala:211)
at scala.util.Either$RightProjection.flatMap(Either.scala:522)
at org.apache.spark.streaming.kafka.KafkaUtils$.getFromOffsets(KafkaUtils.scala:211)
at org.apache.spark.streaming.kafka.KafkaUtils$.createDirectStream(KafkaUtils.scala:484)
at SparkStreaming$.delayedEndpoint$SparkStreaming$1(SparkStreaming.scala:32)
at SparkStreaming$delayedInit$body.apply(SparkStreaming.scala:24)
at scala.Function0$class.apply$mcV$sp(Function0.scala:34)
at scala.runtime.AbstractFunction0.apply$mcV$sp(AbstractFunction0.scala:12)
at scala.App$$anonfun$main$1.apply(App.scala:76)
at scala.App$$anonfun$main$1.apply(App.scala:76)
at scala.collection.immutable.List.foreach(List.scala:381)
at scala.collection.generic.TraversableForwarder$class.foreach(TraversableForwarder.scala:35)
at scala.App$class.main(App.scala:76)
at SparkStreaming$.main(SparkStreaming.scala:24)
at SparkStreaming.main(SparkStreaming.scala)
at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62)
at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
at java.lang.reflect.Method.invoke(Method.java:497)
at com.intellij.rt.execution.application.AppMain.main(AppMain.java:144)
这些是我的依赖
"org.apache.spark" %% "spark-streaming-kafka" % "1.6.2",
"org.apache.spark" %% "spark-core" % "1.6.2",
"org.apache.spark" % "spark-streaming_2.11" % "1.6.2",
"org.apache.kafka" %% "kafka" % "0.9.0.1"
我不知道问题出在哪里?有人能帮我吗?
发布于 2016-07-09 09:43:49
根据星火流文档这里,SparkStreaming1.6.2与Kakfa 0.8.2.1兼容。
Kafka :火花流1.6.2与Kafka 0.8.2.1兼容
因此,要解决您的问题,请使用版本为0.8.2.1的kafka库,而不是0.9.0.1。
希望这能有所帮助!
https://stackoverflow.com/questions/38283598
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