SQOOP安装及使用

SQOOP安装

1、上传并解压

tar -zxvf sqoop-1.4.7_hadoop3.X.tar.gz 

2、修改配置文件

# 切换到sqoop配置文件目录
cd /usr/local/soft/sqoop-1.4.7/conf
# 复制配置文件并重命名
cp sqoop-env-template.sh sqoop-env.sh
# vim sqoop-env.sh 编辑配置文件，并加入以下内容
export HADOOP_COMMON_HOME=/usr/local/soft/hadoop-3.1.1
export HADOOP_MAPRED_HOME=/usr/local/soft/hadoop-3.1.1# 切换到bin目录
cd /usr/local/soft/sqoop-1.4.7/bin
# vim configure-sqoop 修改配置文件，注释掉没用的内容（就是为了去掉警告信息）

3、修改环境变量

vim /etc/profile
# 将sqoop的目录加入环境变量

4、添加MySQL连接驱动

# 从HIVE中复制MySQL连接驱动到$SQOOP_HOME/lib
cp /usr/local/soft/hive-1.2.1/lib/mysql-connector-java-5.1.49.jar /usr/local/soft/sqoop-1.4.7/lib/

5、测试

# 打印sqoop版本
sqoop version

# 测试MySQL连通性
sqoop list-databases -connect jdbc:mysql://master:3306?useSSL=false -username root -password 123456

准备MySQL数据

登录MySQL数据库

mysql -u root -p123456;

创建student数据库

create database student;

切换数据库并导入数据

# mysql shell中执行
use student;
source /usr/local/soft/shell/student.sql;

另外一种导入数据的方式

# linux shell中执行
mysql -u root -p123456 student</usr/local/soft/shell/student.sql
mysql -u root -p123456 student</root/score.sql

使用Navicat运行SQL文件

也可以通过Navicat导入

导出MySQL数据库

mysqldump -u root -p123456 数据库名>任意一个文件名.sql

---

import

从传统的关系型数据库导入HDFS、HIVE、HBASE…

MySQLToHDFS

编写脚本，保存为MySQLToHDFS.conf

import
--connect 
jdbc:mysql://master:3306/student?useSSL=false
--username
root
--password
123456
--table
student
--m
2
--split-by
age
--target-dir
/sqoop/data/student1
--fields-terminated-by
','

执行脚本

sqoop --options-file MySQLToHDFS.conf

注意事项：

1、–m 表示指定生成多少个Map任务，不是越多越好，因为MySQL Server的承载能力有限

2、当指定的Map任务数>1，那么需要结合--split-by参数，指定分割键，以确定每个map任务到底读取哪一部分数据，最好指定数值型的列，最好指定主键（或者分布均匀的列=>避免每个map任务处理的数据量差别过大）

3、如果指定的分割键数据分布不均，可能导致数据倾斜问题

4、分割的键最好指定数值型的，而且字段的类型为int、bigint这样的数值型

5、编写脚本的时候，注意：例如：--username参数，参数值不能和参数名同一行

--username root  // 错误的// 应该分成两行
--username
root

6、运行的时候会报错InterruptedException，hadoop2.7.6自带的问题，忽略即可

21/01/25 14:32:32 WARN hdfs.DFSClient: Caught exception 
java.lang.InterruptedExceptionat java.lang.Object.wait(Native Method)at java.lang.Thread.join(Thread.java:1252)at java.lang.Thread.join(Thread.java:1326)at org.apache.hadoop.hdfs.DFSOutputStream$DataStreamer.closeResponder(DFSOutputStream.java:716)at org.apache.hadoop.hdfs.DFSOutputStream$DataStreamer.endBlock(DFSOutputStream.java:476)at org.apache.hadoop.hdfs.DFSOutputStream$DataStreamer.run(DFSOutputStream.java:652)

7、实际上sqoop在读取mysql数据的时候，用的是JDBC的方式，所以当数据量大的时候，效率不是很高

8、sqoop底层通过MapReduce完成数据导入导出，只需要Map任务，不需要Reduce任务

9、每个Map任务会生成一个文件

MySQLToHive

先会将MySQL的数据导出来并在HDFS上找个目录临时存放，默认为：/user/用户名/表名

然后再将数据加载到Hive中，加载完成后，会将临时存放的目录删除

编写脚本，并保存为MySQLToHIVE.conf文件

import 
--connect
jdbc:mysql://master:3306/student?useSSL=false
--username
root
--password
123456
--table
score
--fields-terminated-by
"\t"
--lines-terminated-by 
"\n"
--m
3
--split-by
student_id
--hive-import
--hive-overwrite
--create-hive-table
--hive-database
bigdata
--hive-table
score_sqoop
--delete-target-dir 

