sqoop操作大全

sqoop介绍

Sqoop依赖与hadoop

       数据的一方，存储在hdfs
       底层的数据传输实现map/reduceyarn 只有map任务
因为官网sqoop没有hadoop2.5对应的版本，要根据hadoop的版本进行编译（好像不用对应版本也可以，不过建议最好对应版本）。所以这里使用CDH，选择cdh对应的sqoop版本。比较稳定。去Cloudera的官网下载相应的发布版本号 http;//archive.cloudera.com/cdh5/

sqoop数据的功能完全可以使用spark代替，基于历史原来很多原来的框架或者平台使用sqoop导出导入数据。

Sqoop： SQL to Hadoop

         场景：数据在RDBMS中，我们如何使用Hive或者Hadoop来进行数据分析呢？

                  1)RDBMS ==> Hadoop

                  2)Hadoop ==> RDBMS

         MapReduce   InputFormat OutputFormat

        

         Sqoop:RDBMS和Hadoop之间的一个桥梁

        

Sqoop 1.x: 1.4.7         ---1.0足够日常工作90%场景使用

         底层是通过MapReduce来实现的，而且是只有map没有reduce的

         ruozedata.person  ===> HDFS

                  jdbc              

                 

Sqoop 2.x: 1.99.7          -----不常用   

RDBMS <==> Hadoop   出发点是Hadoop

导入：RDBMS ==> Hadoop

导出：Hadoop ==> RDBMS

1.1   sqoop框架

1.2   sqoop部署

wget http://archive.cloudera.com/cdh5/cdh/5/sqoop-1.4.6-cdh5.7.0.tar.gz

tar -zxvf xxxxx -C ~/app

exportSQOOP_HOME=/home/hadoop/app/sqoop-1.4.6-cdh5.7.0

export PATH=$SQOOP_HOME/bin:$PATH

$SQOOP_HOME/conf/sqoop-env.sh

export HADOOP_COMMON_HOME=/home/hadoop/app/hadoop-2.6.0-cdh5.7.0

exportHADOOP_MAPRED_HOME=/home/hadoop/app/hadoop-2.6.0-cdh5.7.0

exportHIVE_HOME=/home/hadoop/app/hive-1.1.0-cdh5.7.0

1.3   sqoop常用操作

拷贝mysql驱动到$SQOOP_HOME/lib

[hadoop@hadoop05 lib]$ cpmysql-connector-java-5.1.46.jar  /home/hadoop/app/sqoop/lib/

sqoop导入

sqoop list-tables \

--connectjdbc:mysql://localhost:3306/ruozedata_basic03 \

--username root --password root

1.3.1 sqoop导入mysql-->hdfs

RDBMS ==> HDFS

sqoop import \

--connect jdbc:mysql://localhost:3306/sqoop\

--username root --password root \

--table emp -m 2 \

--mapreduce-job-name FromMySQLToHDFS \

--delete-target-dir \

--columns"EMPNO,ENAME,JOB,SAL,COMM" \

--target-dir EMP_COLUMN_WHERE \

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

--null-string '' --null-non-string '0' \

--where 'SAL>2000'

默认：

         -m4

         emp

         emp.jar

        

        

sqoop import \

--connect jdbc:mysql://localhost:3306/sqoop\

--username root --password root \

-m 2 \

--mapreduce-job-name FromMySQLToHDFS \

--delete-target-dir \

--target-dir EMP_COLUMN_QUERY \

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

--null-string '' --null-non-string '0' \

--query "SELECT * FROM emp WHEREEMPNO>=7566 AND \$CONDITIONS" \

--split-by 'EMPNO'

sqoop eval \

--connect jdbc:mysql://localhost:3306/sqoop\

--username root --password root \

--query 'select * from emp'

        

        

        

        

emp.opt 

import

--connect

jdbc:mysql://localhost:3306/sqoop

--username

root

--password

root

--table

emp

--delete-target-dir

sqoop --options-file emp.opt        

        

        

1.3.2 sqoop 导出FromHDFSToMySQL

sqoop export \

--connect jdbc:mysql://localhost:3306/sqoop\

--username root --password root \

-m 2 \

--mapreduce-job-name FromHDFSToMySQL \

--table emp_demo \

--export-dir /user/hadoop/emp   

        

