Spark BUG实践（包含的BUG：ClassCastException；ConnectException；NoClassDefFoundError；RuntimeExceptio等。。。。）

环境

scala版本：2.11.8
jdk版本：1.8
spark版本：2.1.0
hadoop版本：2.7.1
ubuntu版本：18.04
window版本：win10

scala代码在windows端编程，ubuntu在虚拟机安装，scala，jdk，spark，hadoop都安装在ubuntu端

问题一

问题描述：在使用wget下载scala时，出现 Unable to establish SSL connection

解决：

加上跳过验证证书的参数--no-check-certificate

问题二

问题描述：在使用scala程序测试wordCount程序时出现错误：

(scala程序在主机，spark安装在虚拟机)

22/06/20 22:35:38 INFO StandaloneAppClient$ClientEndpoint: Connecting to master spark://192.168.78.128:7077...
22/06/20 22:35:41 WARN StandaloneAppClient$ClientEndpoint: Failed to connect to master 192.168.78.128:7077
org.apache.spark.SparkException: Exception thrown in awaitResult: 
	at org.apache.spark.util.ThreadUtils$.awaitResult(ThreadUtils.scala:226)
	...
	Caused by: io.netty.channel.AbstractChannel$AnnotatedConnectException: Connection refused: no further information: /192.168.78.128:7077
Caused by: java.net.ConnectException: Connection refused: no further information

解决：

对spark下的conf目录内的spark-env.sh进行配置如下

配置后在spark目录下启动master和worker

bin/start-all.sh

之后再次运行wordCount程序，出现如下错误

Using Spark's default log4j profile: org/apache/spark/log4j-defaults.properties
22/06/20 22:44:09 INFO SparkContext: Running Spark version 2.4.8
Exception in thread "main" java.lang.NoClassDefFoundError: org/apache/hadoop/conf/Configuration$DeprecationDelta
	at org.apache.hadoop.mapreduce.util.ConfigUtil.addDeprecatedKeys(ConfigUtil.java:54)
	at org.apache.hadoop.mapreduce.util.ConfigUtil.loadResources(ConfigUtil.java:42)
	at org.apache.hadoop.mapred.JobConf.<clinit>(JobConf.java:123)

在pom文件内引入hadooop依赖

<dependency>
            <groupId>org.apache.hadoop</groupId>
            <artifactId>hadoop-hdfs</artifactId>
            <version>3.3.2</version>
        </dependency>
        <dependency>
            <groupId>org.apache.hadoop</groupId>
            <artifactId>hadoop-common</artifactId>
            <version>3.3.2</version>
        </dependency>
        <dependency>
            <groupId>org.apache.hadoop</groupId>
            <artifactId>hadoop-core</artifactId>
            <version>1.2.1</version>
</dependency>

刷新依赖后运行程序，出现：

22/06/20 22:50:31 INFO spark.SparkContext: Running Spark version 2.4.8
22/06/20 22:50:31 INFO spark.SparkContext: Submitted application: wordCount
22/06/20 22:50:31 INFO spark.SecurityManager: Changing view acls to: Administrator
22/06/20 22:50:31 INFO spark.SecurityManager: Changing modify acls to: Administrator
22/06/20 22:50:31 INFO spark.SecurityManager: Changing view acls groups to: 
22/06/20 22:50:31 INFO spark.SecurityManager: Changing modify acls groups to: 
22/06/20 22:50:31 INFO spark.SecurityManager: SecurityManager: authentication disabled; ui acls disabled; users  with view permissions: Set(Administrator); groups with view permissions: Set(); users  with modify permissions: Set(Administrator); groups with modify permissions: Set()
Exception in thread "main" java.lang.NoSuchMethodError: io.netty.buffer.PooledByteBufAllocator.metric()Lio/netty/buffer/PooledByteBufAllocatorMetric;
	at org.apache.spark.network.util.NettyMemoryMetrics.registerMetrics(NettyMemoryMetrics.java:80)
	at org.apache.spark.network.util.NettyMemoryMetrics.<init>(NettyMemoryMetrics.java:76)

