Sqoop-1.4.7-部署与常见案例
该文章是基于 、 进行的
1. 前言
在一个完整的大数据处理系统中,除了hdfs+mapreduce+hive组成分析系统的核心之外,还需要数据采集、结果数据导出、任务调度等不可或缺的辅助系统,而这些辅助工具在hadoop生态体系中都有便捷的开源框架,如图所示:
1.1. 概述
sqoop是apache旗下一款“Hadoop和关系数据库服务器之间传送数据”的工具。
导入数据:MySQL,Oracle导入数据到Hadoop的HDFS、HIVE、HBASE等数据存储系统;
导出数据:从Hadoop的文件系统中导出数据到关系数据库
1.3. 工作机制
将导入或导出命令翻译成mapreduce程序来实现
在翻译出的mapreduce中主要是对inputformat和outputformat进行定制
2. Sqoop的安装部署
2.1. 软件部署
1 [yun@mini01 software]$ pwd 2 /app/software 3 [yun@mini01 software]$ tar xf sqoop-1.4.7.bin__hadoop-2.6.0.tar.gz 4 [yun@mini01 software]$ mv sqoop-1.4.7.bin__hadoop-2.6.0 /app/sqoop-1.4.7 5 [yun@mini01 software]$ cd /app/ 6 [yun@mini01 ~]$ ln -s sqoop-1.4.7/ sqoop 7 [yun@mini01 ~]$ ll 8 total 28 9 ………… 10 lrwxrwxrwx 1 yun yun 12 Aug 2 11:40 sqoop -> sqoop-1.4.7/ 11 drwxr-xr-x 9 yun yun 318 Dec 19 2017 sqoop-1.4.7
2.2. 配置修改
1 [yun@mini01 conf]$ pwd 2 /app/sqoop/conf 3 [yun@mini01 conf]$ ll 4 total 32 5 -rw-rw-r-- 1 yun yun 3895 Dec 19 2017 oraoop-site-template.xml 6 -rw-rw-r-- 1 yun yun 1404 Dec 19 2017 sqoop-env-template.cmd 7 -rwxr-xr-x 1 yun yun 1345 Dec 19 2017 sqoop-env-template.sh 8 -rw-rw-r-- 1 yun yun 6044 Dec 19 2017 sqoop-site-template.xml 9 -rw-rw-r-- 1 yun yun 6044 Dec 19 2017 sqoop-site.xml 10 [yun@mini01 conf]$ cp -a sqoop-env-template.sh sqoop-env.sh 11 [yun@mini01 conf]$ cat sqoop-env.sh 12 # Licensed to the Apache Software Foundation (ASF) under one or more 13 ……………… 14 15 # Set Hadoop-specific environment variables here. 16 17 #Set path to where bin/hadoop is available # 修改的配置 18 export HADOOP_COMMON_HOME=${HADOOP_HOME} 19 20 #Set path to where hadoop-*-core.jar is available # 修改的配置 21 export HADOOP_MAPRED_HOME=${HADOOP_HOME} 22 23 #set the path to where bin/hbase is available 24 #export HBASE_HOME= 25 26 #Set the path to where bin/hive is available # 修改的配置 27 export HIVE_HOME=${HIVE_HOME} 28 29 #Set the path for where zookeper config dir is 30 #export ZOOCFGDIR=
2.3. 加入mysql的jdbc驱动包
1 [yun@mini01 software]$ pwd 2 /app/software 3 [yun@mini01 software]$ cp -a mysql-connector-java-5.1.46.jar /app/sqoop/lib
2.4. 加入hive的执行包
1 [yun@mini01 lib]$ pwd 2 /app/hive/lib 3 [yun@mini01 lib]$ cp -a hive-exec-1.2.1.jar /app/sqoop/lib/
避免出现
2.5. 验证启动
1 [yun@mini01 bin]$ pwd 2 /app/sqoop/bin 3 [yun@mini01 bin]$ ./sqoop-version 4 18/08/02 14:56:54 INFO sqoop.Sqoop: Running Sqoop version: 1.4.7 5 Sqoop 1.4.7 6 git commit id 2328971411f57f0cb683dfb79d19d4d19d185dd8 7 Compiled by maugli on Thu Dec 21 15:59:58 STD 2017 8 [yun@mini01 bin]$ ./sqoop help # 查看帮助 9 18/08/02 15:30:00 INFO sqoop.Sqoop: Running Sqoop version: 1.4.7 10 usage: sqoop COMMAND [ARGS] 11 12 Available commands: 13 codegen Generate code to interact with database records 14 create-hive-table Import a table definition into Hive 15 eval Evaluate a SQL statement and display the results 16 export Export an HDFS directory to a database table 17 help List available commands 18 import Import a table from a database to HDFS 19 import-all-tables Import tables from a database to HDFS 20 import-mainframe Import datasets from a mainframe server to HDFS 21 job Work with saved jobs 22 list-databases List available databases on a server 23 list-tables List available tables in a database 24 merge Merge results of incremental imports 25 metastore Run a standalone Sqoop metastore 26 version Display version information 27 28 See 'sqoop help COMMAND' for information on a specific command.
