用Kettle的一套流程完成对整个数据库迁移

Love The Way You Lie 2021-12-21 12:39 349阅读 0赞

转自：  [https://blog.csdn.net/maenlai0086/article/details/80829143][https_blog.csdn.net_maenlai0086_article_details_80829143]

[Kettle日常使用汇总整理][Kettle]：[https://www.cnblogs.com/lsy-blogs/p/8268318.html][Kettle]

pentaho kettle 实现数据库间增量同步: [https://blog.csdn.net/zhangweicsdn/article/details/51008025][https_blog.csdn.net_zhangweicsdn_article_details_51008025]

Kettle使用\_4 Excel批量数据输入: [https://blog.csdn.net/shenliang1985/article/details/80026509][https_blog.csdn.net_shenliang1985_article_details_80026509]

kettle案例六数据表关联--排序记录-记录集连接-过滤记录: [https://blog.csdn.net/zzq900503/article/details/78962029][https_blog.csdn.net_zzq900503_article_details_78962029]

kettle抽取——多平台汇总数据仓库: [https://blog.csdn.net/qq\_35318838/article/details/66974575][https_blog.csdn.net_qq_35318838_article_details_66974575]

kettle 入门 案例（一） 实现不同数据库不同表 的数据同步: [https://blog.csdn.net/weixin\_42354570/article/details/88914671][https_blog.csdn.net_weixin_42354570_article_details_88914671]

Kettle完成不同数据库的表迁移: [https://blog.csdn.net/feng19821209/article/details/8257648][https_blog.csdn.net_feng19821209_article_details_8257648]

kettle数据库的表: [https://blog.csdn.net/qq\_22994783/article/details/82657469][https_blog.csdn.net_qq_22994783_article_details_82657469]

kettle表输入总是报数据库连接不上或者connection reset: [https://blog.csdn.net/niu\_hao/article/details/49022535][https_blog.csdn.net_niu_hao_article_details_49022535]

Kettle入门之二 Kettle应用场景（只增量插入）: [https://www.jianshu.com/p/eb6c0d55bb2c][https_www.jianshu.com_p_eb6c0d55bb2c]

Kettle批量操作流程使用（二）---多个数据源单表批量操作:  [https://blog.csdn.net/wangxiaotaolhc/article/details/79315834][https_blog.csdn.net_wangxiaotaolhc_article_details_79315834]

kettle 入门 案例（二） 实现多表连接查询，数据同步到一个表: [https://blog.csdn.net/weixin\_42354570/article/details/88962722][https_blog.csdn.net_weixin_42354570_article_details_88962722]

KETTLE实现循环批量多表抽取添加字段: [https://blog.csdn.net/qq\_36688928/article/details/90447358][https_blog.csdn.net_qq_36688928_article_details_90447358]

Kettle实现动态SQL:  [http://blog.itpub.net/29254281/viewspace-1270110][http_blog.itpub.net_29254281_viewspace-1270110]

KETTLE实现循环批量多表抽取添加字段: [https://blog.csdn.net/qq\_36688928/article/details/90447358][https_blog.csdn.net_qq_36688928_article_details_90447358]

KETTLE实现循环批量多表抽取添加字段:  [https://blog.csdn.net/qq\_36688928/article/details/90447358][https_blog.csdn.net_qq_36688928_article_details_90447358]

Kettle批量操作流程使用（一）---单个数据源多表批量操作:  [https://blog.csdn.net/wangxiaotaolhc/article/details/79310732][https_blog.csdn.net_wangxiaotaolhc_article_details_79310732]

kettle实现数据库迁移----多表复制向导:  [https://www.cnblogs.com/xqzt/p/5637033.html][https_www.cnblogs.com_xqzt_p_5637033.html]

kettle中如何实现表的批量同步：\[1\]全量同步:  [https://jingyan.baidu.com/article/215817f7e897a21eda142317.html][https_jingyan.baidu.com_article_215817f7e897a21eda142317.html]

Kettle入门之七 Kettle应用场景（多表级联）:  [https://www.jianshu.com/p/b017c5c9234f][https_www.jianshu.com_p_b017c5c9234f]

[使用kettle实现两张表的数据更新][kettle]:    [https://www.cnblogs.com/meng70345/p/3799055.html][kettle]

kettle 批量抽取多个表数据:  [https://blog.csdn.net/qq\_35318838/article/details/53322530][https_blog.csdn.net_qq_35318838_article_details_53322530]

kettle 批量抽取多个表数据: [https://blog.csdn.net/qq\_35318838/article/details/53322530][https_blog.csdn.net_qq_35318838_article_details_53322530]

kettle简单的多表数据同步【只同步数据，不建表】: [https://blog.csdn.net/sky08050025/article/details/79608231][https_blog.csdn.net_sky08050025_article_details_79608231]

kettle 多表查询大量数据同步 mysql 分页实现: [https://blog.csdn.net/chensirbbk/article/details/80760111][https_blog.csdn.net_chensirbbk_article_details_80760111]

Kettle：Oracle多表格批量同步数据=》mysql: [http://blog.itpub.net/10009036/viewspace-2169029/][http_blog.itpub.net_10009036_viewspace-2169029]

KETTLE实现循环批量多表抽取添加字段: [https://blog.csdn.net/qq\_41704358/article/details/79519133][https_blog.csdn.net_qq_41704358_article_details_79519133]

kettle 多表级联 将多个表格的查询的数据插入到一个表格中:  [https://blog.csdn.net/bird\_tp/article/details/83784017][https_blog.csdn.net_bird_tp_article_details_83784017]

kettle实现数据库迁移----多表复制向导:  [https://blog.csdn.net/ncepuzhuang/article/details/41556623][https_blog.csdn.net_ncepuzhuang_article_details_41556623]

编写kettle当中的java脚本获取多个数据库中表的数据:  [http://www.pianshen.com/article/5317198611/][http_www.pianshen.com_article_5317198611]

编写kettle当中的java脚本获取多个数据库中表的数据:   [https://blog.csdn.net/gjq2267787274/article/details/50015563][https_blog.csdn.net_gjq2267787274_article_details_50015563]

Kettle (2) - 抽取数据库表的数据:   [https://www.jianshu.com/p/3537ec697495][https_www.jianshu.com_p_3537ec697495]

Kettle 实现mysql数据库不同表之间数据同步——实验过程:  [https://www.bbsmax.com/A/QV5Zj3725y/][https_www.bbsmax.com_A_QV5Zj3725y]

Kettle入门之七 Kettle应用场景（多表级联）:   [https://blog.csdn.net/weixin\_34221332/article/details/86846513][https_blog.csdn.net_weixin_34221332_article_details_86846513]

kettle教程2（不同数据库表结构复制）:    [https://blog.csdn.net/qq\_40887813/article/details/80337163][https_blog.csdn.net_qq_40887813_article_details_80337163]

[Kettle 实现mysql数据库不同表之间数据同步——实验过程][Kettle _mysql]:    [https://www.cnblogs.com/inuyasha1027/p/kettle\_mysql\_dataSynchronize.html][Kettle _mysql]

使用kettle跨库同步表数据:    [https://blog.csdn.net/fantasic\_van/article/details/77864517][https_blog.csdn.net_fantasic_van_article_details_77864517]

Kettle完成不同数据库的表迁移: [https://blog.csdn.net/feng19821209/article/details/8257648][https_blog.csdn.net_feng19821209_article_details_8257648]

kettle 通过表名批量同步: [https://blog.csdn.net/xufan601391682/article/details/78732025][https_blog.csdn.net_xufan601391682_article_details_78732025]

