sqoop 导出mysql，oracle

sqoop  mysql 导入，导出
1.
安装（前提hadoop启动）


[hadoop@h91 ~]$ tar -zxvf sqoop-1.3.0-cdh3u5.tar.gz 
[hadoop@h91 hadoop-0.20.2-cdh3u5]$ cp hadoop-core-0.20.2-cdh3u5.jar /home/hadoop/sqoop-1.3.0-cdh3u5/lib/


[hadoop@h91 ~]$ cp ojdbc6.jar sqoop-1.3.0-cdh3u5/lib/


[hadoop@h91 ~]$ vi .bash_profile 
添加 
export SQOOP_HOME=/home/hadoop/sqoop-1.3.0-cdh3u5


[hadoop@h91 ~]$ source .bash_profile 


2.


[hadoop@h91 ~]$ cd sqoop-1.3.0-cdh3u5/bin/


[hadoop@h91 bin]$ vi configure-sqoop 
注释掉hbase和zookeeper检查
## Moved to be a runtime check in sqoop.
#if [ ! -d "${HBASE_HOME}" ]; then
#  echo "Warning: $HBASE_HOME does not exist! HBase imports will fail."
#  echo 'Please set $HBASE_HOME to the root of your HBase installation.'
#fi




3.mysql 授权


mysql> insert into mysql.user(Host,User,Password) values("hadoop1","hive",password("mysql"));
mysql> flush privileges;
mysql> grant all privileges on *.* to 'hive'@'%' identified by 'mysql' with grant option;
mysql> flush privileges;


mysql> use test;
mysql> create table sss (id int,name varchar(10));


mysql> insert into sss values(1,'zs');
mysql> insert into sss values(2,'ls');








4.测试sqoop能否连接上mysql
[hadoop@h91 mysql-connector-java-5.0.7]$ cp mysql-connector-java-5.0.7-bin.jar /home/hadoop/sqoop-1.3.0-cdh3u5/lib/


[hadoop@h91 sqoop-1.3.0-cdh3u5]$ bin/sqoop list-tables --connect jdbc:mysql://192.168.159.135:3306/test --username hive --password mysql
（显示有sss表）


5.将mysql中的sqoop用户下sss 导入到HDFS中
[hadoop@h91 sqoop-1.3.0-cdh3u5]$ bin/sqoop import --connect jdbc:mysql://192.168.159.135:3306/test --username hive --password mysql --table sss -m 1
（-m 为并行  默认并行度为4）


[hadoop@h91 hadoop-0.20.2-cdh3u5]$ bin/hadoop fs -ls
多出个sss目录
[hadoop@h91 hadoop-0.20.2-cdh3u5]$ bin/hadoop fs -ls /user/hadoop/sss
[hadoop@h91 hadoop-0.20.2-cdh3u5]$ bin/hadoop fs -cat /user/hadoop/sss/part-m-00000
看到 sss表内容
1,zs
2,ls


6.从HDFS导入到mysql中


mysql> delete from sss;


[hadoop@h91 sqoop-1.3.0-cdh3u5]$ bin/sqoop export --connect jdbc:mysql://192.168.159.135:3306/test --username hive --password mysql --table sss --export-dir hdfs://hadoop1:9000/user/hadoop/sss/part-m-00000


[root@o222 ~]# mysql -usqoop -p
mysql> use test
mysql> select * from sss;
表中的数据 又 回来了




---------------------------------------------------------------
增量抽取 mysql数据 到HDFS中
类型1（字段增长）
bin/sqoop import --connect jdbc:mysql://192.168.159.135:3306/test --username hive --password mysql --table sss -m 1 --target-dir /user/hadoop/a --check-column id --incremental append --last-value 3




类型2（时间增长）
mysql> create table s2 (id int,sj timestamp not null default current_timestamp);
mysql> insert into s2 (id)values(123);
mysql> insert into s2 (id)values(321);
mysql> select * from s2;
+------+---------------------+
| id   | sj                  |
+------+---------------------+
|  123 | 2015-11-20 22:34:09 | 
|  321 | 2015-11-20 22:34:23 | 
+------+---------------------+


bin/sqoop import --connect jdbc:mysql://192.168.159.135:3306/test --username hive --password mysql --table s2 -m 1 --target-dir /user/hadoop/abcd --incremental lastmodified --check-column sj --last-value '2016-02-24 16:40:54' 
结果：只有id为321的行更新了
---------------------------------------------------------
配置 sqoop导入的 
[hadoop@h91 sqoop-1.3.0-cdh3u5]$ bin/sqoop export --connect jdbc:mysql://192.168.159.135:3306/test --username hive --password mysql --table qqq --export-dir hdfs://hadoop1:9000/user/hadoop/qqq.txt --input-fields-terminated-by '\t'


****--input-fields-terminated-by '\t'    
 声明分隔符*******




----------------------------------------------------------
sqoop eval工具：
sqoop下 使用sql语句对 关系型数据库进行操作




[hadoop@h91 sqoop-1.3.0-cdh3u5]$ bin/sqoop eval --connect jdbc:mysql://192.168.159.135:3306/test --username hive --password mysql --query "select * from sss"


[hadoop@h91 sqoop-1.3.0-cdh3u5]$ bin/sqoop eval --connect jdbc:mysql://192.168.159.135:3306/test --username hive --password mysql --query "insert into sss values(3,'ww')"


==============================================================
sqoop hive
mysql 导入到 hive中


mysql> select * from sss;
+------+------+
| id   | name |
+------+------+
|    1 | zs   | 
|    2 | ls   | 
|    3 | ww   | 
|   10 | haha | 
+------+------+




hive> create table tb1(id int,name string)
     row format delimited
     fields terminated by ',';


**** sqoop 默认的分隔符为"," ***********




[hadoop@h101 sqoop-1.3.0-cdh3u5]$ bin/sqoop import --connect jdbc:mysql://192.168.8.101/test --username sqoop --password sqoop --table sss  --hive-import -m 1 --hive-table tb1 --fields-terminated-by ',' 


hive> select * from tb1;










============================================================
sqoop oracle


1.


[hadoop@h91 ~]$ cp ojdbc6.jar sqoop-1.3.0-cdh3u5/lib/


 测试sqoop 连接oracle
[hadoop@h91 sqoop-1.3.0-cdh3u5]$ bin/sqoop list-tables --connect jdbc:oracle:thin:@192.168.8.222:1521:TEST --username scott --password abc


2.
导出到HDFS中 
[hadoop@h91 sqoop-1.3.0-cdh3u5]$ bin/sqoop import --connect jdbc:oracle:thin:@192.168.8.222:1521:TEST --username SCOTT --password abc --verbose -m 1 --table S1
（表名字 和 用户名要大写 ）


HDFS 中查看
[hadoop@h91 hadoop-0.20.2-cdh3u5]$ bin/hadoop fs -cat /user/hadoop/S1/part-m-00000
101,zhangsan
102,lisi