3. 数据库信息
1 # 建库 2 CREATE DATABASE sqoop_test DEFAULT CHARACTER SET utf8 ; 3 # 建账号 数据库在mini03机器上 4 grant all on sqoop_test.* to sqoop_test@'%' identified by 'sqoop_test'; 5 grant all on sqoop_test.* to sqoop_test@'mini03' identified by 'sqoop_test'; 6 # 刷新权限 7 flush privileges;
3.1. 表信息
表emp:
id |
name |
deg |
salary |
dept |
1201 |
gopal |
manager |
50000 |
TP |
1202 |
manisha |
Proof reader |
50000 |
TP |
1203 |
khalil |
php dev |
30000 |
AC |
1204 |
prasanth |
php dev |
30000 |
AC |
1205 |
kranthi |
admin |
20000 |
TP |
表emp_add:
id |
name |
deg |
salary |
1201 |
288A |
vgiri |
jublee |
1202 |
108I |
aoc |
sec-bad |
1203 |
144Z |
pgutta |
hyd |
1204 |
78B |
old city |
sec-bad |
1205 |
720X |
hitec |
sec-bad |
表emp_conn:
id |
name |
deg |
1201 |
2356742 |
gopal@tp.com |
1202 |
1661663 |
manisha@tp.com |
1203 |
8887776 |
khalil@ac.com |
1204 |
9988774 |
prasanth@ac.com |
1205 |
1231231 |
kranthi@tp.com |
4. Sqoop的数据导入
“导入工具”导入单个表从RDBMS到HDFS。表中的每一行被视为HDFS的记录。所有记录都存储为文本文件的文本数据(或者Avro、sequence文件等二进制数据)
1 $ sqoop import (generic-args) (import-args) 2 $ sqoop-import (generic-args) (import-args)
4.1. 导入表数据到HDFS
1 [yun@mini01 sqoop]$ pwd 2 /app/sqoop 3 [yun@mini01 sqoop]$ bin/sqoop import \ 4 --connect jdbc:mysql://mini03:3306/sqoop_test \ 5 --username sqoop_test \ 6 --password sqoop_test \ 7 --table emp \ 8 --m 1 9 18/08/02 15:57:55 INFO sqoop.Sqoop: Running Sqoop version: 1.4.7 10 18/08/02 15:57:55 WARN tool.BaseSqoopTool: Setting your password on the command-line is insecure. Consider using -P instead. 11 ……………… 12 18/08/02 15:58:47 INFO mapreduce.Job: map 100% reduce 0% 13 18/08/02 15:58:47 INFO mapreduce.Job: Job job_1533196573365_0001 completed successfully 14 ……………… 15 18/08/02 15:58:47 INFO mapreduce.ImportJobBase: Transferred 151 bytes in 47.2865 seconds (3.1933 bytes/sec) 16 18/08/02 15:58:47 INFO mapreduce.ImportJobBase: Retrieved 5 records.
