Spark Eclipse 開發環境搭建

時間  2019-11-17
標籤 spark eclipse 開發環境 搭建 欄目 Spark 简体版
原文   原文鏈接

Spark Eclipse 開發環境搭建

1 安裝Spark環境

  • 首先下載與集羣 Hadoop 版本對應的 Spark 編譯好的版本，解壓縮到指定位置，注意用戶權限
  • 進入解壓縮以後的 SPARK_HOME 目錄
  • 配置 /etc/profile 或者 ~/.bashrc 中配置 SPARK_HOME
  • cd $SPARK_HOME/conf cp spark-env.sh.template spark-env.sh
  • vim spark-env.sh
export SCALA_HOME=/home/hadoop/cluster/scala-2.10.5
export JAVA_HOME=/home/hadoop/cluster/jdk1.7.0_79
export HADOOP_HOME=/home/hadoop/cluster/hadoop-2.6.0
export HADOOP_CONF_DIR=$HADOOP_HOME/etc/hadoop
#注意這個地方必定要指定爲IP，不然下面的eclipse去鏈接的時候會報：
#All masters are unresponsive! Giving up. 這個錯誤的。
SPARK_MASTER_IP=10.16.112.121
SPARK_LOCAL_DIRS=/home/hadoop/cluster/spark-1.4.0-bin-hadoop2.6
SPARK_DRIVER_MEMORY=1G

2 standalone 模式開啓 spark

sbin/start-master.sh
sbin/start-slave.sh

此時能夠在瀏覽器中輸入：http://yourip:8080 查看Spark集羣的狀況
此時默認的 Spark-Master 爲： spark://10.16.112.121:7077html

3 利用 Scala-Eclipse IDE 與 Maven 構建 Spark 開發環境

  • 首先下載 Scala-Eclipse IDE 去 scala 官網下載便可
  • 打開IDE, 新建 Maven 項目, pom.xml 填寫以下:
<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>spark.test</groupId>
	<artifactId>FirstTrySpark</artifactId>
	<version>0.0.1-SNAPSHOT</version>

	<properties>
	  <!-- 填寫對應版本 -->
	  <hadoop.version>2.6.0</hadoop.version>
	  <spark.version>1.4.0</spark.version>
	</properties>
	<dependencies>
		<dependency>
		    <groupId>org.apache.hadoop</groupId>
		    <artifactId>hadoop-client</artifactId>
		    <version>${hadoop.version}</version>
		    <scope>provided</scope>
        <!-- 記得排除servlet依賴，不然會報衝突 -->
		    <exclusions>
		      <exclusion>
			      <groupId>javax.servlet</groupId>
			      <artifactId>*</artifactId>
		      </exclusion>
		    </exclusions>
		</dependency>
                <dependency>
                    <groupId>org.apache.hadoop</groupId>
                    <artifactId>hadoop-common</artifactId>
                    <version>2.6.0</version>
                </dependency>
                <dependency>
                    <groupId>org.apache.hadoop</groupId>
                    <artifactId>hadoop-mapreduce-client-jobclient</artifactId>
                    <version>2.6.0</version>
                </dependency>


		<dependency>
			<groupId>org.apache.spark</groupId>
			<artifactId>spark-core_2.10</artifactId>
			<version>${spark.version}</version>
		</dependency>

	</dependencies>


	<build>
		<sourceDirectory>src/main/java</sourceDirectory>
		<plugins>
			<!-- bind the maven-assembly-plugin to the package phase this will create
				a jar file without the storm dependencies suitable for deployment to a cluster. -->

			<plugin>
				<groupId>net.alchim31.maven</groupId>
				<artifactId>scala-maven-plugin</artifactId>
				<version>3.2.0</version>
				<executions>
					<execution>
						<goals>
							<goal>compile</goal>
							<goal>testCompile</goal>
						</goals>
					</execution>
				</executions>
				<configuration>
					<scalaVersion>2.10</scalaVersion>
				</configuration>
			</plugin>

			<plugin>
				<groupId>org.apache.maven.plugins</groupId>
				<artifactId>maven-assembly-plugin</artifactId>
				<version>2.5.5</version>
				<configuration>
					<descriptorRefs>
						<descriptorRef>jar-with-dependencies</descriptorRef>
					</descriptorRefs>
				</configuration>
				<executions>
					<execution>
						<phase>package</phase>
						<goals>
							<goal>single</goal>
						</goals>
					</execution>
				</executions>
			</plugin>

			<plugin>
				<groupId>org.apache.maven.plugins</groupId>
				<artifactId>maven-compiler-plugin</artifactId>
				<configuration>
					<source>1.7</source>
					<target>1.7</target>
				</configuration>
			</plugin>

		</plugins>

		<resources>
			<resource>
				<directory>src/main/resources</directory>
			</resource>
		</resources>

	</build>
</project>
  • 新建幾個 Source Folder
src/main/java      #編寫 java 代碼
src/main/scala     #編寫 scala 代碼
src/main/resources #存放資源文件
src/test/java      #編寫測試 java 代碼
src/test/scala     #編寫測試 scala 代碼
src/test/resources #存放資源文件

此時環境所有搭建完畢！java

4 編寫測試代碼是否能夠鏈接成功

  • 測試代碼以下：
import org.apache.spark.SparkConf
import org.apache.spark.SparkConf
import org.apache.spark.SparkContext

