├── README.md ├── blog ├── BigDataBlogOverview.md └── pic │ ├── 小程序.png │ ├── 微信公众号.png │ ├── 星星.png │ └── 若泽数据--扫描入口.png ├── interview └── 常见面试题.md └── share └── 公开课列表.md /README.md: -------------------------------------------------------------------------------- 1 | ### 欢迎来到若泽数据，感谢大家对我们的支持。 2 | -------------------------------------------------------------------- 3 | 4 | #### Join us if you have a dream. 5 | ##### 若泽数据官网: [http://ruozedata.com](http://ruozedata.com) 6 | ##### 腾讯课堂，搜若泽数据: [http://ruoze.ke.qq.com](http://ruoze.ke.qq.com) 7 | ##### Bilibili网站,搜若泽数据: [https://space.bilibili.com/356836323](https://space.bilibili.com/356836323) 8 | 9 | ##### [若泽大数据--官方博客](https://ruozedata.github.io) 10 | ##### [若泽大数据--博客一览](https://github.com/ruozedata/BigData/blob/master/blog/BigDataBlogOverview.md) 11 | ##### [若泽大数据--内部学员面试题](https://github.com/ruozedata/BigData/blob/master/interview/%E5%B8%B8%E8%A7%81%E9%9D%A2%E8%AF%95%E9%A2%98.md) 12 | ##### 扫一扫，学一学: 13 | ![image](https://github.com/Hackeruncle/BigData/blob/master/blog/pic/%E8%8B%A5%E6%B3%BD%E6%95%B0%E6%8D%AE--%E6%89%AB%E6%8F%8F%E5%85%A5%E5%8F%A3.png?raw=true) 14 | 15 | ###### 有任何疑问的 16 | ###### QQ加课程顾问-星星: `1952249535`， 17 | ###### 或微信(ruoze_star)扫描以上二维码， 邀请进群。 18 | -------------------------------------------------------------------------------- /blog/BigDataBlogOverview.md: -------------------------------------------------------------------------------- 1 | # 若泽大数据--博客一览 2 | 3 | **请花1min，阅读or收藏；** 4 | 我们整理 大数据 系列博文列表+视频， 5 | 内部学员原创博文及我们生产博文，当前更新于 20190620 6 | 7 | 领取大数据实战班和公开课视频，微信关注公众号自动领取 : 8 | 9 | ![若泽大数据](./pic/微信公众号.png) 10 | 11 | ## 创业心声: 12 | 13 | 1. [关于我们](http://www.ruozedata.com/about.html) 14 | 2. [谈谈我和大数据的情缘及入门](https://mp.weixin.qq.com/s?__biz=MzA5ODY0NzgxNA==&mid=2247483702&idx=1&sn=5e21f983876757e9cbb291846ff804b4&chksm=908f2b5fa7f8a24916151090c55c8dc104c7c587965a3335174c0664ff27a459a52824e66057&scene=38#wechat_redirect) 15 | 3. [欢迎有梦想的您](https://mp.weixin.qq.com/s?__biz=MzA5ODY0NzgxNA==&mid=2247483716&idx=1&sn=47094938d1af752cd95e7be41dd8a51d&chksm=908f2b2da7f8a23bf3484b07f74ed523c70e878c47a8b36a93e15962cda87c506dee1e1614b1&scene=38#wechat_redirect) 16 | 17 | 18 | ## 视频 19 | 20 | #### free 21 | 22 | 1. [大数据之零基础生产最佳实践](https://www.bilibili.com/video/av28728859/) 23 | 2. [玩转大数据之Spark零基础到实战](https://www.bilibili.com/video/av29407581/) 24 | 3. [Spark实时分析预警平台(架构+提交流程+现场排错)【free视频】](https://ke.qq.com/course/238183?tuin=11cffd50) 25 | 4. [Spark2.4新特性解析](https://www.bilibili.com/video/av36433084/) 26 | 5. [如何自定义实现Spark外部数据源](https://www.bilibili.com/video/av36387258/) 27 | 6. [Spark Streaming整合Kafka offset管理](https://www.bilibili.com/video/av36387945/) 28 | 7. [Spark Shell启动过程分析及自定义Partition数量设置](https://www.bilibili.com/video/av36299376/) 29 | 8. [企业级Spark实时分析预警平台项目(架构+提交流程+现场排错)](https://www.bilibili.com/video/av35013593/) 30 | 9. [玩转Kylin2.x with Spark](https://www.bilibili.com/video/av29829943/) 31 | 10. [CDH离线部署和暴力卸载、Kerberos【free视频】](https://ke.qq.com/course/241568?tuin=11cffd50) 32 | 11. [全网最详细的CDH5.8.2离线安装](https://www.bilibili.com/video/av30031910/) 33 | 12. [Hadoop集群调优&CDH常规管理](https://www.bilibili.com/video/av34829124/) 34 | 13. [CDH5.16.1企业集群真正离线部署(全网最细，配套视频和文档安装包，生产可实践)](https://www.bilibili.com/video/av52167219/) 35 | 14. [Hive概述及入门](https://www.bilibili.com/video/av35014198/) 36 | 15. [Hive之DDL详解](https://www.bilibili.com/video/av35070832/) 37 | 16. [Hive压缩在大数据中的使用](https://www.bilibili.com/video/av35146656/) 38 | 17. [大数据之Hive元数据](https://www.bilibili.com/video/av35146993/) 39 | 18. [Phoenix生产实战第一季](https://www.bilibili.com/video/av47857831/) 40 | 19. [MySQL入门实战(含彩蛋分享)](https://www.bilibili.com/video/av34828479/) 41 | 20. [MySQL主从复制及生产如何采集至大数据](https://www.bilibili.com/video/av40832418/) 42 | 21. [大数据平台建设](https://www.bilibili.com/video/av36496365/) 43 | 22. [大数据流处理如何做到Exactly Once](https://www.bilibili.com/video/av36432150/) 44 | 23. [数据采集全流程剖析与实现](https://www.bilibili.com/video/av36428924/) 45 | 24. [容器大数据之Docker生产实战](https://www.bilibili.com/video/av35483224/) 46 | 25. [我司大数据从0到1的数据平台架构](https://www.bilibili.com/video/av36008084/) 47 | 26. [大数据不可或缺的JVM](https://www.bilibili.com/video/av36293460/) 48 | 27. [大数据面试系列集合](https://www.bilibili.com/video/av36294263/) 49 | 28. [互联网一线大数据之简历&面试指导(挖坑)](https://www.bilibili.com/video/av47859098/) 50 | 29. [互联网一线大数据之实时数仓(HBase)](https://www.bilibili.com/video/av47858730/) 51 | 30. [大数据平台权限管理之Shiro](https://www.bilibili.com/video/av36388493/) 52 | 31. [Flink第一讲之1小时快速入门](https://www.bilibili.com/video/av36292829/) 53 | 32. [Flink第二讲之Scala编程及核心概念](https://www.bilibili.com/video/av36340591/) 54 | 33. [大数据环境部署之VM虚拟机](https://www.bilibili.com/video/av34989595/) 55 | 34. [大数据环境部署之青云云主机](https://www.bilibili.com/video/av34989732/) 