查看导入的数据
1 [yun@mini02 ~]$ hadoop fs -ls /user/yun/emp 2 Found 2 items 3 -rw-r--r-- 2 yun supergroup 0 2018-08-02 15:58 /user/yun/emp/_SUCCESS 4 -rw-r--r-- 2 yun supergroup 151 2018-08-02 15:58 /user/yun/emp/part-m-00000 5 [yun@mini02 ~]$ hadoop fs -cat /user/yun/emp/part-m-00000 6 1201,gopal,manager,50000,TP 7 1202,manisha,Proof reader,50000,TP 8 1203,khalil,php dev,30000,AC 9 1204,prasanth,php dev,30000,AC 10 1205,kranthi,admin,20000,TP
4.2. 导入表到HDFS指定目录
1 [yun@mini01 sqoop]$ pwd 2 /app/sqoop 3 [yun@mini01 sqoop]$ bin/sqoop import --connect jdbc:mysql://mini03:3306/sqoop_test \ 4 --username sqoop_test --password sqoop_test \ 5 --target-dir /sqoop_test/table_emp/queryresult \ 6 --table emp --num-mappers 1
注意:如果没有目录,那么会创建
查看导入的数据
1 [yun@mini02 ~]$ hadoop fs -ls /sqoop_test/table_emp/queryresult 2 Found 2 items 3 -rw-r--r-- 2 yun supergroup 0 2018-08-02 17:57 /sqoop_test/table_emp/queryresult/_SUCCESS 4 -rw-r--r-- 2 yun supergroup 151 2018-08-02 17:57 /sqoop_test/table_emp/queryresult/part-m-00000 5 [yun@mini02 ~]$ hadoop fs -cat /sqoop_test/table_emp/queryresult/part-m-00000 6 1201,gopal,manager,50000,TP 7 1202,manisha,Proof reader,50000,TP 8 1203,khalil,php dev,30000,AC 9 1204,prasanth,php dev,30000,AC 10 1205,kranthi,admin,20000,TP
4.3. 导入关系表到HIVE
1 [yun@mini01 sqoop]$ pwd 2 /app/sqoop 3 [yun@mini01 sqoop]$ bin/sqoop import --connect jdbc:mysql://mini03:3306/sqoop_test \ 4 --username sqoop_test --password sqoop_test \ 5 --table emp --hive-import \ 6 --num-mappers 1 7 18/08/02 17:40:45 INFO sqoop.Sqoop: Running Sqoop version: 1.4.7 8 18/08/02 17:40:45 WARN tool.BaseSqoopTool: Setting your password on the command-line is insecure. Consider using -P instead. 9 ……………… 10 18/08/02 17:41:09 INFO mapreduce.ImportJobBase: Transferred 151 bytes in 20.6744 seconds (7.3037 bytes/sec) 11 18/08/02 17:41:09 INFO mapreduce.ImportJobBase: Retrieved 5 records. 12 18/08/02 17:41:09 INFO mapreduce.ImportJobBase: Publishing Hive/Hcat import job data to Listeners for table emp 13 18/08/02 17:41:10 INFO manager.SqlManager: Executing SQL statement: SELECT t.* FROM `emp` AS t LIMIT 1 14 18/08/02 17:41:10 WARN hive.TableDefWriter: Column salary had to be cast to a less precise type in Hive 15 18/08/02 17:41:10 INFO hive.HiveImport: Loading uploaded data into Hive 16 18/08/02 17:41:12 INFO hive.HiveImport: 17 18/08/02 17:41:12 INFO hive.HiveImport: Logging initialized using configuration in jar:file:/app/sqoop-1.4.7/lib/hive-exec-1.2.1.jar!/hive-log4j.properties 18 18/08/02 17:41:20 INFO hive.HiveImport: OK 19 18/08/02 17:41:20 INFO hive.HiveImport: Time taken: 1.677 seconds 20 18/08/02 17:41:20 INFO hive.HiveImport: Loading data to table default.emp 21 18/08/02 17:41:21 INFO hive.HiveImport: Table default.emp stats: [numFiles=1, totalSize=151] 22 18/08/02 17:41:21 INFO hive.HiveImport: OK 23 18/08/02 17:41:21 INFO hive.HiveImport: Time taken: 0.629 seconds 24 18/08/02 17:41:21 INFO hive.HiveImport: Hive import complete. 25 18/08/02 17:41:21 INFO hive.HiveImport: Export directory is contains the _SUCCESS file only, removing the directory.