/**
 * @author clebeg
 */
object FirstTry {
  def main(args: Array[String]): Unit = {
    val conf = new SparkConf
    conf.setMaster("spark://yourip:7077")
    conf.set("spark.app.name", "first-tryspark")
    val sc = new SparkContext(conf)
    val rawblocks = sc.textFile("hdfs://yourip:9000/user/hadoop/linkage")
    println(rawblocks.first)
  }
}

5 部分錯誤彙總

大部分問題上面已經提到，這裏很少說，下面提幾個主要的問題：

  • Initial job has not accepted any resources; check your cluster UI to ensure that workers are registered and have sufficient resources
    分析問題：點開運行ID對應的運行日誌發現下面的錯誤：
15/10/10 08:49:01 INFO executor.CoarseGrainedExecutorBackend: Registered signal handlers for [TERM, HUP, INT]
15/10/10 08:49:01 WARN util.NativeCodeLoader: Unable to load native-hadoop library for your platform... using builtin-java classes where applicable
15/10/10 08:49:02 INFO spark.SecurityManager: Changing view acls to: hadoop,Administrator
15/10/10 08:49:02 INFO spark.SecurityManager: Changing modify acls to: hadoop,Administrator
15/10/10 08:49:02 INFO spark.SecurityManager: SecurityManager: authentication disabled; ui acls disabled; users with view permissions: Set(hadoop, Administrator); users with modify permissions: Set(hadoop, Administrator)
15/10/10 08:49:02 INFO slf4j.Slf4jLogger: Slf4jLogger started
15/10/10 08:49:02 INFO Remoting: Starting remoting
15/10/10 08:49:02 INFO Remoting: Remoting started; listening on addresses :[akka.tcp://driverPropsFetcher@10.16.112.121:58708]
15/10/10 08:49:02 INFO util.Utils: Successfully started service 'driverPropsFetcher' on port 58708.
Exception in thread "main" java.lang.reflect.UndeclaredThrowableException
	at org.apache.hadoop.security.UserGroupInformation.doAs(UserGroupInformation.java:1643)
	at org.apache.spark.deploy.SparkHadoopUtil.runAsSparkUser(SparkHadoopUtil.scala:65)
	at org.apache.spark.executor.CoarseGrainedExecutorBackend$.run(CoarseGrainedExecutorBackend.scala:146)
	at org.apache.spark.executor.CoarseGrainedExecutorBackend$.main(CoarseGrainedExecutorBackend.scala:245)
	at org.apache.spark.executor.CoarseGrainedExecutorBackend.main(CoarseGrainedExecutorBackend.scala)
Caused by: java.util.concurrent.TimeoutException: Futures timed out after [120 seconds]
	at scala.concurrent.impl.Promise$DefaultPromise.ready(Promise.scala:219)
	at scala.concurrent.impl.Promise$DefaultPromise.result(Promise.scala:223)
	at scala.concurrent.Await$$anonfun$result$1.apply(package.scala:107)
	at scala.concurrent.BlockContext$DefaultBlockContext$.blockOn(BlockContext.scala:53)
	at scala.concurrent.Await$.result(package.scala:107)
	at org.apache.spark.rpc.RpcEnv.setupEndpointRefByURI(RpcEnv.scala:97)
	at org.apache.spark.executor.CoarseGrainedExecutorBackend$$anonfun$run$1.apply$mcV$sp(CoarseGrainedExecutorBackend.scala:159)
	at org.apache.spark.deploy.SparkHadoopUtil$$anon$1.run(SparkHadoopUtil.scala:66)
	at org.apache.spark.deploy.SparkHadoopUtil$$anon$1.run(SparkHadoopUtil.scala:65)
	at java.security.AccessController.doPrivileged(Native Method)
	at javax.security.auth.Subject.doAs(Subject.java:415)
	at org.apache.hadoop.security.UserGroupInformation.doAs(UserGroupInformation.java:1628)
	... 4 more
15/10/10 08:51:02 INFO util.Utils: Shutdown hook called

仔細一看原來是權限的問題：立馬關閉 Hadoop, 在 etc/hadoop/core-site.xml 中添加：shell

<property>  
  <name>hadoop.security.authorization</name>  
  <value>false</value>  
</property>

設置任何人均可以讀取，問題立馬搞定。apache

  • java.io.IOException: Could not locate executable null\bin\winutils.exe in the Hadoop binaries.
  1. 到地址http://www.barik.net/archive/2015/01/19/172716/ 下載包含 winutils.exe 的 hadoop2.6 從新編譯的版本。注意必定要下載對應本身的Hadoop版本。
  2. 減壓縮到指定位置，設置 HADOOP_HOME 環境變量。注意必定要從新啓動 eclipse。 搞定！
mkdir linkage
cd linkage/
curl -o donation.zip http://bit.ly/1Aoywaq
unzip donation.zip
unzip "block_*.zip"
hdfs dfs -mkdir /user/hadoop/linkage
hdfs dfs -put block_*.csv /user/hadoop/linkage

6 一些有用的連接

  1. http://www.migle.me/post/Spark%E5%AD%A6%E4%B9%A0-hello%20spark/ spark 初探
  2. http://spark.apache.org/docs/latest/index.html spark 官網
  3. http://www.cnblogs.com/hseagle/category/569175.html spark 源碼剖析
  4. http://wuchong.me/blog/2015/04/04/spark-on-yarn-cluster-deploy/ spark 集羣搭建
  5. http://www.barik.net/archive/2015/01/19/172716/ 包含winutil.exe 的Hadoop2.6從新編譯版本
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