编写kettle当中的java脚本获取多个数据库中表的数据: [https://blog.csdn.net/maenlai0086/article/details/80826532][https_blog.csdn.net_maenlai0086_article_details_80826532]

转自：http://blog.csdn.net/Ctrain/article/details/70432078

[ETL工具—Kettle数据的导入导出—批量Excel表到数据库][ETL_Kettle_Excel]:  [https://www.cnblogs.com/dsjxmz/p/6888502.html][ETL_Kettle_Excel]

kettle学习，多表关联数据抽取一： [https://blog.csdn.net/dear\_Alice\_moon/article/details/93716811][https_blog.csdn.net_dear_Alice_moon_article_details_93716811]

使用Kettle批量同步数据库表: [https://blog.csdn.net/lstcui/article/details/81664774][https_blog.csdn.net_lstcui_article_details_81664774]

kettle连接多个数据库:  [https://blog.csdn.net/suk\_java/article/details/76646785][https_blog.csdn.net_suk_java_article_details_76646785]

kettle数据源连接的集群设置: [https://blog.csdn.net/u013991521/article/details/52947581][https_blog.csdn.net_u013991521_article_details_52947581]

kettle实现数据库迁移----多表复制向导: [https://blog.csdn.net/ncepuzhuang/article/details/41556623][https_blog.csdn.net_ncepuzhuang_article_details_41556623]

kettle简单使用以及进行数据抽取同步: [https://www.jianshu.com/p/d98d7d1179c7][https_www.jianshu.com_p_d98d7d1179c7]

kettle\_动态表（每日新建表、表格式统一）数据同步: [https://blog.csdn.net/sky08050025/article/details/79608297][https_blog.csdn.net_sky08050025_article_details_79608297]

Kettle中关于多数据库链接报表或视图不存在的错误总结: [https://blog.csdn.net/m0\_37979608/article/details/77892873][https_blog.csdn.net_m0_37979608_article_details_77892873]

Kettle多个文件间共享数据库连接: [https://blog.csdn.net/gjf281/article/details/79084035][https_blog.csdn.net_gjf281_article_details_79084035]

kettle表数据同步: [https://blog.csdn.net/ls870061011/article/details/52699174][https_blog.csdn.net_ls870061011_article_details_52699174]

使用kettle跨库同步表数据:  [https://blog.csdn.net/ruiguang21/article/details/80337930][https_blog.csdn.net_ruiguang21_article_details_80337930]

[Kettle日常使用汇总整理][Kettle]: [https://www.cnblogs.com/lsy-blogs/p/8268318.html][Kettle]

kettle实现循环多表抽取postgres数据库到另外一个数据库中:    [https://blog.csdn.net/m0\_37951562/article/details/85232528][https_blog.csdn.net_m0_37951562_article_details_85232528]

[KETTLE常见问题和优化][KETTLE]: [https://www.cnblogs.com/scote/p/5918827.html][KETTLE]

kettle表数据同步：  [https://blog.csdn.net/ls870061011/article/details/52699174][https_blog.csdn.net_ls870061011_article_details_52699174]

[Kettle日常使用汇总整理][Kettle]： [https://www.cnblogs.com/lsy-blogs/p/8268318.html][Kettle]

使用kettle跨库同步表数据： [https://blog.csdn.net/ruiguang21/article/details/80337930][https_blog.csdn.net_ruiguang21_article_details_80337930]

kettle实现循环多表抽取postgres数据库到另外一个数据库中： [https://blog.csdn.net/m0\_37951562/article/details/85232528][https_blog.csdn.net_m0_37951562_article_details_85232528]

[KETTLE常见问题和优化][KETTLE]： [https://www.cnblogs.com/scote/p/5918827.html][KETTLE]

使用Kettle同步工具进行两个数据库连接的表数据的同步： [https://blog.csdn.net/alert\_java\_song/article/details/86620148][https_blog.csdn.net_alert_java_song_article_details_86620148]

kettle的并行，集群和分区： [http://f.dataguru.cn/thread-219396-1-1.html][http_f.dataguru.cn_thread-219396-1-1.html]

kettle入门(六) 之kettle抽取变量表名表： [https://blog.csdn.net/xiaohai798/article/details/45367617][https_blog.csdn.net_xiaohai798_article_details_45367617]

[采用Kettle分页处理大数据量抽取任务][Kettle 1]： [https://www.cnblogs.com/greyzeng/p/5524614.html][Kettle 1]

kettle实现循环多表抽取postgres数据库到另外一个数据库中； [https://blog.csdn.net/m0\_37951562/article/details/85232528][https_blog.csdn.net_m0_37951562_article_details_85232528]

kettle表数据同步： [https://blog.csdn.net/ls870061011/article/details/52699174][https_blog.csdn.net_ls870061011_article_details_52699174]

kettle连接多个数据库： [https://blog.csdn.net/suk\_java/article/details/76646785][https_blog.csdn.net_suk_java_article_details_76646785]

【Kettle从零开始】第三弹之Kettle数据源连接配置： [https://blog.csdn.net/rotkang/article/details/20962725][https_blog.csdn.net_rotkang_article_details_20962725]

使用kettle，查询2个数据库中的表作为输入，输出到另外表中： [https://blog.csdn.net/qq\_36698956/article/details/81353344][https_blog.csdn.net_qq_36698956_article_details_81353344]

kettle7.0下实现数据库整体迁移:  [https://blog.csdn.net/gelusheng123456/article/details/79793223][https_blog.csdn.net_gelusheng123456_article_details_79793223]

kettle —— 从一个数据库抽取数据到另一个数据库: [https://blog.csdn.net/mafan121/article/details/42918465/][https_blog.csdn.net_mafan121_article_details_42918465]

使用kettle，查询2个数据库中的表作为输入，输出到另外表中:[https://blog.csdn.net/qq\_36698956/article/details/81353344][https_blog.csdn.net_qq_36698956_article_details_81353344]

Kettle\_使用资源库功能把ktr元数据统一存储到数据库中： [https://blog.csdn.net/huangyanlong/article/details/46117065/][https_blog.csdn.net_huangyanlong_article_details_46117065]

kettle 不改变原表，通过本地辅助表记录時間戳来实际准增量更新： [https://blog.csdn.net/wangzhpwang/article/details/80749237][https_blog.csdn.net_wangzhpwang_article_details_80749237]

kettle实现不同类型数据库表结构和数据的同步： [https://blog.csdn.net/CHL521/article/details/84854131][https_blog.csdn.net_CHL521_article_details_84854131]

Kettle用多个列拆分来处理数据： [https://blog.csdn.net/txinfo/article/details/81176547][https_blog.csdn.net_txinfo_article_details_81176547]

kettle表数据同步：[https://blog.csdn.net/yu8196378/article/details/51745140][https_blog.csdn.net_yu8196378_article_details_51745140]

Kettle (4) - 跨数据库数据迁移： [https://www.jianshu.com/p/0566a10e7f44][https_www.jianshu.com_p_0566a10e7f44]

[Kettle优化就这么多][Kettle 2]: [https://www.cnblogs.com/lcword/p/9571063.html][Kettle 2]

Kettle使用\_4 Excel批量数据输入: [https://blog.csdn.net/shenliang1985/article/details/80026509][https_blog.csdn.net_shenliang1985_article_details_80026509]

pentaho kettle 实现数据库间增量同步: [https://blog.csdn.net/zhangweicsdn/article/details/51008025][https_blog.csdn.net_zhangweicsdn_article_details_51008025]

