我刚开始使用Spark Streaming,我正在尝试构建一个计算来自Kafka流的单词的示例应用程序。虽然它与sbt package
一起编译,但当我运行它时,我得到NoClassDefFoundError
。这个post似乎有同样的问题,但解决方案是针对Maven而我无法用sbt重现它。
KafkaApp.scala
:
import org.apache.spark._
import org.apache.spark.streaming._
import org.apache.spark.streaming.kafka._
object KafkaApp {
def main(args: Array[String]) {
val conf = new SparkConf().setAppName("kafkaApp").setMaster("local[*]")
val ssc = new StreamingContext(conf, Seconds(1))
val kafkaParams = Map(
"zookeeper.connect" -> "localhost:2181",
"zookeeper.connection.timeout.ms" -> "10000",
"group.id" -> "sparkGroup"
)
val topics = Map(
"test" -> 1
)
// stream of (topic, ImpressionLog)
val messages = KafkaUtils.createStream(ssc, kafkaParams, topics, storage.StorageLevel.MEMORY_AND_DISK)
println(s"Number of words: %{messages.count()}")
}
}
build.sbt
:
name := "Simple Project"
version := "1.1"
scalaVersion := "2.10.4"
libraryDependencies ++= Seq(
"org.apache.spark" %% "spark-core" % "1.1.1",
"org.apache.spark" %% "spark-streaming" % "1.1.1",
"org.apache.spark" %% "spark-streaming-kafka" % "1.1.1"
)
resolvers += "Akka Repository" at "http://repo.akka.io/releases/"
我提交的是:
bin/spark-submit \
--class "KafkaApp" \
--master local[4] \
target/scala-2.10/simple-project_2.10-1.1.jar
错误:
14/12/30 19:44:57 INFO AkkaUtils: Connecting to HeartbeatReceiver: akka.tcp://sparkDriver@192.168.5.252:65077/user/HeartbeatReceiver
Exception in thread "main" java.lang.NoClassDefFoundError: org/apache/spark/streaming/kafka/KafkaUtils$
at KafkaApp$.main(KafkaApp.scala:28)
at KafkaApp.main(KafkaApp.scala)
at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:57)
at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
at java.lang.reflect.Method.invoke(Method.java:606)
at org.apache.spark.deploy.SparkSubmit$.launch(SparkSubmit.scala:329)
at org.apache.spark.deploy.SparkSubmit$.main(SparkSubmit.scala:75)
at org.apache.spark.deploy.SparkSubmit.main(SparkSubmit.scala)
Caused by: java.lang.ClassNotFoundException: org.apache.spark.streaming.kafka.KafkaUtils$
at java.net.URLClassLoader$1.run(URLClassLoader.java:366)
at java.net.URLClassLoader$1.run(URLClassLoader.java:355)
at java.security.AccessController.doPrivileged(Native Method)
at java.net.URLClassLoader.findClass(URLClassLoader.java:354)
at java.lang.ClassLoader.loadClass(ClassLoader.java:425)
at java.lang.ClassLoader.loadClass(ClassLoader.java:358)
答案 0 :(得分:17)
spark-submit不会自动放入包含KafkaUtils的包。您需要在项目JAR中拥有。为此,您需要使用sbt assembly创建一个包含所有内容的超级jar。这是一个build.sbt示例。
https://github.com/tdas/spark-streaming-external-projects/blob/master/kafka/build.sbt
您显然还需要将程序集插件添加到SBT。
https://github.com/tdas/spark-streaming-external-projects/tree/master/kafka/project
答案 1 :(得分:7)
请在提交申请时尝试包含所有依赖关系罐:
./ spark-submit --name" SampleApp" --deploy-mode client - master spark:// host:7077 --class com.stackexchange.SampleApp --jars $ SPARK_INSTALL_DIR / spark-streaming-kafka_2.10-1.3.0.jar,$ KAFKA_INSTALL_DIR / libs / kafka_2 .10-0.8.2.0.jar,$ KAFKA_INSTALL_DIR / libs / metrics-core-2.2.0.jar,$ KAFKA_INSTALL_DIR / libs / zkclient-0.3.jar spark-example-1.0-SNAPSHOT.jar
