Sqoop开荒

左手的ㄟ右手 2023-02-14 10:21 80阅读 0赞

### 文章目录 ###

*  Sqoop 简介
 *   *  Sqoop官方介绍
 *  Sqoop1 使用教程
 *   *  Sqoop help
     *  基本操作
     *   *   *  1列出数据库
             *  2列出表
             *  3 Table导入到HDFS
             *  4 指定字段
             *  5 import 条件过滤
             *  6 SQL嵌入
             *  7 增量式抽取
             *  8 Options-file 的使用
     *  Hive
     *   *   *  HDFS 导出到 Mysql

# Sqoop 简介 #

开源 工具

RDBMS---------------------------sqoop---------------------------->HDFS

Sqoop前:  
RDBMS----->Hadoop

MR: DBinputformat------------TestOutputFormat

Hadoop------>RDBMS

MR：TestInputFormat--------->DBOutputFormat

**MR存在的问题**

*  MapReduce麻烦
 *  效率低（一个MR只能对应一个业务线）

**基于MR存在的问题**，抽取出一个框架，需要自定义：

*  Driver
 *  username
 *  password
 *  url
 *  DB/table/sql
 *  hdfs path
 *  mapper’s

**接入到框架之后**

新的业务线接入只需要传入参数递给MR即可

*  hadoop jar的方式来提交
 *  动态的根据业务线传入参数

后期可以采用Spring Boot微服务构建大数据平台

## Sqoop官方介绍 ##

Apache Sqoop™ is a tool designed for efficiently transferring bulk data between Apache Hadoop and structured datastores such as relational databases.

Sqoop successfully graduated from the Incubator in March of 2012 and is now a Top-Level Apache project: More information

Latest stable release is 1.4.7 (download, documentation). Latest cut of Sqoop2 is 1.99.7 (download, documentation). Note that 1.99.7 is not compatible with 1.4.7 and not feature complete, it is not intended for production deployment.

**Sqoop : SQL - to - Hadoop**

RDBMS <---------sqoop-----------> Hadoop（HDFS/Hive）

底层：一个读写操作，只需要map就能搞定 不需要reduce

**Sqoop的两个版本 1.X 2.X(1.99.X)**

**Sqoop 1 架构图**

只用到了Map task ，没用到Recude  
![在这里插入图片描述][watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L3dlaXhpbl8zOTM4MTgzMw_size_16_color_FFFFFF_t_70]  
**Sqoop 2(1.99.x)架构图**

recude也用到了  
![在这里插入图片描述][watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L3dlaXhpbl8zOTM4MTgzMw_size_16_color_FFFFFF_t_70 1]

/opt/cloudera/parcels/CDH-6.3.1-1.cdh6.3.1.p0.1470567/bin/../lib/sqoop/../accumulo does not exist
    /opt/cloudera/parcels/CDH-5.12.1-1.cdh5.12.1.p0.3/lib/sqoop/
    解压后放到 sqoop home 的 lib 文件夹下

# Sqoop1 使用教程 #

## Sqoop help ##

## 基本操作 ##

#### 1列出数据库 ####

sqoop list-databases \
    --connect jdbc:mysql://10.103.66.88:3306 \
    --username name \
    --password password

#### 2列出表 ####

sqoop list-tables \
    --connect jdbc:mysql://10.103.66.88:3306/information_schema \
    --username \
    --password

#### 3 Table导入到HDFS ####

sqoop import \
    --connect jdbc:mysql://10.103.66.88:3306/lenovosbom \
    --username xingwj1 \
    --password xingwj1 \
    --table ec

![在这里插入图片描述][20200602202118684.png]  
由于MySQL表中没有主键，出现了错误

需要用 --split-by 指定主键
    或者是 -m 1 顺序导入,没有主键的话推荐这种方式

sqoop import \
    --connect jdbc:mysql://10.103.66.88:3306/lenovosbom \
    --username xingwj1 \
    --password xingwj1 \
    --table ec \
    -m 1