1.3.3 sqoop导入mysql-->HIVE

        

sqoop import \

--connect jdbc:mysql://localhost:3306/sqoop\

--username root --password root \

--table emp -m 2 \

--mapreduce-job-name FromMySQLToHive \

--delete-target-dir \

--hive-database ruozedata \

--hive-table ruozedata_emp_partition \

--hive-import \

--hive-partition-key 'pt' \

--hive-partition-value '2018-08-08' \

--fields-terminated-by '\t'--hive-overwrite

        

--create-hive-table不建议使用，建议大家先创建一个hive表再进行sqoop导入数据到hive表

        

        

create table ruozedata_emp_partition

(empno int, ename string, job string, mgrint, hiredate string, salary double, comm double, deptno int)

partitioned by (pt string)

ROW FORMAT DELIMITED

FIELDS TERMINATED BY '\t'

        

         Hive的数据：HDFS

         HDFS2MySQL==  Hive2MySQL

        

        

sqoop job --create ruozejob -- \

import \

--connect jdbc:mysql://localhost:3306/sqoop\

--username root --password root \

--table emp -m 2 \

--mapreduce-job-name FromMySQLToHDFS \

--delete-target-dir

crontab

         job

         --options-file

        

1.3.4 sqoop导出Hive ToMySQL

--- [hadoop@hadoop05 ~]$ sqoop export  --help 参数帮助

sqoop export \

--connect jdbc:mysql://hadoop0:3306/hivedb\

--username root \

--password 123456 \

--mapreduce-job-name FromHiveToMySQL \

--table results \

--export-dir/user/hive/warehouse/hive.db/results \

--input-fields-terminated-by '\t'   

        

1.4   总结：

sqoop参数特别多，推荐使用opt方式编写脚本，如果有遇到参数单引号和双引号，特别注意里面的特殊字符的转义。

需求：统计各个区域下最热门的TOP3的商品       

1) MySQL: city_info   静态

2) MySQL: product_info  静态

         DROPTABLE product_info;

         CREATETABLE `product_info` (

           `product_id` int(11) DEFAULT NULL,

           `product_name` varchar(255) DEFAULT NULL,

           `extend_info` varchar(255) DEFAULT NULL

         )ENGINE=InnoDB DEFAULT CHARSET=utf8;        

3) Hive: user_click  用户行为日志   date分区      

user_id int

session_id string

action_time string

city_id int

product_id int

实现需求：

1) city_info ===> hive

2) product_info ===> hive

3) 三表的join  取 TOP3(按区域进行分组)   按天分区表

最终的统计结果字段如下：

product_id 商品ID

product_name 商品名称

area 区域

click_count 点击数/访问量

rank 排名

day    时间

====> MySQL

        

day : 20180808

hive 2 mysql: delete xxx from whereday='20180808'

        

