hadoop生态搭建（3节点）-17.sqoop配置_单节点

时间：2022-01-20 08:46:40

# ==================================================================安装 sqoop

tar -zxvf ~/sqoop-1.4.7.bin__hadoop-2.6.0.tar.gz

mv ~/sqoop-1.4.7.bin__hadoop-2.6.0 /usr/local/sqoop-1.4.7

# 环境变量

# ==================================================================node1

vi /etc/profile

# 在export PATH USER LOGNAME MAIL HOSTNAME HISTSIZE HISTCONTROL下添加

export JAVA_HOME=/usr/java/jdk1.8.0_111

export JRE_HOME=/usr/java/jdk1.8.0_111/jre

export ZOOKEEPER_HOME=/usr/local/zookeeper-3.4.12

export HADOOP_HOME=/usr/local/hadoop-2.7.6

export MYSQL_HOME=/usr/local/mysql

export HBASE_HOME=/usr/local/hbase-1.2.4

export HIVE_HOME=/usr/local/hive-2.1.1

export SCALA_HOME=/usr/local/scala-2.12.4

export KAFKA_HOME=/usr/local/kafka_2.12-0.10.2.1

export FLUME_HOME=/usr/local/flume-1.8.0

export SPARK_HOME=/usr/local/spark-2.3.0

export STORM_HOME=/usr/local/storm-1.1.0

export REDIS_HOME=/usr/local/redis-4.0.2

export ERLANG_HOME=/usr/local/erlang

export RABBITMQ_HOME=/usr/local/rabbitmq_server-3.7.5

export MONGODB_HOME=/usr/local/mongodb-3.4.5

export NGINX_HOME=/usr/local/nginx

export CATALINA_BASE=/usr/local/tomcat

export CATALINA_HOME=/usr/local/tomcat

export TOMCAT_HOME=/usr/local/tomcat

export KEEPALIVED_HOME=/usr/local/keepalived

export ELASTICSEARCH_HOME=/usr/local/elasticsearch-6.2.4

export LOGSTASH_HOME=/usr/local/logstash-6.2.4

export KIBANA_HOME=/usr/local/kibana-6.2.4

export SQOOP_HOME=/usr/local/sqoop-1.4.7

export PATH=$PATH:$JAVA_HOME/bin:$JAVA_HOME/jre/bin:$ZOOKEEPER_HOME/bin:$HADOOP_HOME/bin:$HADOOP_HOME/sbin:$MYSQL_HOME/bin:$HBASE_HOME/bin:$HIVE_HOME/bin:$SCALA_HOME/bin:$KAFKA_HOME/bin:$FLUME_HOME/bin:$SPARK_HOME/bin:$STORM_HOME/bin:$REDIS_HOME/bin:$ERLANG_HOME/bin:$RABBITMQ_HOME/ebin:$RABBITMQ_HOME/sbin:$MONGODB_HOME/bin:$NGINX_HOME/sbin:$CATALINA_HOME/bin:$KEEPALIVED_HOME/sbin:$ELASTICSEARCH_HOME/bin:$LOGSTASH_HOME/bin:$KIBANA_HOME/bin:$SQOOP_HOME/bin

export CLASSPATH=.:$JAVA_HOME/lib/dt.jar:$JAVA_HOME/lib/tools.jar

export HADOOP_INSTALL=$HADOOP_HOME

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
# 使环境变量生效

source /etc/profile

# 查看配置结果

echo $SQOOP_HOME
cp -a $SQOOP_HOME/conf/sqoop-env-template.sh $SQOOP_HOME/conf/sqoop-env.sh

vi $SQOOP_HOME/conf/sqoop-env.sh 

#Set path to where bin/hadoop is available

export HADOOP_COMMON_HOME=${HADOOP_HOME}

#Set path to where hadoop-*-core.jar is available

export HADOOP_MAPRED_HOME=${HADOOP_HOME}

#set the path to where bin/hbase is available

#export HBASE_HOME=${HBASE_HOME}

#Set the path to where bin/hive is available

export HIVE_HOME=${HIVE_HOME}

#Set the path for where zookeper config dir is

#export ZOOCFGDIR=

cp -a ~/mysql-connector-java-5.1.46.jar $SQOOP_HOME/lib/

cp -a $HIVE_HOME/lib/hive-exec-2.1.1.jar $SQOOP_HOME/lib/

sqoop-version
mysql -u root -p

> create database sqooptest character set utf8 ;

