小编在学习编写wordcount时发现异常（tried to access method com.google.common.base.Stopwatch.()V from class org.apache.hadoop.mapred.FileInputFormat）
具体如下
Exception in thread "main" java.lang.IllegalAccessError: tried to access method com.google.common.base.Stopwatch.<init>()V from class org.apache.hadoop.mapred.FileInputFormatat org.apache.hadoop.mapred.FileInputFormat.getSplits(FileInputFormat.java:312)at org.apache.spark.rdd.HadoopRDD.getPartitions(HadoopRDD.scala:194)at org.apache.spark.rdd.RDD$$anonfun$partitions$2.apply(RDD.scala:252)at org.apache.spark.rdd.RDD$$anonfun$partitions$2.apply(RDD.scala:250)at scala.Option.getOrElse(Option.scala:121)at org.apache.spark.rdd.RDD.partitions(RDD.scala:250)at org.apache.spark.rdd.MapPartitionsRDD.getPartitions(MapPartitionsRDD.scala:35)at org.apache.spark.rdd.RDD$$anonfun$partitions$2.apply(RDD.scala:252)at org.apache.spark.rdd.RDD$$anonfun$partitions$2.apply(RDD.scala:250)at scala.Option.getOrElse(Option.scala:121)at org.apache.spark.rdd.RDD.partitions(RDD.scala:250)at org.apache.spark.rdd.MapPartitionsRDD.getPartitions(MapPartitionsRDD.scala:35)at org.apache.spark.rdd.RDD$$anonfun$partitions$2.apply(RDD.scala:252)at org.apache.spark.rdd.RDD$$anonfun$partitions$2.apply(RDD.scala:250)at scala.Option.getOrElse(Option.scala:121)at org.apache.spark.rdd.RDD.partitions(RDD.scala:250)at org.apache.spark.rdd.MapPartitionsRDD.getPartitions(MapPartitionsRDD.scala:35)at org.apache.spark.rdd.RDD$$anonfun$partitions$2.apply(RDD.scala:252)at org.apache.spark.rdd.RDD$$anonfun$partitions$2.apply(RDD.scala:250)at scala.Option.getOrElse(Option.scala:121)at org.apache.spark.rdd.RDD.partitions(RDD.scala:250)at org.apache.spark.Partitioner$$anonfun$defaultPartitioner$2.apply(Partitioner.scala:66)at org.apache.spark.Partitioner$$anonfun$defaultPartitioner$2.apply(Partitioner.scala:66)at scala.collection.TraversableLike$$anonfun$map$1.apply(TraversableLike.scala:234)at scala.collection.TraversableLike$$anonfun$map$1.apply(TraversableLike.scala:234)at scala.collection.immutable.List.foreach(List.scala:392)at scala.collection.TraversableLike$class.map(TraversableLike.scala:234)at scala.collection.immutable.List.map(List.scala:296)at org.apache.spark.Partitioner$.defaultPartitioner(Partitioner.scala:66)at org.apache.spark.rdd.PairRDDFunctions$$anonfun$reduceByKey$3.apply(PairRDDFunctions.scala:329)at org.apache.spark.rdd.PairRDDFunctions$$anonfun$reduceByKey$3.apply(PairRDDFunctions.scala:329)at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:151)at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:112)at org.apache.spark.rdd.RDD.withScope(RDD.scala:362)at org.apache.spark.rdd.PairRDDFunctions.reduceByKey(PairRDDFunctions.scala:328)at day1.Demo$.main(Demo.scala:13)
经过不懈努力的“百度”各种方法
最后加入了两个hadoop的包就好了
<dependency><groupId>org.apache.hadoop</groupId><artifactId>hadoop-common</artifactId><version>2.7.1</version>
</dependency>
<dependency><groupId>org.apache.hadoop</groupId><artifactId>hadoop-mapreduce-client-core</artifactId><version>2.7.1</version>
</dependency>完整版 pom.xml 如下
<properties><maven.compiler.source>1.7</maven.compiler.source><maven.compiler.target>1.7</maven.compiler.target><encoding>UTF-8</encoding><scala.version>2.11.12</scala.version><spark.version>2.2.0</spark.version>
</properties><dependencies><dependency><groupId>org.scala-lang</groupId><artifactId>scala-library</artifactId><version>${scala.version}</version></dependency><dependency><groupId>org.apache.spark</groupId><artifactId>spark-core_2.11</artifactId><version>${spark.version}</version></dependency><dependency><groupId>org.apache.spark</groupId><artifactId>spark-streaming_2.11</artifactId><version>${spark.version}</version></dependency><dependency><groupId>org.apache.spark</groupId><artifactId>spark-streaming-kafka-0-8_2.11</artifactId><version>${spark.version}</version></dependency><dependency><groupId>redis.clients</groupId><artifactId>jedis</artifactId><version>2.9.0</version></dependency><dependency><groupId>org.apache.spark</groupId><artifactId>spark-sql_2.11</artifactId><version>${spark.version}</version></dependency><dependency><groupId>mysql</groupId><artifactId>mysql-connector-java</artifactId><version>5.1.31</version></dependency><dependency><groupId>org.elasticsearch</groupId><artifactId>elasticsearch</artifactId><version>2.4.0</version></dependency><dependency><groupId>junit</groupId><artifactId>junit</artifactId><version>4.12</version></dependency><dependency><groupId>org.apache.hadoop</groupId><artifactId>hadoop-common</artifactId><version>2.7.1</version></dependency><dependency><groupId>org.apache.hadoop</groupId><artifactId>hadoop-mapreduce-client-core</artifactId><version>2.7.1</version></dependency></dependencies><build><sourceDirectory>src/main/scala</sourceDirectory><testSourceDirectory>src/test/scala</testSourceDirectory><plugins><plugin><groupId>net.alchim31.maven</groupId><artifactId>scala-maven-plugin</artifactId><version>3.2.2</version><executions><execution><goals><goal>compile</goal><goal>testCompile</goal></goals><configuration><args><!--<arg>-make:transitive</arg>--><arg>-dependencyfile</arg><arg>${project.build.directory}/.scala_dependencies</arg></args></configuration></execution></executions></plugin><plugin><groupId>org.apache.maven.plugins</groupId><artifactId>maven-shade-plugin</artifactId><version>2.4.3</version><executions><execution><phase>package</phase><goals><goal>shade</goal></goals><configuration><filters><filter><artifact>*:*</artifact><excludes><exclude>META-INF/*.SF</exclude><exclude>META-INF/*.DSA</exclude><exclude>META-INF/*.RSA</exclude></excludes></filter></filters><transformers><transformer implementation="org.apache.maven.plugins.shade.resource.ManifestResourceTransformer"><mainClass>day01.SparkWordCount</mainClass></transformer></transformers></configuration></execution></executions></plugin></plugins>
</build>