查看导入的数据
1 hive (default)> show tables; 2 OK 3 emp 4 Time taken: 0.031 seconds, Fetched: 1 row(s) 5 hive (default)> select * from emp; 6 OK 7 1201 gopal manager 50000.0 TP 8 1202 manisha Proof reader 50000.0 TP 9 1203 khalil php dev 30000.0 AC 10 1204 prasanth php dev 30000.0 AC 11 1205 kranthi admin 20000.0 TP 12 Time taken: 0.489 seconds, Fetched: 5 row(s)
4.4. 导入表到HIVE指定库指定表
1 [yun@mini01 sqoop]$ pwd 2 /app/sqoop 3 [yun@mini01 sqoop]$ bin/sqoop import --connect jdbc:mysql://mini03:3306/sqoop_test \ 4 --username sqoop_test --password sqoop_test \ 5 --table emp \ 6 --delete-target-dir \ 7 --fields-terminated-by '\t' \ 8 --hive-import \ 9 --hive-database sqoop_test \ 10 --hive-table hive_emp \ 11 --num-mappers 1
注意:hive的库sqoop_test,必须先建立。否则会报:FAILED: SemanticException [Error 10072]: Database does not exist: sqoop_test
查看导入的数据
1 0: jdbc:hive2://mini01:10000> use sqoop_test; 2 No rows affected (0.049 seconds) 3 0: jdbc:hive2://mini01:10000> show tables; 4 +-----------+--+ 5 | tab_name | 6 +-----------+--+ 7 | hive_emp | 8 +-----------+--+ 9 1 row selected (0.076 seconds) 10 0: jdbc:hive2://mini01:10000> select * from hive_emp; 11 +--------------+----------------+---------------+------------------+----------------+--+ 12 | hive_emp.id | hive_emp.name | hive_emp.deg | hive_emp.salary | hive_emp.dept | 13 +--------------+----------------+---------------+------------------+----------------+--+ 14 | 1201 | gopal | manager | 50000.0 | TP | 15 | 1202 | manisha | Proof reader | 50000.0 | TP | 16 | 1203 | khalil | php dev | 30000.0 | AC | 17 | 1204 | prasanth | php dev | 30000.0 | AC | 18 | 1205 | kranthi | admin | 20000.0 | TP | 19 +--------------+----------------+---------------+------------------+----------------+--+ 20 5 rows selected (0.162 seconds)
4.5. 导入表数据子集
4.5.1. where子句的导入
1 [yun@mini01 sqoop]$ pwd 2 /app/sqoop 3 [yun@mini01 sqoop]$ bin/sqoop import --connect jdbc:mysql://mini03:3306/sqoop_test \ 4 --username sqoop_test --password sqoop_test \ 5 --table emp_add \ 6 --where "city ='sec-bad'" \ 7 --target-dir /sqoop_test/table_emp/queryresult2 \ 8 --num-mappers 1
查看导入的数据
1 [yun@mini02 ~]$ hadoop fs -ls /sqoop_test/table_emp/queryresult2 2 Found 2 items 3 -rw-r--r-- 2 yun supergroup 0 2018-08-02 19:33 /sqoop_test/table_emp/queryresult2/_SUCCESS 4 -rw-r--r-- 2 yun supergroup 72 2018-08-02 19:33 /sqoop_test/table_emp/queryresult2/part-m-00000 5 [yun@mini02 ~]$ hadoop fs -cat /sqoop_test/table_emp/queryresult2/part-m-00000 6 1202,108I,aoc,sec-bad 7 1204,78B,old city,sec-bad 8 1205,720X,hitec,sec-bad
4.5.2. query按需导入
1 [yun@mini01 sqoop]$ pwd 2 /app/sqoop 3 [yun@mini01 sqoop]$ bin/sqoop import --connect jdbc:mysql://mini03:3306/sqoop_test \ 4 --username sqoop_test --password sqoop_test \ 5 --query 'select id,name,deg from emp WHERE id>1203 and $CONDITIONS' \ 6 --split-by id \ 7 --fields-terminated-by '\t' \ 8 --target-dir /sqoop_test/table_emp/queryresult4 \ 9 --num-mappers 1
查看导入的数据
1 [yun@mini02 ~]$ hadoop fs -cat /sqoop_test/table_emp/queryresult4/part-m-00000 2 1204 prasanth php dev 3 1205 kranthi admin
4.6. 增量导入
所需参数
1 --check-column (col) 2 --incremental (mode) # mode include append and lastmodified 3 --last-value (value)