用Kettle的一套流程完成对整个数据库迁移: [https://blog.csdn.net/maenlai0086/article/details/80829143][https_blog.csdn.net_maenlai0086_article_details_80829143]

[Kettle学习系列之数据仓库、数据整合、ETL、ELT和EII之间的区别][Kettle_ETL_ELT_EII]: [https://www.cnblogs.com/zlslch/p/6906809.html][Kettle_ETL_ELT_EII]

kettle系列之常见问题: [https://blog.csdn.net/hzp666/article/details/68066341][https_blog.csdn.net_hzp666_article_details_68066341]

Kettle入门之二 Kettle应用场景（只增量插入）: [https://www.jianshu.com/p/eb6c0d55bb2c][https_www.jianshu.com_p_eb6c0d55bb2c]

[Kettle日常使用汇总整理][Kettle 3]: [https://www.cnblogs.com/nbjin/p/9707808.html][Kettle 3]

kettle表输入总是报数据库连接不上或者connection reset: [https://blog.csdn.net/niu\_hao/article/details/49022535][https_blog.csdn.net_niu_hao_article_details_49022535]

kettle数据库的表: [https://blog.csdn.net/qq\_22994783/article/details/82657469][https_blog.csdn.net_qq_22994783_article_details_82657469]

Kettle完成不同数据库的表迁移: [https://blog.csdn.net/feng19821209/article/details/8257648][https_blog.csdn.net_feng19821209_article_details_8257648]

kettle抽取——多平台汇总数据仓库: [https://blog.csdn.net/qq\_35318838/article/details/66974575][https_blog.csdn.net_qq_35318838_article_details_66974575]

kettle案例六数据表关联--排序记录-记录集连接-过滤记录: [https://blog.csdn.net/zzq900503/article/details/78962029][https_blog.csdn.net_zzq900503_article_details_78962029]

kettle案例六数据表关联--排序记录-记录集连接-过滤记录： [https://blog.csdn.net/zzq900503/article/details/78962029][https_blog.csdn.net_zzq900503_article_details_78962029]

Kettle配置数据源时加载外部properties配置文件： [https://www.jianshu.com/p/ac7c0566d782][https_www.jianshu.com_p_ac7c0566d782]

kettle —— 从一个数据库抽取数据到另一个数据库： [https://blog.csdn.net/mafan121/article/details/42918465][https_blog.csdn.net_mafan121_article_details_42918465 1]

kettle —— 从一个数据库抽取数据到另一个数据库： [https://blog.csdn.net/mafan121/article/details/42918465/][https_blog.csdn.net_mafan121_article_details_42918465]

Kettle入门之二 Kettle应用场景（只增量插入）： [https://www.jianshu.com/p/eb6c0d55bb2c][https_www.jianshu.com_p_eb6c0d55bb2c]

[Kettle优化就这么多][Kettle 2]： [https://www.cnblogs.com/lcword/p/9571063.html][Kettle 2]

kettle 入门 案例（二） 实现多表连接查询，数据同步到一个表： [https://blog.csdn.net/weixin\_42354570/article/details/88962722][https_blog.csdn.net_weixin_42354570_article_details_88962722]

Kettle\_使用资源库功能把ktr元数据统一存储到数据库中： [https://blog.csdn.net/huangyanlong/article/details/46117065/][https_blog.csdn.net_huangyanlong_article_details_46117065]

ETL工具：Kettle(Spoon)实现跨库跨表迁移不同表结构的数据： [https://blog.csdn.net/u011019141/article/details/87801843][https_blog.csdn.net_u011019141_article_details_87801843]

Kettle用多个列拆分来处理数据： [https://blog.csdn.net/txinfo/article/details/81176547][https_blog.csdn.net_txinfo_article_details_81176547]

kettle详解（数据抽取、转换、装载）： [https://blog.csdn.net/qq\_35731570/article/details/71123413][https_blog.csdn.net_qq_35731570_article_details_71123413]

KETTLE实现循环批量多表抽取添加字段： [https://blog.csdn.net/qq\_36688928/article/details/90447358][https_blog.csdn.net_qq_36688928_article_details_90447358]

kettle表数据同步： [https://blog.csdn.net/yu8196378/article/details/51745140][https_blog.csdn.net_yu8196378_article_details_51745140]

Kettle记录集连接： [https://blog.csdn.net/u014307117/article/details/79351471][https_blog.csdn.net_u014307117_article_details_79351471]

ETL工具—Kettle数据的导入导出—批量Excel表到数据库： [https://blog.csdn.net/fendou\_0123456789/article/details/88974530][https_blog.csdn.net_fendou_0123456789_article_details_88974530]

在kettle资源库中找某一个表或sql在哪个job中使用的： [https://blog.csdn.net/wang12345566/article/details/77680304][https_blog.csdn.net_wang12345566_article_details_77680304]

kettle系列之三 数据库资源库分析： [https://blog.csdn.net/wangjx92/article/details/83021394][https_blog.csdn.net_wangjx92_article_details_83021394]

kettle 数据同时插入删除问题： [https://blog.csdn.net/zhangfeng1742/article/details/78651404][https_blog.csdn.net_zhangfeng1742_article_details_78651404]

[ETL工具—Kettle数据的导入导出—Excel表到数据库][ETL_Kettle_Excel 1]： [https://www.cnblogs.com/dsjxmz/p/6884812.html][ETL_Kettle_Excel 1]

kettle 从数据库表将数据写入 hadoop hdfs： [https://blog.csdn.net/maenlai0086/article/details/81170633][https_blog.csdn.net_maenlai0086_article_details_81170633]

[kettle中含有参数传递的定时任务][kettle 1]： [https://www.cnblogs.com/OliverQin/p/5857734.html][kettle 1]

kettle常见问题及相关解决方案： [https://blog.csdn.net/maenlai0086/article/details/81347146][https_blog.csdn.net_maenlai0086_article_details_81347146]

Kettle学习， 更新表数据： [https://blog.csdn.net/dear\_Alice\_moon/article/details/91870388][https_blog.csdn.net_dear_Alice_moon_article_details_91870388]

利用Kettle完成简单的单表数据转换： [https://blog.csdn.net/u011342403/article/details/85271826][https_blog.csdn.net_u011342403_article_details_85271826]

kettle\_2自动创建数据库表： [https://blog.csdn.net/weixin\_34195364/article/details/88255718][https_blog.csdn.net_weixin_34195364_article_details_88255718]

Kettle使用统一的数据库配置：[https://blog.csdn.net/xiezhongkai08/article/details/71244528][https_blog.csdn.net_xiezhongkai08_article_details_71244528]

Kettle-根据源表（source table）数据更新情况对目标表（target table）中数据进行删除：[https://blog.csdn.net/shen\_xy/article/details/80800506][https_blog.csdn.net_shen_xy_article_details_80800506]

etl工具，kettle实现循环： [https://blog.csdn.net/lili72/article/details/39716455][https_blog.csdn.net_lili72_article_details_39716455]

kettle的数据库连接： [https://blog.csdn.net/u012848709/article/details/62044670/][https_blog.csdn.net_u012848709_article_details_62044670]

ETL工具：Kettle(Spoon)实现跨库跨表迁移不同表结构的数据： [https://blog.csdn.net/u011019141/article/details/87801843][https_blog.csdn.net_u011019141_article_details_87801843]

