投稿
  1. 云图网首页
  2. 技术专区
  3. 大数据

Sqoop基本语法简介

• 大数据, 开源, 研发管理, 移动开发, 编程笔记 • 阅读 48

简介：
本篇文章主要介绍sqoop的基本语法及简单使用方法。

1.查看命令帮助
[hadoop@hadoop000 ~]$ sqoop help
usage: sqoop COMMAND [ARGS]

Available commands:
  codegen            Generate code to interact with database records
  create-hive-table  Import a table definition into Hive
  eval               Evaluate a SQL statement and display the results
  export             Export an HDFS directory to a database table
  help               List available commands
  import             Import a table from a database to HDFS
  import-all-tables  Import tables from a database to HDFS
  import-mainframe   Import datasets from a mainframe server to HDFS
  job                Work with saved jobs
  list-databases     List available databases on a server
  list-tables        List available tables in a database
  merge              Merge results of incremental imports
  metastore          Run a standalone Sqoop metastore
  version            Display version information

See 'sqoop help COMMAND' for information on a specific command.

# 这里提示我们使用sqoop help command（要查询的命令）进行该命令的详细查询
2.list-databases
# 查看list-databases命令帮助
[hadoop@hadoop000 ~]$ sqoop help list-databases
usage: sqoop list-databases [GENERIC-ARGS] [TOOL-ARGS]

Common arguments:
   --connect <jdbc-uri>                         Specify JDBC connect
                                                string
   --connection-manager <class-name>            Specify connection manager
                                                class name
   --connection-param-file <properties-file>    Specify connection
                                                parameters file
   --driver <class-name>                        Manually specify JDBC
                                                driver class to use
   --hadoop-home <hdir>                         Override
                                                $HADOOP_MAPRED_HOME_ARG
   --hadoop-mapred-home <dir>                   Override
                                                $HADOOP_MAPRED_HOME_ARG
   --help                                       Print usage instructions
-P                                              Read password from console
   --password <password>                        Set authentication
                                                password
   --password-alias <password-alias>            Credential provider
                                                password alias
   --password-file <password-file>              Set authentication
                                                password file path
   --relaxed-isolation                          Use read-uncommitted
                                                isolation for imports
   --skip-dist-cache                            Skip copying jars to
                                                distributed cache
   --username <username>                        Set authentication
                                                username
   --verbose                                    Print more information
                                                while working

# 简单使用
[hadoop@oradb3 ~]$ sqoop list-databases /
> --connect jdbc:mysql://localhost:3306 /
> --username root /
> --password 123456

# 结果
information_schema
mysql
performance_schema
slow_query_log
sys
test
3.list-tables
# 命令帮助
[hadoop@hadoop000 ~]$ sqoop help list-tables
usage: sqoop list-tables [GENERIC-ARGS] [TOOL-ARGS]

Common arguments:
   --connect <jdbc-uri>                         Specify JDBC connect
                                                string
   --connection-manager <class-name>            Specify connection manager
                                                class name
   --connection-param-file <properties-file>    Specify connection
                                                parameters file
   --driver <class-name>                        Manually specify JDBC
                                                driver class to use
   --hadoop-home <hdir>                         Override
                                                $HADOOP_MAPRED_HOME_ARG
   --hadoop-mapred-home <dir>                   Override
                                                $HADOOP_MAPRED_HOME_ARG
   --help                                       Print usage instructions
-P                                              Read password from console
   --password <password>                        Set authentication
                                                password
   --password-alias <password-alias>            Credential provider
                                                password alias
   --password-file <password-file>              Set authentication
                                                password file path
   --relaxed-isolation                          Use read-uncommitted
                                                isolation for imports
   --skip-dist-cache                            Skip copying jars to
                                                distributed cache
   --username <username>                        Set authentication
                                                username
   --verbose                                    Print more information
                                                while working

# 使用方法
[hadoop@hadoop000 ~]$ sqoop list-tables /
> --connect jdbc:mysql://localhost:3306/test /
> --username root /
> --password 123456

