spark单机模式简单搭建

待安装列表
hadoop
hive
scala
spark
一.环境变量配置：
~/.bash_profile
PATH=$PATH:$HOME/bin

export PATH

JAVA_HOME=/usr/local/jdk
export SCALA_HOME=/usr/local/scala
export SPARK_HOME=/usr/local/spark
export PATH=.:$JAVA_HOME/bin:$SCALA_HOME/bin:$PATH

HADOOP_HOME=/usr/local/hadoop
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_CONF_DIR=$HADOOP_HOME/etc/hadoop
export HDFS_CONF_DIR=$HADOOP_HOME/etc/hadoop
export YARN_CONF_DIR=$HADOOP_HOME/etc/hadoop
PATH=$HADOOP_HOME/bin:$HADOOP_HOME/sbin:$PATH
export HADOOP_HOME PATH

HIVE_HOME=/usr/local/hive
PATH=$HIVE_HOME/bin:$PATH
export HIVE_HOME PATH

二.hadoop 安装搭建
1.配置ssh互信
ssh-keygen -t dsa -P '' -f ~/.ssh/id_dsa
cat ~/.ssh/id_dsa.pub >> ~/.ssh/authorized_keys
chmod 700 ~/.ssh
chmod 600 ~/.ssh/authorized_keys

2.修改hostname 为yul32 vi/etc/hosts vi /etc/sysconfig/network
（3.修改hadoop-env.sh
export JAVA_HOME=/usr/local/jdk）

(4.修改core-site.xml)
<property>
<name>fs.defaultFS</name>
<value>hdfs://yul32:9000</value>
</property>

(5.修改hdfs-site.xml) （/usr/hadoop-2.3.0/etc/hadoop)
<property>
<name>dfs.namenode.name.dir</name>
<value>/usr/local/hadoop/dfs/name</value>
</property>
<property>
<name>dfs.datanode.data.dir</name>
<value>/usr/local/hadoop/dfs/data</value>
</property>
<property>
<name>dfs.replication</name>
<value>1</value>
</property>
<property>
<name>dfs.permission</name>
<value>false</value>
</property>

(5.修改mapred-site.xml) (mapred-site.xml.template ?) （/usr/hadoop-2.3.0/etc/hadoop)
<property>
<name>mapreduce.cluster.temp.dir</name>
<value></value>
<description>No description</description>
<final>true</final>
</property>
<property>
<name>mapreduce.cluster.local.dir</name>
<value></value>
<description>No description</description>
<final>true</final>
</property>

（6.修改yarn-site.xml） （/usr/hadoop-2.3.0/etc/hadoop)
<property>
<name>mapreduce.framework.name</name>
<value>yarn</value>
</property>
<property>
<name>yarn.nodemanager.aux-services</name>
<value>mapreduce_shuffle</value>
</property>

7.修改slaves.sh ？？
yul32
8.namenode format
输入命令hadoop namenode –format
9.启动hadoop
cd hadoop/sbin start-all.sh

ifup ifdown

三.spark 搭建
(/usr/spark-1.1.0-bin-hadoop2.3/conf) <报错 readonly>
1.修改conf/slaves
yul32

(2.修改spark-env.sh (/usr/spark-1.1.0-bin-hadoop2.3/conf))
export SCALA_HOME=/usr/local/scala
export JAVA_HOME=/usr/local/jdk
export SPARK_MASTER_IP=yul32
export SPARK_WORKER_CORES=1
export SPARK_WORKER_INSTANCES=1
export SPARK_MASTER_PORT=7077
export SPARK_WORKER_MEMORY=1g
export MASTER=spark://${SPARK_MASTER_IP}:${SPARK_MASTER_PORT}

3.启动spark
./sbin/start-all.sh
4.运行spark例子
./bin/run-example org.apache.spark.examples.JavaSparkPi 2
5.运行scala-shell
./bin/spark-shell --master local[2]
6.python
./bin/pyspark --master local[2]
7.启动spark sql
./sbin/start-thriftserver.sh(./sbin/start-thriftserver.sh --master yarn)
在后台运行命令： nohup ./sbin/start-thriftserver.sh --master yarn &
查看后台运行进程命令： jobs -l
启动后jps 中包含 SparkSubmit
8.spark sql 客户端连接
./bin/beeline -u jdbc:hive2://yul32:10000 -n spark -p spark
说明 -n 用户名 -p 密码
或者输入命令 ./bin/beeline
beeline> !connect jdbc:hive2://yul32:10000
用户名
密码

上传文件，创建表；
1.hadoop fs -ls /user/ocdc/coc
hadoop fs -put /home/ocdc/CI_CUSER_20141104112305197.csv /user/ocdc/coc
2.shark> create table CI_CUSER_20141104112305196( PRODUCT_NO string)ROW FORMAT DELIMITED FIELDS TERMINATED BY ',' LINES TERMINATED BY '\n' ;
shark> load data inpath '/user/ocdc/coc/CI_CUSER_20141104112305197.csv' into table CI_CUSER_20141104112305196;
shark> create table CI_CUSER_20141104112305197( PRODUCT_NO string)ROW FORMAT DELIMITED FIELDS TERMINATED BY ',' LINES TERMINATED BY '\n' stored as rcfile;
shark> insert into table CI_CUSER_20141104112305197 select * from CI_CUSER_20141104112305196;

