PySpark(一) Hadoop SingleNode部署下Spark on yarn

环境: MacOX系统
1. Java: 8
2. Scala: 2.12.4
3. Hadoop: 2.7.7
4. Spark: 2.4.0

1. 准备工作

1. 安装Java, Scala, 并下载Spark及其相应版本的Hadoop;
2. 编辑~/.zshrc

   export JAVA_HOME=/Library/Java/JavaVirtualMachines/jdk1.8.0_151.jdk/Contents/Home
   export HADOOP_HOME=/Users/dang/work/hadoop/hadoop-2.7.7
   export SCALA_HOME=/Users/dang/work/hadoop/scala-2.12.4
   export SPARK_HOME=/Users/dang/work/hadoop/spark-2.4.0
   export PATH=$PATH:$SCALA_HOME/bin:$SPARK_HOME/bin:$HADOOP_HOME/bin:$HADOOP_HOME/sbin
   export HADOOP_MAPRED_HOME=$HADOOP_HOME
   export HADOOP_COMMON_HOME=$HADOOP_HOME
   export HADOOP_HDFS_HOME=$HADOOP_HOME
   export YARN_HOME=$HADOOP_HOME
   export HADOOP_COMMON_LIB_NATIVE_DIR=$HADOOP_HOME/lib/native
   export HADOOP_OPTS="-Djava.library.path=$HADOOP_HOME/lib"
   export HADOOP_CONF_DIR=$HADOOP_HOME/etc/hadoop
   export JAVA_LIBRARY_PATH=$HADOOP_HOME/lib/native:$JAVA_LIBRARY_PATH

2. 配置并启动Hadoop

1. 配置

1. 编辑$HADOOP_HOME/etc/hadoop/core-site.xml,并添加如下内容:

   <configuration>
   <property>
   <name>fs.defaultFS</name>
   <value>hdfs://localhost:9000</value>
   </property>
   </configuration>

2. 编辑$HADOOP_HOME/etc/hadoop/hdfs-site.xml,并添加如下内容:

   <configuration>
   <property>
   <name>dfs.replication</name>
   <value>1</value>
   </property>
   <property>
   <name>dfs.namenode.name.dir</name>
   <value>file:/Users/dang/work/hadoop/hadoop_data/hdfs/namenode</value>
   </property>
   <property>
   <name>dfs.datanode.data.dir</name>
   <value>file:/Users/dang/work/hadoop/hadoop_data/hdfs/datanode</value>
   </property>
   </configuration>

注意: dfs.namenode.name.dir和dfs.datanode.data.dir目录在Hadoop启动前必须已存在

3. 编辑`$HADOOP_HOME/etc/hadoop/mapred-site.xml``,并添加如下内容:

首先执行cp mapred-site.xml.template mapred-site.xml

<configuration>
<property>
  <name>mapreduce.framework.name</name>
  <value>yarn</value>
</property>
</configuration>

4. 编辑$HADOOP_HOME/etc/hadoop/yarn-site.xml,并添加如下内容:

   <configuration>
   <property>
   <name>yarn.nodemanager.aux-services</name>
   <value>mapreduce_shuffle</value>
   </property>
   <property>
   <name>yarn.nodemanager.aux-services.mapreduce.shuffle.class</name>
   <value>org.apache.hadoop.mapred.ShuffleHandler</value>
   </property>
   <property>
   <name>yarn.nodemanager.pmem-check-enabled</name>
   <value>false</value>
   </property>
   

yarn.nodemanager.vmem-check-enabled false Whether to enable log aggregation yarn.log-aggregation-enable true ``` 5. 编辑`$HADOOP_HOME/etc/hadoop/hadoop-env.sh`,并添加如下内容: ```bash export JAVA_HOME=/Library/Java/JavaVirtualMachines/jdk1.8.0_151.jdk/Contents/Home ```

3. 初始化HDFS

执行如下命令:

hadoop namenode -format

3. 启动/停止

执行如下命令:

# 启动
start-all.sh
## 或者
start-dfs.sh # 先执行
start-yarn.sh # 后执行

# 停止
stop-all.sh
## 或者
stop-yarn.sh # 先执行
stop-dfs.sh # 后执行

2. Spark配置并启动

1. 配置

1. 编辑$SPARK_HOME/conf/spark-env.sh,并添加如下内容:

首先执行 cp spark-env.template spark-env.sh

export JAVA_HOME=/Library/Java/JavaVirtualMachines/jdk1.8.0_151.jdk/Contents/Home
export HADOOP_HOME=/Users/dang/work/hadoop/hadoop-2.7.7
export HADOOP_CONF_DIR=$HADOOP_HOME/etc/hadoop
export SPARK_HOME=/Users/dang/work/hadoop/spark-2.4.0
export SPARK_LOCAL_IP="127.0.0.1"
export SPARK_LIBARY_PATH=.:$JAVA_HOME/lib:$JAVA_HOME/jre/lib:$HADOOP_HOME/lib/native
export LD_LIBRARY_PATH=$HADOOP_HOME/lib/native/:$LD_LIBRARY_PATH

2. 上传Spark Jar包到Hadoop HDFS

   hadoop fs -put -p jars/ /hadoop/spark_jars

3. 编辑$SPARK_HOME/conf/spark-defaults.conf,并添加如下内容:

首先执行 cp spark-defaults.conf.templatespark-defaults.conf

spark.yarn.jars hdfs://localhost:9000/hadoop/spark_jars/*

2.启动

执行如下命令:

pyspark --master yarn --deploy-mode client

4. 遇到的问题:

Exception from container-launch.
Container id: container_e64_1481762217559_27152_01_000002
Exit code: 127

解决方法:

• 设置hadoop-env.sh中的JAVA_HOME
• 设置spark-env.sh
• Hadoop启动之后等几步分钟,让程序完全启动后,再去启动Spark