也不知道标题这样说是否有毛病,等功力长进了再来定夺吧.闲来无事,整理一下如何从零开始构建spark项目的maven依赖.首先一个破解版的idea是必须的.这里附上一个Mac版本的安装地址,留着下次自己试试效果.https://blog.youkuaiyun.com/qq_17213067/article/details/81449797
构建可以本地测试的spark代码(也就是local模式),使用maven的依赖管理就可以了,无需在本地电脑上安装其他任何东西,这里指Hadoop集群,HDFS,spark集群等 .就是这么简单明了.当然JDK肯定是要本地安装的哈!!!由于使用Scala语言开发,所以本地还需要安装Scala的sdk(与jdk安装相同)!!!
安装好idea之后,需要Scala插件.如果网络不好,下载不成功的话,那就可以去这里下载.https://plugins.jetbrains.com/plugin/1347-scala.这里不会的,自行百度,因为本次整理没有重新弄这个,就不多介绍了.
重点来了,maven中最重要的文件pom.xml.
自己尝试玩玩spark时,在网上借鉴了pom.xml的格式.由于spark需要Hadoop的hdfs和yarn,所以这里加了Hadoop的相关依赖.
<?xml version="1.0" encoding="UTF-8"?>
<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/xsd/maven-4.0.0.xsd">
<modelVersion>4.0.0</modelVersion>
<groupId>com.sandra</groupId>
<artifactId>mydemo</artifactId>
<version>1.0-SNAPSHOT</version>
<properties>
<project.build.sourceEncoding>UTF-8</project.build.sourceEncoding>
<spark.version>2.2.0</spark.version>
<scala.version>2.11</scala.version>
<hadoop.version>2.7.2</hadoop.version>
</properties>
<dependencies>
<dependency>
<groupId>org.apache.spark</groupId>
<artifactId>spark-core_${scala.version}</artifactId>
<version>${spark.version}</version>
</dependency>
<dependency>
<groupId>org.apache.spark</groupId>
<artifactId>spark-sql_${scala.version}</artifactId>
<version>${spark.version}</version>
</dependency>
<dependency>
<groupId>org.apache.spark</groupId>
<artifactId>spark-hive_${scala.version}</artifactId>
<version>${spark.version}</version>
</dependency>
<dependency>
<groupId>org.apache.spark</groupId>
<artifactId>spark-streaming_${scala.version}</artifactId>
<version>${spark.version}</version>
</dependency>
<dependency>
<groupId>org.apache.hadoop</groupId>
<artifactId>hadoop-core</artifactId>
<version>1.2.1</version>
</dependency>
<dependency>
<groupId>org.apache.hadoop</groupId>
<artifactId>hadoop-common</artifactId>
<version>${hadoop.version}</version>
</dependency>
<dependency>
<groupId>org.apache.hadoop</groupId>
<artifactId>hadoop-client</artifactId>
<version>${hadoop.version}</version>
</dependency>
<dependency>
<groupId>org.apache.hadoop</groupId>
<artifactId>hadoop-hdfs</artifactId>
<version>${hadoop.version}</version>
</dependency>
<dependency>
<groupId>org.apache.spark</groupId>
<artifactId>spark-mllib_${scala.version}</artifactId>
<version>${spark.version}</version>
</dependency>
<dependency>
<groupId>mysql</groupId>
<artifactId>mysql-connector-java</artifactId>
<version>5.1.39</version>
</dependency>
<dependency>
<groupId>junit</groupId>
<artifactId>junit</artifactId>
<version>4.12</version>
</dependency>
<dependency>
<groupId>org.apache.kafka</groupId>
<artifactId>kafka_2.10</artifactId>
<version>0.10.0.0</version>
</dependency>
</dependencies>
</project>
弄好pom.xml后,建立一个Scala文件,运行一个Wordcount代码,如下:
object wordcount {
def main(args: Array[String]): Unit = {
val conf = new SparkConf().setMaster("local").setAppName("test")
val sc = new SparkContext(conf)
val lines = sc.textFile("file:///Users/suning/txt")
//val lines = sc.parallelize(List("hadoop hive storm","spark hive"))
lines.flatMap(_.split(" "))
.map((_,1))
.reduceByKey(_+_)
.foreach(x=>println(x))
sc.stop
}
}
好了?没那么简单.问题出现了,,粘贴如下:
java.lang.NoSuchMethodError: org.apache.hadoop.fs.FileSystem$Statistics.getThreadStatistics()Lorg/apache/hadoop/fs/FileSystem$Statistics$Statistics
各种百度后,感谢 https://blog.youkuaiyun.com/dapanbest/article/details/79344571给出的意见.将pom.xml中Hadoop-core的依赖删除,其他Hadoop依赖保留,问题解决了.原本贴图,结果打败我的不是技术bug,而是上传失败...