四.hive 安装配置（非必须）
1.修改hive-env.sh
export HADOOP_HOME=/usr/local/hadoop
export HIVE_CONF_DIR=/usr/local/hive/conf
2.hive 远程服务 (端口号10000) 启动方式
hive --service hiveserver &
连接Hive JDBC URL：jdbc:hive://ip:10000/default （Hive默认端口：10000 默认数据库名：default）
hive数据仓库的位置
hive/conf/hive-site.xml
hive.metastroe.warehouse.dir：数据仓库的位置，默认是/user/hive/warehouse；
<property>
<name>hive.metastore.warehouse.dir</name>
<value>/user/hive/warehouse</value>
<description>location of default database for the warehouse</description>
</property>

shark　jdbc 连接
1.查看SharServer 是否启动
[ocdc@oc98 conf]$ jps
7983 Kafka
8803 SharkCliDriver
7377 ResourceManager
16894 SharkServer
6925 JournalNode
12601 CoarseGrainedExecutorBackend
17056 CoarseGrainedExecutorBackend
18424 Jps
14486 Master
4108 QuorumPeerMain
23408 HRegionServer
17655 RunJar
6727 DataNode
7132 DFSZKFailoverController
7510 NodeManager
12553 WorkerLauncher
6614 NameNode
23268 HMaster
12415 SharkCliDriver
2.查看SharkServer端口
[ocdc@oc98 conf]$ netstat -apn | grep 16894
tcp 0 0 ::ffff:10.1.251.98:57902 :::* LISTEN 16894/java
tcp 0 0 :::52309 :::* LISTEN 16894/java
tcp 0 0 :::9977 :::* LISTEN 16894/java
tcp 0 0 :::41222 :::* LISTEN 16894/java
tcp 0 0 :::4040 :::* LISTEN 16894/java
tcp 0 0 :::45192 :::* LISTEN 16894/java
tcp 0 0 ::ffff:10.1.251.98:35289 ::ffff:10.1.251.98:3306 ESTABLISHED 16894/java
tcp 0 0 ::ffff:10.1.251.98:57902 ::ffff:10.1.251.104:41877 ESTABLISHED 16894/java
tcp 0 0 ::ffff:10.1.251.98:57902 ::ffff:10.1.251.98:53176 ESTABLISHED 16894/java
tcp 0 0 ::ffff:10.1.251.98:9977 ::ffff:10.1.48.20:60586 ESTABLISHED 16894/java
tcp 1 0 ::ffff:10.1.251.98:57320 ::ffff:10.1.251.98:50012 CLOSE_WAIT 16894/java
tcp 0 0 ::ffff:10.1.251.98:9977 ::ffff:10.1.48.20:59756 ESTABLISHED 16894/java
tcp 0 0 ::ffff:10.1.251.98:57902 ::ffff:10.1.251.101:50160 ESTABLISHED 16894/java
tcp 0 0 ::ffff:10.1.251.98:57902 ::ffff:10.1.251.98:53172 ESTABLISHED 16894/java
tcp 0 0 ::ffff:10.1.251.98:57902 ::ffff:10.1.251.101:50159 ESTABLISHED 16894/java
unix 2 [ ] STREAM CONNECTED 8889813 16894/java
unix 2 [ ] STREAM CONNECTED 8889793 16894/java
端口为9977 即shark服务启动端口 nohup ./bin/shark –-service sharkserver –-p 9977 &

3.jdbc连接
public class SharkTest {
private static String driverName = "org.apache.hadoop.hive.jdbc.HiveDriver";

public static void main(String args[]) throws SQLException {
try {
Class.forName(driverName);
} catch (ClassNotFoundException e) {

e.printStackTrace();

System.exit(1);
}
Connection con = DriverManager.getConnection(
"jdbc:hive://10.1.251.98:9977/default", "ocdc", "asiainfo");
Statement stmt = con.createStatement();
ResultSet res = stmt.executeQuery("select * from src ");
if (res.next()) {
System.out.println(res.getString(1)+ " " + res.getString(2));
}
}
}

Sparksql Sever启动命令
./sbin/start-thriftserver.sh --master yarn
客户端连接
./bin/beeline -u jdbc:hive2://10.1.251.98:10000 -n ocdc -p asiainfo
让配置文件立即生效
source /etc/profile

依赖jar包
hive-common-0.8.1.jar
hive-exec-0.8.1.jar
hive-jdbc-0.8.1.jar
hive-metastore-0.8.1.jar
hive-service-0.8.1.jar
libfb303.jar
slf4j-api-1.4.3.jar
slf4j-log4j12-1.4.3.jar
httpclient-4.2.5.jar
hadoop-common-2.3.0.jar

wq 是保存
i 是编辑
q 是强制退出

（赋权）
1、到你想要赋权的文件夹路径下
2、使用 chmod 777 slaves（为这个文件赋权）
3、赋权给ysy(用户）写的权限 chown -R ysy132:ysy132 dfs

切换用户 使用 su - ysy

(hadoop报错日志位置为 /usr/hadoop-2.3.0/logs)
tail -500 hadoop-root-namenode-ysy0915.log 查看500行报错日志

(启动hadoop）
在hadoop-2.3.0目录下 输入./sbin/start-dfs.sh
停止 .sbin/stop-dfs.sh ./sbin/stop-dfs.sh

查看启动的节点 jps
(回退到上一个目录下)

eg:spark SQL
(select a+b from table)
val a:Int = inputRow.getInt(0)
val b:Int = inputRow.getInt(1)
val result:Int = a + b
resultRow.setInt(0,result)

def generateCode(e: Expression): Tree = e match{
case Attribute(ordinal) =>
q"inputRow.getInt($ordinal)"
case Add(left,right)=>
q"""
{
val leftResult = ${generateCode(left)}
val rightResult = ${generateCode(right)}
leftResult + rightResult
}
"""
}