> create user 'sqoop'@'%' identified by 'Sqoop-123';

> grant all privileges on *.* to 'sqoop'@'%';

> flush privileges;

> show databases;

> quit;

# 用户 sqoop 登录 mysql

mysql -u sqoop -p

Enter password: Sqoop-123

> use sqooptest;

> create table emp(id INT NOT NULL PRIMARY KEY, name VARCHAR(20), age INT);

> insert into emp(id, name, age)values(1, 'zhangsan', 11);

  insert into emp(id, name, age)values(2, 'lisi', 12);

  insert into emp(id, name, age)values(3, '王五', 13);

> create table emp_add(id INT NOT NULL PRIMARY KEY, name VARCHAR(20), age INT, sex VARCHAR(20));

> insert into emp_add(id, name, age, sex)values(1, 'zhangsan', 11, '男');

  insert into emp_add(id, name, age, sex)values(2, 'lisi', 12, '男');

  insert into emp_add(id, name, age, sex)values(3, '王五', 13, '女');

  insert into emp_add(id, name, age, sex)values(4,'liuliu', 11, '男');

> show tables;

> select * from emp;

  select * from emp_add;

> quit;

# 启动 hadoop

# ==================================================================node1 node2 node3

zkServer.sh start

# ==================================================================node1

# 启动hadoop所有进程

$HADOOP_HOME/sbin/start-all.sh

$HADOOP_HOME/sbin/hadoop-daemon.sh start zkfc

# ==================================================================node2

$HADOOP_HOME/sbin/yarn-daemon.sh start resourcemanager

$HADOOP_HOME/sbin/hadoop-daemon.sh start zkfc

hadoop dfsadmin -safemode get

# 命令强制离开

# hadoop dfsadmin -safemode leave

# 网页访问

# http://node1:50070?user.name=hadoop

# http://node2:50070?user.name=hadoop

# http://node1:8088?user.name=hadoop/cluster/nodes

# 导入表数据到HDFS

# ==================================================================node1

sqoop import \

  --connect jdbc:mysql://node1:3306/sqooptest \

  --username sqoop \

  --password Sqoop-123 \

  --table emp \

  --m 1

# 如果包下面的错误请将 $HADOOP_HOME/etc/hadoop/yarn-site.xml 文件进行调整
# ERROR tool.ImportTool: Import failed: java.io.IOException: org.apache.hadoop.yarn.exceptions.InvalidResourceRequestException:
# Invalid resource request, requested memory < 0, or requested memory > max configured, requestedMemory=1536, maxMemory=1024

# ==================================================================node1 node2 node3

vi $HADOOP_HOME/etc/hadoop/yarn-site.xml

<property>

	<name>yarn.nodemanager.resource.memory-mb</name>

	<value>2048</value>

</property>

<property>

	<name>yarn.scheduler.maximum-allocation-mb</name>

	<value>2048</value>

</property>

# 重启Yarn

# ==================================================================node1

$HADOOP_HOME/sbin/start-yarn.sh
# 导入表数据到HDFS

sqoop import \

  --connect jdbc:mysql://node1:3306/sqooptest \

  --username sqoop \

  --password Sqoop-123 \

  --table emp \

  --m 1

# 查看导入的数据

hadoop fs -ls /user/root/emp

hadoop fs -cat /user/root/emp/part-m-00000

# 导入表到HDFS指定目录

sqoop import --connect jdbc:mysql://node1:3306/sqooptest \

  --username sqoop --password Sqoop-123 \

  --target-dir /sqooptest/table_emp/queryresult \

  --table emp --num-mappers 1

# 查看导入的数据

hadoop fs -ls /sqooptest/table_emp/queryresult

hadoop fs -cat /sqooptest/table_emp/queryresult/part-m-00000

# 导入关系表到HIVE

sqoop import --connect jdbc:mysql://node1:3306/sqooptest \

  --username sqoop --password Sqoop-123 \

  --table emp --hive-import \

  --num-mappers 1

# 如报下面的错误，请先删除 /user/root/emp

# ERROR tool.ImportTool: Import failed: org.apache.hadoop.mapred.FileAlreadyExistsException: Output directory hdfs://appcluster/user/root/emp already exists