答案 2 :(得分:2)
以下build.sbt
为我工作。它还要求您将sbt-assembly
插件放在projects/
目录下的文件中。
build.sbt
name := "NetworkStreaming" // https://github.com/sbt/sbt-assembly/blob/master/Migration.md#upgrading-with-bare-buildsbt
libraryDependencies ++= Seq(
"org.apache.spark" % "spark-streaming_2.10" % "1.4.1",
"org.apache.spark" % "spark-streaming-kafka_2.10" % "1.4.1", // kafka
"org.apache.hbase" % "hbase" % "0.92.1",
"org.apache.hadoop" % "hadoop-core" % "1.0.2",
"org.apache.spark" % "spark-mllib_2.10" % "1.3.0"
)
mergeStrategy in assembly := {
case m if m.toLowerCase.endsWith("manifest.mf") => MergeStrategy.discard
case m if m.toLowerCase.matches("meta-inf.*\\.sf$") => MergeStrategy.discard
case "log4j.properties" => MergeStrategy.discard
case m if m.toLowerCase.startsWith("meta-inf/services/") => MergeStrategy.filterDistinctLines
case "reference.conf" => MergeStrategy.concat
case _ => MergeStrategy.first
}
项目/ plugins.sbt
addSbtPlugin("com.eed3si9n" % "sbt-assembly" % "0.14.1")
答案 3 :(得分:0)
遇到同样的问题,我通过构建带有依赖关系的jar来解决它。
将以下代码添加到pom.xml
<build>
<sourceDirectory>src/main/java</sourceDirectory>
<testSourceDirectory>src/test/java</testSourceDirectory>
<plugins>
<!--
Bind the maven-assembly-plugin to the package phase
this will create a jar file without the storm dependencies
suitable for deployment to a cluster.
-->
<plugin>
<artifactId>maven-assembly-plugin</artifactId>
<configuration>
<descriptorRefs>
<descriptorRef>jar-with-dependencies</descriptorRef>
</descriptorRefs>
<archive>
<manifest>
<mainClass></mainClass>
</manifest>
</archive>
</configuration>
<executions>
<execution>
<id>make-assembly</id>
<phase>package</phase>
<goals>
<goal>single</goal>
</goals>
</execution>
</executions>
</plugin>
</plugins>
</build>
mvn包 提交&#34; example-jar-with-dependencies.jar&#34;
答案 4 :(得分:0)
在外部添加了依赖项,项目 - &gt;属性 - &gt; java构建路径 - &gt;库 - &gt;添加外部罐子并添加所需的罐子。
这解决了我的问题。答案 5 :(得分:0)
使用Spark 1.6为我做的工作没有处理这么多外部罐子的麻烦......管理起来会变得非常复杂......
答案 6 :(得分:0)
你也可以下载jar文件并把它放在Spark lib文件夹中,因为它没有安装Spark,而不是试图让SBT build.sbt下功来。
将其复制到:
/usr/local/spark/spark-2.1.0-bin-hadoop2.6/jars /
答案 7 :(得分:0)
import org.apache.spark.streaming.kafka.KafkaUtils
在build.sbt中使用以下内容
name := "kafka"
version := "0.1"
scalaVersion := "2.11.12"
retrieveManaged := true
fork := true
//libraryDependencies += "org.apache.spark" % "spark-streaming_2.11" % "2.2.0"
//libraryDependencies += "org.apache.spark" % "spark-streaming-kafka-0-8_2.11" % "2.1.0"
libraryDependencies += "org.apache.spark" %% "spark-core" % "2.2.0"
//libraryDependencies += "org.apache.spark" %% "spark-sql" % "2.2.0"
libraryDependencies += "org.apache.spark" %% "spark-streaming" % "2.2.0"
// https://mvnrepository.com/artifact/org.apache.spark/spark-streaming-kafka-0-8
libraryDependencies += "org.apache.spark" %% "spark-streaming-kafka-0-8" % "2.2.0" % "provided"
// https://mvnrepository.com/artifact/org.apache.spark/spark-streaming-kafka-0-8-assembly
libraryDependencies += "org.apache.spark" %% "spark-streaming-kafka-0-8-assembly" % "2.2.0"
这将解决问题
答案 8 :(得分:0)
在--packages
上使用spark-submit
参数,它将以group:artifact:version,...
格式使用mvn软件包