1、mysql建表 CREATE TABLE `city_info` (   `city_id` int(11) DEFAULT NULL,   `city_name` varchar(255) DEFAULT NULL,   `area` varchar(255) DEFAULT NULL ) ENGINE=InnoDB DEFAULT CHARSET=utf8;     insert  into `city_info`(`city_id`,`city_name`,`area`) values (1,'BEIJING','NC'), (2,'SHANGHAI','EC'),(3,'NANJING','EC'),(4,'GUANGZHOU','SC'),(5,'SANYA','SC'),(6,' WUHAN','CC'),(7,'CHANGSHA','CC'),(8,'XIAN','NW'),(9,'CHENGDU','SW'),(10,'HAERBIN' ,'NE');   [hadoop@hadoop05 data]$ mysql -uroot -P3308 -h172.16.18.153 -p123456 -D ruozedata_basic03 mysql> source city_info.sql Query OK, 1 row affected (0.02 sec) Query OK, 0 rows affected (0.02 sec) Query OK, 10 rows affected (0.01 sec) Records: 10  Duplicates: 0  Warnings: 0 mysql> CREATE TABLE `product_info` (     ->   `product_id` int(11) DEFAULT NULL,     ->   `product_name` varchar(255) DEFAULT NULL,     ->   `extend_info` varchar(255) DEFAULT NULL     -> ) ENGINE=InnoDB DEFAULT CHARSET=utf8; Query OK, 0 rows affected (0.01 sec) mysql> source product_info.sql Query OK, 1 row affected (0.00 sec) Query OK, 1 row affected (0.01 sec) 2、hive建立分区表 hive> create table user_clik(     > user_id int,     > session_id string,     > action_time string,     > city_id int,     > product_id int     > )     > partitioned by (day string)     > row format delimited fields terminated by '\t'; OK Time taken: 0.134 seconds hive> desc user_clik; OK user_id             int                                      session_id             string                                     action_time           string                                     city_id                int                                       product_id            int                                      day                         string                                                        # Partition Information           # col_name                data_type           comment                                day                         string                                     Time taken: 0.217 seconds, Fetched: 11 row(s) 3、数据导入前将数据中^A字符处理掉 cat -v user_click.txt |sed 's/\^A//g' >user_click2.txt 53,^A561e94c2fa99467d956a26d55aab3cb6^A,2016-05-05 3:10:07^A,9,18 ---处理前的数据 53,561e94c2fa99467d956a26d55aab3cb6,2016-05-05 3:10:07,9,18  ---处理后的数据 --导入字段 hive> LOAD DATA LOCAL INPATH '/home/hadoop/data/user_click.txt'     > OVERWRITE INTO TABLE user_clik     > PARTITION(day='2016-05-05'); ---分区字段名称我们随便指定，就像相当于建立一个分区，分区叫2016-05-05，我们的数据全部导入到这个分区中 Loading data to table hive.user_clik partition (day=2016-05-05) Failed with exception MetaException(message:Error(s) were found while auto-creating/validating the datastore for classes. The errors are printed in the log, and are attached to this exception.) FAILED: Execution Error, return code 1 from org.apache.hadoop.hive.ql.exec.MoveTask 分析：我们的数据库默认的字符集已经不是latin1;需要将meta数据表字符集改为lantin1 Tail -f /tmp/hadoop/hive.log com.mysql.jdbc.exceptions.jdbc4.MySQLSyntaxErrorException: Specified key was too long; max key length is 3072 bytes alter table PARTITION_KEYS convert to character set latin1; 将meta数据表PARTITION_KEYS字符集，还是报错，那就是还有表需要改字符集 ---将meta整个数据库字符集改为latin1; alter database ruozedata_basic03 character set latin1; mysql> alter database ruozedata_basic03 character set latin1; Query OK, 1 row affected (0.02 sec) hive> LOAD DATA LOCAL INPATH '/home/hadoop/data/user_click.txt'     > OVERWRITE INTO TABLE user_clik     > PARTITION(day='2016-05-05'); Loading data to table hive.user_clik partition (day=2016-05-05) Partition hive.user_clik{day=2016-05-05} stats: [numFiles=1, numRows=0, totalSize=725264, rawDataSize=0] OK Time taken: 1.061 seconds hive> 4、将两个静态数据sqoop导入到hive中 先创建一个hive表再进行sqoop导入数据到hive CREATE TABLE `city_info` (   `city_id` int,   `city_name` string,   `area` string )ROW FORMAT DELIMITED FIELDS TERMINATED BY '\t' ;  CREATE TABLE `product_info` (      `product_id` int,       `product_name` string,      `extend_info` string   ) ROW FORMAT DELIMITED FIELDS TERMINATED BY '\t' ; 表没有主键 m=1 18/05/22 13:22:06 ERROR tool.ImportTool: Error during import: No primary key could be found for table city_info. Please specify one with --split-by or perform a sequential import with '-m 1'. sqoop import \ --connect jdbc:mysql://172.16.18.153:3308/hivedb \ --username root \ --password 123456 \ --table city_info \ --m 1 \ --mapreduce-job-name FromMySQLToHive \ --hive-database hive \ --hive-table city_info \ --hive-import \ --fields-terminated-by '\t' \ --delete-target-dir \ --hive-overwrite sqoop import \ --connect jdbc:mysql://172.16.18.153:3308/hivedb \ --username root \ --password 123456 \ --table product_info \ --m 1 \ --mapreduce-job-name FromMySQLToHive \ --hive-database hive \ --hive-table product_info \ --hive-import \ --fields-terminated-by '\t' \ --delete-target-dir \ --hive-overwrite 18/05/22 13:36:03 INFO mapreduce.ImportJobBase: Beginning import of city_info Exception in thread "main" java.lang.NoClassDefFoundError: org/json/JSONObject                   at org.apache.sqoop.util.SqoopJsonUtil.getJsonStringforMap(SqoopJsonUtil.java:43)                   at org.apache.sqoop.SqoopOptions.writeProperties(SqoopOptions.java:758)                   at org.apache.sqoop.mapreduce.JobBase.putSqoopOptionsToConfiguration(JobBase.java:369)                   at org.apache.sqoop.mapreduce.JobBase.createJob(JobBase.java:355)                   at org.apache.sqoop.mapreduce.ImportJobBase.runImport(ImportJobBase.java:256)                   at org.apache.sqoop.manager.SqlManager.importTable(SqlManager.java:692)                   at org.apache.sqoop.manager.MySQLManager.importTable(MySQLManager.java:127)                   at org.apache.sqoop.tool.ImportTool.importTable(ImportTool.java:507)                   at org.apache.sqoop.tool.ImportTool.run(ImportTool.java:615)                   at org.apache.sqoop.Sqoop.run(Sqoop.java:143)                   at org.apache.hadoop.util.ToolRunner.run(ToolRunner.java:70)                   at org.apache.sqoop.Sqoop.runSqoop(Sqoop.java:179)                   at org.apache.sqoop.Sqoop.runTool(Sqoop.java:218)                   at org.apache.sqoop.Sqoop.runTool(Sqoop.java:227)                   at org.apache.sqoop.Sqoop.main(Sqoop.java:236) Caused by: java.lang.ClassNotFoundException: org.json.JSONObject                   at java.net.URLClassLoader$1.run(URLClassLoader.java:366)                   at java.net.URLClassLoader$1.run(URLClassLoader.java:355)                   at java.security.AccessController.doPrivileged(Native Method)                   at java.net.URLClassLoader.findClass(URLClassLoader.java:354)                   at java.lang.ClassLoader.loadClass(ClassLoader.java:425)                   at sun.misc.Launcher$AppClassLoader.loadClass(Launcher.java:308)                   at java.lang.ClassLoader.loadClass(ClassLoader.java:358)          ... 15 more 分析：确实java_json.jar包 下载java_json.jar  导入java-json.jar包， 下载地址http://www.java2s.com/Code/Jar/j/Downloadjavajsonjar.htm， 把java-json.jar添加到../sqoop/lib目录          问题2：          18/05/22 13:39:13 ERROR hive.HiveConfig: Could not load org.apache.hadoop.hive.conf.HiveConf. Make sure HIVE_CONF_DIR is set correctly. 18/05/22 13:39:13 ERROR tool.ImportTool: Encountered IOException running import job: java.io.IOException: java.lang.ClassNotFoundException: org.apache.hadoop.hive.conf.HiveConf                   at org.apache.sqoop.hive.HiveConfig.getHiveConf(HiveConfig.java:50)                   at org.apache.sqoop.hive.HiveImport.getHiveArgs(HiveImport.java:392)                   at org.apache.sqoop.hive.HiveImport.executeExternalHiveScript(HiveImport.java:379)                   at org.apache.sqoop.hive.HiveImport.executeScript(HiveImport.java:337)                   at org.apache.sqoop.hive.HiveImport.importTable(HiveImport.java:241)                   at org.apache.sqoop.tool.ImportTool.importTable(ImportTool.java:524)                   at org.apache.sqoop.tool.ImportTool.run(ImportTool.java:615)                   at org.apache.sqoop.Sqoop.run(Sqoop.java:143)                   at org.apache.hadoop.util.ToolRunner.run(ToolRunner.java:70)                   at org.apache.sqoop.Sqoop.runSqoop(Sqoop.java:179)                   at org.apache.sqoop.Sqoop.runTool(Sqoop.java:218)                   at org.apache.sqoop.Sqoop.runTool(Sqoop.java:227)                   at org.apache.sqoop.Sqoop.main(Sqoop.java:236) Caused by: java.lang.ClassNotFoundException: org.apache.hadoop.hive.conf.HiveConf                   at java.net.URLClassLoader$1.run(URLClassLoader.java:366)                   