# 结果
t_order
test0001
test_1013
test_dyc
test_tb
4.将mysql导入HDFS中(import)

(默认导入当前用户目录下/user/用户名/表名)
说到这里扩展一个小知识点：

  • hadoop fs -ls 显示的是当前的用户目录 即/user/hadoop
    hadoop fs -ls / 显示的是HDFS根目录
# 查看命令帮助
[hadoop@hadoop000 ~]$ sqoop help import
# 执行import
[hadoop@hadoop000 ~]$ sqoop import /
> --connect jdbc:mysql://localhost:3306/test /
> --username root /
> --password 123456 /
> --table students

这时很可能会出现这个错误
Exception in thread "main" java.lang.NoClassDefFoundError: org/json/JSONObject
这里我们需要导入java-json.jar包 下载地址 把java-json.jar添加到../sqoop/lib目录下即可

# 再次执行 import导入
[hadoop@hadoop000 ~]$ sqoop import /
> --connect jdbc:mysql://localhost:3306/test /
> --username root /
> --password 123456 /
> --table students

18/07/04 13:28:35 INFO sqoop.Sqoop: Running Sqoop version: 1.4.6-cdh6.7.0
18/07/04 13:28:35 WARN tool.BaseSqoopTool: Setting your password on the command-line is insecure. Consider using -P instead.
18/07/04 13:28:35 INFO manager.MySQLManager: Preparing to use a MySQL streaming resultset.
18/07/04 13:28:35 INFO tool.CodeGenTool: Beginning code generation
18/07/04 13:28:35 INFO manager.SqlManager: Executing SQL statement: SELECT t.* FROM `students` AS t LIMIT 1
18/07/04 13:28:35 INFO manager.SqlManager: Executing SQL statement: SELECT t.* FROM `students` AS t LIMIT 1
18/07/04 13:28:35 INFO orm.CompilationManager: HADOOP_MAPRED_HOME is /home/hadoop/app/hadoop-2.6.0-cdh6.7.0
18/07/04 13:28:37 INFO orm.CompilationManager: Writing jar file: /tmp/sqoop-hadoop/compile/3024b8df04f623e8c79ed9b5b30ace75/students.jar
18/07/04 13:28:37 WARN manager.MySQLManager: It looks like you are importing from mysql.
18/07/04 13:28:37 WARN manager.MySQLManager: This transfer can be faster! Use the --direct
18/07/04 13:28:37 WARN manager.MySQLManager: option to exercise a MySQL-specific fast path.
18/07/04 13:28:37 INFO manager.MySQLManager: Setting zero DATETIME behavior to convertToNull (mysql)
18/07/04 13:28:37 INFO mapreduce.ImportJobBase: Beginning import of students
18/07/04 13:28:38 INFO Configuration.deprecation: mapred.jar is deprecated. Instead, use mapreduce.job.jar
18/07/04 13:28:39 INFO Configuration.deprecation: mapred.map.tasks is deprecated. Instead, use mapreduce.job.maps
18/07/04 13:28:39 INFO client.RMProxy: Connecting to ResourceManager at /0.0.0.0:8032
18/07/04 13:28:41 INFO db.DBInputFormat: Using read commited transaction isolation
18/07/04 13:28:41 INFO db.DataDrivenDBInputFormat: BoundingValsQuery: SELECT MIN(`id`), MAX(`id`) FROM `students`
18/07/04 13:28:41 INFO db.IntegerSplitter: Split size: 0; Num splits: 4 from: 1001 to: 1003
18/07/04 13:28:41 INFO mapreduce.JobSubmitter: number of splits:3
18/07/04 13:28:42 INFO mapreduce.JobSubmitter: Submitting tokens for job: job_1530598609758_0015
18/07/04 13:28:42 INFO impl.YarnClientImpl: Submitted application application_1530598609758_0015
18/07/04 13:28:42 INFO mapreduce.Job: The url to track the job: http://oradb3:8088/proxy/application_1530598609758_0015/
18/07/04 13:28:42 INFO mapreduce.Job: Running job: job_1530598609758_0015
18/07/04 13:28:52 INFO mapreduce.Job: Job job_1530598609758_0015 running in uber mode : false
18/07/04 13:28:52 INFO mapreduce.Job:  map 0% reduce 0%
18/07/04 13:28:58 INFO mapreduce.Job:  map 33% reduce 0%
18/07/04 13:28:59 INFO mapreduce.Job:  map 67% reduce 0%
18/07/04 13:29:00 INFO mapreduce.Job:  map 100% reduce 0%
18/07/04 13:29:00 INFO mapreduce.Job: Job job_1530598609758_0015 completed successfully
18/07/04 13:29:00 INFO mapreduce.Job: Counters: 30
...
18/07/04 13:29:00 INFO mapreduce.ImportJobBase: Transferred 40 bytes in 21.3156 seconds (1.8766 bytes/sec)
18/07/04 13:29:00 INFO mapreduce.ImportJobBase: Retrieved 3 records.
# 生成的日志信息大家一定要好好理解
# 查看HDFS上的文件
[hadoop@hadoop000 ~]$ hadoop fs -ls /user/hadoop/students
Found 4 items
-rw-r--r--   1 hadoop supergroup          0 2018-07-04 13:28 /user/hadoop/students/_SUCCESS
-rw-r--r--   1 hadoop supergroup         13 2018-07-04 13:28 /user/hadoop/students/part-m-00000
-rw-r--r--   1 hadoop supergroup         13 2018-07-04 13:28 /user/hadoop/students/part-m-00001
-rw-r--r--   1 hadoop supergroup         14 2018-07-04 13:28 /user/hadoop/students/part-m-00002
[hadoop@hadoop000 ~]$ hadoop fs -cat /user/hadoop/students/"part*"
1001,lodd,23
1002,sdfs,21
1003,sdfsa,24

