java.lang.NoSuchMethodError: scala.reflect.api.JavaUniverse.runtimeMirror(Ljava/lang/ClassLoader;)Lscala/reflect/api/JavaMirrors$JavaMirror;
at org.elasticsearch.spark.serialization.ReflectionUtils$.org$elasticsearch$spark$serialization$ReflectionUtils$$checkCaseClass(ReflectionUtils.scala:42)
at org.elasticsearch.spark.serialization.ReflectionUtils$$anonfun$checkCaseClassCache$1.apply(ReflectionUtils.scala:84)
似乎 scala 版本不兼容,但我看到 spark、spark 2.10 和 scala 2.11.8 的文档是可以的。
那是我的 pom.xml,这只是一个测试 spark 用 es-hadoop 写入 elasticsearch,我不知道如何解决这个异常。`
<project xmlns="http://maven.apache.org/POM/4.0.0" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance"
xsi:schemaLocation="http://maven.apache.org/POM/4.0.0 http://maven.apache.org/maven-v4_0_0.xsd">
<modelVersion>4.0.0</modelVersion>
<groupId>cn.jhTian</groupId>
<artifactId>sparkLink</artifactId>
<version>0.0.1-SNAPSHOT</version>
<packaging>jar</packaging>
<name>${project.artifactId}</name>
<description>My wonderfull scala app</description>
<inceptionYear>2015</inceptionYear>
<licenses>
<license>
<name>My License</name>
<url>http://....</url>
<distribution>repo</distribution>
</license>
</licenses>
<properties>
<encoding>UTF-8</encoding>
<scala.version>2.11.8</scala.version>
<scala.compat.version>2.11</scala.compat.version>
</properties>
<repositories>
<repository>
<id>ainemo</id>
<name>xylink</name>
<url>http://10.170.209.180:8081/nexus/content/groups/public/</url>
</repository>
</repositories>
<dependencies>
<dependency>
<groupId>org.apache.spark</groupId>
<artifactId>spark-core_2.11</artifactId>
<version>2.1.0</version>
</dependency>
<dependency>
<groupId>org.apache.hadoop</groupId>
<artifactId>hadoop-client</artifactId>
<version>2.6.4</version><!-- 2.64 -->
</dependency>
<dependency>
<groupId>org.scala-lang</groupId>
<artifactId>scala-library</artifactId>
<version>${scala.version}</version>
</dependency>
<!--<dependency>-->
<!--<groupId>org.scala-lang</groupId>-->
<!--<artifactId>scala-compiler</artifactId>-->
<!--<version>${scala.version}</version>-->
<!--</dependency>-->
<dependency>
<groupId>org.scala-lang</groupId>
<artifactId>scala-reflect</artifactId>
<version>${scala.version}</version>
</dependency>
<dependency>
<groupId>org.apache.hadoop</groupId>
<artifactId>hadoop-hdfs</artifactId>
<version>2.6.4</version>
</dependency>
<dependency>
<groupId>org.apache.spark</groupId>
<artifactId>spark-streaming_2.11</artifactId>
<version>2.1.0</version>
</dependency>
<dependency>
<groupId>org.apache.spark</groupId>
<artifactId>spark-streaming-kafka-0-8_2.11</artifactId>
<version>2.1.0</version>
</dependency>
<dependency>
<groupId>com.google.protobuf</groupId>
<artifactId>protobuf-java</artifactId>
<version>3.1.0</version>
</dependency>
<dependency>
<groupId>org.elasticsearch</groupId>
<artifactId>elasticsearch-hadoop</artifactId>
<version>5.3.0 </version>
</dependency>
<!-- Test -->
<dependency>
<groupId>junit</groupId>
<artifactId>junit</artifactId>
<version>4.10</version>
<scope>test</scope>
</dependency>
<dependency>
<groupId>org.specs2</groupId>
<artifactId>specs2-core_${scala.compat.version}</artifactId>
<version>2.4.16</version>
<scope>test</scope>
</dependency>
<dependency>
<groupId>org.scalatest</groupId>
<artifactId>scalatest_${scala.compat.version}</artifactId>
<version>2.2.4</version>
<scope>test</scope>
</dependency>
</dependencies>
</project>'
这是我的代码
import org.apache.spark.{SparkConf, SparkContext}
import org.elasticsearch.spark._
/**
* Created by jhTian on 2017/4/19.
*/
object EsWrite {
def main(args: Array[String]) {
val sparkConf = new SparkConf()
.set("es.nodes", "1.1.1.1")
.set("es.port", "9200")
.set("es.index.auto.create", "true")
.setAppName("es-spark-demo")
val sc = new SparkContext(sparkConf)
val job1 = Job("C开发工程师","http://job.c.com","c公司","10000")
val job2 = Job("C++开发工程师","http://job.c++.com","c++公司","10000")
val job3 = Job("C#开发工程师","http://job.c#.com","c#公司","10000")
val job4 = Job("Java开发工程师","http://job.java.com","java公司","10000")
val job5 = Job("Scala开发工程师","http://job.scala.com","java公司","10000")
// val numbers = Map("one" -> 1, "two" -> 2, "three" -> 3)
// val airports = Map("arrival" -> "Otopeni", "SFO" -> "San Fran")
// val rdd=sc.makeRDD(Seq(numbers,airports))
val rdd=sc.makeRDD(Seq(job1,job2,job3,job4,job5))
rdd.saveToEs("job/info")
sc.stop()
}
}
case class Job(jobName:String, jobUrl:String, companyName:String, salary:String)'