在Hive中创建testsqoop库

hive> create database testsqoop;

如果重新导入表存在，那么就需要将–create-hive-table 选项去除

如果遇到如下错误

22/04/18 09:08:42 ERROR tool.ImportTool: Import failed: java.io.IOException: java.la                                       ng.ClassNotFoundException: org.apache.hadoop.hive.conf.HiveConfat 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.jav                                       a: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:537)at org.apache.sqoop.tool.ImportTool.run(ImportTool.java:628)at org.apache.sqoop.Sqoop.run(Sqoop.java:147)at org.apache.hadoop.util.ToolRunner.run(ToolRunner.java:70)at org.apache.sqoop.Sqoop.runSqoop(Sqoop.java:183)at org.apache.sqoop.Sqoop.runTool(Sqoop.java:234)at org.apache.sqoop.Sqoop.runTool(Sqoop.java:243)at org.apache.sqoop.Sqoop.main(Sqoop.java:252)
Caused by: java.lang.ClassNotFoundException: org.apache.hadoop.hive.conf.HiveConfat java.net.URLClassLoader.findClass(URLClassLoader.java:381)at java.lang.ClassLoader.loadClass(ClassLoader.java:424)at sun.misc.Launcher$AppClassLoader.loadClass(Launcher.java:349)at java.lang.ClassLoader.loadClass(ClassLoader.java:357)at java.lang.Class.forName0(Native Method)at java.lang.Class.forName(Class.java:264)at org.apache.sqoop.hive.HiveConfig.getHiveConf(HiveConfig.java:44)... 12 more

解决办法：

cp /usr/local/soft/hive-1.2.1/lib/hive-common-1.2.1.jar  /usr/local/soft/sqoop-1.4.7/lib/

Exception in thread "main" java.lang.NoClassDefFoundError: org/apache/hadoop/hive/shims/ShimLoaderat org.apache.hadoop.hive.conf.HiveConf$ConfVars.<clinit>(HiveConf.java:368)at org.apache.hadoop.hive.conf.HiveConf.<clinit>(HiveConf.java:105)at java.lang.Class.forName0(Native Method)at java.lang.Class.forName(Class.java:264)at org.apache.sqoop.hive.HiveConfig.getHiveConf(HiveConfig.java:44)at org.apache.sqoop.hive.HiveImport.getHiveArgs(HiveImport.java:392)at org.apache.sqoop.hive.HiveImport.executeExternalHiveScript(HiveImport.java:379)at org.apache.sqoop.hive.HiveImport.executeScript(HiveImport.java:337)at org.apache.sqoop.hive.HiveImport.importTable(HiveImport.java:241)at org.apache.sqoop.tool.ImportTool.importTable(ImportTool.java:537)at org.apache.sqoop.tool.ImportTool.run(ImportTool.java:628)at org.apache.sqoop.Sqoop.run(Sqoop.java:147)at org.apache.hadoop.util.ToolRunner.run(ToolRunner.java:70)at org.apache.sqoop.Sqoop.runSqoop(Sqoop.java:183)at org.apache.sqoop.Sqoop.runTool(Sqoop.java:234)at org.apache.sqoop.Sqoop.runTool(Sqoop.java:243)at org.apache.sqoop.Sqoop.main(Sqoop.java:252)
Caused by: java.lang.ClassNotFoundException: org.apache.hadoop.hive.shims.ShimLoaderat java.net.URLClassLoader.findClass(URLClassLoader.java:381)at java.lang.ClassLoader.loadClass(ClassLoader.java:424)at sun.misc.Launcher$AppClassLoader.loadClass(Launcher.java:349)at java.lang.ClassLoader.loadClass(ClassLoader.java:357)... 17 more