我们还可以加一些其他参数 使导入过程更加可控

-m 指定启动map进程个数，默认是4个
--delete-target-dir 删除目标目录
--mapreduce-job-name 指定mapreduce的job的名字
--target-dir 导入到指定目录
--fields-terminated-by 指定字段之间的分隔符
--null-string 含义是 string类型的字段，当Value是NULL，替换成指定的字符
--null-non-string 含义是非string类型的字段，当Value是NULL，替换成指定字符
--columns 导入表中的部分字段
--where 按条件导入数据
--query 按照sql语句进行导入 使用–query关键字，就不能使用–table和–columns
--options-file 在文件中执行

# 执行导入
[hadoop@hadoop000 ~]$ sqoop import /
> --connect jdbc:mysql://localhost:3306/test /
> --username root --password 123456 /
> --mapreduce-job-name FromMySQL2HDFS /
> --delete-target-dir /
> --table students /
> -m 1

# HDFS中查看
[hadoop@hadoop000 ~]$ hadoop fs -ls /user/hadoop/students              
Found 2 items
-rw-r--r--   1 hadoop supergroup          0 2018-07-04 13:53 /user/hadoop/students/_SUCCESS
-rw-r--r--   1 hadoop supergroup         40 2018-07-04 13:53 /user/hadoop/students/part-m-00000
[hadoop@oradb3 ~]$ hadoop fs -cat /user/hadoop/students/"part*"
1001,lodd,23
1002,sdfs,21
1003,sdfsa,24
# 使用where 参数
[hadoop@hadoop000 ~]$ sqoop import /
> --connect jdbc:mysql://localhost:3306/test /
> --username root --password 123456 /
> --table students /
> --mapreduce-job-name FromMySQL2HDFS2 /
> --delete-target-dir /
> --fields-terminated-by '/t' /
> -m 1 /
> --null-string 0 /
> --columns "name" /
> --target-dir STU_COLUMN_WHERE /
> --where 'id<1002'

# HDFS 结果
[hadoop@hadoop000 ~]$ hadoop fs -cat STU_COLUMN_WHERE/"part*"
lodd
# 使用query 参数
[hadoop@hadoop000 ~]$ sqoop import /
> --connect jdbc:mysql://localhost:3306/test /
> --username root --password 123456 /
> --mapreduce-job-name FromMySQL2HDFS3 /
> --delete-target-dir /
> --fields-terminated-by '/t' /
> -m 1 /
> --null-string 0 /
> --target-dir STU_COLUMN_QUERY /
> --query "select * from students where id>1001 and /$CONDITIONS"