56 | 35. [大数据之Flume入门](https://www.bilibili.com/video/av35071702/) 57 | 36. [大数据之Flume实战](https://www.bilibili.com/video/av35136152/) 58 | 37. [大数据调度平台之Rundeck生产实践](https://www.bilibili.com/video/av35466584/) 59 | 38. [ELK入门实战](https://www.bilibili.com/video/av35467284/) 60 | 39. [玩转大数据之Shell脚本生产最佳实践](https://www.bilibili.com/video/av34781104/) 61 | 40. [零基础大数据课程介绍与常见问题](https://www.bilibili.com/video/av34777256/) 62 | 41. [人工智能之课程简介与常见问题](https://www.bilibili.com/video/av34777492/) 63 | 42. [生产项目线下班之面试和简历指导](https://www.bilibili.com/video/av34829926/) 64 | 43. [Kafka生产最佳实践](https://www.bilibili.com/video/av34832634/) 65 | 44. [细说Kafka之监控风云](https://www.bilibili.com/video/av30013463/) 66 | 45. [如何让VPC网络成为大数据集群的利器(彩蛋)](https://www.bilibili.com/video/av34778452/) 67 | 46. [大数据之实时数据源同步中间件--生产上Canal与Maxwell颠峰对决](https://www.bilibili.com/video/av34778187/) 68 | 69 | #### buy 70 | 71 | 1. [Hive应用实战课程【buy视频】](https://ke.qq.com/course/236561?tuin=11cffd50) 72 | 2. [Sqoop应用实战课程【buy视频】](https://ke.qq.com/course/243478?tuin=11cffd50) 73 | 3. [批处理ETL已亡，Kafka才是数据处理的未来【buy视频】](https://ke.qq.com/course/278667?tuin=11cffd50) 74 | 4. [全网唯一Azkaban3.x应用实战【buy视频】](https://ke.qq.com/course/238175?tuin=11cffd50) 75 | 5. [《零基础企业级CDH(安全)平台实战》，详情查看课程概述或进行试听](https://ke.qq.com/course/302442) 76 | 77 | 78 | ## 博客文章 79 | 80 | ##### Linux And Shell 81 | 82 | 1. [VMware Workstation9 下安装 CentOS6.5( 安装图文教程 )](http://blog.itpub.net/30089851/viewspace-2131153/) 83 | 2. [Linux最常用命令及快捷键整理](http://blog.itpub.net/30089851/viewspace-2131167/) 84 | 3. [配置多台机器SSH相互通信信任](http://blog.itpub.net/30089851/viewspace-1992210/) 85 | 4. [Memory参数，你真的懂吗?](http://blog.itpub.net/30089851/viewspace-2131678/) 86 | 5. [yum安装xxx包时出错，提示No package xxx available.](http://blog.itpub.net/30089851/viewspace-2120628/) 87 | 6. [CentOS6.x使用163和epel yum源的选择](http://blog.itpub.net/30089851/viewspace-2130239/) 88 | 7. [Centos6.5 python2.6.6 升级到2.7.5](http://blog.itpub.net/30089851/viewspace-2129636/) 89 | 8. [CentOS清理swap和buffer/cache](http://blog.itpub.net/30089851/viewspace-2147840/) 90 | 9. [记录在shell脚本中使用sudo echo x > 时,抛Permission denied错误](http://blog.itpub.net/30089851/viewspace-2132326/) 91 | 10. [Linux系统重要参数调优，你知道吗](http://mp.weixin.qq.com/s?__biz=MzA5ODY0NzgxNA==&mid=2247483967&idx=1&sn=ae3a4b8c3b8ec271aa25ce8355672433&chksm=908f2856a7f8a140967e6c55712511fdf4582261f1be7237646a1e362771140649703a0797f3&scene=27#wechat_redirect) 92 | 11. [大数据之必会的Linux命令](http://mp.weixin.qq.com/s?__biz=MzA5ODY0NzgxNA==&mid=2247484114&idx=1&sn=38b76cb666d7d571c01b3784092a4cab&chksm=908f28bba7f8a1adfa9868a99fbdd14a835e9470d19a57292e9889d5cd6c27161d491c5d2e40&scene=27#wechat_redirect) 93 | 94 | ##### DataBase And SQL 95 | 96 | 1. [携程统一SQL引擎的实现思路](https://mp.weixin.qq.com/s?__biz=MzA5ODY0NzgxNA==&mid=2247484677&idx=1&sn=42a98ca5e79ae12f1509c63a238f04d4&chksm=908f2f6ca7f8a67a5010fbfbf1957d7890d3f1afd36c51832eee4bd7abcdf42f2174e5460aa8&scene=38#wechat_redirect) 97 | 98 | ##### Hadoop 99 | 100 | 1. [Hadoop2.8.1全网最详细编译](https://mp.weixin.qq.com/s?__biz=MzA5ODY0NzgxNA==&mid=2247483841&idx=1&sn=a34e93ca29a523a6ab34781f68a02d41&chksm=908f2ba8a7f8a2bea89641d4e77a7c3daf50036c7c234eabb986a1128885d66c09cf9a50030e&scene=38#wechat_redirect) 101 | 2. [Hadoop全网最详细的伪分布式部署(HDFS)](https://mp.weixin.qq.com/s?__biz=MzA5ODY0NzgxNA==&mid=2247483731&idx=1&sn=40021b1c7db069b56dad3646bfa45408&chksm=908f2b3aa7f8a22c7d9d2bd4b19956fee63cb02c205c0f1bf836426abf5c26f1e2e40af1f045#rd) 102 | 3. [Hadoop全网最详细的伪分布式部署(MapReduce+Yarn)](https://mp.weixin.qq.com/s?__biz=MzA5ODY0NzgxNA==&mid=2247483744&idx=1&sn=9d0d61ecc3be2f71de640c9bcd7f8027&chksm=908f2b09a7f8a21fe62cd8adda08acb6f2ce040d5e2b73dbcf6dd2874dcedd3baf0f64804cfc#rd) 103 | 4. [Hadoop常用命令大全01](https://mp.weixin.qq.com/s?__biz=MzA5ODY0NzgxNA==&mid=2247483764&idx=1&sn=7a4c9d254f85cf8f302724a0b511e16c&chksm=908f2b1da7f8a20bdc4928c13f313f379204256d809c4e7212f16574f7b4a2eb3b265d1b59cb#rd) 104 | 5. [Hadoop-2.7.2+zookeeper-3.4.6完全分布式环境搭建(HDFS、YARN HA)](http://blog.itpub.net/30089851/viewspace-1994585/) 105 | 6. [Hadoop2.x 参数汇总](http://blog.itpub.net/30089851/viewspace-2006108/) 106 | 7. [YARN的Memory和CPU调优配置详解](http://blog.itpub.net/30089851/viewspace-2127851/) 107 | 8. [资源调度yarn之生产详解](http://mp.weixin.qq.com/s?__biz=MzA5ODY0NzgxNA==&mid=2247484061&idx=1&sn=2a5f030ce2ad509efa909891957f8788&chksm=908f28f4a7f8a1e2519c59eed168f651365c86ef14affc0c4640b7de09936cee0bea5a0aecb4&scene=27#wechat_redirect) 108 | 9. [fsimage？editlog？这些都是什么？？](http://mp.weixin.qq.com/s?__biz=MzA5ODY0NzgxNA==&mid=2247484084&idx=1&sn=8a4bb03a613c8bb5c3ea900aee29643b&chksm=908f28dda7f8a1cbbcf42ce87623ec2c7e475b156f051d368902b513827ade5bbf34520c0f0a&scene=27#wechat_redirect) 109 | 10. [你真的了解jps命令吗](http://mp.weixin.qq.com/s?