pom.xml文件配置
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>${hadoop.version}</version>
27 </dependency>
28 </dependencies>
29
30 <!-- 配置构建信息 -->
31 <build>
32 <!-- 资源文件夹 -->
33 <sourceDirectory>src/main/scala</sourceDirectory>
34 <!-- 声明并引入构建的插件 -->
35 <plugins>
36 <!-- 用于编译Scala代码到class -->
37 <plugin>
38 <groupId>net.alchim31.maven</groupId>
39 <artifactId>scala-maven-plugin</artifactId>
40 <version>3.2.2</version>
41 <executions>
42 <execution>
43 <goals>
44 <goal>compile</goal>
45 <goal>testCompile</goal>
46 </goals>
47 <configuration>
48 <args>
49 <arg>-dependencyfile</arg>
50 <arg>${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>
第一个WordCount
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)
26
27 //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(_+_)
36
37 //println(sumed.collect().toList)
38
39 sc.stop()//关闭Sparkcontext
40
41
42 //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 }
程序打包提交集群
将jar包上传到对应节点,然后在Spark安装目录下bin目录下执行以下操作
./spark-submit \
> --class SparkCore_01.SparkWordCount\
> --master spark://hadoop01:7077 \
> --executor-memory 512m \
> --total-executor-cores 2 \
> /root/Spark_1905-1.0-SNAPSHOT.jar hdfs://hadoop01:8020/word.txt hdfs://hadoop01:8020/out2
ps: jar包所在路径 hdfs集群读取文件 写入到hdfs集群中
去掉打印日志
log4j.properties
1 # contributor license agreements. See the NOTICE file distributed with
2 # this work for additional information regarding copyright ownership.
3 # The ASF licenses this file to You under the Apache License, Version 2.0
4 # (the "License"); you may not use this file except in compliance with
5 # the License. You may obtain a copy of the License at
6 #
7 # http://www.apache.org/licenses/LICENSE-2.0
8 #
9 # Unless required by applicable law or agreed to in writing, software
10 # distributed under the License is distributed on an "AS IS" BASIS,
11 # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
12 # See the License for the specific language governing permissions and
13 # limitations under the License.
14 #
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
原文地址：https://www.cnblogs.com/yumengfei/p/12028338.html
时间： 2024-10-12 05:05:21