Kettle7.1 创建数据库资源库及常见错误解决（一）： [https://blog.csdn.net/qq\_36698956/article/details/80752618][https_blog.csdn.net_qq_36698956_article_details_80752618]

kettle中设置日志表： [https://blog.csdn.net/oufua/article/details/50917775][https_blog.csdn.net_oufua_article_details_50917775]

[Kettle日常使用汇总整理][Kettle 3]： [https://www.cnblogs.com/nbjin/p/9707808.html][Kettle 3]

Kettle下实现Excel数据导入至数据库：[https://blog.csdn.net/qiang\_hao/article/details/80032082][https_blog.csdn.net_qiang_hao_article_details_80032082]

ETL工具之Kettle的简单使用一(不同数据库之间的数据抽取-转换-加载)：[https://blog.csdn.net/weixin\_34186950/article/details/85982591][https_blog.csdn.net_weixin_34186950_article_details_85982591]

ettle (2) - 抽取数据库表的数据： [https://blog.csdn.net/weixin\_33964094/article/details/87275654][https_blog.csdn.net_weixin_33964094_article_details_87275654]

kettle 不同数据库的数据复制（sybase到mysql）： [https://blog.csdn.net/w50feng/article/details/82698283][https_blog.csdn.net_w50feng_article_details_82698283]

Kettle中根据一个输入行派生出多个输出行： [https://blog.csdn.net/kinghomes/article/details/75035724][https_blog.csdn.net_kinghomes_article_details_75035724]

kettle的并行，集群和分区： [https://blog.csdn.net/gyg1990/article/details/43242133][https_blog.csdn.net_gyg1990_article_details_43242133]

1024 的一篇博客, kettle 抽取一个database的数据到另一个database： [https://blog.csdn.net/weixin\_42144379/article/details/83347103][https_blog.csdn.net_weixin_42144379_article_details_83347103]

Kettle记录集连接： [https://blog.csdn.net/u014307117/article/details/79351471][https_blog.csdn.net_u014307117_article_details_79351471]

ETL工具—Kettle数据的导入导出—批量Excel表到数据库：[https://blog.csdn.net/fendou\_0123456789/article/details/88974530][https_blog.csdn.net_fendou_0123456789_article_details_88974530]

在kettle资源库中找某一个表或sql在哪个job中使用的: [https://blog.csdn.net/wang12345566/article/details/77680304][https_blog.csdn.net_wang12345566_article_details_77680304]

***Kettle实现数据库迁移:  ***[https://www.cnblogs.com/xqzt/p/5637032.html][https_www.cnblogs.com_xqzt_p_5637032.html]

kettle数据库表梳理: [https://blog.csdn.net/qq\_22994783/article/details/82744580][https_blog.csdn.net_qq_22994783_article_details_82744580]

oracle到mysql的多表批量数据迁移-kettle的使用: [https://blog.csdn.net/weixin\_38673554/article/details/86309928][https_blog.csdn.net_weixin_38673554_article_details_86309928]

kettle 实现字段合并插入到另一个数据表： [https://blog.csdn.net/bird\_tp/article/details/83758749][https_blog.csdn.net_bird_tp_article_details_83758749]

kettle案例-kettle分库分表导入数据： [https://blog.csdn.net/u014636209/article/details/82026392][https_blog.csdn.net_u014636209_article_details_82026392]

\[2019 ETL \] Kettle 8.2 怎么连数据库资源库： [https://blog.csdn.net/qq\_36688928/article/details/89204075][https_blog.csdn.net_qq_36688928_article_details_89204075]

kettle的数据库连接： [https://blog.csdn.net/u012848709/article/details/62044670/][https_blog.csdn.net_u012848709_article_details_62044670]

[ETL工具—Kettle数据的导入导出—Excel表到数据库][ETL_Kettle_Excel 1]： [https://www.cnblogs.com/dsjxmz/p/6884812.html][ETL_Kettle_Excel 1]

\[2019 ETL \] Kettle 8.2 怎么连数据库资源库： [https://blog.csdn.net/weixin\_37477226/article/details/87192797][https_blog.csdn.net_weixin_37477226_article_details_87192797]

用Kettle从MySQL迁移数据到Trafodion牛刀小试： [https://blog.csdn.net/post\_yuan/article/details/52804105][https_blog.csdn.net_post_yuan_article_details_52804105]

Kettle提高表输出写入速度（每秒万条记录）： [https://blog.csdn.net/qq\_37124304/article/details/82664665][https_blog.csdn.net_qq_37124304_article_details_82664665]

kettle5.3批量插入impala： [https://blog.csdn.net/maenlai0086/article/details/86699427][https_blog.csdn.net_maenlai0086_article_details_86699427]

Kettle简单应用：实现数据迁移： [https://blog.csdn.net/qq\_30258957/article/details/81464167][https_blog.csdn.net_qq_30258957_article_details_81464167]

kettle —— 数据过滤和值映射： [https://blog.csdn.net/mafan121/article/details/42920411][https_blog.csdn.net_mafan121_article_details_42920411]

KETTLE 实现三表同步的问题： [https://blog.csdn.net/qjlsw415695632/article/details/50345661][https_blog.csdn.net_qjlsw415695632_article_details_50345661]

Kettle提高表输出写入速度（每秒万条记录）： [https://blog.csdn.net/dream1120757048/article/details/82868611][https_blog.csdn.net_dream1120757048_article_details_82868611]

kettle的数据库连接： [https://blog.csdn.net/u012848709/article/details/62044670][https_blog.csdn.net_u012848709_article_details_62044670 1]

kettle 从数据库表将数据写入 hadoop hdfs： [https://blog.csdn.net/cdmamata/article/details/56846895][https_blog.csdn.net_cdmamata_article_details_56846895]

Kettle的一些常见问题： [https://blog.csdn.net/iquicksandi/article/details/7635031][https_blog.csdn.net_iquicksandi_article_details_7635031]

kettle表输出和插入/更新的区别： [https://blog.csdn.net/yks0527/article/details/90717659][https_blog.csdn.net_yks0527_article_details_90717659]

Kettle学习， 输出表数据： [https://blog.csdn.net/dear\_Alice\_moon/article/details/91890289][https_blog.csdn.net_dear_Alice_moon_article_details_91890289]

[kettle优化][kettle 2]： [https://www.cnblogs.com/kongxc/p/6580128.html][kettle 2]

Kettle自动创建同步表： [https://blog.csdn.net/gjf281/article/details/79175124][https_blog.csdn.net_gjf281_article_details_79175124]

解决 kettle 调用informix 设置数据源 查询中文乱码： [https://blog.csdn.net/chen978616649/article/details/9056311/][https_blog.csdn.net_chen978616649_article_details_9056311]

[Kettle实现遗留数据库迁移][Kettle 4]： [https://wiselyman.iteye.com/blog/2411583][Kettle 4]

使用kettle与prd定时生成pdf报表： [https://blog.kokojia.com/yyls/b-14.html][https_blog.kokojia.com_yyls_b-14.html]

干货放送:基于Kettle的数据处理实践：[http://tech.it168.com/a2015/1201/1783/000001783611.shtml][http_tech.it168.com_a2015_1201_1783_000001783611.shtml]

kettle 教程（二）：常用输出（插入更新、表输出、执行 SQL 脚本）： [https://blog.csdn.net/qqfo24/article/details/82215761?utm\_source=blogxgwz1][https_blog.csdn.net_qqfo24_article_details_82215761_utm_source_blogxgwz1]