__biz=MzA5ODY0NzgxNA==&mid=2247484108&idx=1&sn=fa0afcdc9109ecd4876e5cf3de99199d&chksm=908f28a5a7f8a1b36f9ec3e456b791af7b2c77fb1e3f7a8a5c8f4be1bcabab3a66d53c75435b&scene=27#wechat_redirect) 110 | 11.[Hadoop HA 的配置，你了解吗？](http://mp.weixin.qq.com/s?__biz=MzA5ODY0NzgxNA==&mid=2247484125&idx=1&sn=b1155d6f09e5d17f39f04750dc53b29c&chksm=908f28b4a7f8a1a2655f396b649c8ed35ff7c939b54d2c3c27344d2e6273644c68205ea6e04d&scene=27#wechat_redirect) 111 | 12. [Hadoop之Yarn架构设计(command memory cpu)](http://mp.weixin.qq.com/s?__biz=MzA5ODY0NzgxNA==&mid=2247484128&idx=1&sn=2b8dc90a5caf08e24f79fab4b6f0b639&chksm=908f2889a7f8a19f0d4208d823cc5fd008c5b6d82baa18d67f6eef1a466126553b37114c7f84&scene=27#wechat_redirect) 112 | 13. [HDFS之垃圾回收箱配置及使用](http://mp.weixin.qq.com/s?__biz=MzA5ODY0NzgxNA==&mid=2247484159&idx=1&sn=19e63529fb75ed897d8ce4b7c571d770&chksm=908f2896a7f8a18020f40219dd9e1edadd80e9e8e8de3e7dd7d8db216690a39d9449c1f1148e&scene=27#wechat_redirect) 113 | 114 | ##### Hive 115 | 116 | 1. [Hive全网最详细的编译及部署](https://mp.weixin.qq.com/s?__biz=MzA5ODY0NzgxNA==&mid=2247483748&idx=1&sn=3a7db2f9c8a667bcad3aa37ece461360&chksm=908f2b0da7f8a21b5fb24869d7204709176fd417da2ab55afa88c3f15e45546eb8906a4b9496#rd) 117 | 2. [Hive DDL，你真的了解吗？](https://mp.weixin.qq.com/s?__biz=MzA5ODY0NzgxNA==&mid=2247483815&idx=1&sn=63b2a8307fab8d53efcb6677b8140e82&chksm=908f2bcea7f8a2d80b06d5f01c8cfe0dd2382e3226d54d325d9aa51834bfcf911de01b96a484&scene=38#wechat_redirect) 118 | 3. [Hive自定义函数(UDF)的编程开发，你会吗？](https://mp.weixin.qq.com/s?__biz=MzA5ODY0NzgxNA==&mid=2247483821&idx=1&sn=996cd6ddab7fa237cfdb297466651443&chksm=908f2bc4a7f8a2d28e838aa20ac34b6bcba80983df6df0bc3ae91cea9df2a91fd3c96fb1f1fe&scene=38#wechat_redirect) 119 | 4. [Hive自定义函数(UDF)的部署使用，你会吗？](https://mp.weixin.qq.com/s?__biz=MzA5ODY0NzgxNA==&mid=2247483825&idx=1&sn=e8f240339d698d44a0aba30245437ed5&chksm=908f2bd8a7f8a2ceb1cbe0a7afe847f0b23d5c61a24fa1b27c4d41bb0198c7ca48d2f9b0bd16&scene=38#wechat_redirect) 120 | 5. [2min快速了解，Hive内部表和外部表](https://mp.weixin.qq.com/s?__biz=MzA5ODY0NzgxNA==&mid=2247483840&idx=1&sn=eff7a0596d3dde834073cba4b2dbc9f4&chksm=908f2ba9a7f8a2bf03e5dc2a674d7653df6c0c90acea484f77a4b802bfe1c578f152d0838fe0&scene=38#wechat_redirect) 121 | 6. [5min掌握，Hive的HiveServer2 和JDBC客户端&代码的生产使用](https://mp.weixin.qq.com/s?__biz=MzA5ODY0NzgxNA==&mid=2247483846&idx=1&sn=4f1ce755bc9807121351d4f0b92c8183&chksm=908f2bafa7f8a2b9580a8dc2f299eb23398cd469259730c4403571a91fc2aed8afe000ea6797&scene=38#wechat_redirect) 122 | 7. [生产中Hive静态和动态分区表，该怎样抉择呢？](https://mp.weixin.qq.com/s?__biz=MzA5ODY0NzgxNA==&mid=2247483850&idx=1&sn=62c50ce20116818a22db8f71da7f2ab1&chksm=908f2ba3a7f8a2b514bd7c4adba3d69e8f90886e9c7f01701ce385e6096efcfc782f187d6309#rd) 123 | 8. [Hive中自定义UDAF函数生产小案例](http://mp.weixin.qq.com/s?__biz=MzA5ODY0NzgxNA==&mid=2247483923&idx=1&sn=631bbb80949dad73a76a9ab5fb50f5a3&chksm=908f287aa7f8a16c12838454bb634227502083d5455993bb43015da35e1368fbbcc87b714956&scene=27#wechat_redirect) 124 | 9. [从Hive中的stored as file_foramt看hive调优](http://mp.weixin.qq.com/s?__biz=MzA5ODY0NzgxNA==&mid=2247483951&idx=1&sn=d967c0495f1f08eb0f6b1e15482333c9&chksm=908f2846a7f8a15006aa8fad55237095ca0562e95072de3cc8f4b18689d2b08e822e8e62feb2&scene=27#wechat_redirect) 125 | 10. [你真的了解 Hive 的元数据吗？](http://mp.weixin.qq.com/s?__biz=MzA5ODY0NzgxNA==&mid=2247484030&idx=1&sn=f9bfe226a4efc3b38536caee21fa070d&chksm=908f2817a7f8a10123445446fe035e04374b3c6e173831c50920fcd9d6810886814e7bc50b20&scene=27#wechat_redirect) 126 | 11. [hive实战](https://blog.csdn.net/liweihope/article/details/88584985) 127 | 12. [Hive压缩格式的生产应用](https://mp.weixin.qq.com/s?__biz=MzA5ODY0NzgxNA==&mid=2247483779&idx=1&sn=03051f1cfc307b70bd442bf16dcf0d67&chksm=908f2beaa7f8a2fc49ac09613db06679dc41955cdaa4ef07c9704da357d6c7d8b5350a3e67cf#rd) 128 | 13. [Hive存储格式的生产应用](https://mp.weixin.qq.com/s/B2tsou1siflOVh7cIVqh3Q) 129 | 14. [Hive生产上，压缩和存储结合使用案例](https://mp.weixin.qq.com/s?__biz=MzA5ODY0NzgxNA==&mid=2247483811&idx=1&sn=cb6473764efdc4c2796cd832042887b4&chksm=908f2bcaa7f8a2dc4fdb5c25aa35356a5ee26376af2e585e7b3cec7c73e9d1049a10f15ed519&scene=38#wechat_redirect) 130 | 15. [Hive中扩展GIS函数](https://mp.weixin.qq.com/s?__biz=MzA5ODY0NzgxNA==&mid=2247485176&idx=1&sn=4bfa3ef7172ae98d565634cf8bdb71a7&chksm=908f2c91a7f8a587e8efe948776799256b3ac8d86f2674cec0b43abb82be04054d1ca8423f9f&scene=38#wechat_redirect) 131 | 16. [别有洞天之Hive作业无法申请资源](https://mp.weixin.qq.com/s?__biz=MzA5ODY0NzgxNA==&mid=2247484912&idx=1&sn=44017e01b66978e4a17e40a8cb1aeb1c&chksm=908f2f99a7f8a68f8090a1350bf6dd20891f44a4dd3cd955c39f52edc744a46d826f59255b8e&scene=38#wechat_redirect) 132 | 133 | ##### Compress And Storage Format 134 | 135 | 1. [大数据压缩格式，你们真的了解吗？](https://mp.weixin.qq.com/s?