IDEA中环境配置和使用

                 1
                <!--
                 声明公有的属性 
                -->
                 2
                <
                properties
                >
                 3
                <
                maven.compiler.source
                >1.8</maven.compiler.source> 4<maven.compiler.target>1.8</maven.compiler.target> 5<encoding>UTF-8</encoding> 6<scala.version>2.11.8</scala.version> 7<spark.version>2.2.0</spark.version> 8<hadoop.version>2.7.1</hadoop.version> 9<scala.compat.version>2.11</scala.compat.version>10</properties>11<!-- 声明并引入公有的依赖 -->12<dependencies>13<dependency>14<groupId>org.scala-lang</groupId>15<artifactId>scala-library</artifactId>16<version>${scala.version}</version>17</dependency>18<dependency>19<groupId>org.apache.spark</groupId>20<artifactId>spark-core_2.11</artifactId>21<version>${spark.version}</version>22</dependency>23<dependency>24<groupId>org.apache.hadoop</groupId>25<artifactId>hadoop-client</artifactId>26<version>${hadoop.version}</version>27</dependency>28</dependencies>2930<!-- 配置构建信息 -->31<build>32<!-- 资源文件夹 -->33<sourceDirectory>src/main/scala</sourceDirectory>34<!-- 声明并引入构建的插件 -->35<plugins>36<!-- 用于编译Scala代码到class -->37<plugin>38<groupId>net.alchim31.maven</groupId>39<artifactId>scala-maven-plugin</artifactId>40<version>3.2.2</version>41<executions>42<execution>43<goals>44<goal>compile</goal>45<goal>testCompile</goal>46</goals>47<configuration>48<args>49<arg>-dependencyfile</arg>50<arg>${project.build.directory}/.scala_dependencies</arg>51</args>52</configuration>53</execution>54</executions>55</plugin>56<plugin>57<!-- 程序打包 -->58<groupId>org.apache.maven.plugins</groupId>59<artifactId>maven-shade-plugin</artifactId>60<version>2.4.3</version>61<executions>62<execution>63<phase>package</phase>64<goals>65<goal>shade</goal>66</goals>67<configuration>68<!-- 过滤掉以下文件，不打包 ：解决包重复引用导致的打包错误-->69<filters>70<filter><artifact>*:*</artifact>71<excludes>72<exclude>META-INF/*.SF</exclude>73<exclude>META-INF/*.DSA</exclude>74<exclude>META-INF/*.RSA</exclude>75</excludes>76</filter>77</filters>78<transformers>79<!-- 打成可执行的jar包 的主方法入口-->80<transformer  implementation="org.apache.maven.plugins.shade.resource.ManifestResourceTransformer">81<mainClass></mainClass>82</transformer>83</transformers>84</configuration>85</execution>86</executions>87</plugin>88</plugins>89</build>

                 1
                package
                 SparkCore_01

                 2
                 3
                import
                 org.apache.spark.rdd.RDD

                 4
                import
                 org.apache.spark.{SparkConf, SparkContext}

                 5
                 6
                /**
                 7
                  * 第一个Spark程序

                 8
                */
                 9
                object SparkWordCount {

                10
                //
                Spark程序都需要使用main
                11   def main(args: Array[String]): Unit = {
12//0.构建系统环境变量,为了SparkContext加在环境变量所使用13/*14      三个核心方法
15       set(key,value) --> 主要应对的是 环境变量设置  key 环境变量名  value 是具体值
16       setAppName(name) --> 设置程序运行的名称
17       setMaster(执行方式),如果需要运行本地环境,那么就需要配置SetMaster这个值
18       "local"  --> 代表本地模式,相当于启用一个线程来模拟Spark运行
19       "local[数值]"  --> 代表本地模式, 根据数值来决定启用多少个线程来模拟spark运行
20       ps:数值不能大于当前cpu 核心数
21       "local[*]"  --> 代表本地模式 * 相当于是系统空闲多少线程就用多少线程来执行spark程序
22*/23       val conf =new SparkConf().setAppName("SparkWordCount").setMaster("local")
24//1.先构建SparkContext对象,需要对SparkContext对象进行环境配置即将conf对象传入到SparkContext中25       val sc = new SparkContext(conf)
2627//Spark对数据的处理
28//1.读取文件内容,参数是文件路径(多用于读取txt或log文件)29     val lines: RDD[String] = sc.textFile("dir/SparkCore_01/File.txt")
30//2.对文件中数据进行切分处理31     val words: RDD[String] = lines.flatMap(_.split(" "))
32//3.对单词进行统计之前,需要对单词的个数进行计数33     val tuples: RDD[(String, Int)] = words.map((_,1))
34//Spark中提供了一个根据key计算value的算子(这个算子是你使用最广泛一个算子),相同key为一组计算一次value的值35     val sumed: RDD[(String, Int)] = tuples.reduceByKey(_+_)
3637//println(sumed.collect().toList)3839    sc.stop()//关闭Sparkcontext
404142//提交集群版本(修改位置):
43//sc.textFile(args(0)) //获取外部输入读取数据路径
44//将数据文件存储到集群(也可以存储在本地)没有返回值
45// sumed.saveAsTextFile(args(1)) // 获取外部输入的存储路径 ,不要打印语句46  }
47 }

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15 # Set everything to be logged to the console
16 # 修改此处更改显示信息级别
17 log4j.rootCategory=ERROR, console
18 log4j.appender.console=org.apache.log4j.ConsoleAppender
19 log4j.appender.console.target=System.err
20 log4j.appender.console.layout=org.apache.log4j.PatternLayout
21 log4j.appender.console.layout.ConversionPattern=%d{yy/MM/dd HH:mm:ss} %p %c{1}: %m%n