spark单机模式简单搭建

短命女 2022-03-27 12:35 526阅读 0赞

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  
\}  
"""  
\}