cp /usr/local/soft/hive-1.2.1/lib/hive-shims* /usr/local/soft/sqoop-1.4.7/lib/

执行脚本

sqoop --options-file MySQLToHIVE.conf

–direct

加上这个参数，可以在导出MySQL数据的时候，使用MySQL提供的导出工具mysqldump，加快导出速度，提高效率

错误信息

22/04/18 09:42:33 INFO mapreduce.Job: Task Id : attempt_1650084984186_0048_m_000002_2, Status : FAILED
Error: java.io.IOException: Cannot run program "mysqldump": error=2, 没有那个文件或目录at java.lang.ProcessBuilder.start(ProcessBuilder.java:1048)at java.lang.Runtime.exec(Runtime.java:620)at java.lang.Runtime.exec(Runtime.java:485)at org.apache.sqoop.mapreduce.MySQLDumpMapper.map(MySQLDumpMapper.java:405)at org.apache.sqoop.mapreduce.MySQLDumpMapper.map(MySQLDumpMapper.java:49)at org.apache.hadoop.mapreduce.Mapper.run(Mapper.java:146)at org.apache.hadoop.mapred.MapTask.runNewMapper(MapTask.java:787)at org.apache.hadoop.mapred.MapTask.run(MapTask.java:341)at org.apache.hadoop.mapred.YarnChild$2.run(YarnChild.java:164)at java.security.AccessController.doPrivileged(Native Method)at javax.security.auth.Subject.doAs(Subject.java:422)at org.apache.hadoop.security.UserGroupInformation.doAs(UserGroupInformation.java:1758)at org.apache.hadoop.mapred.YarnChild.main(YarnChild.java:158)
Caused by: java.io.IOException: error=2, 没有那个文件或目录at java.lang.UNIXProcess.forkAndExec(Native Method)at java.lang.UNIXProcess.<init>(UNIXProcess.java:247)at java.lang.ProcessImpl.start(ProcessImpl.java:134)at java.lang.ProcessBuilder.start(ProcessBuilder.java:1029)... 12 more

解决办法：

需要将master上的/usr/bin/mysqldump分发至 node1、node2的/usr/bin目录下

scp /usr/bin/mysqldump node1:/usr/bin/
scp /usr/bin/mysqldump node2:/usr/bin/

-e参数的使用

import 
--connect 
jdbc:mysql://master:3306/student?useSSL=false
--username 
root 
--password 
123456 
--m 
2 
--split-by 
student_id 
--e 
"select * from score where student_id=1500100011 and $CONDITIONS" 
--fields-terminated-by 
"\t" 
--lines-terminated-by 
"\n" 
--target-dir 
/testQ 
--hive-import 
--hive-overwrite 
--create-hive-table 
--hive-database 
testsqoop 
--hive-table 
score2

分析导入日志：

22/04/18 10:24:34 INFO manager.MySQLManager: Preparing to use a MySQL streaming resultset.
22/04/18 10:24:34 INFO tool.CodeGenTool: Beginning code generation
Mon Apr 18 10:24:34 CST 2022 WARN: Establishing SSL connection without server's identity verification is not recommended. According to MySQL 5.5.45+, 5.6.26+ and 5.7.6+ requirements SSL connection must be established by default if explicit option isn't set. For compliance with existing applications not using SSL the verifyServerCertificate property is set to 'false'. You need either to explicitly disable SSL by setting useSSL=false, or set useSSL=true and provide truststore for server certificate verification.
22/04/18 10:24:34 INFO manager.SqlManager: Executing SQL statement: select * from score where student_id=1500100011 and  (1 = 0)
22/04/18 10:24:34 INFO manager.SqlManager: Executing SQL statement: select * from score where student_id=1500100011 and  (1 = 0)
22/04/18 10:24:34 INFO manager.SqlManager: Executing SQL statement: select * from score where student_id=1500100011 and  (1 = 0)
22/04/18 10:24:34 INFO orm.CompilationManager: HADOOP_MAPRED_HOME is /usr/local/soft/hadoop-2.7.6

解释：

​ 其中的三条SQL语句是为了检查SQL语句是否正确

BoundingValsQuery: SELECT MIN(student_id), MAX(student_id) FROM (select * from score where student_id=1500100011 and  (1 = 1) ) AS t1

MySQLToHBase

编写脚本，并保存为MySQLToHBase.conf

import 
--connect 
jdbc:mysql://master:3306/student?useSSL=false
--username 
root 
--password 
123456
--table 
student
--hbase-table 
stu 
--hbase-create-table 
--hbase-row-key 
id 
--m 
1
--column-family 
cf1

在HBase中创建student表

create 'stu','cf1'