at java.net.URLClassLoader$1.run(URLClassLoader.java:355)                   at java.security.AccessController.doPrivileged(Native Method)                   at java.net.URLClassLoader.findClass(URLClassLoader.java:354)                   at java.lang.ClassLoader.loadClass(ClassLoader.java:425)                   at sun.misc.Launcher$AppClassLoader.loadClass(Launcher.java:308)                   at java.lang.ClassLoader.loadClass(ClassLoader.java:358)                   at java.lang.Class.forName0(Native Method)                   at java.lang.Class.forName(Class.java:191)                   at org.apache.sqoop.hive.HiveConfig.getHiveConf(HiveConfig.java:44) 分析： 找不到hive相关的配置路径库文件，配置lib路径，如果还不行就是缺少连接hive 驱动lib包，和连接mysql驱动jar一样 vim .bash_profile export CLASSPATH=.:$JAVA_HOME/lib:$JAVA_HOME/jre/lib:$HADOOP_HOME/lib:$CLASSPATH:$SQOOP_HOME/lib 添加sqoop库文件路径到环境变量   将hive的jar包拷贝到sqoop/lib/ [hadoop@hadoop05 lib]$ cp hive-exec-1.1.0-cdh5.9.0.jar  ../../sqoop/lib/ [hadoop@hadoop05 lib]$ pwd /home/hadoop/app/hive/lib [hadoop@hadoop05 lib]$   select c.area,p.product_name,count(u.product_id) from user_click u left join city_info c on u.city_id=c.city_id left join product_info p on u.product_id=p.product_id AND u.day='2016-05-05' group by c.area,p.product_name; select * from ( select aa.area,aa.name,aa.ct, row_number() over(partition by aa.area order by ct  desc) as rn from (     select c.area area,p.product_name name,count(t.product_id) ct     from user_clik t left join city_info c on t.city_id=c.city_id     left join product_info p on t.product_id=p.product_id     where t.day='2016-05-05'     group by c.area,p.product_name) aa  ) tt where tt.rn<=3;   select * from ( select aa.area,aa.name,aa.ct, row_number() over(partition by aa.area order by ct  desc) as rn from (     select c.area area,p.product_name name,count(t.product_id) ct     from  user_clik t  left join  city_info  c on t.city_id=c.city_id     left join product_info p on t.product_id=p.product_id     where t.day='2016-05-05' and t.city_id is not NULL     group by c.area,p.product_name) aa  ) tt where tt.rn<=3; select * from ( select aa.area,aa.name,aa.ct, row_number() over(partition by aa.area order by ct  desc) as rn from (     select c.area area,p.product_name name,count(t.product_id) ct     from city_info  c left join user_clik t on t.city_id=c.city_id     left join product_info p on t.product_id=p.product_id     where t.day='2016-05-05' and t.city_id is not NULL     group by c.area,p.product_name) aa  ) tt where tt.rn<=3; 以区域关联，排查区域为空的3条数据 将这个数据存放到一个计算中间表中，如果将中间表导出到mysql中， 1.4.1.1 Hive最终结果表 CREATE TABLE `results` (      `city_name` string,       `product_name` string,      `count`  int,       rank int   ) ROW FORMAT DELIMITED FIELDS TERMINATED BY '\t' ; Hive计算结果数据保存 Hive计算结果数据之间保存到hive中，（也可保存到本地文件系统，hdfs上都可以）  insert overwrite  table results select * from ( select aa.area,aa.name,aa.ct, row_number() over(partition by aa.area order by ct  desc) as rn from (     select c.area area,p.product_name name,count(t.product_id) ct     from city_info  c left join user_clik t on t.city_id=c.city_id     left join product_info p on t.product_id=p.product_id     where t.day='2016-05-05' and t.city_id is not NULL     group by c.area,p.product_name) aa  ) tt where tt.rn<=3; 将结果数据从hive中sqoop导出到mysql中 导入过程报错 re. Consider using -P instead. 18/05/22 17:33:37 INFO manager.MySQLManager: Preparing to use a MySQL streaming r 18/05/22 17:33:37 INFO tool.CodeGenTool: Beginning code generation 18/05/22 17:33:37 ERROR manager.SqlManager: Error executing statement: com.mysql.ns.jdbc4.CommunicationsException: Communications link failure The last packet sent successfully to the server was 0 milliseconds ago. The driveeived any packets from the server. com.mysql.jdbc.exceptions.jdbc4.CommunicationsException: Communications link fail The last packet sent successfully to the server was 0 milliseconds ago. The driveeived any packets from the server.          at sun.reflect.NativeConstructorAccessorImpl.newInstance0(Native Method)          at sun.reflect.NativeConstructorAccessorImpl.newInstance(NativeConstructo.java:57)          at sun.reflect.DelegatingConstructorAccessorImpl.newInstance(DelegatingCossorImpl.java:45)          at java.lang.reflect.Constructor.newInstance(Constructor.java:526)          at com.mysql.jdbc.Util.handleNewInstance(Util.java:425)          at com.mysql.jdbc.SQLError.createCommunicationsException(SQLError.java:99          at com.mysql.jdbc.MysqlIO.