# HDFS查看
[hadoop@hadoop000 ~]$ hadoop fs -cat STU_COLUMN_QUERY/"part*"
1002    sdfs    21
1003    sdfsa   24
# 使用options-file参数
[hadoop@hadoop000 ~]$ vi sqoop-import-hdfs.txt
import
--connect
jdbc:mysql://localhost:3306/test
--username
root
--password
123456
--table
students
--target-dir
STU_option_file
# 执行导入
[hadoop@hadoop000 ~]$ sqoop --options-file /home/hadoop/sqoop-import-hdfs.txt
# HDFS查看
[hadoop@hadoop000 ~]$ hadoop fs -cat STU_option_file/"part*"
1001,lodd,23
1002,sdfs,21
1003,sdfsa,24
5.eval

查看帮助命令对与该命令的解释为： Evaluate a SQL statement and display the results，也就是说执行一个SQL语句并查询出结果。

# 查看命令帮助
[hadoop@hadoop000 ~]$ sqoop help eval
usage: sqoop eval [GENERIC-ARGS] [TOOL-ARGS]

Common arguments:
   --connect <jdbc-uri>                         Specify JDBC connect
                                                string
   --connection-manager <class-name>            Specify connection manager
                                                class name
   --connection-param-file <properties-file>    Specify connection
                                                parameters file
   --driver <class-name>                        Manually specify JDBC
                                                driver class to use
   --hadoop-home <hdir>                         Override
                                                $HADOOP_MAPRED_HOME_ARG
   --hadoop-mapred-home <dir>                   Override
                                                $HADOOP_MAPRED_HOME_ARG
   --help                                       Print usage instructions
-P                                              Read password from console
   --password <password>                        Set authentication
                                                password
   --password-alias <password-alias>            Credential provider
                                                password alias
   --password-file <password-file>              Set authentication
                                                password file path
   --relaxed-isolation                          Use read-uncommitted
                                                isolation for imports
   --skip-dist-cache                            Skip copying jars to
                                                distributed cache
   --username <username>                        Set authentication
                                                username
   --verbose                                    Print more information
                                                while working

SQL evaluation arguments:
-e,--query <statement>    Execute 'statement' in SQL and exit
# 执行
[hadoop@hadoop000 ~]$ sqoop eval /
> --connect jdbc:mysql://localhost:3306/test /
> --username root --password 123456 /
> --query "select * from students"

18/07/04 14:28:44 INFO sqoop.Sqoop: Running Sqoop version: 1.4.6-cdh6.7.0
18/07/04 14:28:44 WARN tool.BaseSqoopTool: Setting your password on the command-line is insecure. Consider using -P instead.
18/07/04 14:28:44 INFO manager.MySQLManager: Preparing to use a MySQL streaming resultset.
----------------------------------------------------
| id          | name                 | age         | 
----------------------------------------------------
| 1001        | lodd                 | 23          | 
| 1002        | sdfs                 | 21          | 
| 1003        | sdfsa                | 24          | 
----------------------------------------------------
6.export (HDFS数据导出到MySQL或Hive中的数据导入到MySQL)

常用参数：

--table 指定导出表的名称
--input-fields-terminated-by 指定hdfs上文件的分隔符，默认是逗号
--export-dir 导出数据的目录
--columns 指定导出的字段

在执行导出语句前mysql要先创建表（不创建表会报错）：

# HDFS原文件
[hadoop@hadoop000 ~]$ hadoop fs -cat /user/hadoop/students/part-m-00000
1001,lodd,23
1002,sdfs,21
1003,sdfsa,24
# export导出到mysql
[hadoop@hadoop000 ~]$ sqoop export /
> --connect jdbc:mysql://localhost:3306/test /
> --username root /
> --password 123456 /
> --table students_demo /
> --export-dir /user/hadoop/students/