执行脚本

sqoop --options-file MySQLToHBase.conf

export

HDFSToMySQL

编写脚本，并保存为HDFSToMySQL.conf

export
--connect
jdbc:mysql://master:3306/student?useSSL=false&useUnicode=true&characterEncoding=utf-8
--username
root
--password
123456
--table
student2
-m
1
--columns
id,name,age,gender,clazz
--export-dir
/sqoop/data/student1
--fields-terminated-by 
','

先清空MySQL student表中的数据，不然会造成主键冲突

执行脚本

sqoop --options-file HDFSToMySQL.conf

查看sqoop help

sqoop help21/04/26 15:50:36 INFO sqoop.Sqoop: Running Sqoop version: 1.4.6
usage: sqoop COMMAND [ARGS]Available commands:codegen            Generate code to interact with database recordscreate-hive-table  Import a table definition into Hiveeval               Evaluate a SQL statement and display the resultsexport             Export an HDFS directory to a database tablehelp               List available commandsimport             Import a table from a database to HDFSimport-all-tables  Import tables from a database to HDFSimport-mainframe   Import datasets from a mainframe server to HDFSjob                Work with saved jobslist-databases     List available databases on a serverlist-tables        List available tables in a databasemerge              Merge results of incremental importsmetastore          Run a standalone Sqoop metastoreversion            Display version informationSee 'sqoop help COMMAND' for information on a specific command.

# 查看import的详细帮助
sqoop import --help

分区导入

-- 创建分区表
CREATE TABLE `partition_student`(`id` int, `name` string, `age` int, `gender` string, `clazz` string, `last_mod` string)COMMENT 'Imported by sqoop on 2023/10/20 14:52:43'partitioned by(dt string)ROW FORMAT SERDE 'org.apache.hadoop.hive.serde2.lazy.LazySimpleSerDe' WITH SERDEPROPERTIES ( 'field.delim'='\t', 'line.delim'='\n', 'serialization.format'='\t');

import 
--connect 
jdbc:mysql://master:3306/student?useSSL=false
--username 
root 
--password 
123456 
--m 
2 
--split-by 
id 
--e 
"SELECT * FROM student2 WHERE substr(last_mod,1,11) = '2023-10-21' and $CONDITIONS"
--fields-terminated-by 
"\t" 
--lines-terminated-by 
"\n" 
--target-dir 
/testQ 
--hive-import 
--hive-database 
testsqoop 
--hive-table 
partition_student
--hive-partition-key
dt
--hive-partition-value
2023-10-21

sqoop --options-file insert_10_21_partition_mysql2hive.conf

增量导入

#  模拟做全量数据导入：
sqoop import \
--connect 'jdbc:mysql://master:3306/student?useSSL=false' \
--username root \
--password 123456 \
--e "select * from student2 where id <= 1500100990 and \$CONDITIONS" \
--target-dir /sqoop/incremental/student \
--m 2 \
--split-by id \
--fields-terminated-by ',' \#  增量导入
sqoop import \
--connect 'jdbc:mysql://master:3306/student?useSSL=false' \
--username root \
--password 123456 \
--table student2 \
--target-dir /sqoop/incremental/student \
--m 2 \
--split-by id \
--fields-terminated-by ',' \
--incremental append \
--check-column id \
--last-value 1500100990

**注意：对于sqoop可以直接使用命令模式加上参数，同时参数和参数值在同一行 末尾使用 \ 表示当前行的命令未结束，下一行继续编辑 同时 --e 参数中的 $ 需要使用反斜杠将其取消转义 **

# 模拟做全量数据导入：
sqoop import \
--connect 'jdbc:mysql://master:3306/student?useSSL=false' \
--username root \
--password 123456 \
--e "select * from student2 where last_mod <= '2023-10-20 14:34:12' and \$CONDITIONS" \
--target-dir /sqoop/incremental/student2 \
--m 2 \
--split-by id \
--fields-terminated-by ',' # 针对时间字段进行做增量合并操作
sqoop import \
--connect 'jdbc:mysql://master:3306/student?useSSL=false' \
--username root \
--driver com.mysql.jdbc.Driver \
--password 123456 \
--table student2 \
--target-dir /sqoop/incremental/student2 \
--split-by id \
--m 2 \
--fields-terminated-by ',' \
--incremental lastmodified \
--check-column last_mod \
--last-value "2023-10-20 14:34:20" \
--merge-key \
id

**merge-key是针对某个ID进行合并 将时间戳最大的进行保存 --last-value 指定上一次最大时间 在做查询时日志中 SQL查询语句为where last_mode >= ‘2023-10-20 14:34:20’ **