示例
1 [yun@mini01 sqoop]$ pwd 2 /app/sqoop 3 [yun@mini01 sqoop]$ bin/sqoop import --connect jdbc:mysql://mini03:3306/sqoop_test \ 4 --username sqoop_test --password sqoop_test \ 5 --table emp \ 6 --incremental append \ 7 --check-column id \ 8 --last-value 1202 \ 9 --fields-terminated-by '\t' \ 10 --target-dir /sqoop_test/table_emp/queryresult4 \ 11 --num-mappers 1
查看导入的数据
1 [yun@mini02 ~]$ hadoop fs -ls /sqoop_test/table_emp/queryresult4/ 2 Found 3 items 3 -rw-r--r-- 2 yun supergroup 0 2018-08-02 19:47 /sqoop_test/table_emp/queryresult4/_SUCCESS 4 -rw-r--r-- 2 yun supergroup 41 2018-08-02 19:47 /sqoop_test/table_emp/queryresult4/part-m-00000 5 -rw-r--r-- 2 yun supergroup 88 2018-08-02 20:16 /sqoop_test/table_emp/queryresult4/part-m-00001 6 [yun@mini02 ~]$ 7 [yun@mini02 ~]$ hadoop fs -cat /sqoop_test/table_emp/queryresult4/part-m-00000 8 1204 prasanth php dev 9 1205 kranthi admin 10 [yun@mini02 ~]$ hadoop fs -cat /sqoop_test/table_emp/queryresult4/part-m-00001 11 1203 khalil php dev 30000 AC 12 1204 prasanth php dev 30000 AC 13 1205 kranthi admin 20000 TP
5. Sqoop的数据导出
将数据从HDFS导出到RDBMS数据库
导出前,目标表必须存在于目标数据库中。
- 默认操作是从将文件中的数据使用INSERT语句插入到表中
- 更新模式下,是生成UPDATE语句更新表数据
1 $ sqoop export (generic-args) (export-args) 2 $ sqoop-export (generic-args) (export-args)
5.1. 示例
数据
1 [yun@mini02 ~]$ hadoop fs -ls /sqoop_test/table_emp/queryresult 2 Found 2 items 3 -rw-r--r-- 2 yun supergroup 0 2018-08-02 17:57 /sqoop_test/table_emp/queryresult/_SUCCESS 4 -rw-r--r-- 2 yun supergroup 151 2018-08-02 17:57 /sqoop_test/table_emp/queryresult/part-m-00000 5 [yun@mini02 ~]$ hadoop fs -cat /sqoop_test/table_emp/queryresult/part-m-00000 6 1201,gopal,manager,50000,TP 7 1202,manisha,Proof reader,50000,TP 8 1203,khalil,php dev,30000,AC 9 1204,prasanth,php dev,30000,AC 10 1205,kranthi,admin,20000,TP
1、首先需要手动创建mysql中的目标表
1 MariaDB [(none)]> use sqoop_test; 2 Database changed 3 4 MariaDB [sqoop_test]> CREATE TABLE employee ( 5 id INT NOT NULL PRIMARY KEY, 6 name VARCHAR(20), 7 deg VARCHAR(20), 8 salary INT, 9 dept VARCHAR(10)); 10 Query OK, 0 rows affected (0.00 sec) 11 12 MariaDB [sqoop_test]> show tables; 13 +----------------------+ 14 | Tables_in_sqoop_test | 15 +----------------------+ 16 | emp | 17 | emp_add | 18 | emp_conn | 19 | employee | 20 +----------------------+ 21 4 rows in set (0.00 sec)
2、然后执行导出命令
1 [yun@mini01 sqoop]$ pwd 2 /app/sqoop 3 [yun@mini01 sqoop]$ bin/sqoop export \ 4 --connect jdbc:mysql://mini03:3306/sqoop_test \ 5 --username sqoop_test --password sqoop_test \ 6 --table employee \ 7 --export-dir /sqoop_test/table_emp/queryresult/
3、验证表mysql命令行
1 MariaDB [sqoop_test]> select * from employee; 2 +------+----------+--------------+--------+------+ 3 | id | name | deg | salary | dept | 4 +------+----------+--------------+--------+------+ 5 | 1201 | gopal | manager | 50000 | TP | 6 | 1202 | manisha | Proof reader | 50000 | TP | 7 | 1203 | khalil | php dev | 30000 | AC | 8 | 1204 | prasanth | php dev | 30000 | AC | 9 | 1205 | kranthi | admin | 20000 | TP | 10 +------+----------+--------------+--------+------+ 11 5 rows in set (0.00 sec)
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