导入成功  
![在这里插入图片描述][20200618171727658.png]  
**尝试一下指定主键**  
使用–direct确实会变快 但是主键会被打乱

sqoop import \
    --connect jdbc:mysql://10.103.66.88:3306/lenovosbom \
    --username xingwj1 \
    --password xingwj1 \
    --table ec \
    --split-by OldPart

已经存在此表  
![在这里插入图片描述][20200618173125517.png]  
先删掉

hadoop fs -rmr ec

![在这里插入图片描述][20200618173736657.png]  
再次指定主键导入  
![在这里插入图片描述][20200618174606963.png]  
导入HDFS是文本格式的，所以要加入 allow\_text\_splitter=ture

导入成功

File Output Format Counters 
    		Bytes Written=16546
    20/06/18 17:47:34 INFO mapreduce.ImportJobBase: Transferred 16.1582 KB in 17.0518 seconds (970.3367 bytes/sec)
    20/06/18 17:47:34 INFO mapreduce.ImportJobBase: Retrieved 523 records.

![在这里插入图片描述][watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L3dlaXhpbl8zOTM4MTgzMw_size_16_color_FFFFFF_t_70 2]  
**删除（覆盖）模式 自动删除以前的同名**  
![在这里插入图片描述][20200618183436303.png]

实现了覆盖  
![在这里插入图片描述][watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L3dlaXhpbl8zOTM4MTgzMw_size_16_color_FFFFFF_t_70 3]  
![在这里插入图片描述][watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L3dlaXhpbl8zOTM4MTgzMw_size_16_color_FFFFFF_t_70 4]  
**设置MR作业的名称**  
Yarn的名字都为ec.jar 尝试修改  
![在这里插入图片描述][20200618194957178.png]

![在这里插入图片描述][watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L3dlaXhpbl8zOTM4MTgzMw_size_16_color_FFFFFF_t_70 5]

#### 4 指定字段 ####

![在这里插入图片描述][20200618200443507.png]

sqoop import "-Dorg.apache.sqoop.splitter.allow_text_splitter=true" \
    --connect jdbc:mysql://10.103.66.88:3306/lenovosbom \
    --username xingwj1 \
    --password xingwj1 \
    --table ec \
    --split-by OldPart \
    --delete-target-dir \
    --mapreduce-job-name Test_name \
    --columns "OldPart,NewPart"

**查看HDFS文件目录**

hadoop fs -ls /user/root/ec

**HDFS查看文本**

hadoop fs -text ec/part-m-00000

![在这里插入图片描述][watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L3dlaXhpbl8zOTM4MTgzMw_size_16_color_FFFFFF_t_70 6]  
**指定导入到HDFS的路径**  
![在这里插入图片描述][20200618210951720.png]

![在这里插入图片描述][watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L3dlaXhpbl8zOTM4MTgzMw_size_16_color_FFFFFF_t_70 7]  
**指定Map数量（默认4个）**  
![在这里插入图片描述][20200618211504635.png]

只有一个Map任务（-m 指定1）  
![在这里插入图片描述][watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L3dlaXhpbl8zOTM4MTgzMw_size_16_color_FFFFFF_t_70 8]

#### 5 import 条件过滤 ####

![在这里插入图片描述][20200618212130655.png]

注意： “ ’ ’ ”where条件要用  
![在这里插入图片描述][20200618213040659.png]

#### 6 SQL嵌入 ####

![在这里插入图片描述][20200618213200530.png]

![在这里插入图片描述][20200618223406860.png]  
指定了query就不能再指定table

sqoop import "-Dorg.apache.sqoop.splitter.allow_text_splitter=true" \
    --connect jdbc:mysql://10.103.66.88:3306/lenovosbom \
    --username xingwj1 \
    --password xingwj1 \
    --split-by OldPart \
    --delete-target-dir \
    --mapreduce-job-name Test_name \
    --columns "OldPart,NewPart" \
    --target-dir Test_dir \
    --query "SELECT * FROM `ec` where NewPart = '01YR067'"

![在这里插入图片描述][watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L3dlaXhpbl8zOTM4MTgzMw_size_16_color_FFFFFF_t_70 9]

sqoop import "-Dorg.apache.sqoop.splitter.allow_text_splitter=true" \
    --connect jdbc:mysql://10.103.66.88:3306/lenovosbom \
    --username xingwj1 \
    --password xingwj1 \
    --split-by OldPart \
    --delete-target-dir \
    --mapreduce-job-name Test_name \
    --columns "OldPart,NewPart" \
    --target-dir Test_dir \
    --query "SELECT * FROM `ec` where NewPart = '01YR067'and \$CONDITIONS"

使用转义\\ 后仍不可以  
![在这里插入图片描述][20200618225247515.png]  
**1 使用单引号 并用\`\`(1左边)括起来**

sqoop import "-Dorg.apache.sqoop.splitter.allow_text_splitter=true" \
    --connect jdbc:mysql://10.103.66.88:3306/lenovosbom \
    --username xingwj1 \
    --password xingwj1 \
    --split-by OldPart \
    --delete-target-dir \
    --mapreduce-job-name Test_name \
    --columns "OldPart,NewPart" \
    --target-dir Test_dir \
    --query 'SELECT * FROM ec `$CONDITIONS`'

版本问题，目前看来只有上面一种方法

**设置分隔符**  
![在这里插入图片描述][20200619100756965.png]

sqoop import "-Dorg.apache.sqoop.splitter.allow_text_splitter=true" \
    --connect jdbc:mysql://10.103.66.88:3306/lenovosbom \
    --username xingwj1 \
    --password xingwj1 \
    --split-by OldPart \
    --delete-target-dir \
    --mapreduce-job-name Test_name \
    --m 1 \
    --target-dir Test_dir \
    --query 'SELECT * FROM eccase `$CONDITIONS`' \
    --fields-terminated-by '\t'

![x][]  
**null值替换**  
![在这里插入图片描述][watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L3dlaXhpbl8zOTM4MTgzMw_size_16_color_FFFFFF_t_70 10]

sqoop import "-Dorg.apache.sqoop.splitter.allow_text_splitter=true" \
    --connect jdbc:mysql://10.103.66.88:3306/lenovosbom \
    --username xingwj1 \
    --password xingwj1 \
    --split-by OldPart \
    --delete-target-dir \
    --mapreduce-job-name Test_name \
    --m 1 \
    --target-dir Test_dir \
    --query 'SELECT * FROM eccase `$CONDITIONS`' \
    --fields-terminated-by '\t' \
    --null-non-string ' ' \
    -null-string '0'

![在这里插入图片描述][watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L3dlaXhpbl8zOTM4MTgzMw_size_16_color_FFFFFF_t_70 11]

#### 7 增量式抽取 ####

![在这里插入图片描述][watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L3dlaXhpbl8zOTM4MTgzMw_size_16_color_FFFFFF_t_70 12]

sqoop import "-Dorg.apache.sqoop.splitter.allow_text_splitter=true" \
    --connect jdbc:mysql://10.103.66.88:3306/lenovosbom \
    --username xingwj1 \
    --password xingwj1 \
    --table sbom_total \
    --split-by id \
    --mapreduce-job-name Test_name \
    --target-dir Test_dir \
    --m 1 \
    --check-column id \
    --incremental append \
    --last-value 5

![在这里插入图片描述][watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L3dlaXhpbl8zOTM4MTgzMw_size_16_color_FFFFFF_t_70 13]  
**eval 执行SQL 展示结果**

sqoop eval "-Dorg.apache.sqoop.splitter.allow_text_splitter=true" \
    --connect jdbc:mysql://10.103.66.88:3306/lenovosbom \
    --username xingwj1 \
    --password xingwj1 \
    -e "select * from ec "

![在这里插入图片描述][watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L3dlaXhpbl8zOTM4MTgzMw_size_16_color_FFFFFF_t_70 14]

#### 8 Options-file 的使用 ####

options-file可以保存一系列配置

编辑options-file

import 
    "-Dorg.apache.sqoop.splitter.allow_text_splitter=true" 
    --connect 
    jdbc:mysql://10.103.66.88:3306/lenovosbom 
    --username 
    xingwj1 
    --password 
    xingwj1 
    --delete-target-dir

执行options-file

sqoop --options-file /home/ETL/test/88.txt --table ec -m1

## Hive ##

Hive arguments:
       --create-hive-table                         Fail if the target hive
                                                   table exists
       --external-table-dir <hdfs path>            Sets where the external
                                                   table is in HDFS
       --hive-database <database-name>             Sets the database name to
                                                   use when importing to hive
       --hive-delims-replacement <arg>             Replace Hive record \0x01
                                                   and row delimiters (\n\r)
                                                   from imported string fields
                                                   with user-defined string
       --hive-drop-import-delims                   Drop Hive record \0x01 and
                                                   row delimiters (\n\r) from
                                                   imported string fields
       --hive-home <dir>                           Override $HIVE_HOME
       --hive-import                               Import tables into Hive
                                                   (Uses Hive's default
                                                   delimiters if none are
                                                   set.)
       --hive-overwrite                            Overwrite existing data in
                                                   the Hive table
       --hive-partition-key <partition-key>        Sets the partition key to
                                                   use when importing to hive
       --hive-partition-value <partition-value>    Sets the partition value to
                                                   use when importing to hive
       --hive-table <table-name>                   Sets the table name to use
                                                   when importing to hive
       --hs2-keytab <arg>                          The location of the keytab
                                                   of the HiveServer2 user.
       --hs2-url <arg>                             The URL to the HiveServer2.
       --hs2-user <arg>                            The user/principal for
                                                   HiveServer2.
       --map-column-hive <arg>                     Override mapping for
                                                   specific column to hive
                                                   types.

sqoop --options-file /home/ETL/test/88.txt \
    --table ec \
    -m1 \
    --hive-import \
    --create-hive-table \
    --hive-table ec_test

![在这里插入图片描述][202006192018089.png]

查看表的数据类型  
![在这里插入图片描述][watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L3dlaXhpbl8zOTM4MTgzMw_size_16_color_FFFFFF_t_70 15]

--create-hive-table 不建议使用，自动生成会导致表结构类型出错，应该手动创建

#### HDFS 导出到 Mysql ####

show create table tablename;

![在这里插入图片描述][watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L3dlaXhpbl8zOTM4MTgzMw_size_16_color_FFFFFF_t_70 16]

sqoop export "-Dorg.apache.sqoop.splitter.allow_text_splitter=true" \
    --connect 'jdbc:sqlserver://10.103.66.45:1444;databasename=test11' \
    --username data_update \
    --password 1qaz2wsx! \
    --table ib_t_wty_data_outbound \
    --fields-terminated-by '|' \
    --export-dir hdfs://ifeng01:8020/DataWarehouse/IQS_Data/IB_T_WTY_DATA_OUTBOUND/20201031

sqoop export "-Dorg.apache.sqoop.splitter.allow_text_splitter=true" \
    --connect 'jdbc:sqlserver://10.103.66.45:1444;databasename=test11' \
    --username data_update \
    --password 1qaz2wsx! \
    --table ib_t_entitlement_outbound_history_20190604_archive \
    --fields-terminated-by ',' \
    --export-dir hdfs://ifeng01:8020/user/hive/warehouse/st_iqs.db/ib_t_entitlement_outbound_history_20190604_archive/IB_T_ENTITLEMENT_OUTBOUND_HISTORY_20190604_ARCHIVE_04.txt

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