__biz=MzA5ODY0NzgxNA==&mid=2247483778&idx=1&sn=ea586218142d9b21cb4d68d9675956b6&chksm=908f2beba7f8a2fda956ea7b128ed7c419cc322715199813bff22c3c00667afa34d93cf96853#rd) 136 | 2. [大数据存储格式，你们真的了解吗？](https://mp.weixin.qq.com/s?__biz=MzA5ODY0NzgxNA==&mid=2247483808&idx=1&sn=a3d1377b50ecb87bb75c9a089e9273c8&chksm=908f2bc9a7f8a2dfed87b00d06239dc175a70f70a2851343273a942ee74cb3121a9849a50353#rd) 137 | 138 | ##### Flume 139 | 140 | 1. [生产Flume源码导入IDEA方式](https://mp.weixin.qq.com/s?__biz=MzA5ODY0NzgxNA==&mid=2247485245&idx=1&sn=db2434ba0bdb14ba1abdedc75e79b35e&chksm=908f2d54a7f8a442d41278d6cc17fa81f24546b0121186d6ce7bcf8342b4b4d575605f283ec2&scene=38#wechat_redirect) 141 | 142 | ##### Kafka 143 | 144 | 1. [记一次生产Kafka不能消费故障](https://mp.weixin.qq.com/s?__biz=MzA5ODY0NzgxNA==&mid=2247484889&idx=1&sn=7517c0e50f17cd190b3910df4fa23cc9&chksm=908f2fb0a7f8a6a6eb426f8c19eda746879087f9601d20b7dff70ab7b677343a5963429960bf&scene=38#wechat_redirect) 145 | 2. [生产上Kafka 数据迁移案例](https://mp.weixin.qq.com/s?__biz=MzA5ODY0NzgxNA==&mid=2247484761&idx=1&sn=28a72ef1f0109d4fe58bafff9294918c&chksm=908f2f30a7f8a626ad4b00349fef3ce8f47a85d46681bfcaed409bfc5a4bd1442f09ab60be5c&scene=38#wechat_redirect) 146 | 147 | ##### Spark 148 | 149 | 1. [Spark2.2.0 全网最详细的源码编译](https://mp.weixin.qq.com/s?__biz=MzA5ODY0NzgxNA==&mid=2247483751&idx=1&sn=5b0b76b6fba35e1cb32ad8bf49530f3c&chksm=908f2b0ea7f8a2187e9745f816d2582b1544277fe863b14be319bd1f9e7018b70718691f67e6#rd) 150 | 2. [Spark-2.2.0-bin-2.6.0-cdh5.12.1.tgz 编译方法总结！](https://blog.csdn.net/lsr40/article/details/80116235) 151 | 3. [生产改造Spark1.6源代码，create table语法支持Oracle列表分区](https://mp.weixin.qq.com/s?__biz=MzA5ODY0NzgxNA==&mid=2247483862&idx=1&sn=7b66ca607dd4335918747d15e535a4e1&chksm=908f2bbfa7f8a2a9bfb2117f53e8ae5aae2c275801b8860b2b6ba633ba8f6a17903c3ff4baf4#rd) 152 | 4. [Spark History Server Web UI配置](https://mp.weixin.qq.com/s?__biz=MzA5ODY0NzgxNA==&mid=2247483867&idx=1&sn=6a6998b735f2ddd9b5d0ca8e07787398&chksm=908f2bb2a7f8a2a42858e5430461dbe90b8cfc099dccf94f20da6bfe6af3f6ea79c32c75b7e5#rd) 153 | 5. [Spark on YARN-Cluster和YARN-Client的区别](https://mp.weixin.qq.com/s?__biz=MzA5ODY0NzgxNA==&mid=2247483875&idx=1&sn=a6fe847f74ef213312589836585f2ef7&chksm=908f2b8aa7f8a29cecd379618ef51c2ef765d73266c091a04ea8ece8098f79446cc523fe99b7#rd) 154 | 6. [Spark RDD、DataFrame和DataSet的区别](https://mp.weixin.qq.com/s?__biz=MzA5ODY0NzgxNA==&mid=2247483897&idx=1&sn=ddcd1e7d6f1220847319b0facc6bd3d2&chksm=908f2b90a7f8a286c6a5df5f3d5dba8c856fd105e425706a74db7ea71d94d2ea3bd3044c6229&scene=38#wechat_redirect) 155 | 7. [Spark RDD、DataFrame和DataSet的区别](https://mp.weixin.qq.com/s?__biz=MzA5ODY0NzgxNA==&mid=2247483897&idx=1&sn=ddcd1e7d6f1220847319b0facc6bd3d2&chksm=908f2b90a7f8a286c6a5df5f3d5dba8c856fd105e425706a74db7ea71d94d2ea3bd3044c6229&scene=38#wechat_redirect) 156 | 8. [Spark不得不理解的重要概念——从源码角度看RDD](https://mp.weixin.qq.com/s?__biz=MzA5ODY0NzgxNA==&mid=2247483908&idx=1&sn=030c206ab12edcf8f63b20fb99fc85c0&chksm=908f286da7f8a17b28ceef4c73fbc99ffae01ccc656e4656288c865dc4702bb779a02fc50dd0&scene=38#wechat_redirect) 157 | 9. [Spark 基本概念](http://mp.weixin.qq.com/s?__biz=MzA5ODY0NzgxNA==&mid=2247483917&idx=1&sn=c6197eea3bc83cbe9154ce5853a1bd1a&chksm=908f2864a7f8a1727233f6c65dd8bbe06c67ca5f4aca9b5aa4820ef66db524e03aa652152211&scene=27#wechat_redirect) 158 | 10. [Spark调优的关键之——RDD Cache缓存使用详解](http://mp.weixin.qq.com/s?__biz=MzA5ODY0NzgxNA==&mid=2247483936&idx=1&sn=5354cda77d0183e47030767054da274d&chksm=908f2849a7f8a15f42046717d0977421ffbfc8fe079a2996c3a1117229a6a3c778177f59fb43&scene=27#wechat_redirect) 159 | 11. [Spark之序列化在生产中的应用](http://mp.weixin.qq.com/s?__biz=MzA5ODY0NzgxNA==&mid=2247483947&idx=1&sn=3f2a3a7a1bf27f69ddc05e348fb1b3c2&chksm=908f2842a7f8a154a70f7d62e821e118e1346ccbe873abf1b3e8af0c8398059ba4467d088ac2&scene=27#wechat_redirect) 160 | 12. [还不收藏？Spark动态内存管理源码解析！](http://mp.weixin.qq.com/s?__biz=MzA5ODY0NzgxNA==&mid=2247483962&idx=1&sn=11729c88e10122daf0b86313d5961b0d&chksm=908f2853a7f8a145df09f08fe1de28ad2f422eaa2c08635f082b8ca17c6975d8a8630af0c42a&scene=27#wechat_redirect) 161 | 13. [Spark SQL 外部数据源（External DataSource）](http://mp.weixin.qq.com/s?__biz=MzA5ODY0NzgxNA==&mid=2247483971&idx=1&sn=cf1f4b6cc314c1cd97ca27bf1596e9b5&chksm=908f282aa7f8a13c6d52be7875b72a00342aa6793c5dde1102ec2fe96d87b9d5b55e68b320f1&scene=27#wechat_redirect) 162 | 14. [你大爷永远是你大爷，RDD血缘关系源码详解！](http://mp.weixin.qq.com/s?__biz=MzA5ODY0NzgxNA==&mid=2247483984&idx=1&sn=80c4fde272713caf64296c62235a2179&chksm=908f2839a7f8a12fd7aba4535559616b9b3ce25c41f0854097389c8fbd17d2239dd821011bb3&scene=27#wechat_redirect) 163 | 15. [Apache Spark 技术团队开源机器学习平台 MLflow](http://mp.weixin.qq.com/s?__biz=MzA5ODY0NzgxNA==&mid=2247483997&idx=1&sn=751e7cfe35f7738688d48eefffa94ca2&chksm=908f2834a7f8a1221ee03cbe234be501d610bf4066e42d552146b5d2179dbeb3ef95c7bc2d30&scene=27#wechat_redirect) 164 | 16. [生产开发必用-Spark RDD转DataFrame的两种方法](http://mp.weixin.qq.com/s?