标签:var table 元数据库 use export roo 查看 jdbc term
一、准备数据
# 在我的mysql下创建数据库和表,并插入几条数据 mysql> create database if not exists student default character set utf8 collate utf8_general_ci; mysql> use student; mysql> create table if not exists stu_info( id int(10) primary key not null auto_increment, name varchar(20) not null) default character set utf8 collate utf8_general_ci; mysql> insert into stu_info(name) values("李建"); mysql> insert into stu_info(name) values("张明"); mysql> insert into stu_info(name) values("赵兴"); mysql> insert into stu_info(name) values("陈琦"); mysql> insert into stu_info(name) values("刘铭"); mysql> select id,name from stu_info; +----+--------+ | id | name | +----+--------+ | 1 | 李建 | | 2 | 张明 | | 3 | 赵兴 | | 4 | 陈琦 | | 5 | 刘铭 | +----+--------+ 5 rows in set (0.00 sec)
二、使用sqoop将mysql中的这张表导入到hdfs上
bin/sqoop import --connect jdbc:mysql://10.0.0.108:3306/student --username root --password root --table stu_info --target-dir /student --num-mappers 1 --fields-terminated-by ‘\t‘
三、使用sqoop将mysql中的这张表导入到hive
方式一、 1. 在hive中创建数据库和表 create database if not exists student; create table if not exists stu_info(id int,name string) row format delimited fields terminated by ‘\t‘; 2. bin/sqoop import --connect jdbc:mysql://hadoop09-linux-01.ibeifeng.com:3306/student --username root --password root --table stu_info --delete-target-dir --target-dir /user/hive/warehouse/student.db/stu_info --hive-import --hive-database student --hive-table stu_info --hive-overwrite --num-mappers 1 --fields-terminated-by ‘\t‘ 方式二、 1. 使用sqoop create-hive-table,但必须创建出自定义数据库,否则目标路径将是元数据库 2. bin/sqoop create-hive-table 、 --connect jdbc:mysql://10.0.0.108:3306/student 、 --username root --password root --table stu_info --hive-table student.stu_info 3. bin/sqoop import --connect jdbc:mysql://10.0.0.108:3306/student --username root --password root --table stu_info --hive-import --hive-database student --hive-table stu_info --hive-overwrite --num-mappers 1 --fields-terminated-by ‘\t‘ --delete-target-dir --target-dir /user/hive/warehouse/student.db/stu_info 4. 在hive中查询会发现数据全部为NULL 但是从hdfs上查看却是正常的,确定hive无法解析数据,定位在分隔符问题 使用--fields-terminated-by ‘\001‘ 即可 # \001就是ctrl+A,hive默认分隔符,mysql默认分隔符为","
五、从hdfs或hive导出数据到mysql表
1. 在mysql上准备好数据库和表 2. 数据库我就直接使用student数据库 create table if not exists stu_info_export like stu_info; 3. 根据hdfs/hive表数据分隔符为主 bin/sqoop export --connect jdbc:mysql://10.0.0.108/student --username root --password root --table stu_info_export --export-dir /user/hive/warehouse/student.db/stu_info --num-mappers 1 --input-fields-terminated-by ‘\001‘
标签:var table 元数据库 use export roo 查看 jdbc term
原文地址:http://www.cnblogs.com/eRrsr/p/6050902.html