Question

让config.json成为一个小的json文件：

{
    "toto": 1
}

我制作了一个简单的代码，用sc.textFile读取json文件（因为该文件可以在S3，本地或HDFS上，因此textFile很方便）

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

object testAwsSdk {
  def main( args:Array[String] ):Unit = {
    val sparkConf = new SparkConf().setAppName("test-aws-sdk").setMaster("local[*]")
    val sc = new SparkContext(sparkConf)
    val json = sc.textFile("config.json") 
    println(json.collect().mkString("\n"))
  }
}

SBT文件仅提取spark-core库

libraryDependencies ++= Seq(
  "org.apache.spark" %% "spark-core" % "1.5.1" % "compile"
)

程序按预期工作，在标准输出上编写config.json的内容。

现在我想与aws-java-sdk，亚马逊的sdk链接以访问S3。

libraryDependencies ++= Seq(
  "com.amazonaws" % "aws-java-sdk" % "1.10.30" % "compile",
  "org.apache.spark" %% "spark-core" % "1.5.1" % "compile"
)

执行相同的代码，spark抛出以下异常。

Exception in thread "main" com.fasterxml.jackson.databind.JsonMappingException: Could not find creator property with name 'id' (in class org.apache.spark.rdd.RDDOperationScope)
 at [Source: {"id":"0","name":"textFile"}; line: 1, column: 1]
    at com.fasterxml.jackson.databind.JsonMappingException.from(JsonMappingException.java:148)
    at com.fasterxml.jackson.databind.DeserializationContext.mappingException(DeserializationContext.java:843)
    at com.fasterxml.jackson.databind.deser.BeanDeserializerFactory.addBeanProps(BeanDeserializerFactory.java:533)
    at com.fasterxml.jackson.databind.deser.BeanDeserializerFactory.buildBeanDeserializer(BeanDeserializerFactory.java:220)
    at com.fasterxml.jackson.databind.deser.BeanDeserializerFactory.createBeanDeserializer(BeanDeserializerFactory.java:143)
    at com.fasterxml.jackson.databind.deser.DeserializerCache._createDeserializer2(DeserializerCache.java:409)
    at com.fasterxml.jackson.databind.deser.DeserializerCache._createDeserializer(DeserializerCache.java:358)
    at com.fasterxml.jackson.databind.deser.DeserializerCache._createAndCache2(DeserializerCache.java:265)
    at com.fasterxml.jackson.databind.deser.DeserializerCache._createAndCacheValueDeserializer(DeserializerCache.java:245)
    at com.fasterxml.jackson.databind.deser.DeserializerCache.findValueDeserializer(DeserializerCache.java:143)
    at com.fasterxml.jackson.databind.DeserializationContext.findRootValueDeserializer(DeserializationContext.java:439)
    at com.fasterxml.jackson.databind.ObjectMapper._findRootDeserializer(ObjectMapper.java:3666)
    at com.fasterxml.jackson.databind.ObjectMapper._readMapAndClose(ObjectMapper.java:3558)
    at com.fasterxml.jackson.databind.ObjectMapper.readValue(ObjectMapper.java:2578)
    at org.apache.spark.rdd.RDDOperationScope$.fromJson(RDDOperationScope.scala:82)
    at org.apache.spark.rdd.RDDOperationScope$$anonfun$5.apply(RDDOperationScope.scala:133)
    at org.apache.spark.rdd.RDDOperationScope$$anonfun$5.apply(RDDOperationScope.scala:133)
    at scala.Option.map(Option.scala:145)
    at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:133)
    at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:108)
    at org.apache.spark.SparkContext.withScope(SparkContext.scala:709)
    at org.apache.spark.SparkContext.hadoopFile(SparkContext.scala:1012)
    at org.apache.spark.SparkContext$$anonfun$textFile$1.apply(SparkContext.scala:827)
    at org.apache.spark.SparkContext$$anonfun$textFile$1.apply(SparkContext.scala:825)
    at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:147)
    at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:108)
    at org.apache.spark.SparkContext.withScope(SparkContext.scala:709)
    at org.apache.spark.SparkContext.textFile(SparkContext.scala:825)
    at testAwsSdk$.main(testAwsSdk.scala:11)
    at testAwsSdk.main(testAwsSdk.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:140)

读取堆栈时，似乎当aws-java-sdk被链接时，sc.textFile检测到该文件是json文件并尝试使用jackson解析它，假设某种格式，当然找不到它。我需要链接aws-java-sdk，所以我的问题是：

1-为什么添加aws-java-sdk会修改spark-core的行为？

2-是否有解决办法（文件可以在HDFS，S3或本地）？

Answer 1

谈到亚马逊的支持。这是杰克逊图书馆的依赖性问题。在SBT中，覆盖杰克逊：

libraryDependencies ++= Seq( 
"com.amazonaws" % "aws-java-sdk" % "1.10.30" % "compile",
"org.apache.spark" %% "spark-core" % "1.5.1" % "compile"
) 

dependencyOverrides ++= Set( 
"com.fasterxml.jackson.core" % "jackson-databind" % "2.4.4" 
)

他们的回答： 我们在Mac，Ec2（redhat AMI）实例和EMR（Amazon Linux）上完成了这项工作。 3种不同的环境。问题的根本原因是sbt构建依赖图，然后通过逐出旧版本并选择最新版本的依赖库来处理版本冲突问题。在这种情况下，spark需要2.4版本的jackson库，而AWS SDK需要2.5。因此存在版本冲突，并且sbt驱逐了spark的依赖版本（更旧版本）并选择了AWS SDK版本（这是最新版本）。

Answer 2

添加到Boris' answer，如果您不想使用固定版本的Jackson（可能将来会升级Spark）但仍希望丢弃AWS中的那个，您可以执行以下操作：

libraryDependencies ++= Seq( 
  "com.amazonaws" % "aws-java-sdk" % "1.10.30" % "compile" excludeAll (
    ExclusionRule("com.fasterxml.jackson.core", "jackson-databind")
  ),
  "org.apache.spark" %% "spark-core" % "1.5.1" % "compile"
)

与aws-java-sdk链接时，在读取json文件时发生Spark崩溃

2 个答案: