Spark记录-Spark作业调试
在本地IDE里直接运行spark程序操作远程集群
一般运行spark作业的方式有两种：
本机调试，通过设置master为local模式运行spark作业，这种方式一般用于调试，不用连接远程集群。
集群运行。一般本机调试通过后会将作业打成jar包通过spark-submit提交运行。生产环境一般使用这种方式。
操作方法
1.设置master
两种方式：
- 在程序中设置
SparkConf conf = new SparkConf()
.setAppName("helloworld")
.setMaster("spark://192.168.66.66:7077");- 在run configuration中设置
VM options中添加：
-Dspark.master="spark://192.168.66.66:7077"2.设置HDFS
在程序中使用HDFS路径，会出现文件系统不匹配hdfs，可以将集群中的hadoop配置中的core-site.xml和hdfs-site.xml拷贝到项目src/main/resources下
3.发送jar包
如果程序中使用了自定义的算子和依赖的jar包，需要将本项目jar包和依赖的jar包发送到集群中SPARK_HOME/jars目录下，可以用maven-assembly打成带依赖的jar包，spark的jars相当于mvn库。
注意集群中每个节点的jars目录下都要放自己的jar包。
可能遇到的问题
如果遇到了节点间通信问题，可能是jar包没有在所有节点放置好。
incompatible loaded等问题，是依赖的spark版本不匹配，修改dependency。
至此，就可以直接在IDE中运行了
实战操作
1.安装jdk1.8、idea2017，maven3、idea2017安装scala插件
2.新建maven项目-scala
3.配置pom.xml，下载依赖包
<?xml version="1.0" encoding="UTF-8"?>
<!--
Licensed to the Apache Software Foundation (ASF) under one
or more contributor license agreements. See the NOTICE file
distributed with this work for additional information
regarding copyright ownership. The ASF licenses this file
to you under the Apache License, Version 2.0 (the
"License"); you may not use this file except in compliance
with the License. You may obtain a copy of the License at http://www.apache.org/licenses/LICENSE-2.0 Unless required by applicable law or agreed to in writing,
software distributed under the License is distributed on an
"AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
KIND, either express or implied. See the License for the
specific language governing permissions and limitations
under the License.
-->
<!-- $Id: pom.xml 642118 2008-03-28 08:04:16Z reinhard $ -->
<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/maven-v4_0_0.xsd"> <modelVersion>4.0.0</modelVersion>
<packaging>war</packaging> <name>scala</name>
<groupId>scala</groupId>
<artifactId>scala</artifactId>
<version>1.0-SNAPSHOT</version> <build>
<plugins>
<plugin>
<groupId>org.mortbay.jetty</groupId>
<artifactId>maven-jetty-plugin</artifactId>
<version>6.1.7</version>
<configuration>
<connectors>
<connector implementation="org.mortbay.jetty.nio.SelectChannelConnector">
<port>8888</port>
<maxIdleTime>30000</maxIdleTime>
</connector>
</connectors>
<webAppSourceDirectory>${project.build.directory}/${pom.artifactId}-${pom.version}</webAppSourceDirectory>
<contextPath>/</contextPath>
</configuration>
</plugin>
</plugins>
</build>
<properties>
<scala.version>2.10.5</scala.version>
<hadoop.version>2.7.3</hadoop.version>
</properties> <repositories>
<repository>
<id>scala-tools.org</id>
<name>Scala-Tools Maven2 Repository</name>
<url>http://scala-tools.org/repo-releases</url>
</repository>
</repositories> <dependencies>
<!--dependency>
<groupId>scala</groupId>
<artifactId>[the artifact id of the block to be mounted]</artifactId>
<version>1.0-SNAPSHOT</version>
</dependency-->
<dependency>
<groupId>org.apache.spark</groupId>
<artifactId>spark-core_2.10</artifactId>
<version>1.6.3</version>
</dependency>
<dependency>
<groupId>org.apache.spark</groupId>
<artifactId>spark-sql_2.10</artifactId>
<version>1.6.3</version>
</dependency>
<dependency>
<groupId>org.apache.spark</groupId>
<artifactId>spark-streaming_2.10</artifactId>
<version>1.6.3</version>
</dependency>
<dependency>
<groupId>org.apache.hadoop</groupId>
<artifactId>hadoop-client</artifactId>
<version>${hadoop.version}</version>
</dependency>
<dependency>
<groupId>org.apache.hadoop</groupId>
<artifactId>hadoop-common</artifactId>
<version>${hadoop.version}</version>
</dependency>
<dependency>
<groupId>org.apache.hadoop</groupId>
<artifactId>hadoop-hdfs</artifactId>
<version>${hadoop.version}</version>
</dependency>
</dependencies> </project>
4.打开File-Project Structure-Modules，Sources-scala项目src-main新建一个scala目录，设置为Sources
5.打开File-Project Structure-Libraries,添加scala sdk（2.10.5）
6.从集群里复制一个hadoop程序到D盘，再到网上下载https://github.com/srccodes/hadoop-common-2.2.0-bin，解压合并bin文件夹即可，设置用户环境变量HADOOP_HOME。
7.返回主界面，在src-main-scala下新建一个object：sparkPi:
import scala.math.random
import org.apache.spark._ object sparkPi {
def main(args: Array[String]) {
System.setProperty("hadoop.home.dir", "D:\\hadoop")
val conf = new SparkConf().setAppName("Spark Pi").setMaster("spark://192.168.66.66:7077")
.set("spark.executor.memory.","1g")
.set("spark.serializer","org.apache.spark.serializer.KryoSerializer")
.setJars(Seq("D:\\workspace\\scala\\out\\scala.jar"))
val spark = new SparkContext(conf)
val slices = if (args.length > 0) args(0).toInt else 2
println("Time:" + spark.startTime)
val n = math.min(1000L * slices, Int.MaxValue).toInt // avoid overflow
val count = spark.parallelize(1 until n, slices).map { i =>
val x = random * 2 - 1
val y = random * 2 - 1
if (x*x + y*y < 1) 1 else 0
}.reduce(_ + _)
println("Pi is roughly " + 4.0 * count / n)
spark.stop()
}
}
8.打开File-Project Structure-Artifacts,添加JAR-from modules with dependencies,选择好主类-sparkPi，设置好Output，去除不必要的包；
9.Build-Build Artifacts-scala.jar
10.Run-Run sparkPi
"C:\Program Files\Java\jdk1.8.0_121\bin\java" "-javaagent:D:\Program Files (x86)\JetBrains\IntelliJ IDEA 173.3302.5\lib\idea_rt.jar=53908:D:\Program Files (x86)\JetBrains\IntelliJ IDEA 173.3302.5\bin" -Dfile.encoding=UTF-8 -classpath "C:\Program Files\Java\jdk1.8.0_121\jre\lib\charsets.jar;C:\Program Files\Java\jdk1.8.0_121\jre\lib\deploy.jar;C:\Program Files\Java\jdk1.8.0_121\jre\lib\ext\access-bridge-64.jar;C:\Program Files\Java\jdk1.8.0_121\jre\lib\ext\cldrdata.jar;C:\Program Files\Java\jdk1.8.0_121\jre\lib\ext\dnsns.jar;C:\Program Files\Java\jdk1.8.0_121\jre\lib\ext\jaccess.jar;C:\Program Files\Java\jdk1.8.0_121\jre\lib\ext\jfxrt.jar;C:\Program Files\Java\jdk1.8.0_121\jre\lib\ext\localedata.jar;C:\Program Files\Java\jdk1.8.0_121\jre\lib\ext\nashorn.jar;C:\Program Files\Java\jdk1.8.0_121\jre\lib\ext\sunec.jar;C:\Program Files\Java\jdk1.8.0_121\jre\lib\ext\sunjce_provider.jar;C:\Program Files\Java\jdk1.8.0_121\jre\lib\ext\sunmscapi.jar;C:\Program Files\Java\jdk1.8.0_121\jre\lib\ext\sunpkcs11.jar;C:\Program Files\Java\jdk1.8.0_121\jre\lib\ext\zipfs.jar;C:\Program Files\Java\jdk1.8.0_121\jre\lib\javaws.jar;C:\Program Files\Java\jdk1.8.0_121\jre\lib\jce.jar;C:\Program Files\Java\jdk1.8.0_121\jre\lib\jfr.jar;C:\Program Files\Java\jdk1.8.0_121\jre\lib\jfxswt.jar;C:\Program Files\Java\jdk1.8.0_121\jre\lib\jsse.jar;C:\Program Files\Java\jdk1.8.0_121\jre\lib\management-agent.jar;C:\Program Files\Java\jdk1.8.0_121\jre\lib\plugin.jar;C:\Program Files\Java\jdk1.8.0_121\jre\lib\resources.jar;C:\Program Files\Java\jdk1.8.0_121\jre\lib\rt.jar;D:\workspace\scala\target\classes;C:\Users\xinfang\.m2\repository\org\scala-lang\scala-library\2.10.5\scala-library-2.10.5.jar;C:\Users\xinfang\.m2\repository\org\scala-lang\scala-reflect\2.10.5\scala-reflect-2.10.5.jar;C:\Users\xinfang\.m2\repository\org\apache\spark\spark-core_2.10\1.6.3\spark-core_2.10-1.6.3.jar;C:\Users\xinfang\.m2\repository\org\apache\avro\avro-mapred\1.7.7\avro-mapred-1.7.7-hadoop2.jar;C:\Users\xinfang\.m2\repository\org\apache\avro\avro-ipc\1.7.7\avro-ipc-1.7.7.jar;C:\Users\xinfang\.m2\repository\org\apache\avro\avro-ipc\1.7.7\avro-ipc-1.7.7-tests.jar;C:\Users\xinfang\.m2\repository\com\twitter\chill_2.10\0.5.0\chill_2.10-0.5.0.jar;C:\Users\xinfang\.m2\repository\com\esotericsoftware\kryo\kryo\2.21\kryo-2.21.jar;C:\Users\xinfang\.m2\repository\com\esotericsoftware\reflectasm\reflectasm\1.07\reflectasm-1.07-shaded.jar;C:\Users\xinfang\.m2\repository\com\esotericsoftware\minlog\minlog\1.2\minlog-1.2.jar;C:\Users\xinfang\.m2\repository\org\objenesis\objenesis\1.2\objenesis-1.2.jar;C:\Users\xinfang\.m2\repository\com\twitter\chill-java\0.5.0\chill-java-0.5.0.jar;C:\Users\xinfang\.m2\repository\org\apache\xbean\xbean-asm5-shaded\4.4\xbean-asm5-shaded-4.4.jar;C:\Users\xinfang\.m2\repository\org\apache\spark\spark-launcher_2.10\1.6.3\spark-launcher_2.10-1.6.3.jar;C:\Users\xinfang\.m2\repository\org\apache\spark\spark-network-common_2.10\1.6.3\spark-network-common_2.10-1.6.3.jar;C:\Users\xinfang\.m2\repository\org\apache\spark\spark-network-shuffle_2.10\1.6.3\spark-network-shuffle_2.10-1.6.3.jar;C:\Users\xinfang\.m2\repository\com\fasterxml\jackson\core\jackson-annotations\2.4.4\jackson-annotations-2.4.4.jar;C:\Users\xinfang\.m2\repository\org\apache\spark\spark-unsafe_2.10\1.6.3\spark-unsafe_2.10-1.6.3.jar;C:\Users\xinfang\.m2\repository\net\java\dev\jets3t\jets3t\0.7.1\jets3t-0.7.1.jar;C:\Users\xinfang\.m2\repository\org\apache\curator\curator-recipes\2.4.0\curator-recipes-2.4.0.jar;C:\Users\xinfang\.m2\repository\org\apache\curator\curator-framework\2.4.0\curator-framework-2.4.0.jar;C:\Users\xinfang\.m2\repository\org\eclipse\jetty\orbit\javax.servlet\3.0.0.v201112011016\javax.servlet-3.0.0.v201112011016.jar;C:\Users\xinfang\.m2\repository\org\apache\commons\commons-lang3\3.3.2\commons-lang3-3.3.2.jar;C:\Users\xinfang\.m2\repository\org\apache\commons\commons-math3\3.4.1\commons-math3-3.4.1.jar;C:\Users\xinfang\.m2\repository\com\google\code\findbugs\jsr305\1.3.9\jsr305-1.3.9.jar;C:\Users\xinfang\.m2\repository\org\slf4j\slf4j-api\1.7.10\slf4j-api-1.7.10.jar;C:\Users\xinfang\.m2\repository\org\slf4j\jul-to-slf4j\1.7.10\jul-to-slf4j-1.7.10.jar;C:\Users\xinfang\.m2\repository\org\slf4j\jcl-over-slf4j\1.7.10\jcl-over-slf4j-1.7.10.jar;C:\Users\xinfang\.m2\repository\log4j\log4j\1.2.17\log4j-1.2.17.jar;C:\Users\xinfang\.m2\repository\org\slf4j\slf4j-log4j12\1.7.10\slf4j-log4j12-1.7.10.jar;C:\Users\xinfang\.m2\repository\com\ning\compress-lzf\1.0.3\compress-lzf-1.0.3.jar;C:\Users\xinfang\.m2\repository\org\xerial\snappy\snappy-java\1.1.2.6\snappy-java-1.1.2.6.jar;C:\Users\xinfang\.m2\repository\net\jpountz\lz4\lz4\1.3.0\lz4-1.3.0.jar;C:\Users\xinfang\.m2\repository\org\roaringbitmap\RoaringBitmap\0.5.11\RoaringBitmap-0.5.11.jar;C:\Users\xinfang\.m2\repository\commons-net\commons-net\2.2\commons-net-2.2.jar;C:\Users\xinfang\.m2\repository\com\typesafe\akka\akka-remote_2.10\2.3.11\akka-remote_2.10-2.3.11.jar;C:\Users\xinfang\.m2\repository\com\typesafe\akka\akka-actor_2.10\2.3.11\akka-actor_2.10-2.3.11.jar;C:\Users\xinfang\.m2\repository\com\typesafe\config\1.2.1\config-1.2.1.jar;C:\Users\xinfang\.m2\repository\org\uncommons\maths\uncommons-maths\1.2.2a\uncommons-maths-1.2.2a.jar;C:\Users\xinfang\.m2\repository\com\typesafe\akka\akka-slf4j_2.10\2.3.11\akka-slf4j_2.10-2.3.11.jar;C:\Users\xinfang\.m2\repository\org\json4s\json4s-jackson_2.10\3.2.10\json4s-jackson_2.10-3.2.10.jar;C:\Users\xinfang\.m2\repository\org\json4s\json4s-core_2.10\3.2.10\json4s-core_2.10-3.2.10.jar;C:\Users\xinfang\.m2\repository\org\json4s\json4s-ast_2.10\3.2.10\json4s-ast_2.10-3.2.10.jar;C:\Users\xinfang\.m2\repository\org\scala-lang\scalap\2.10.0\scalap-2.10.0.jar;C:\Users\xinfang\.m2\repository\org\scala-lang\scala-compiler\2.10.0\scala-compiler-2.10.0.jar;C:\Users\xinfang\.m2\repository\com\sun\jersey\jersey-server\1.9\jersey-server-1.9.jar;C:\Users\xinfang\.m2\repository\asm\asm\3.1\asm-3.1.jar;C:\Users\xinfang\.m2\repository\com\sun\jersey\jersey-core\1.9\jersey-core-1.9.jar;C:\Users\xinfang\.m2\repository\org\apache\mesos\mesos\0.21.1\mesos-0.21.1-shaded-protobuf.jar;C:\Users\xinfang\.m2\repository\io\netty\netty-all\4.0.29.Final\netty-all-4.0.29.Final.jar;C:\Users\xinfang\.m2\repository\com\clearspring\analytics\stream\2.7.0\stream-2.7.0.jar;C:\Users\xinfang\.m2\repository\io\dropwizard\metrics\metrics-core\3.1.2\metrics-core-3.1.2.jar;C:\Users\xinfang\.m2\repository\io\dropwizard\metrics\metrics-jvm\3.1.2\metrics-jvm-3.1.2.jar;C:\Users\xinfang\.m2\repository\io\dropwizard\metrics\metrics-json\3.1.2\metrics-json-3.1.2.jar;C:\Users\xinfang\.m2\repository\io\dropwizard\metrics\metrics-graphite\3.1.2\metrics-graphite-3.1.2.jar;C:\Users\xinfang\.m2\repository\com\fasterxml\jackson\core\jackson-databind\2.4.4\jackson-databind-2.4.4.jar;C:\Users\xinfang\.m2\repository\com\fasterxml\jackson\core\jackson-core\2.4.4\jackson-core-2.4.4.jar;C:\Users\xinfang\.m2\repository\com\fasterxml\jackson\module\jackson-module-scala_2.10\2.4.4\jackson-module-scala_2.10-2.4.4.jar;C:\Users\xinfang\.m2\repository\org\scala-lang\scala-reflect\2.10.4\scala-reflect-2.10.4.jar;C:\Users\xinfang\.m2\repository\com\thoughtworks\paranamer\paranamer\2.6\paranamer-2.6.jar;C:\Users\xinfang\.m2\repository\org\apache\ivy\ivy\2.4.0\ivy-2.4.0.jar;C:\Users\xinfang\.m2\repository\oro\oro\2.0.8\oro-2.0.8.jar;C:\Users\xinfang\.m2\repository\org\tachyonproject\tachyon-client\0.8.2\tachyon-client-0.8.2.jar;C:\Users\xinfang\.m2\repository\org\tachyonproject\tachyon-underfs-hdfs\0.8.2\tachyon-underfs-hdfs-0.8.2.jar;C:\Users\xinfang\.m2\repository\org\tachyonproject\tachyon-underfs-s3\0.8.2\tachyon-underfs-s3-0.8.2.jar;C:\Users\xinfang\.m2\repository\org\tachyonproject\tachyon-underfs-local\0.8.2\tachyon-underfs-local-0.8.2.jar;C:\Users\xinfang\.m2\repository\net\razorvine\pyrolite\4.9\pyrolite-4.9.jar;C:\Users\xinfang\.m2\repository\net\sf\py4j\py4j\0.9\py4j-0.9.jar;C:\Users\xinfang\.m2\repository\org\spark-project\spark\unused\1.0.0\unused-1.0.0.jar;C:\Users\xinfang\.m2\repository\org\apache\spark\spark-sql_2.10\1.6.3\spark-sql_2.10-1.6.3.jar;C:\Users\xinfang\.m2\repository\org\apache\spark\spark-catalyst_2.10\1.6.3\spark-catalyst_2.10-1.6.3.jar;C:\Users\xinfang\.m2\repository\org\codehaus\janino\janino\2.7.8\janino-2.7.8.jar;C:\Users\xinfang\.m2\repository\org\codehaus\janino\commons-compiler\2.7.8\commons-compiler-2.7.8.jar;C:\Users\xinfang\.m2\repository\org\apache\parquet\parquet-column\1.7.0\parquet-column-1.7.0.jar;C:\Users\xinfang\.m2\repository\org\apache\parquet\parquet-common\1.7.0\parquet-common-1.7.0.jar;C:\Users\xinfang\.m2\repository\org\apache\parquet\parquet-encoding\1.7.0\parquet-encoding-1.7.0.jar;C:\Users\xinfang\.m2\repository\org\apache\parquet\parquet-generator\1.7.0\parquet-generator-1.7.0.jar;C:\Users\xinfang\.m2\repository\org\apache\parquet\parquet-hadoop\1.7.0\parquet-hadoop-1.7.0.jar;C:\Users\xinfang\.m2\repository\org\apache\parquet\parquet-format\2.3.0-incubating\parquet-format-2.3.0-incubating.jar;C:\Users\xinfang\.m2\repository\org\apache\parquet\parquet-jackson\1.7.0\parquet-jackson-1.7.0.jar;C:\Users\xinfang\.m2\repository\org\apache\spark\spark-streaming_2.10\1.6.3\spark-streaming_2.10-1.6.3.jar;C:\Users\xinfang\.m2\repository\org\apache\hadoop\hadoop-client\2.7.3\hadoop-client-2.7.3.jar;C:\Users\xinfang\.m2\repository\org\apache\hadoop\hadoop-mapreduce-client-app\2.7.3\hadoop-mapreduce-client-app-2.7.3.jar;C:\Users\xinfang\.m2\repository\org\apache\hadoop\hadoop-mapreduce-client-common\2.7.3\hadoop-mapreduce-client-common-2.7.3.jar;C:\Users\xinfang\.m2\repository\org\apache\hadoop\hadoop-yarn-client\2.7.3\hadoop-yarn-client-2.7.3.jar;C:\Users\xinfang\.m2\repository\org\apache\hadoop\hadoop-yarn-server-common\2.7.3\hadoop-yarn-server-common-2.7.3.jar;C:\Users\xinfang\.m2\repository\org\apache\hadoop\hadoop-mapreduce-client-shuffle\2.7.3\hadoop-mapreduce-client-shuffle-2.7.3.jar;C:\Users\xinfang\.m2\repository\org\apache\hadoop\hadoop-yarn-api\2.7.3\hadoop-yarn-api-2.7.3.jar;C:\Users\xinfang\.m2\repository\org\apache\hadoop\hadoop-mapreduce-client-core\2.7.3\hadoop-mapreduce-client-core-2.7.3.jar;C:\Users\xinfang\.m2\repository\org\apache\hadoop\hadoop-yarn-common\2.7.3\hadoop-yarn-common-2.7.3.jar;C:\Users\xinfang\.m2\repository\javax\xml\bind\jaxb-api\2.2.2\jaxb-api-2.2.2.jar;C:\Users\xinfang\.m2\repository\javax\xml\stream\stax-api\1.0-2\stax-api-1.0-2.jar;C:\Users\xinfang\.m2\repository\javax\activation\activation\1.1\activation-1.1.jar;C:\Users\xinfang\.m2\repository\com\sun\jersey\jersey-client\1.9\jersey-client-1.9.jar;C:\Users\xinfang\.m2\repository\org\apache\hadoop\hadoop-mapreduce-client-jobclient\2.7.3\hadoop-mapreduce-client-jobclient-2.7.3.jar;C:\Users\xinfang\.m2\repository\org\apache\hadoop\hadoop-annotations\2.7.3\hadoop-annotations-2.7.3.jar;C:\Users\xinfang\.m2\repository\org\apache\hadoop\hadoop-common\2.7.3\hadoop-common-2.7.3.jar;C:\Users\xinfang\.m2\repository\com\google\guava\guava\11.0.2\guava-11.0.2.jar;C:\Users\xinfang\.m2\repository\commons-cli\commons-cli\1.2\commons-cli-1.2.jar;C:\Users\xinfang\.m2\repository\xmlenc\xmlenc\0.52\xmlenc-0.52.jar;C:\Users\xinfang\.m2\repository\commons-httpclient\commons-httpclient\3.1\commons-httpclient-3.1.jar;C:\Users\xinfang\.m2\repository\commons-codec\commons-codec\1.4\commons-codec-1.4.jar;C:\Users\xinfang\.m2\repository\commons-io\commons-io\2.4\commons-io-2.4.jar;C:\Users\xinfang\.m2\repository\commons-collections\commons-collections\3.2.2\commons-collections-3.2.2.jar;C:\Users\xinfang\.m2\repository\javax\servlet\servlet-api\2.5\servlet-api-2.5.jar;C:\Users\xinfang\.m2\repository\org\mortbay\jetty\jetty\6.1.26\jetty-6.1.26.jar;C:\Users\xinfang\.m2\repository\org\mortbay\jetty\jetty-util\6.1.26\jetty-util-6.1.26.jar;C:\Users\xinfang\.m2\repository\javax\servlet\jsp\jsp-api\2.1\jsp-api-2.1.jar;C:\Users\xinfang\.m2\repository\com\sun\jersey\jersey-json\1.9\jersey-json-1.9.jar;C:\Users\xinfang\.m2\repository\org\codehaus\jettison\jettison\1.1\jettison-1.1.jar;C:\Users\xinfang\.m2\repository\com\sun\xml\bind\jaxb-impl\2.2.3-1\jaxb-impl-2.2.3-1.jar;C:\Users\xinfang\.m2\repository\org\codehaus\jackson\jackson-jaxrs\1.8.3\jackson-jaxrs-1.8.3.jar;C:\Users\xinfang\.m2\repository\org\codehaus\jackson\jackson-xc\1.8.3\jackson-xc-1.8.3.jar;C:\Users\xinfang\.m2\repository\commons-logging\commons-logging\1.1.3\commons-logging-1.1.3.jar;C:\Users\xinfang\.m2\repository\commons-lang\commons-lang\2.6\commons-lang-2.6.jar;C:\Users\xinfang\.m2\repository\commons-configuration\commons-configuration\1.6\commons-configuration-1.6.jar;C:\Users\xinfang\.m2\repository\commons-digester\commons-digester\1.8\commons-digester-1.8.jar;C:\Users\xinfang\.m2\repository\commons-beanutils\commons-beanutils\1.7.0\commons-beanutils-1.7.0.jar;C:\Users\xinfang\.m2\repository\commons-beanutils\commons-beanutils-core\1.8.0\commons-beanutils-core-1.8.0.jar;C:\Users\xinfang\.m2\repository\org\codehaus\jackson\jackson-core-asl\1.9.13\jackson-core-asl-1.9.13.jar;C:\Users\xinfang\.m2\repository\org\codehaus\jackson\jackson-mapper-asl\1.9.13\jackson-mapper-asl-1.9.13.jar;C:\Users\xinfang\.m2\repository\org\apache\avro\avro\1.7.4\avro-1.7.4.jar;C:\Users\xinfang\.m2\repository\com\google\protobuf\protobuf-java\2.5.0\protobuf-java-2.5.0.jar;C:\Users\xinfang\.m2\repository\com\google\code\gson\gson\2.2.4\gson-2.2.4.jar;C:\Users\xinfang\.m2\repository\org\apache\hadoop\hadoop-auth\2.7.3\hadoop-auth-2.7.3.jar;C:\Users\xinfang\.m2\repository\org\apache\httpcomponents\httpclient\4.2.5\httpclient-4.2.5.jar;C:\Users\xinfang\.m2\repository\org\apache\httpcomponents\httpcore\4.2.4\httpcore-4.2.4.jar;C:\Users\xinfang\.m2\repository\org\apache\directory\server\apacheds-kerberos-codec\2.0.0-M15\apacheds-kerberos-codec-2.0.0-M15.jar;C:\Users\xinfang\.m2\repository\org\apache\directory\server\apacheds-i18n\2.0.0-M15\apacheds-i18n-2.0.0-M15.jar;C:\Users\xinfang\.m2\repository\org\apache\directory\api\api-asn1-api\1.0.0-M20\api-asn1-api-1.0.0-M20.jar;C:\Users\xinfang\.m2\repository\org\apache\directory\api\api-util\1.0.0-M20\api-util-1.0.0-M20.jar;C:\Users\xinfang\.m2\repository\com\jcraft\jsch\0.1.42\jsch-0.1.42.jar;C:\Users\xinfang\.m2\repository\org\apache\curator\curator-client\2.7.1\curator-client-2.7.1.jar;C:\Users\xinfang\.m2\repository\org\apache\htrace\htrace-core\3.1.0-incubating\htrace-core-3.1.0-incubating.jar;C:\Users\xinfang\.m2\repository\org\apache\zookeeper\zookeeper\3.4.6\zookeeper-3.4.6.jar;C:\Users\xinfang\.m2\repository\org\apache\commons\commons-compress\1.4.1\commons-compress-1.4.1.jar;C:\Users\xinfang\.m2\repository\org\tukaani\xz\1.0\xz-1.0.jar;C:\Users\xinfang\.m2\repository\org\apache\hadoop\hadoop-hdfs\2.7.3\hadoop-hdfs-2.7.3.jar;C:\Users\xinfang\.m2\repository\commons-daemon\commons-daemon\1.0.13\commons-daemon-1.0.13.jar;C:\Users\xinfang\.m2\repository\io\netty\netty\3.6.2.Final\netty-3.6.2.Final.jar;C:\Users\xinfang\.m2\repository\xerces\xercesImpl\2.9.1\xercesImpl-2.9.1.jar;C:\Users\xinfang\.m2\repository\xml-apis\xml-apis\1.3.04\xml-apis-1.3.04.jar;C:\Users\xinfang\.m2\repository\org\fusesource\leveldbjni\leveldbjni-all\1.8\leveldbjni-all-1.8.jar" sparkPi
Using Spark's default log4j profile: org/apache/spark/log4j-defaults.properties
17/11/07 15:34:22 INFO SparkContext: Running Spark version 1.6.3
17/11/07 15:34:24 WARN NativeCodeLoader: Unable to load native-hadoop library for your platform... using builtin-java classes where applicable
17/11/07 15:34:24 INFO SecurityManager: Changing view acls to: xinfang
17/11/07 15:34:24 INFO SecurityManager: Changing modify acls to: xinfang
17/11/07 15:34:24 INFO SecurityManager: SecurityManager: authentication disabled; ui acls disabled; users with view permissions: Set(xinfang); users with modify permissions: Set(xinfang)
17/11/07 15:34:26 INFO Utils: Successfully started service 'sparkDriver' on port 53931.
17/11/07 15:34:26 INFO Slf4jLogger: Slf4jLogger started
17/11/07 15:34:26 INFO Remoting: Starting remoting
17/11/07 15:34:27 INFO Remoting: Remoting started; listening on addresses :[akka.tcp://sparkDriverActorSystem@172.20.107.151:53944]
17/11/07 15:34:27 INFO Utils: Successfully started service 'sparkDriverActorSystem' on port 53944.
17/11/07 15:34:27 INFO SparkEnv: Registering MapOutputTracker
17/11/07 15:34:27 INFO SparkEnv: Registering BlockManagerMaster
17/11/07 15:34:27 INFO DiskBlockManager: Created local directory at C:\Users\xinfang\AppData\Local\Temp\blockmgr-d4ba2426-7f9b-47f1-800e-2aad1aa75f70
17/11/07 15:34:27 INFO MemoryStore: MemoryStore started with capacity 1122.0 MB
17/11/07 15:34:27 INFO SparkEnv: Registering OutputCommitCoordinator
17/11/07 15:34:27 INFO Utils: Successfully started service 'SparkUI' on port 4040.
17/11/07 15:34:27 INFO SparkUI: Started SparkUI at http://172.20.107.151:4040
17/11/07 15:34:27 INFO HttpFileServer: HTTP File server directory is C:\Users\xinfang\AppData\Local\Temp\spark-150f8c4e-c5df-4254-a9f0-a8158b4caff0\httpd-b0aaa30f-cd92-4fbd-b064-6284fa604359
17/11/07 15:34:27 INFO HttpServer: Starting HTTP Server
17/11/07 15:34:28 INFO Utils: Successfully started service 'HTTP file server' on port 53947.
17/11/07 15:34:28 INFO SparkContext: Added JAR D:\workspace\scala\out\scala.jar at http://172.20.107.151:53947/jars/scala.jar with timestamp 1510040068032
17/11/07 15:34:28 INFO AppClient$ClientEndpoint: Connecting to master spark://192.168.66.66:7077...
17/11/07 15:34:30 INFO SparkDeploySchedulerBackend: Connected to Spark cluster with app ID app-20171107153300-0010
17/11/07 15:34:30 INFO AppClient$ClientEndpoint: Executor added: app-20171107153300-0010/0 on worker-20171106165832-192.168.66.66-7078 (192.168.66.66:7078) with 2 cores
17/11/07 15:34:30 INFO SparkDeploySchedulerBackend: Granted executor ID app-20171107153300-0010/0 on hostPort 192.168.66.66:7078 with 2 cores, 1024.0 MB RAM
17/11/07 15:34:30 INFO AppClient$ClientEndpoint: Executor updated: app-20171107153300-0010/0 is now RUNNING
17/11/07 15:34:30 INFO Utils: Successfully started service 'org.apache.spark.network.netty.NettyBlockTransferService' on port 53967.
17/11/07 15:34:30 INFO NettyBlockTransferService: Server created on 53967
17/11/07 15:34:30 INFO BlockManagerMaster: Trying to register BlockManager
17/11/07 15:34:30 INFO BlockManagerMasterEndpoint: Registering block manager 172.20.107.151:53967 with 1122.0 MB RAM, BlockManagerId(driver, 172.20.107.151, 53967)
17/11/07 15:34:30 INFO BlockManagerMaster: Registered BlockManager
17/11/07 15:34:31 INFO SparkDeploySchedulerBackend: SchedulerBackend is ready for scheduling beginning after reached minRegisteredResourcesRatio: 0.0
Time:1510040062460
17/11/07 15:34:31 INFO SparkContext: Starting job: reduce at sparkPi.scala:17
17/11/07 15:34:31 INFO DAGScheduler: Got job 0 (reduce at sparkPi.scala:17) with 2 output partitions
17/11/07 15:34:31 INFO DAGScheduler: Final stage: ResultStage 0 (reduce at sparkPi.scala:17)
17/11/07 15:34:31 INFO DAGScheduler: Parents of final stage: List()
17/11/07 15:34:31 INFO DAGScheduler: Missing parents: List()
17/11/07 15:34:32 INFO DAGScheduler: Submitting ResultStage 0 (MapPartitionsRDD[1] at map at sparkPi.scala:13), which has no missing parents
17/11/07 15:34:32 INFO MemoryStore: Block broadcast_0 stored as values in memory (estimated size 1848.0 B, free 1122.0 MB)
17/11/07 15:34:32 INFO MemoryStore: Block broadcast_0_piece0 stored as bytes in memory (estimated size 1206.0 B, free 1122.0 MB)
17/11/07 15:34:32 INFO BlockManagerInfo: Added broadcast_0_piece0 in memory on 172.20.107.151:53967 (size: 1206.0 B, free: 1122.0 MB)
17/11/07 15:34:32 INFO SparkContext: Created broadcast 0 from broadcast at DAGScheduler.scala:1006
17/11/07 15:34:32 INFO DAGScheduler: Submitting 2 missing tasks from ResultStage 0 (MapPartitionsRDD[1] at map at sparkPi.scala:13)
17/11/07 15:34:32 INFO TaskSchedulerImpl: Adding task set 0.0 with 2 tasks
17/11/07 15:34:36 INFO SparkDeploySchedulerBackend: Registered executor NettyRpcEndpointRef(null) (xinfang:53977) with ID 0
17/11/07 15:34:36 INFO TaskSetManager: Starting task 0.0 in stage 0.0 (TID 0, xinfang, partition 0,PROCESS_LOCAL, 2130 bytes)
17/11/07 15:34:36 INFO TaskSetManager: Starting task 1.0 in stage 0.0 (TID 1, xinfang, partition 1,PROCESS_LOCAL, 2130 bytes)
17/11/07 15:34:37 INFO BlockManagerMasterEndpoint: Registering block manager xinfang:64456 with 511.1 MB RAM, BlockManagerId(0, xinfang, 64456)
17/11/07 15:34:42 INFO BlockManagerInfo: Added broadcast_0_piece0 in memory on xinfang:64456 (size: 1206.0 B, free: 511.1 MB)
17/11/07 15:34:44 INFO TaskSetManager: Finished task 1.0 in stage 0.0 (TID 1) in 7589 ms on xinfang (1/2)
17/11/07 15:34:44 INFO TaskSetManager: Finished task 0.0 in stage 0.0 (TID 0) in 7654 ms on xinfang (2/2)
17/11/07 15:34:44 INFO TaskSchedulerImpl: Removed TaskSet 0.0, whose tasks have all completed, from pool
17/11/07 15:34:44 INFO DAGScheduler: ResultStage 0 (reduce at sparkPi.scala:17) finished in 11.849 s
17/11/07 15:34:44 INFO DAGScheduler: Job 0 finished: reduce at sparkPi.scala:17, took 12.553598 s
Pi is roughly 3.15
17/11/07 15:34:44 INFO SparkUI: Stopped Spark web UI at http://172.20.107.151:4040
17/11/07 15:34:44 INFO SparkDeploySchedulerBackend: Shutting down all executors
17/11/07 15:34:44 INFO SparkDeploySchedulerBackend: Asking each executor to shut down
17/11/07 15:34:44 INFO MapOutputTrackerMasterEndpoint: MapOutputTrackerMasterEndpoint stopped!
17/11/07 15:34:44 INFO MemoryStore: MemoryStore cleared
17/11/07 15:34:44 INFO BlockManager: BlockManager stopped
17/11/07 15:34:44 INFO BlockManagerMaster: BlockManagerMaster stopped
17/11/07 15:34:44 INFO OutputCommitCoordinator$OutputCommitCoordinatorEndpoint: OutputCommitCoordinator stopped!
17/11/07 15:34:44 INFO SparkContext: Successfully stopped SparkContext
17/11/07 15:34:44 INFO RemoteActorRefProvider$RemotingTerminator: Shutting down remote daemon.
17/11/07 15:34:44 INFO RemoteActorRefProvider$RemotingTerminator: Remote daemon shut down; proceeding with flushing remote transports.