<init>(MysqlIO.java:342)          at com.mysql.jdbc.ConnectionImpl.coreConnect(ConnectionImpl.java:2188)          at com.mysql.jdbc.ConnectionImpl.connectOneTryOnly(ConnectionImpl.java:22          at com.mysql.jdbc.ConnectionImpl.createNewIO(ConnectionImpl.java:2016)          at com.mysql.jdbc.ConnectionImpl.<init>(ConnectionImpl.java:776)          at com.mysql.jdbc.JDBC4Connection.<init>(JDBC4Connection.java:47)          at sun.reflect.NativeConstructorAccessorImpl.newInstance0(Native Method)          at sun.reflect.NativeConstructorAccessorImpl.newInstance(NativeConstructo.java:57)          at sun.reflect.DelegatingConstructorAccessorImpl.newInstance(DelegatingCossorImpl.java:45)          at java.lang.reflect.Constructor.newInstance(Constructor.java:526)          at com.mysql.jdbc.Util.handleNewInstance(Util.java:425)          at com.mysql.jdbc.ConnectionImpl.getInstance(ConnectionImpl.java:386)          at com.mysql.jdbc.NonRegisteringDriver.connect(NonRegisteringDriver.java:          at java.sql.DriverManager.getConnection(DriverManager.java:571)          at java.sql.DriverManager.getConnection(DriverManager.java:215)          at org.apache.sqoop.manager.SqlManager.makeConnection(SqlManager.java:904          at org.apache.sqoop.manager.GenericJdbcManager.getConnection(GenericJdbcM2)          at org.apache.sqoop.manager.SqlManager.execute(SqlManager.java:763)          at org.apache.sqoop.manager.SqlManager.execute(SqlManager.java:786)          at org.apache.sqoop.manager.SqlManager.getColumnInfoForRawQuery(SqlManage          at org.apache.sqoop.manager.SqlManager.getColumnTypesForRawQuery(SqlManag          at org.apache.sqoop.manager.SqlManager.getColumnTypes(SqlManager.java:246          at org.apache.sqoop.manager.ConnManager.getColumnTypes(ConnManager.java:3          at org.apache.sqoop.orm.ClassWriter.getColumnTypes(ClassWriter.java:1853)          at org.apache.sqoop.orm.ClassWriter.generate(ClassWriter.java:1653)          at org.apache.sqoop.tool.CodeGenTool.generateORM(CodeGenTool.java:107)          at org.apache.sqoop.tool.ExportTool.exportTable(ExportTool.java:64)          at org.apache.sqoop.tool.ExportTool.run(ExportTool.java:100)          at org.apache.sqoop.Sqoop.run(Sqoop.java:143)          at org.apache.hadoop.util.ToolRunner.run(ToolRunner.java:70)          at org.apache.sqoop.Sqoop.runSqoop(Sqoop.java:179)          at org.apache.sqoop.Sqoop.runTool(Sqoop.java:218)          at org.apache.sqoop.Sqoop.runTool(Sqoop.java:227)          at org.apache.sqoop.Sqoop.main(Sqoop.java:236) Caused by: java.net.UnknownHostException: hadoop0          at java.net.Inet4AddressImpl.lookupAllHostAddr(Native Method)          at java.net.InetAddress$1.lookupAllHostAddr(InetAddress.java:901)          at java.net.InetAddress.getAddressesFromNameService(InetAddress.java:1295          at java.net.InetAddress.getAllByName0(InetAddress.java:1248)          at java.net.InetAddress.getAllByName(InetAddress.java:1164)          at java.net.InetAddress.getAllByName(InetAddress.java:1098)          at com.mysql.jdbc.StandardSocketFactory.connect(StandardSocketFactory.jav          at com.mysql.jdbc.MysqlIO.<init>(MysqlIO.java:301)          ... 33 more 18/05/22 17:33:37 ERROR tool.ExportTool: Encountered IOException running export jOException: No columns to generate for ClassWriter ---建立mysql表 CREATE TABLE ` results` (            city_name   varchar(255)  DEFAULT NULL,            product_name  varchar(255) DEFAULT NULL,            count   int(8) DEFAULT NULL,       rank  int(8) default null          ) ENGINE=InnoDB DEFAULT CHARSET=utf8;         sqoop export \ --connect jdbc:mysql://172.16.18.153:3308/hivedb \ --username root \ --password 123456 \ --mapreduce-job-name FromHiveToMySQL \ --table results \ --export-dir /user/hive/warehouse/hive.db/results \ --input-fields-terminated-by '\t'    --connect jdbc:mysql://172.16.18.153:3308/hivedb  ---导入到哪个mysql库 Hive的meta数据配置文件里面已经配置好了，不要和这的mysql库混一起了 ---mysql查询数据

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