__biz=MzA5ODY0NzgxNA==&mid=2247484006&idx=1&sn=3dc65a83f94fc419aed7da5fd71742e0&chksm=908f280fa7f8a119cd9c9231e5a84b79eab8e7ab7ca0d4865345b55bfd952f13ded40a7023f9&scene=27#wechat_redirect) 165 | 17. [最前沿！带你读Structured Streaming重量级论文！](http://mp.weixin.qq.com/s?__biz=MzA5ODY0NzgxNA==&mid=2247484010&idx=1&sn=30ce4120dc5f82c84930b36959ec1daa&chksm=908f2803a7f8a115ce408d7f85f222ff6a455db01db94f3311997fc7af9bb8919660a128c230&scene=27#wechat_redirect) 166 | 18. [Apache Spark和DL/AI结合，谁与争锋? 期待Spark3.0的到来！](http://mp.weixin.qq.com/s?__biz=MzA5ODY0NzgxNA==&mid=2247484039&idx=1&sn=54a3fa60316b787b081b45aa68eee6a0&chksm=908f28eea7f8a1f80244c82f5e6622213bb1b6705c7f5bcbd437f9dff2ac100401f81887c965&scene=27#wechat_redirect) 167 | 19. [又又又是源码！RDD 作业的DAG是如何切分的？](http://mp.weixin.qq.com/s?__biz=MzA5ODY0NzgxNA==&mid=2247484048&idx=1&sn=3453b497dbf53ea507d54d7f29f9fe69&chksm=908f28f9a7f8a1efcf3c48935c90b36fd8ffd04886103c24717c9529ed761d39edc75d7cca25&scene=27#wechat_redirect) 168 | 20. [Spark Streaming 状态管理函数，你了解吗](http://mp.weixin.qq.com/s?__biz=MzA5ODY0NzgxNA==&mid=2247484051&idx=1&sn=650f10652f15103af7b711e50a0759d2&chksm=908f28faa7f8a1ec86cc64f407756966cbc8d4a0dfac116398af4aace5c77936b73efbec678f&scene=27#wechat_redirect) 169 | 21. [Spark序列化，你了解吗](http://mp.weixin.qq.com/s?__biz=MzA5ODY0NzgxNA==&mid=2247484152&idx=1&sn=7a50b1ab285969c1eb739b23e0d0c451&chksm=908f2891a7f8a187220e87a923eadf3f0972b11622b85a17e22e0db48170e181df51d3914ff4&scene=27#wechat_redirect) 170 | 171 | --------2019--------- 172 | 173 | 22. [某头条公司Spark结构化流的SQL实现](https://mp.weixin.qq.com/s?__biz=MzA5ODY0NzgxNA==&mid=2247484665&idx=1&sn=2cfa5eef6ea187deab0f71818d392649&chksm=908f2e90a7f8a78615ffa64541e455a7ef5ad21ef7596a3b80c74cff5d248de0c2c8aa271623&scene=38#wechat_redirect) 174 | 23. [再谈，某头条公司Spark结构化流的SQL实现](https://mp.weixin.qq.com/s?__biz=MzA5ODY0NzgxNA==&mid=2247484681&idx=1&sn=45a011d428f821614e6988b24635bc04&chksm=908f2f60a7f8a6769fc6f1188b52ecee50a018fd063b962ba9e35d721f9d7cf243b6c1a1350f&scene=38#wechat_redirect) 175 | 24. [每天起床第一句，看看Spark调度器](https://mp.weixin.qq.com/s?__biz=MzA5ODY0NzgxNA==&mid=2247484701&idx=1&sn=586d2ff53dfdcf6d4e55c8d1f4df415a&chksm=908f2f74a7f8a662bfcc5a38f156dfd5f5cafd97873ff22079ed7890bdefc7fbee1de60e1b86&scene=38#wechat_redirect) 176 | 25. [Spark监控报错javax.servlet.http.HttpServletRequest.isAsyncStarted](https://mp.weixin.qq.com/s?__biz=MzA5ODY0NzgxNA==&mid=2247484742&idx=1&sn=267d5554c256095b9f07d90eaad874cd&chksm=908f2f2fa7f8a6399abd35c9580dce34b0d838ae923cece8503db3218fc148e630fdc1149fe2&scene=38#wechat_redirect) 177 | 26. [Spark UI界面实现原理](https://mp.weixin.qq.com/s?__biz=MzA5ODY0NzgxNA==&mid=2247484779&idx=1&sn=ccfde11a8e012600ea4073a563a3a95b&chksm=908f2f02a7f8a614e48875d901380fd7a16a320ceb9f42d7c1aa164af89e4d58f9b14a5b3bcd&scene=38#wechat_redirect) 178 | 27. [生产Spark开发读取云主机HDFS异常剖析流程](https://mp.weixin.qq.com/s?__biz=MzA5ODY0NzgxNA==&mid=2247484790&idx=1&sn=447b9d635c9aa2e93da998fbe47e3f39&chksm=908f2f1fa7f8a6090f9f5c6b680bd8495bcab1eb158a3a2e1f78a5ff04019ff6f3c6fa0ef5f5&scene=38#wechat_redirect) 179 | 28. [生产SparkSQL如何读写本地外部数据源及排错](https://mp.weixin.qq.com/s?__biz=MzA5ODY0NzgxNA==&mid=2247484801&idx=1&sn=35154abd41f9dca9c75fe92c7fafc7a9&chksm=908f2fe8a7f8a6fe9e06ce51c3541e41a2cd2783e0229c58838b4f00872b27fbc2701f9b531c&scene=38#wechat_redirect) 180 | 29. [Spark Shuffle详解剖析](https://mp.weixin.qq.com/s?__biz=MzA5ODY0NzgxNA==&mid=2247484821&idx=1&sn=2c82a9c777e80934121e58e75bfb6b7e&chksm=908f2ffca7f8a6ea0b3250d6248daaea5525b264cc8ebba92d6fba23aaa4bea74bca0d31a3c4&scene=38#wechat_redirect) 181 | 30. [生产Spark Streaming 黑名单过滤案例](https://mp.weixin.qq.com/s?__biz=MzA5ODY0NzgxNA==&mid=2247484835&idx=1&sn=9914834b627f8f3336837b13755dde28&chksm=908f2fcaa7f8a6dcef571229a49d8c76d2d1d997a626d4c1c83e3f91ecfe29820a0251a7d080&scene=38#wechat_redirect) 182 | 31. [生产Spark Executor Dead快速剖析](https://mp.weixin.qq.com/s?__biz=MzA5ODY0NzgxNA==&mid=2247484859&idx=1&sn=bc67b9dff45af761d3d5b85ae4b31d41&chksm=908f2fd2a7f8a6c4204661fcf712b025192d51a9b28a24cccaa589e15229fcd641f39b6dc430&scene=38#wechat_redirect) 183 | 32. [最佳实践之Spark写入Hfile经典案例](https://mp.weixin.qq.com/s?__biz=MzA5ODY0NzgxNA==&mid=2247484931&idx=1&sn=c7ee07760e13f0c8a6fa92be5143af17&chksm=908f2c6aa7f8a57c4b148fcf88dbd49840d0ee47116e6143acf912bc4b8ebee4220e11b3e41a&scene=38#wechat_redirect) 184 | 33. [Spark内存管理之一 静态内存管理](https://mp.weixin.qq.com/s?__biz=MzA5ODY0NzgxNA==&mid=2247484975&idx=1&sn=2a865cc0cd270f51c823ec736ae75aeb&chksm=908f2c46a7f8a55033d6dd0dbcd9dd728131fe42a267376c120d0844e68418e2efad7776d4ac&scene=38#wechat_redirect) 185 | 34. [Spark内存管理之二 统一内存管理及设计理念](https://mp.weixin.qq.com/s?