17/11/07 15:34:44 INFO ShutdownHookManager: Shutdown hook called
17/11/07 15:34:44 INFO ShutdownHookManager: Deleting directory C:\Users\xinfang\AppData\Local\Temp\spark-150f8c4e-c5df-4254-a9f0-a8158b4caff0\httpd-b0aaa30f-cd92-4fbd-b064-6284fa604359
17/11/07 15:34:44 INFO ShutdownHookManager: Deleting directory C:\Users\xinfang\AppData\Local\Temp\spark-150f8c4e-c5df-4254-a9f0-a8158b4caff0 Process finished with exit code 0
Spark记录-Spark作业调试的更多相关文章
- Spark记录-spark编程介绍
Spark核心编程 Spark 核心是整个项目的基础.它提供了分布式任务调度,调度和基本的 I/O 功能.Spark 使用一种称为RDD(弹性分布式数据集)一个专门的基础数据结构,是整个机器分区数据的 ...
- Spark记录-Spark性能优化解决方案
Spark性能优化的10大问题及其解决方案 问题1:reduce task数目不合适解决方式:需根据实际情况调节默认配置,调整方式是修改参数spark.default.parallelism.通常,r ...
- Spark记录-spark介绍
Apache Spark是一个集群计算设计的快速计算.它是建立在Hadoop MapReduce之上,它扩展了 MapReduce 模式,有效地使用更多类型的计算,其中包括交互式查询和流处理.这是一个 ...
- Spark记录-Spark On YARN内存分配（转载）
Spark On YARN内存分配(转载) 说明 按照Spark应用程序中的driver分布方式不同,Spark on YARN有两种模式: yarn-client模式.yarn-cluster模式. ...
- Spark记录-Spark性能优化（开发、资源、数据、shuffle）
开发调优篇 原则一:避免创建重复的RDD 通常来说,我们在开发一个Spark作业时,首先是基于某个数据源(比如Hive表或HDFS文件)创建一个初始的RDD:接着对这个RDD执行某个算子操作,然后得到 ...
- Spark记录-Spark on Yarn框架
一.客户端进行操作 1.根据yarnConf来初始化yarnClient,并启动yarnClient2.创建客户端Application,并获取Application的ID,进一步判断集群中的资源是否 ...
- Spark记录-Spark on mesos配置
1.安装mesos #用centos6的源yum安装 # rpm -Uvh http://repos.mesosphere.io/el/6/noarch/RPMS/mesosphere-el-repo ...
- Spark记录-spark与storm比对与选型（转载）
大数据实时处理平台市场上产品众多,本文着重讨论spark与storm的比对,最后结合适用场景进行选型. 一.spark与storm的比较 比较点 Storm Spark Streaming 实时计算模 ...
- Spark记录-spark报错Unable to load native-hadoop library for your platform
解决方案一: #cp $HADOOP_HOME/lib/native/libhadoop.so $JAVA_HOME/jre/lib/amd64 #源码编译snappy---./configure ...
随机推荐
- Markdown 入门指南
导语: Markdown是一种轻量级的标记语言,语法简单,学习成本不算太高,但确实可以让你专注于文字,不用太分心与排版等等. Markdown 官方文档 这里可以看到官方的Markdown语法规则: ...
- git 创建标签和删除标签
创建标签 在Git中打标签非常简单,首先,切换到需要打标签的分支上: $ git branch * dev master $ git checkout master Switched to branc ...
- 关于UNITY学习，给新生建议
没有不可能,只有不努力. 本人自学UNITY,实力不敢称最好,但绝对不是小白,自己独立做出过游戏,AR.(用C#) 1. 导入模型一定要注意坐标,否则会很麻烦.本人因为这个吃了很多盐 2. 学unit ...
- Istio 流量治理功能原理与实战
一.负载均衡算法原理与实战 负载均衡算法(load balancing algorithm),定义了几种基本的流量分发方式,在Istio中共有4种标准负载均衡算法. •Round_Robin: 轮询算 ...
- 微软职位内部推荐-Senior Software Engineer-Eco
微软近期Open的职位: The MOD Ecosystem team is dedicated to expanding the reach and value of Office by enabl ...
- Arcengine效率探究之一——属性的读取(转载)
http://blog.csdn.net/lk103852503/article/details/6566652 在写一个对属性表的统计函数时,发现执行速度奇慢无比,百思不得其解,其实算法并不复杂,后 ...
- 【MOOC EXP】Linux内核分析实验五报告
程涵 原创博客 <Linux内核分析>MOOC课程http://mooc.study.163.com/course/USTC-1000029000 分析system_call中断处理过程 ...
- 第一个Sprint冲刺总结（事后诸葛亮及团队贡献分）
第一个Sprint冲刺总结(事后诸葛亮及团队贡献分) 组员:欧其锋 廖焯燊 林海信 何武鹏 第一阶段的最终燃尽图如下: 2.事后诸葛亮: 3.团队贡献分: 欧其锋:22 林海信:21 何武鹏:19 ...
- Beta阶段冲刺-2
一. 每日会议 1. 照片 2. 昨日完成工作 3. 今日完成工作 4. 工作中遇到的困难 杨晨露:突然就没有紧迫感了,很烦 戴志斌:一些遗漏的点有点多,解决都不难,就是琐碎 游舒婷:主题风格不好确定 ...
- wia驱动扫描仪
.net wia驱动扫描仪 通过各种途径,将当前比较流行的驱动扫描仪封装成了一个简单实用的class,调用扫描仪时,只需要重新创建个对象即可,代码如下: using System;using Syst ...