更新spark-core依赖版本，原本是2.1.0，现在更新为2.3.0，spark-core的pom依赖如下

<dependency>
            <groupId>org.apache.spark</groupId>
            <artifactId>spark-core_2.10</artifactId>
            <version>2.3.0</version>
</dependency>

刷新依赖后再次运行又出现连接问题

修改pom依赖为

<dependency>
            <groupId>org.apache.spark</groupId>
            <artifactId>spark-mesos_2.11</artifactId>
            <version>2.1.0</version>
</dependency>
        

刷新后再次报错：java.lang.RuntimeException: java.lang.NoSuchFieldException: DEFAULT_TINY_CACHE_SIZE

添加io.netty依赖

<dependency>
                <groupId>io.netty</groupId>
                <artifactId>netty-all</artifactId>
                <version>4.0.52.Final</version>
</dependency>

运行后再次出现连接问题

查看虚拟机的spark的master启动情况

确实都启动成功，排除未启动成功原因

修改spark的conf下的spark-env .sh文件

重新启动spark

sbin/start-all.sh

启动程序后成功连接到虚拟机的spark的master

问题三

问题描述：

运行scala的wordCount出现：com.fasterxml.jackson.databind.JsonMappingException: Incompatible Jackson version: 2.13.0

这是由于Jackson这个工具库的版本不一致导致的。解决方案：首先在Kafka的依赖项中，排除对于Jackon的依赖，从而阻止Maven自动导入高版本的库，随后手动添加较低版本Jackon库的依赖项，重新import即可。

添加依赖：

<dependency>
            <groupId> org.apache.kafka</groupId>
            <artifactId>kafka_2.11</artifactId>
            <version>1.1.1</version>
            <exclusions>
                <exclusion>
                    <groupId>com.fasterxml.jackson.core</groupId>
                    <artifactId>*</artifactId>
                </exclusion>
            </exclusions>
        </dependency>
        <dependency>
            <groupId>com.fasterxml.jackson.core</groupId>
            <artifactId>jackson-core</artifactId>
            <version>2.6.6</version>
</dependency>

导入后重新运行程序，再次出现问题：

NoClassDefFoundError: com/fasterxml/jackson/core/util/JacksonFeature

原因是jackson依赖不全,导入jackson依赖

<dependency>
            <groupId>com.fasterxml.jackson.core</groupId>
            <artifactId>jackson-databind</artifactId>
            <version>2.6.7</version>
        </dependency>
        <dependency>
            <groupId>com.fasterxml.jackson.core</groupId>
            <artifactId>jackson-core</artifactId>
            <version>2.6.7</version>
        </dependency>
        <dependency>
            <groupId>com.fasterxml.jackson.core</groupId>
            <artifactId>jackson-annotations</artifactId>
            <version>2.6.7</version>
</dependency>

再次运行出现：Exception in thread “main” java.net.ConnectException: Call From WIN-P2FQSL3EP74/192.168.78.1 to 192.168.78.128:9000 failed on connection exception: java.net.ConnectException: Connection refused: no further information; For more details see: http://wiki.apache.org/hadoop/ConnectionRefused
at sun.reflect.NativeConstructorAccessorImpl.newInstance0(Native Method)
at sun.reflect.NativeConstructorAccessorImpl.newInstance(NativeConstructorAccessorImpl.java:62)
at sun.reflect.DelegatingConstructorAccessorImpl.newInstance(DelegatingConstructorAccessorImpl.java:45)
at java.lang.reflect.Constructor.newInstance(Constructor.java:423)