18/07/04 14:46:20 INFO sqoop.Sqoop: Running Sqoop version: 1.4.6-cdh6.7.0
18/07/04 14:46:20 WARN tool.BaseSqoopTool: Setting your password on the command-line is insecure. Consider using -P instead.
18/07/04 14:46:20 INFO manager.MySQLManager: Preparing to use a MySQL streaming resultset.
18/07/04 14:46:20 INFO tool.CodeGenTool: Beginning code generation
18/07/04 14:46:21 INFO manager.SqlManager: Executing SQL statement: SELECT t.* FROM `students_demo` AS t LIMIT 1
18/07/04 14:46:21 INFO manager.SqlManager: Executing SQL statement: SELECT t.* FROM `students_demo` AS t LIMIT 1
18/07/04 14:46:21 INFO orm.CompilationManager: HADOOP_MAPRED_HOME is /home/hadoop/app/hadoop-2.6.0-cdh6.7.0
18/07/04 14:46:24 INFO orm.CompilationManager: Writing jar file: /tmp/sqoop-hadoop/compile/fc7b53dd6eef701c0731c7a7c4a4b340/students_demo.jar
18/07/04 14:46:24 INFO mapreduce.ExportJobBase: Beginning export of students_demo
18/07/04 14:46:25 INFO Configuration.deprecation: mapred.jar is deprecated. Instead, use mapreduce.job.jar
18/07/04 14:46:25 INFO Configuration.deprecation: mapred.map.max.attempts is deprecated. Instead, use mapreduce.map.maxattempts
18/07/04 14:46:26 INFO Configuration.deprecation: mapred.reduce.tasks.speculative.execution is deprecated. Instead, use mapreduce.reduce.speculative
18/07/04 14:46:26 INFO Configuration.deprecation: mapred.map.tasks.speculative.execution is deprecated. Instead, use mapreduce.map.speculative
18/07/04 14:46:26 INFO Configuration.deprecation: mapred.map.tasks is deprecated. Instead, use mapreduce.job.maps
...
18/07/04 14:46:55 INFO mapreduce.ExportJobBase: Transferred 672 bytes in 29.3122 seconds (22.9256 bytes/sec)
18/07/04 14:46:55 INFO mapreduce.ExportJobBase: Exported 3 records.

# mysql中查看
mysql> select * from students_demo;
+------+-------+------+
| id   | name  | age  |
+------+-------+------+
| 1001 | lodd  |   23 |
| 1002 | sdfs  |   21 |
| 1003 | sdfsa |   24 |
+------+-------+------+
3 rows in set (0.00 sec)

如果再导入一次会追加在表中

# 增加columns参数
[hadoop@hadoop000 ~]$ sqoop export /
> --connect jdbc:mysql://localhost:3306/test /
> --username root /
> --password 123456 /
> --table students_demo2 /
> --export-dir /user/hadoop/students/ /
> --columns id,name

# mysql结果
mysql> select * from students_demo2;
+------+-------+------+
| id   | name  | age  |
+------+-------+------+
| 1001 | lodd  | NULL |
| 1002 | sdfs  | NULL |
| 1003 | sdfsa | NULL |
+------+-------+------+
3 rows in set (0.00 sec)
7.MySQL的中的数据导入到Hive中

常用参数：

--create-hive-table 创建目标表，如果有会报错
--hive-database 指定hive数据库
--hive-import 指定导入hive（没有这个条件导入到hdfs中）
--hive-overwrite 覆盖
--hive-table 指定hive中表的名字，如果不指定使用导入的表的表名
--hive-partition-key 指定Hive分区表字段
--hive-partition-value 指定导入的分区值

首次导入可能会报错如下：
18/07/04 15:06:26 ERROR hive.HiveConfig: Could not load org.apache.hadoop.hive.conf.HiveConf. Make sure HIVE_CONF_DIR is set correctly.<br/>18/07/04 15:06:26 ERROR tool.ImportTool: Encountered IOException running import job: java.io.IOException: java.lang.ClassNotFoundException: org.apache.hadoop.hive.conf.HiveConf
解决方法：到hive目录的lib下拷贝几个jar包，问题就解决了