ETL工具kettle不同字符集数据库之间抽取出现的中文乱码问题： [https://bbs.csdn.net/topics/392340967?page=1][https_bbs.csdn.net_topics_392340967_page_1]

你不知道的Kettle学习笔记2--kettle的常用操作： [https://blog.csdn.net/lin434406218/article/details/52622275][https_blog.csdn.net_lin434406218_article_details_52622275]

kettle根据主键批量更新： [https://blog.csdn.net/xufan601391682/article/details/78731966][https_blog.csdn.net_xufan601391682_article_details_78731966]

Kettle 流查询，数据库查询和Merge Join的区别：[https://blog.csdn.net/lan12334321234/article/details/70049471][https_blog.csdn.net_lan12334321234_article_details_70049471]

使用Kettle连接动态分库： [https://blog.csdn.net/wzy0623/article/details/53883505][https_blog.csdn.net_wzy0623_article_details_53883505]

ETL工具之Kettle的简单使用一(不同数据库之间的数据抽取-转换-加载)： [https://blog.csdn.net/weixin\_34186950/article/details/85982591][https_blog.csdn.net_weixin_34186950_article_details_85982591]

kettle中间表值映射： [https://blog.csdn.net/hsb\_lucky/article/details/75194966][https_blog.csdn.net_hsb_lucky_article_details_75194966]

使用Kettle实现数据实时增量同步： [https://blog.csdn.net/dora\_310/article/details/80511793][https_blog.csdn.net_dora_310_article_details_80511793]

kettle的并行，集群和分区： [https://blog.csdn.net/gyg1990/article/details/43242133][https_blog.csdn.net_gyg1990_article_details_43242133]

在kettle资源库中找某一个表或sql在哪个job中使用的： [https://blog.csdn.net/wang12345566/article/details/77680304][https_blog.csdn.net_wang12345566_article_details_77680304]

java调用kettle链接数据库操作： [https://blog.csdn.net/Jokedo/article/details/78567477][https_blog.csdn.net_Jokedo_article_details_78567477]

使用kettle把XML文档转换成数据表结构： [https://blog.csdn.net/neweastsun/article/details/39006487][https_blog.csdn.net_neweastsun_article_details_39006487]

kettle的转换里面sql脚本执行顺序以执行次数：[https://blog.csdn.net/u012848709/article/details/67679366][https_blog.csdn.net_u012848709_article_details_67679366]

学习使用kettle链接hive数据库： [https://blog.csdn.net/y\_hai\_yang/article/details/84030282][https_blog.csdn.net_y_hai_yang_article_details_84030282]

数据对接—kettle使用之六： [https://blog.csdn.net/huangaigang6688/article/details/13988149][https_blog.csdn.net_huangaigang6688_article_details_13988149]

KETTLE常见问题和优化： [https://blog.csdn.net/liufang1991/article/details/51896342][https_blog.csdn.net_liufang1991_article_details_51896342]

Kettle之“检查表是否存在”： [https://blog.csdn.net/wzy0623/article/details/53884107][https_blog.csdn.net_wzy0623_article_details_53884107]

kettle\_3添加数据库表字段： [https://blog.csdn.net/weixin\_34281477/article/details/88171636][https_blog.csdn.net_weixin_34281477_article_details_88171636]

kettle 教程（二）：常用输出（插入更新、表输出、执行 SQL 脚本）： [https://blog.csdn.net/qqfo24/article/details/82215761][https_blog.csdn.net_qqfo24_article_details_82215761]

KETTLE使用教程（包含几个小示例）： [https://blog.csdn.net/l23456789o/article/details/84589997][https_blog.csdn.net_l23456789o_article_details_84589997]

数据迁移之Kettle的使用小结： [https://blog.csdn.net/ybygjy/article/details/7478113][https_blog.csdn.net_ybygjy_article_details_7478113]

使用kettle 定时同步csv文件数据到数据库表： [https://blog.csdn.net/weixin\_33814685/article/details/88196533][https_blog.csdn.net_weixin_33814685_article_details_88196533]

在 kettle 里如何使用 JNDI 方式连接数据源： [https://blog.csdn.net/conkeyn/article/details/83679737][https_blog.csdn.net_conkeyn_article_details_83679737]

关于powerbi拖动多表关系，出现的关键字重复问题： [https://blog.csdn.net/blueboygo/article/details/77192066][https_blog.csdn.net_blueboygo_article_details_77192066]

Kettle实现Oracle到Trafodion数据定时抽取： [https://blog.csdn.net/post\_yuan/article/details/64440466][https_blog.csdn.net_post_yuan_article_details_64440466]

企业级数据单表全量增量抽取数据模型（Kettle版）： [https://blog.csdn.net/jinyusheng\_1991/article/details/83864268][https_blog.csdn.net_jinyusheng_1991_article_details_83864268]

kettle抓取网页上的数据存储到数据表中： [https://blog.csdn.net/bird\_tp/article/details/83892598][https_blog.csdn.net_bird_tp_article_details_83892598]

使用kettle交换工具自动创建oracle表分区： [https://blog.csdn.net/nuts1903/article/details/69568937][https_blog.csdn.net_nuts1903_article_details_69568937]

KETTLE- 共享数据库： [https://blog.csdn.net/weixin\_41634885/article/details/81218737][https_blog.csdn.net_weixin_41634885_article_details_81218737]

kettle\_1自动创建数据库表字段： [https://blog.csdn.net/weixin\_34293902/article/details/88228663][https_blog.csdn.net_weixin_34293902_article_details_88228663]

Kettle简单应用：实现数据迁移：[https://blog.csdn.net/qq\_30258957/article/details/81464167][https_blog.csdn.net_qq_30258957_article_details_81464167]

Kettle提高表输出写入速度（每秒万条记录）： [https://blog.csdn.net/dream1120757048/article/details/82868611][https_blog.csdn.net_dream1120757048_article_details_82868611]

kettle的数据库连接： [https://blog.csdn.net/u012848709/article/details/62044670][https_blog.csdn.net_u012848709_article_details_62044670 1]

kettle 从数据库表将数据写入 hadoop hdfs： [https://blog.csdn.net/cdmamata/article/details/56846895][https_blog.csdn.net_cdmamata_article_details_56846895]

Kettle 导入文件夹下的多个文件： [https://blog.csdn.net/paopaopotter/article/details/88692550][https_blog.csdn.net_paopaopotter_article_details_88692550]

kettle根据主键批量更新： [https://blog.csdn.net/xufan601391682/article/details/78731966][https_blog.csdn.net_xufan601391682_article_details_78731966]

Kettle 流查询，数据库查询和Merge Join的区别： [https://blog.csdn.net/lan12334321234/article/details/70049471][https_blog.csdn.net_lan12334321234_article_details_70049471]

Kettle TableInput 将从前一步骤获取参数整合到数据流中： [https://blog.csdn.net/jdk2006/article/details/51550633][https_blog.csdn.net_jdk2006_article_details_51550633]

etl kettle 执行日志输出到数据库： [https://blog.csdn.net/xiaosemei/article/details/78563146][https_blog.csdn.net_xiaosemei_article_details_78563146]

kettle的转换里面sql脚本执行顺序以执行次数： [https://blog.csdn.net/u012848709/article/details/67679366][https_blog.csdn.net_u012848709_article_details_67679366]

java调用kettle，数据源使用JNDI方式： [https://blog.csdn.net/u012848709/article/details/89044633][https_blog.csdn.net_u012848709_article_details_89044633]

kettle 数据库连接中断重置： [https://blog.csdn.net/u011750989/article/details/42237395][https_blog.csdn.net_u011750989_article_details_42237395]