__biz=MzA5ODY0NzgxNA==&mid=2247484992&idx=1&sn=ef433d9279e4f457215a428d6fd2439a&chksm=908f2c29a7f8a53ff3ed4e5790956394d2dd568102f8549afe688716646c13e640b48e68bd93&scene=38#wechat_redirect) 186 | 35. [Spark内存管理之三 UnifiedMemoryManager分析](https://mp.weixin.qq.com/s?__biz=MzA5ODY0NzgxNA==&mid=2247485031&idx=1&sn=2450bebd583de0dd43adfe7f3f851bc6&chksm=908f2c0ea7f8a518c88c7060fd3c2a167fa152998d5d45906898c10321fb6b65d693460cc232&scene=38#wechat_redirect) 187 | 37. [生产SparkStreaming数据零丢失最佳实践(含代码)](https://mp.weixin.qq.com/s?__biz=MzA5ODY0NzgxNA==&mid=2247485022&idx=1&sn=4a2f3d0e360c8681619a4603df84bb43&chksm=908f2c37a7f8a5210e611d8f77721ebaa01e887a312f76fa72e32c77cc9fa023d426d1181278&scene=38#wechat_redirect) 188 | 38. [人人都应该会的-生产Spark2.4.0如何Debug源代码](https://mp.weixin.qq.com/s?__biz=MzA5ODY0NzgxNA==&mid=2247485034&idx=1&sn=f2ebe2d54388ce2c49067e158948d46a&chksm=908f2c03a7f8a515142920dd0c49ada71b3db1452b66a95eb62f53bdf93847251ecc9f1c7e08&scene=38#wechat_redirect) 189 | 39. [老司机带你详解~Spark2.4.2新版本变化](https://mp.weixin.qq.com/s?__biz=MzA5ODY0NzgxNA==&mid=2247485085&idx=1&sn=f07ca47d4a24de2e1d50b03a50d65c36&chksm=908f2cf4a7f8a5e2b6435eb95c3742796ca87b034c320111e57ab20ee488efae42d7979ad79e&scene=38#wechat_redirect) 190 | 40. [Kudu与Spark 生产最佳实践](https://mp.weixin.qq.com/s?__biz=MzA5ODY0NzgxNA==&mid=2247485117&idx=1&sn=a33bca142725f5d2a567add84208bb63&chksm=908f2cd4a7f8a5c2afcfa2c0a537d0a45d7d0ddc67d8c7fcb9ad7e2af80044b5771b04bc1807&scene=38#wechat_redirect) 191 | 41. [Spark中Cache与Persist的巅峰对决](https://mp.weixin.qq.com/s?__biz=MzA5ODY0NzgxNA==&mid=2247485240&idx=1&sn=76a1490d730a337786c20e56c60ad58f&chksm=908f2d51a7f8a44746dcf378de5b5dbc0c58e4a045c6224782d5995860b9b799c8315d7e22ec&scene=38#wechat_redirect) 192 | 42. [不得不会的Spark SQL常见4种数据源](https://mp.weixin.qq.com/s?__biz=MzA5ODY0NzgxNA==&mid=2247485255&idx=1&sn=f06cb78d09668aea2b07a7656a3890c8&chksm=908f2d2ea7f8a438efd7cc2bc0ec368ebeda004f21b3f843d4f85bd61b28e721f1c700c243f0&scene=38#wechat_redirect) 193 | 43. [生产常用Spark累加器剖析之一](https://mp.weixin.qq.com/s?__biz=MzA5ODY0NzgxNA==&mid=2247485045&idx=1&sn=5e18fdb78320f6adf2a3d063bde1ff62&chksm=908f2c1ca7f8a50ad1d6c0c9936e48e59a13bf1000ed8a8a4486ee0cfabfdd7834acd222f6bc&scene=38#wechat_redirect) 194 | 44. [生产常用Spark累加器剖析之二](https://mp.weixin.qq.com/s?__biz=MzA5ODY0NzgxNA==&mid=2247485077&idx=1&sn=ef13c89d8c155b4c4c43bec67b53cd7f&chksm=908f2cfca7f8a5eae16b7b2ac1275f80fae32951c6561d3fad98ad9c0d9a92b8eb868ac2d81b&scene=38#wechat_redirect) 195 | 45. [生产常用Spark累加器剖析之三(自定义累加器)](https://mp.weixin.qq.com/s?__biz=MzA5ODY0NzgxNA==&mid=2247485128&idx=1&sn=2dbf2fb557fd37b05cb39eafbae155fd&chksm=908f2ca1a7f8a5b738620e573f52a4134147e74108d53a2d84837669d9a0086c4cb0b304116b&scene=38#wechat_redirect) 196 | 46. [生产常用Spark累加器剖析四](https://mp.weixin.qq.com/s?__biz=MzA5ODY0NzgxNA==&mid=2247485191&idx=1&sn=0e52db02ab49536f4e1eebc506534851&chksm=908f2d6ea7f8a478c7fc1c5ca1d826059f97e8085c66b7e5975bf46025166d0178e76a0489c0&scene=38#wechat_redirect) 197 | 198 | ##### Flink 199 | 200 | 1. [若泽数据Flink实战系列](https://ke.qq.com/course/350493) 201 | 2. [最全的Flink部署及开发案例(KafkaSource+SinkToMySQL)](https://mp.weixin.qq.com/s?__biz=MzA5ODY0NzgxNA==&mid=2247484501&idx=1&sn=8fb72307838fcd5abe0614d2887b10e2&chksm=908f2e3ca7f8a72a311f28c0c961b5861fab2f55d89095ba439e5e61baf4ad4027c22f1f84b0&mpshare=1&scene=23&srcid=1110xBCjEud8MbVLBkZURrNJ#rd ) 202 | 203 | ##### HBase 204 | 205 | 1. [HBase全面解读](https://mp.weixin.qq.com/s?__biz=MzA5ODY0NzgxNA==&mid=2247484963&idx=1&sn=1d8864515c20d38c19d40aa5446e704d&chksm=908f2c4aa7f8a55cb82f640ddb0d51c2ad4f2f8d613422769ee977d95958fdb7e9e3bdf50dce&scene=38#wechat_redirect) 206 | 2. [记录2018年底最后1次HBase故障维护](https://mp.weixin.qq.com/s?__biz=MzA5ODY0NzgxNA==&mid=2247484729&idx=1&sn=74aca97d3904593416ede7ee9f39c5a9&chksm=908f2f50a7f8a646e11c6ed67209c52ce81bc9d90d2cc5d750d5668a04e621d4ff680cf3701e&scene=38#wechat_redirect) 207 | 3. [HBase集群间实现数据相互同步](https://mp.weixin.qq.com/s?__biz=MzA5ODY0NzgxNA==&mid=2247484705&idx=1&sn=ff9c4b9b578104f81e8af9933a58b62f&chksm=908f2f48a7f8a65e3e6a8de88ddaf4926cfc1df12c557105051ee295348925fe14e07bbe4cfc&scene=38#wechat_redirect) 208 | 4. [某司生产 | Nginx配置HBaseWeb转发](https://mp.weixin.qq.com/s?__biz=MzA5ODY0NzgxNA==&mid=2247484685&idx=1&sn=a8e31a4a21600000ed1a2722be6c57ad&chksm=908f2f64a7f8a67275204a294aa368c7cd5ef4e449fb2b453a6386504d2684ef5cee1262c4d3&scene=38#wechat_redirect) 209 | 210 | ##### Hue 211 | 212 | 1. [hue解决下载10万行的限制](https://mp.weixin.qq.com/s?__biz=MzA5ODY0NzgxNA==&mid=2247484749&idx=1&sn=b92427e390bf71fd44cc203caa939b06&chksm=908f2f24a7f8a632427ec9f9d12e6483a30d8df3515892f539231005a8480242358b08a73e9e&scene=38#wechat_redirect) 213 | 214 | ##### Azkaban 215 | 216 | 1. [Azkaban3.X 全面解读](https://mp.weixin.qq.com/s?__biz=MzA5ODY0NzgxNA==&mid=2247485039&idx=1&sn=5d305aacfd58d2b820d07a204d8065e7&chksm=908f2c06a7f8a510ec1dfe79af6bef7c9e64fbc7352b2a92a1cc7a1781f6256bfa445c2b4f1d&scene=38#wechat_redirect) 217 | 218 | ##### Docker 219 | 220 | 1. [Docker使用详解](https://mp.weixin.qq.com/s?__biz=MzA5ODY0NzgxNA==&mid=2247485124&idx=1&sn=3a73219292ea18bb9e2dee574b1001c4&chksm=908f2cada7f8a5bb2f7aa8ca55bf19697bfb0ed37347bf3b53f29355143404d306a394b83c4c&scene=38#wechat_redirect) 221 | 222 | ##### Ambari 223 | 224 | 1. [Ambari2.7部署文档](https://mp.weixin.qq.com/s?__biz=MzA5ODY0NzgxNA==&mid=2247484813&idx=1&sn=67fcf7e37d1371147542e38c0d0fecc7&chksm=908f2fe4a7f8a6f2cd5cc7d1c2be54b035860e992614b702ee219c98e361ad07dcb518580267&scene=38#wechat_redirect) 225 | 226 | ##### Impala 227 | 228 | 1. [入门 Impala只需此篇](https://mp.weixin.qq.com/s?__biz=MzA5ODY0NzgxNA==&mid=2247485170&idx=1&sn=65aad9ea33c14a134eb8b93b9c6cbc7a&chksm=908f2c9ba7f8a58d65100fa76aedadb5064b539f4a49cd284aebb32b2df49456319fa3c3e98c&scene=38#wechat_redirect) 229 | 230 | ##### Python 231 | 232 | 1. [PyTorch 1.0宣布用于研究和生产AI项目](http://mp.weixin.qq.com/s?__biz=MzA5ODY0NzgxNA==&mid=2247483922&idx=1&sn=6a9d3fd86618657370fcc1d76cc6e2c3&chksm=908f287ba7f8a16d38a2db5d661e55f2b406c62502f701ee6abf58421b7863756c4534ca676d&scene=27#wechat_redirect) 233 | 2. [Python核心笔记（一）](https://mp.weixin.qq.com/s?__biz=MzA5ODY0NzgxNA==&mid=2247484184&idx=1&sn=b59de2a180a9a7dd30b0fe36caf64579&chksm=908f2971a7f8a0671b9c8378a7343e3747cf0b74f2c55fcf733e833aa9b5f0c392a33c598306&scene=38#wechat_redirect) 234 | 3. [Python核心笔记（二）](https://mp.weixin.qq.com/s?__biz=MzA5ODY0NzgxNA==&mid=2247484185&idx=1&sn=8040433e2ba557364b73536fbbf164a6&chksm=908f2970a7f8a066398a577e75586b0f1687ac57eece3a78802f154287fa3c34d13bc5882a7b&scene=38#wechat_redirect) 235 | 4. [Pandas数据分析入门（一）](https://mp.weixin.qq.com/s?__biz=MzA5ODY0NzgxNA==&mid=2247484190&idx=1&sn=53dfa78568d493b5eeec0149577a1945&chksm=908f2977a7f8a061b211dd701e6dd2478bc8b3f39b9f3fb8d017bb4f951e9802e65ae8e41842&scene=38#wechat_redirect) 236 | 5. [Pandas数据分析入门（二）](https://mp.weixin.qq.com/s?__biz=MzA5ODY0NzgxNA==&mid=2247484193&idx=1&sn=d79339ff1f04bdd8ee6b938c24f357cc&chksm=908f2948a7f8a05eccc7c62e591953b732822e621b7ecba657506e17250b7d344401def9a2c3&scene=38#wechat_redirect) 237 | 6. [Kaggle入门经典：Titanic生还预测](https://mp.weixin.qq.com/s?__biz=MzA5ODY0NzgxNA==&mid=2247484197&idx=1&sn=30d1a46a45154240acdd64a13a81843d&chksm=908f294ca7f8a05ad8ae971745f9ec3995664d912d0d6ba6ad20fefe3269199c6e3be2bbbbc7&scene=38#wechat_redirect) 238 | 7. [Titanic生还预测（一）构建基本模型](https://mp.weixin.qq.com/s?__biz=MzA5ODY0NzgxNA==&mid=2247484203&idx=1&sn=dc892ec40da8bb0601ba70cb7bcd7e25&chksm=908f2942a7f8a05475c784612c5ae46fdb86b1522ad6bb5f0e941c4a97a75c711d890e9c60b7&scene=38#wechat_redirect) 239 | 8. [Titanic生还预测（二）](https://mp.weixin.qq.com/s?__biz=MzA5ODY0NzgxNA==&mid=2247484202&idx=1&sn=0327f9d82e5242ca720faa4ae4d57b18&chksm=908f2943a7f8a055f2013bfae49f16407e9bc393b370a5c2ed6e8160ef3228018685b5627944&scene=38#wechat_redirect) 240 | 9. [Titanic生还预测（三）](https://mp.weixin.qq.com/s?__biz=MzA5ODY0NzgxNA==&mid=2247484206&idx=1&sn=a49f51074dbc4ace404b885233d1f18d&chksm=908f2947a7f8a05149a14a0838616a1aa19197904e7598b87940684c0b569c4f48ab4ab3aedb&scene=38#wechat_redirect) 241 | 10. [Titanic生还预测（四）](https://mp.weixin.qq.com/s?__biz=MzA5ODY0NzgxNA==&mid=2247484209&idx=1&sn=10960b21f750bd77eb58713a68f60101&chksm=908f2958a7f8a04ecfb134006c876e4fc950125049b7e1b4b4a3eb84ae4be789e13250910e47&scene=38#wechat_redirect) 242 | 11. [Titanic生还预测（五）](https://mp.weixin.qq.com/s?__biz=MzA5ODY0NzgxNA==&mid=2247484212&idx=1&sn=9462578cd45bfe1ac9152522eb7f27aa&chksm=908f295da7f8a04be16a2bef07e4fc6c90e3a3302978d20dfce0ad3f439c4ef2d68f46994220&scene=38#wechat_redirect) 243 | 244 | ##### 实时同步中间件 245 | 246 | 1. [大数据之实时数据源同步中间件--生产上Canal与Maxwell颠峰对决](大数据之实时数据源同步中间件--生产上Canal与Maxwell颠峰对决) 247 | 2. [实时数仓之Maxwell读取MySQL binlog日志](https://mp.weixin.qq.com/s?__biz=MzA5ODY0NzgxNA==&mid=2247484916&idx=1&sn=69d6ddcf5cb1a81b26e6eeaf67f6e457&chksm=908f2f9da7f8a68baa61ee23b990dfb392ba925d5b1e744cba7f06503910fecb8741cb4867fe&scene=38#wechat_redirect) 248 | 3. [实时数仓之Maxwell读取MySQL binlog日志到Kafka](https://mp.weixin.qq.com/s?__biz=MzA5ODY0NzgxNA==&mid=2247484936&idx=1&sn=f695fe5c743afd13651934d9c048df9e&chksm=908f2c61a7f8a57788c35ac259d7643176985f43dfc252038e14bba436cbb746de1d6d02bf7e&scene=38#wechat_redirect) 249 | 250 | ##### Java 251 | 252 | 1. [Java可扩展线程池之ThreadPoolExecutor](https://mp.weixin.qq.com/s?__biz=MzA5ODY0NzgxNA==&mid=2247484003&idx=1&sn=b2a7c375204d0077c7e949193bd3afc3&chksm=908f280aa7f8a11c7502fc8312d907ea35cbb7abb80ac70952485a770a28c14974835e9663d4&scene=27#wechat_redirect) 253 | 2. [面试常考点-Java线程池之拒绝策略](http://mp.weixin.qq.com/s?