# 报错解决方法
[hadoop@hadoop000 lib]$ pwd
/home/hadoop/app/hive-1.1.0-cdh6.7.0/lib
[hadoop@hadoop000 lib]$ cp hive-common-1.1.0-cdh6.7.0.jar /home/hadoop/app/sqoop-1.4.6-cdh6.7.0/lib/
[hadoop@hadoop000 lib]$ cp hive-shims* /home/hadoop/app/sqoop-1.4.6-cdh6.7.0/lib/
# 报错解决后执行导入
[hadoop@hadoop000 ~]$ sqoop import /
> --connect jdbc:mysql://localhost:3306/test /
> --username root --password 123456 /
> --table students /
> --create-hive-table /
> --hive-database hive /
> --hive-import /
> --hive-overwrite /
> --hive-table stu_import /
> --mapreduce-job-name FromMySQL2HIVE /
> --delete-target-dir /
> --fields-terminated-by '/t' /
> -m 1 /
> --null-non-string 0

# Hive中查看
hive> show tables;
OK
stu_import
Time taken: 0.051 seconds, Fetched: 1 row(s)
hive> select * from stu_import;
OK
1001    lodd    23
1002    sdfs    21
1003    sdfsa   24
Time taken: 0.969 seconds, Fetched: 3 row(s)

建议：导入Hive不建议大家使用–create-hive-table参数,建议事先创建好hive表；因为自动创建的表字段类型可能并不是我们想要的。

# 增加partition参数
[hadoop@hadoop000 ~]$ sqoop import /
> --connect jdbc:mysql://localhost:3306/test /
> --username root --password 123456 /
> --table students /
> --create-hive-table /
> --hive-database hive /
> --hive-import /
> --hive-overwrite /
> --hive-table stu_import2 /
> --mapreduce-job-name FromMySQL2HIVE2 /
> --delete-target-dir /
> --fields-terminated-by '/t' /
> -m 1 /
> --null-non-string 0 /
> --hive-partition-key dt /
> --hive-partition-value "2018-08-08"
# Hive中查看
hive> select * from stu_import2;
OK
1001    lodd    23      2018-08-08
1002    sdfs    21      2018-08-08
1003    sdfsa   24      2018-08-08
Time taken: 0.192 seconds, Fetched: 3 row(s)
8.sqoop job的使用

sqoop job可以将执行的语句变成一个job，并不是在创建语句的时候执行，你可以查看该job，可以任何时候执行该job，也可以删除job，这样就方便我们进行任务的调度。

--create <job-id> 创建一个新的job.
--delete <job-id> 删除job
--exec <job-id> 执行job
--show <job-id> 显示job的参数
--list 列出所有的job

# 创建job
[hadoop@hadoop000 ~]$ sqoop job --create person_job1 -- import --connect jdbc:mysql://localhost:3306/test /
> --username root /
> --password 123456 /
> --table students_demo /
> -m 1 /
> --delete-target-dir
# 查看job
[hadoop@hadoop000 ~]$ sqoop job --list
Available jobs:
  person_job1
# 执行job 会提示输入mysql root用户密码
[hadoop@hadoop000 ~]$ sqoop job --exec person_job1
# HDFS查看
[hadoop@hadoop000 lib]$ hadoop fs -ls /user/hadoop/students_demo
Found 2 items
-rw-r--r--   1 hadoop supergroup          0 2018-07-04 15:34 /user/hadoop/students_demo/_SUCCESS
-rw-r--r--   1 hadoop supergroup         40 2018-07-04 15:34 /user/hadoop/students_demo/part-m-00000

我们发现执行person_job的时候，需要输入数据库的密码，怎么样能不输入密码呢
配置sqoop-site.xml即可解决

# 将sqoop.metastore.client.record.password参数的注释去掉 或者再添加一下
[hadoop@hadoop000 conf]$ pwd
/home/hadoop/app/sqoop-1.4.6-cdh6.7.0/conf
[hadoop@hadoop000 conf]$ vi sqoop-site.xml
  <property>
    <name>sqoop.metastore.client.record.password</name>
    <value>true</value>
    <description>If true, allow saved passwords in the metastore.
    </description>
  </property>

参考文章：https://blog.csdn.net/yu0_zhang0/article/details/79069251

原创文章，作者：Maggie-Hunter，如若转载，请注明出处：https://blog.ytso.com/tech/opensource/196843.html

赞 (0)
0 0
上一篇 2021年11月16日 23:54
下一篇 2021年11月16日 23:54

相关推荐

发表回复

登录后才能评论