[数据库数据格式化之Kettle Spoon][Kettle Spoon]： [https://www.cnblogs.com/soundcode/p/8989467.html][Kettle Spoon]

kettle详解（数据抽取、转换、装载）： [https://blog.csdn.net/u010735147/article/details/81905485][https_blog.csdn.net_u010735147_article_details_81905485]

(Kettle)合并记录步骤： [https://blog.csdn.net/an342647823/article/details/7476898][https_blog.csdn.net_an342647823_article_details_7476898]

ETL工具kettle不同字符集数据库之间抽取出现的中文乱码问题： [https://bbs.csdn.net/topics/392340967?page=1][https_bbs.csdn.net_topics_392340967_page_1]

KETTLE 实现三表同步的问题： [https://blog.csdn.net/qjlsw415695632/article/details/50345661][https_blog.csdn.net_qjlsw415695632_article_details_50345661]

kettle 数据提取效率提升： [https://blog.csdn.net/xpliruizhi123/article/details/54580850][https_blog.csdn.net_xpliruizhi123_article_details_54580850]

Kettle-7.0增量抽取订单数据： [https://blog.csdn.net/zisheng\_wang\_data/article/details/71632011][https_blog.csdn.net_zisheng_wang_data_article_details_71632011]

在Kettle里使用参照表进行数据校验（子转换实现）： [https://blog.csdn.net/wzy0623/article/details/53887111][https_blog.csdn.net_wzy0623_article_details_53887111]‘

Kettle多线程导致的抽取问题解决： [http://www.doc88.com/p-0763233945647.html][http_www.doc88.com_p-0763233945647.html]

[kettle中通过 时间戳（timestamp）方式 来实现数据库的增量同步操作（一）][kettle_ _timestamp_]： [https://www.cnblogs.com/inuyasha1027/p/Kettle\_update\_timestamp.html][kettle_ _timestamp_]

[以连接为例 说明Kettle和SQL处理数据的区别][_Kettle_SQL]： [https://www.cnblogs.com/wanggs/p/5116111.html][_Kettle_SQL]’

[Kettle6.0表输入连接数据库][Kettle6.0]： [https://www.cnblogs.com/liyunzhouts/p/6760826.html][Kettle6.0]

kettle与各数据库建立链接的链接字符串： [https://blog.csdn.net/weixin\_34331102/article/details/85724886][https_blog.csdn.net_weixin_34331102_article_details_85724886]

【Kettle从零开始】第四弹之Kettle转换数据抽取使用： [https://blog.csdn.net/rotkang/article/details/20962819][https_blog.csdn.net_rotkang_article_details_20962819]

kettle连接gbase数据库： [https://blog.csdn.net/qq\_34485930/article/details/80434519][https_blog.csdn.net_qq_34485930_article_details_80434519]

kettle数据同步例子： [https://blog.csdn.net/stubborn\_cow/article/details/49996021][https_blog.csdn.net_stubborn_cow_article_details_49996021]‘

[kettle 创建数据库资源库][kettle 3]： [https://www.cnblogs.com/jszmrx741/p/6362636.html][kettle 3]

[测试Kettle在增量更新的时候是否支持级联——不支持（基于mysql）][Kettle_mysql]： [https://www.cnblogs.com/inuyasha1027/p/kettle\_foreign\_key\_constraint\_update.html][Kettle_mysql]

Kettle:使用触发器和快照表进行增量数据同步： [https://blog.csdn.net/weixin\_34364071/article/details/85102201][https_blog.csdn.net_weixin_34364071_article_details_85102201]

【Kettle】如何输出固定格式报表： [https://blog.csdn.net/NextAction/article/details/80620708][https_blog.csdn.net_NextAction_article_details_80620708]

数据清洗------kettle将txt数据转至数据库表中： [https://blog.csdn.net/qq\_34082113/article/details/84573592][https_blog.csdn.net_qq_34082113_article_details_84573592]

Kettle总结： [https://blog.csdn.net/whaoxysh/article/details/50737687][https_blog.csdn.net_whaoxysh_article_details_50737687]

Kettle——表输出步骤异常处理方式探究： [https://blog.csdn.net/jdk2006/article/details/50531841/][https_blog.csdn.net_jdk2006_article_details_50531841]

Kettle学习笔记003之数据库连接配置： [https://blog.csdn.net/HNDX2018/article/details/83093969][https_blog.csdn.net_HNDX2018_article_details_83093969]

kettle是进行数据库连接配置,出现数据库报错： [https://blog.csdn.net/u014723529/article/details/41554417][https_blog.csdn.net_u014723529_article_details_41554417]

KETTLE整库迁移方案（SQL server迁移至Mysql，迁移过程自动创建表结构）： [https://blog.csdn.net/m0\_37213323/article/details/72538816][https_blog.csdn.net_m0_37213323_article_details_72538816]

kettle(四):kettle连接Mysql数据库，将表的数据转换成excel文件： [https://blog.csdn.net/junliucq/article/details/87901907][https_blog.csdn.net_junliucq_article_details_87901907]

数据对接—kettle使用之七： [https://blog.csdn.net/huangaigang6688/article/details/15028447][https_blog.csdn.net_huangaigang6688_article_details_15028447]

kettle 使用java脚本连接获取数据库中的值： [https://blog.csdn.net/qq\_35201754/article/details/78678011][https_blog.csdn.net_qq_35201754_article_details_78678011]

kettle与各数据库建立链接的链接字符串： [https://blog.csdn.net/weixin\_34331102/article/details/85724886][https_blog.csdn.net_weixin_34331102_article_details_85724886]

kettle中"数据库查询"与"数据库连接"步骤的区别： [https://blog.csdn.net/qklwdd6/article/details/71487808][https_blog.csdn.net_qklwdd6_article_details_71487808]

Kettle总结： [https://blog.csdn.net/whaoxysh/article/details/50737687][https_blog.csdn.net_whaoxysh_article_details_50737687]

Kettle 流查询，数据库查询和Merge Join的区别： [https://blog.csdn.net/lan12334321234/article/details/88328129][https_blog.csdn.net_lan12334321234_article_details_88328129]

转载\]kettle常见问题解决（转）： [http://blog.sina.com.cn/s/blog\_48d8cc950101bbpx.html][http_blog.sina.com.cn_s_blog_48d8cc950101bbpx.html]

KETTLE —— 表输出： [https://blog.csdn.net/Jiweilai1/article/details/86668396][https_blog.csdn.net_Jiweilai1_article_details_86668396]

Data Integration (kettle) 7.0 连接Hive： [https://www.jianshu.com/p/ec45c21a977f][https_www.jianshu.com_p_ec45c21a977f]

kettle增量同步mysql到greenplum： [https://blog.csdn.net/weixin\_42451919/article/details/89813301][https_blog.csdn.net_weixin_42451919_article_details_89813301]

kettle中设置日志表： [https://blog.csdn.net/oufua/article/details/50917775][https_blog.csdn.net_oufua_article_details_50917775]

Kettle spoon中mysql数据导入hive从建表到导数据解决方案参考： [https://blog.csdn.net/qq\_27384505/article/details/79570470][https_blog.csdn.net_qq_27384505_article_details_79570470]

关于kettle工具表新增字段同步的时候无法显示的问题： [https://blog.csdn.net/qq\_39362786/article/details/81221372][https_blog.csdn.net_qq_39362786_article_details_81221372]

kettle(四):kettle连接Mysql数据库，将表的数据转换成excel文件： [https://blog.csdn.net/junliucq/article/details/87901907][https_blog.csdn.net_junliucq_article_details_87901907]

数据对接—kettle使用之七： [https://blog.csdn.net/huangaigang6688/article/details/15028447][https_blog.csdn.net_huangaigang6688_article_details_15028447]

kettle实现数据增量同步： [https://blog.csdn.net/wyazyf/article/details/82963811][https_blog.csdn.net_wyazyf_article_details_82963811]

kettle查询-数据库连接： [https://blog.csdn.net/qq\_39735532/article/details/80598786][https_blog.csdn.net_qq_39735532_article_details_80598786]

使用Kettle向CDH集群中Hive导入数据表： [https://blog.csdn.net/u010758605/article/details/81215844][https_blog.csdn.net_u010758605_article_details_81215844]

kettle以JNDI的方式连接数据库 以及 乱码问题： [https://blog.csdn.net/u012848709/article/details/79339419/][https_blog.csdn.net_u012848709_article_details_79339419]

开源KETTLE系列： [https://blog.csdn.net/zhaoxinglin123/article/details/37600119][https_blog.csdn.net_zhaoxinglin123_article_details_37600119]

ETL-kettle表输入到表输出： [https://blog.csdn.net/qq\_32711309/article/details/84441418][https_blog.csdn.net_qq_32711309_article_details_84441418]

Kettle 流查询，数据库查询和Merge Join的区别： [https://blog.csdn.net/lan12334321234/article/details/84733240][https_blog.csdn.net_lan12334321234_article_details_84733240]

利用kettle组件导入excel文件到数据库： [https://blog.csdn.net/neweastsun/article/details/41114453][https_blog.csdn.net_neweastsun_article_details_41114453]

需求：  
1.你是否遇到了需要将mysql数据库中的所有表与数据迁移到Oracle。  
2.你是否还在使用kettle重复的画着：表输入-表输出、创建表，而烦恼。  
  
下面为你实现了一套通用的数据库迁移流程。  
  
技术引导：  
实现之初，在kettle提供的例子中找到了一个类似的（samples\\jobs\\process all tables）。  
通过相关改造，终于达到目标。  
  
实现过程解剖：  
整套流程分为：2个job，4个trans。  
使用到的Trans插件：表输入、字段选择、复制记录到结果、从结果获取记录、设置变量、自定义java脚本、表输出。  
1.大job。  
![65f75098-7ca3-3909-82ab-4d6018ce3978.jpg][]  
  
2.要迁移的源库表名称获取，并设置到结果集，为下面的job使用。  
![ebdcfbb7-0c5e-33a7-82ac-b0e50a3fae99.jpg][]  
  
3.配置子job为前面的每一条记录（即每个表）执行一次该子job  
![a5a813b4-af6e-312f-a070-def4802287b6.jpg][]  
  
4.下面是子job。  
![014b4e97-55c4-37e9-8f30-00725635fdcc.jpg][]  
  
5.获取记录中的表名称，并设置为到变量。  
![4fbda7e9-0b22-3098-82c2-dc747f4eb730.jpg][]  
  
6.读取当前表的结果信息，并在目标库中创建表（这个是难点）。  
![28812255-89ac-36ab-89de-08e1eec35e62.jpg][]  
因为只需要获取抓取要抽取表的结构信息，故在sql后面加上 where 1=2。  
![19759806-7975-3081-ae66-a42a2981d338.jpg][]  
下面代码是创建目标库表。

Java代码 [![复制代码][icon_copy.gif]][icon_copy.gif 1] [![收藏代码][icon_star.png]![spinner.gif][]][icon_star.png_spinner.gif]

\[java\] [view plain][] [copy][view plain]

1.  public boolean processRow(StepMetaInterface smi, StepDataInterface sdi) throws KettleException  
2.  \{  
3.      // First, get a row from the default input hop  
4.      //  
5.      Object\[\] r = getRow();  
6.    
7.      org.pentaho.di.core.database.DatabaseMeta dbmeta = null;  
8.        
9.      java.util.List list = getTrans().getRepository().readDatabases();//3.x中获取资源库的所有数据库连接信息用getDatabases();  
10.       
11.     if(list != null && !list.isEmpty())  
12.     \{  
13.         for(int i=0;i<list.size();i++)  
14.         \{  
15.             dbmeta = (org.pentaho.di.core.database.DatabaseMeta)list.get(i);  
16.                         //下面是目标库的数据库连接，大家可根据需要修改  
17.             if("mysql\_test".equalsIgnoreCase(dbmeta.getName()))  
18.             \{                 
19.                 break;  
20.             \}  
21.         \}  
22.     \}  
23.   
24.     if(dbmeta!=null)  
25.     \{  
26.         org.pentaho.di.core.database.Database db=new org.pentaho.di.core.database.Database(dbmeta);  
27.           
28.         try  
29.         \{  
30.             db.connect();  
31.   
32.             String tablename = getVariable("TABLENAME");  
33.   
34.             logBasic("开始创建表：" + tablename);  
35.               
36.             if(tablename!=null && tablename.trim().length()>0)  
37.             \{  
38.                 String sql = db.getDDL(tablename, data.inputRowMeta);//$\{TABLENAME\}  
39.                               
40.                 db.execStatement(sql.replace(";", ""));  
41.   
42.                 logBasic(sql);  
43.             \}  
44.         \}  
45.         catch(Exception e)  
46.         \{             
47.             logError("创建表出现异常",e);  
48.               
49.         \}finally\{  
50.             db.disconnect();  
51.         \}  
52.     \}  
53.     return false;  
54. \}

7.表数据迁移。  
![5af488f0-b688-3756-bc18-d954d0921bc4.jpg][]  
![2d7dff20-fac2-3e78-834d-4f2a0a58d751.jpg][]  
  
8.差不多就行了，本人使用mysql到mysql、oracle的测试是没有问题的不过在测试过程中，发现源表若存在有blob的表，会有问题，可能是由于表输出没有指定字段的原因，具体解决办法，也没有去多想，以后有时间在完善把。  
  
上面的整套流程的是在kettle4.3下完成的，附件里面可下载完整流程。

[https_blog.csdn.net_maenlai0086_article_details_80829143]: https://blog.csdn.net/maenlai0086/article/details/80829143
[Kettle]: https://www.cnblogs.com/lsy-blogs/p/8268318.html
[https_blog.csdn.net_zhangweicsdn_article_details_51008025]: https://blog.csdn.net/zhangweicsdn/article/details/51008025
[https_blog.csdn.net_shenliang1985_article_details_80026509]: https://blog.csdn.net/shenliang1985/article/details/80026509
[https_blog.csdn.net_zzq900503_article_details_78962029]: https://blog.csdn.net/zzq900503/article/details/78962029
[https_blog.csdn.net_qq_35318838_article_details_66974575]: https://blog.csdn.net/qq_35318838/article/details/66974575
[https_blog.csdn.net_weixin_42354570_article_details_88914671]: https://blog.csdn.net/weixin_42354570/article/details/88914671
[https_blog.csdn.net_feng19821209_article_details_8257648]: https://blog.csdn.net/feng19821209/article/details/8257648
[https_blog.csdn.net_qq_22994783_article_details_82657469]: https://blog.csdn.net/qq_22994783/article/details/82657469
[https_blog.csdn.net_niu_hao_article_details_49022535]: https://blog.csdn.net/niu_hao/article/details/49022535
[https_www.jianshu.com_p_eb6c0d55bb2c]: https://www.jianshu.com/p/eb6c0d55bb2c
[https_blog.csdn.net_wangxiaotaolhc_article_details_79315834]: https://blog.csdn.net/wangxiaotaolhc/article/details/79315834
[https_blog.csdn.net_weixin_42354570_article_details_88962722]: https://blog.csdn.net/weixin_42354570/article/details/88962722
[https_blog.csdn.net_qq_36688928_article_details_90447358]: https://blog.csdn.net/qq_36688928/article/details/90447358
[http_blog.itpub.net_29254281_viewspace-1270110]: http://blog.itpub.net/29254281/viewspace-1270110
[https_blog.csdn.net_wangxiaotaolhc_article_details_79310732]: https://blog.csdn.net/wangxiaotaolhc/article/details/79310732
[https_www.cnblogs.com_xqzt_p_5637033.html]: https://www.cnblogs.com/xqzt/p/5637033.html
[https_jingyan.baidu.com_article_215817f7e897a21eda142317.html]: https://jingyan.baidu.com/article/215817f7e897a21eda142317.html
[https_www.jianshu.com_p_b017c5c9234f]: https://www.jianshu.com/p/b017c5c9234f
[kettle]: https://www.cnblogs.com/meng70345/p/3799055.html
[https_blog.csdn.net_qq_35318838_article_details_53322530]: https://blog.csdn.net/qq_35318838/article/details/53322530
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[https_blog.csdn.net_ncepuzhuang_article_details_41556623]: https://blog.csdn.net/ncepuzhuang/article/details/41556623
[http_www.pianshen.com_article_5317198611]: http://www.pianshen.com/article/5317198611/
[https_blog.csdn.net_gjq2267787274_article_details_50015563]: https://blog.csdn.net/gjq2267787274/article/details/50015563
[https_www.jianshu.com_p_3537ec697495]: https://www.jianshu.com/p/3537ec697495
[https_www.bbsmax.com_A_QV5Zj3725y]: https://www.bbsmax.com/A/QV5Zj3725y/
[https_blog.csdn.net_weixin_34221332_article_details_86846513]: https://blog.csdn.net/weixin_34221332/article/details/86846513
[https_blog.csdn.net_qq_40887813_article_details_80337163]: https://blog.csdn.net/qq_40887813/article/details/80337163
[Kettle _mysql]: https://www.cnblogs.com/inuyasha1027/p/kettle_mysql_dataSynchronize.html
[https_blog.csdn.net_fantasic_van_article_details_77864517]: https://blog.csdn.net/fantasic_van/article/details/77864517
[https_blog.csdn.net_xufan601391682_article_details_78732025]: https://blog.csdn.net/xufan601391682/article/details/78732025
[https_blog.csdn.net_maenlai0086_article_details_80826532]: https://blog.csdn.net/maenlai0086/article/details/80826532
[ETL_Kettle_Excel]: https://www.cnblogs.com/dsjxmz/p/6888502.html
[https_blog.csdn.net_dear_Alice_moon_article_details_93716811]: https://blog.csdn.net/dear_Alice_moon/article/details/93716811
[https_blog.csdn.net_lstcui_article_details_81664774]: https://blog.csdn.net/lstcui/article/details/81664774
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[https_blog.csdn.net_u013991521_article_details_52947581]: https://blog.csdn.net/u013991521/article/details/52947581
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[https_blog.csdn.net_sky08050025_article_details_79608297]: https://blog.csdn.net/sky08050025/article/details/79608297
[https_blog.csdn.net_m0_37979608_article_details_77892873]: https://blog.csdn.net/m0_37979608/article/details/77892873
[https_blog.csdn.net_gjf281_article_details_79084035]: https://blog.csdn.net/gjf281/article/details/79084035
[https_blog.csdn.net_ls870061011_article_details_52699174]: https://blog.csdn.net/ls870061011/article/details/52699174
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[https_blog.csdn.net_m0_37951562_article_details_85232528]: https://blog.csdn.net/m0_37951562/article/details/85232528
[KETTLE]: https://www.cnblogs.com/scote/p/5918827.html
[https_blog.csdn.net_alert_java_song_article_details_86620148]: https://blog.csdn.net/alert_java_song/article/details/86620148
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[https_blog.csdn.net_xiaohai798_article_details_45367617]: https://blog.csdn.net/xiaohai798/article/details/45367617
[Kettle 1]: https://www.cnblogs.com/greyzeng/p/5524614.html
[https_blog.csdn.net_rotkang_article_details_20962725]: https://blog.csdn.net/rotkang/article/details/20962725
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[https_blog.csdn.net_wangzhpwang_article_details_80749237]: https://blog.csdn.net/wangzhpwang/article/details/80749237
[https_blog.csdn.net_CHL521_article_details_84854131]: https://blog.csdn.net/CHL521/article/details/84854131
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[https_blog.csdn.net_yu8196378_article_details_51745140]: https://blog.csdn.net/yu8196378/article/details/51745140
[https_www.jianshu.com_p_0566a10e7f44]: https://www.jianshu.com/p/0566a10e7f44
[Kettle 2]: https://www.cnblogs.com/lcword/p/9571063.html
[Kettle_ETL_ELT_EII]: https://www.cnblogs.com/zlslch/p/6906809.html
[https_blog.csdn.net_hzp666_article_details_68066341]: https://blog.csdn.net/hzp666/article/details/68066341
[Kettle 3]: https://www.cnblogs.com/nbjin/p/9707808.html
[https_www.jianshu.com_p_ac7c0566d782]: https://www.jianshu.com/p/ac7c0566d782
[https_blog.csdn.net_mafan121_article_details_42918465 1]: https://blog.csdn.net/mafan121/article/details/42918465
[https_blog.csdn.net_u011019141_article_details_87801843]: https://blog.csdn.net/u011019141/article/details/87801843
[https_blog.csdn.net_qq_35731570_article_details_71123413]: https://blog.csdn.net/qq_35731570/article/details/71123413
[https_blog.csdn.net_u014307117_article_details_79351471]: https://blog.csdn.net/u014307117/article/details/79351471
[https_blog.csdn.net_fendou_0123456789_article_details_88974530]: https://blog.csdn.net/fendou_0123456789/article/details/88974530
[https_blog.csdn.net_wang12345566_article_details_77680304]: https://blog.csdn.net/wang12345566/article/details/77680304
[https_blog.csdn.net_wangjx92_article_details_83021394]: https://blog.csdn.net/wangjx92/article/details/83021394
[https_blog.csdn.net_zhangfeng1742_article_details_78651404]: https://blog.csdn.net/zhangfeng1742/article/details/78651404
[ETL_Kettle_Excel 1]: https://www.cnblogs.com/dsjxmz/p/6884812.html
[https_blog.csdn.net_maenlai0086_article_details_81170633]: https://blog.csdn.net/maenlai0086/article/details/81170633
[kettle 1]: https://www.cnblogs.com/OliverQin/p/5857734.html
[https_blog.csdn.net_maenlai0086_article_details_81347146]: https://blog.csdn.net/maenlai0086/article/details/81347146
[https_blog.csdn.net_dear_Alice_moon_article_details_91870388]: https://blog.csdn.net/dear_Alice_moon/article/details/91870388
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