推测这应该是hadoop连接拒绝，而不是spark的master连接问题

修改hadoop的etc下的core-site.xml文件

之后重新启动hadoop运行程序，出现新的问题：

WARN scheduler.TaskSetManager: Lost task 1.0 in stage 0.0 (TID 1, 0.0.0.0, executor 0): java.lang.ClassCastException: cannot assign instance of scala.collection.immutable.List$SerializationProxy to field org.apache.spark.rdd.RDD.org$apache$spark$rdd$RDD$$dependencies_ of type scala.collection.Seq in instance of org.apache.spark.rdd.MapPartitionsRDD
	at java.io.ObjectStreamClass$FieldReflector.setObjFieldValues(ObjectStreamClass.java:2301)
	at java.io.ObjectStreamClass.setObjFieldValues(ObjectStreamClass.java:1431)
	at java.io.ObjectInputStream.defaultReadFields(ObjectInputStream.java:2411)
	at java.io.ObjectInputStream.readSerialData(ObjectInputStream.java:2329)
	at java.io.ObjectInputStream.readOrdinaryObject(ObjectInputStream.java:2187)
	at java.io.ObjectInputStream.readObject0(ObjectInputStream.java:1667)
	at java.io.ObjectInputStream.defaultReadFields(ObjectInputStream.java:2405)
	at java.io.ObjectInputStream.readSerialData(ObjectInputStream.java:2329)
	at java.io.ObjectInputStream.readOrdinaryObject(ObjectInputStream.java:2187)
	at java.io.ObjectInputStream.readObject0(ObjectInputStream.java:1667)
	at java.io.ObjectInputStream.readObject(ObjectInputStream.java:503)
	at java.io.ObjectInputStream.readObject(ObjectInputStream.java:461)
	at org.apache.spark.serializer.JavaDeserializationStream.readObject(JavaSerializer.scala:75)
	at org.apache.spark.serializer.JavaSerializerInstance.deserialize(JavaSerializer.scala:114)
	at org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:85)
	at org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:53)
	at org.apache.spark.scheduler.Task.run(Task.scala:99)
	at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:282)
	at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149)
	at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)
	at java.lang.Thread.run(Thread.java:748)

从问题截图应该可以看到连接应该是没有问题的，以及开始了预定的wordCount工作，这次可能是代码层面的问题。

wordCount完整scala代码：

import org.apache.spark.{
    SparkConf, SparkContext}

object WordCount {
    
  def main(arg: Array[String]): Unit = {
    
    val ip = "192.168.78.128";
    val inputFile = "hdfs://" + ip + ":9000/hadoop/README.txt";
    val conf = new SparkConf().setMaster("spark://" + ip + ":7077").setAppName("wordCount");
    val sc = new SparkContext(conf)
    val textFile = sc.textFile(inputFile)
    val wordCount = textFile.flatMap(line => line.split(" "))
      .map(word => (word, 1)).reduceByKey((a, b) => a + b)
    wordCount.foreach(println)
  }
}

需要设置jar包，将项目进行打包

然后打包后的项目在target路径下，找到对应jar包位置，复制

复制路径添加到配置setJar方法内，完整Scala WordCount代码

import org.apache.spark.{
    SparkConf, SparkContext}



object WordCount {
    
  def main(arg: Array[String]): Unit = {
    
    //打包后的jar包地址
    val jar = Array[String]("D:\\IDEA_CODE_F\\com\\BigData\\Proj\\target\\Proj-1.0-SNAPSHOT.jar")
    //spark虚拟机地址
    val ip = "192.168.78.129";
    val inputFile = "hdfs://" + ip + ":9000/hadoop/README.txt";
    val conf = new SparkConf()
      .setMaster("spark://" + ip + ":7077") //master节点地址
      .setAppName("wordCount")      //spark程序名
      .setSparkHome("/root/spark")  //spark安装地址（应该可以不用）
      .setIfMissing("spark.driver.host", "192.168.1.112")
      .setJars(jar) //设置打包后的jar包
    val sc = new SparkContext(conf)
    val textFile = sc.textFile(inputFile)
    val wordCount = textFile.flatMap(line => line.split(" "))
      .map(word => (word, 1)).reduceByKey((a, b) => a + b)
	val str1 = textFile.first()
    println("str: " + str1)
    val l = wordCount.count()
    println(l)
    println("------------------")
    val tuples = wordCount.collect()
    tuples.foreach(println)
    sc.stop()
  }
}

运行的大致结果：

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