hadoop fs -rmr /user/root/emp

# 重新导入关系表到HIVE

sqoop import --connect jdbc:mysql://node1:3306/sqooptest \

  --username sqoop --password Sqoop-123 \

  --table emp --hive-import \

  --num-mappers 1

# 启动 hive

hive
# 查看导入的数据

> show tables;

> select * from emp;

# 导入表到HIVE指定库指定表

sqoop import --connect jdbc:mysql://node1:3306/sqooptest \

  --username sqoop --password Sqoop-123 \

  --table emp \

  --delete-target-dir \

  --fields-terminated-by '\t' \

  --hive-import \

  --hive-database sqooptest \

  --hive-table hive_emp \

  --num-mappers 1 

# 报错 hive的库sqooptest，必须先建立。否则会报：FAILED: SemanticException [Error 10072]: Database does not exist: sqooptest

> create database sqooptest;

> show databases;

# 导入表到HIVE指定库指定表

sqoop import --connect jdbc:mysql://node1:3306/sqooptest \

  --username sqoop --password Sqoop-123 \

  --table emp \

  --delete-target-dir \

  --fields-terminated-by '\t' \

  --hive-import \

  --hive-database sqooptest \

  --hive-table hive_emp \

  --num-mappers 1

> use sqooptest;

> show tables;

> select * from hive_emp;

# 导入表数据子集 where子句的导入

sqoop import --connect jdbc:mysql://node1:3306/sqooptest \

  --username sqoop --password Sqoop-123 \

  --table emp_add \

  --where "age =11" \

  --target-dir /sqooptest/table_emp/queryresult2 \

  --num-mappers 1

# 查看导入的数据

hadoop fs -ls /sqooptest/table_emp/queryresult2

hadoop fs -cat /sqooptest/table_emp/queryresult2/part-m-00000

# query按需导入

sqoop import --connect jdbc:mysql://node1:3306/sqooptest \

  --username sqoop --password Sqoop-123 \

  --query 'select id,name,age from emp WHERE  id>=2 and $CONDITIONS' \

  --split-by id \

  --fields-terminated-by '\t' \

  --target-dir /sqooptest/table_emp/queryresult3 \

  --num-mappers 1

# 查看导入的数据

hadoop fs -cat /sqooptest/table_emp/queryresult3/part-m-00000

# 增量导入

sqoop import --connect jdbc:mysql://node1:3306/sqooptest \

  --username sqoop --password Sqoop-123 \

  --table emp \

  --incremental append \

  --check-column id \

  --last-value 2 \

  --fields-terminated-by '\t' \

  --target-dir /sqooptest/table_emp/queryresult4 \

  --num-mappers 1

# 查看导入的数据

hadoop fs -ls /sqooptest/table_emp/queryresult4/

hadoop fs -cat /sqooptest/table_emp/queryresult4/part-m-00000

# Sqoop的数据导出

# 查看 hdfs 数据

hadoop fs -ls /sqooptest/table_emp/queryresult

hadoop fs -cat /sqooptest/table_emp/queryresult/part-m-00000

# 1、首先需要手动创建mysql中的目标表

mysql -u sqoop -p

Enter password: Sqoop-123

> use sqooptest;

> CREATE TABLE employee(id INT NOT NULL PRIMARY KEY,name VARCHAR(20),age INT);

> show tables;

> select * from employee;

# 2、然后执行导出命令

sqoop export \

  --connect jdbc:mysql://node1:3306/sqooptest \

  --username sqoop --password Sqoop-123 \

  --table employee \

  --export-dir /sqooptest/table_emp/queryresult/

# 验证表mysql命令行

> select * from employee;

> quit;

shutdown -h now
# sqoop

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