__biz=MzA5ODY0NzgxNA==&mid=2247484034&idx=1&sn=27d8fbcc33788b7dbb4de6a0a7f0155f&chksm=908f28eba7f8a1fd7ae42c8f21932d4cebd9c1d2e7cdd4a604adc48d3f3f479085c19d7eb864&scene=27#wechat_redirect) 254 | 3. [再谈单例设计模式](http://mp.weixin.qq.com/s?__biz=MzA5ODY0NzgxNA==&mid=2247484120&idx=1&sn=9c48b5aa6e515590d3c4de7d0112378b&chksm=908f28b1a7f8a1a77c10a821b7a60cbe17d9b103f733cff775349844168c79b72c79596d57bb&scene=27#wechat_redirect) 255 | 4. [Java类加载方式你知道几种？](http://mp.weixin.qq.com/s?__biz=MzA5ODY0NzgxNA==&mid=2247484156&idx=1&sn=bedde12e5ee13fc14060ad484671e012&chksm=908f2895a7f8a183c0585d83af54bbcee64bd2e8a46f6cca906ccc52cab6b46a2cb7c90aa1a5&scene=27#wechat_redirect) 256 | 257 | ##### Github 258 | 259 | 1. [如何将我们谱写的代码供凡人瞻仰](https://mp.weixin.qq.com/s?__biz=MzA5ODY0NzgxNA==&mid=2247484169&idx=1&sn=37fc35363216396fd18ae4caef87a657&chksm=908f2960a7f8a0760939286b2c97daa75aa0783515805839434a099557837e434f58519d2447&scene=27#wechat_redirect) 260 | 261 | ##### CDH 262 | 263 | 1. [CDH下载各种软件包](http://blog.itpub.net/30089851/viewspace-2092318/) 264 | 2. [CDH4/5集群正确启动和停止顺序](http://blog.itpub.net/30089851/viewspace-2126298/) 265 | 3. [CDH5 快速入门手册v1.0(体系架构+目录详解)](http://blog.itpub.net/30089851/viewspace-1991862/) 266 | 4. [CDH4/5配置文件之深度解析](http://blog.itpub.net/30089851/viewspace-2110288/) 267 | 5. [CDH5之Trash](http://blog.itpub.net/30089851/viewspace-1990991/) 268 | 6. [记录一次帮网友解决CDH集群机器的时钟偏差](http://blog.itpub.net/30089851/viewspace-2133322/) 269 | 7. [CDH集群机器,安装多个CDH版,会出现命令找不到,如hadoop,hdfs等等](http://blog.itpub.net/30089851/viewspace-2128683/) 270 | 8. [CDH5.8.2安装之Hash verification failed](http://blog.itpub.net/30089851/viewspace-2128607/) 271 | 9. [记录CDH Spark2的spark2-submit的一个No such file or directory问题](http://blog.itpub.net/30089851/viewspace-2134627/) 272 | 10. [记录CDH5.10一个clients.NetworkClient: Bootstrap broker ip:9092 disconnected问题](http://blog.itpub.net/30089851/viewspace-2135135/) 273 | 11. [记录自定义kafka的parcel库,CDH安装kafka服务,无法安装过去的排雷过程](http://blog.itpub.net/30089851/viewspace-2136372/) 274 | 12. [记录CDH安装的一个坑:could not contact scm server at localhost:7182, giving up](http://blog.itpub.net/30089851/viewspace-2137618/) 275 | 13. [CDH5之Found class jline.Terminal, but interface was expected](http://blog.itpub.net/30089851/viewspace-2082146/) 276 | 14. [CDH5之Exhausted available authentication methods](http://blog.itpub.net/30089851/viewspace-2075759/) 277 | 15. [CDH5之Unexpected error.Unable to verify database connection](http://blog.itpub.net/30089851/viewspace-1987886/) 278 | 16. [生产CDH5配置lzo](http://mp.weixin.qq.com/s?__biz=MzA5ODY0NzgxNA==&mid=2247484122&idx=1&sn=bf236f01873ad65d7da4503adbd6614e&chksm=908f28b3a7f8a1a5caedb3437baf9667a649a4575b0d7a23ea396366a5f870540a902f3649bd&scene=27#wechat_redirect) 279 | 17. [CDH5.16.1集群企业真正离线部署](https://mp.weixin.qq.com/s?__biz=MzA5ODY0NzgxNA==&mid=2247485164&idx=1&sn=d19b4cf1bd7d0d0fdd73f91019a70b3a&chksm=908f2c85a7f8a593a03b10a8557e67e2088e5c6e820623040a693e0bd7da9fc3a41da0b5223b&scene=38#wechat_redirect) 280 | 18. [生产CDH Hadoop编译-支持4种压缩格式(含面试题)](https://mp.weixin.qq.com/s?__biz=MzA5ODY0NzgxNA==&mid=2247485180&idx=1&sn=06db711f44da25ac321ea8e1907330e8&chksm=908f2c95a7f8a583afea0810eebb1af7be1614335e06795ce8f61ab0e33c6601ad93446d583e&scene=38#wechat_redirect) 281 | 282 | ##### 故障案例 283 | 284 | 1. [上海某公司生产MySQL灾难性挽救](https://mp.weixin.qq.com/s?__biz=MzA5ODY0NzgxNA==&mid=2247485187&idx=1&sn=407674c9adeca9056b4401e0d5229cf7&chksm=908f2d6aa7f8a47c806f9de4bcf9c86621908cfdc9f7b38a42714944a43b65d4cee03b6a924d&scene=38#wechat_redirect) 285 | 286 | 287 | ## 线下班学员风采 288 | 289 | 1. [2019元旦-线下项目第11期圆满结束](https://mp.weixin.qq.com/s?__biz=MzA5ODY0NzgxNA==&mid=2247484658&idx=1&sn=79308ce0a33de74a70ca9ab4cfd3fd12&chksm=908f2e9ba7f8a78d97055c40e6d80ca3439728ccae29d979ec94915f37d850498cb39d46a1b6&scene=38#wechat_redirect) 290 | 2. [2019清明-线下项目第12期圆满结束](https://mp.weixin.qq.com/s?__biz=MzA5ODY0NzgxNA==&mid=2247484991&idx=1&sn=300dead9c8c0d93140e10a4782ec7177&chksm=908f2c56a7f8a5403775a4af31b23badf9b18e8d40923e6879f44cb4ae236a6183285a96b40c&scene=38#wechat_redirect) 291 | 3. [2019五一-线下项目第13期圆满结束](https://mp.weixin.qq.com/s?__biz=MzA5ODY0NzgxNA==&mid=2247485111&idx=1&sn=d31a088d6066b4dc166747606cb2b13d&chksm=908f2cdea7f8a5c873695527e244d8274913bedc27bb1428b0972dcdcdc963473b43b1b94a17&scene=38#wechat_redirect) 292 | 4. [2019端午-线下项目第14期圆满结束](https://mp.weixin.qq.com/s?__biz=MzA5ODY0NzgxNA==&mid=2247485224&idx=1&sn=d7c252710afbc84693a2f700d9cf27ee&chksm=908f2d41a7f8a457b188c71efeeac4a8c53526c40aac3f10b72738e946c985e5196ebc81921a&scene=38#wechat_redirect) 293 | 294 | ## 高薪就业及面试题 295 | 296 | [高薪就业](http://ruozedata.com/job.html) 297 | 298 | [2018年高薪就业及面试题](https://github.com/ruozedata/BigData/blob/master/interview/%E5%B8%B8%E8%A7%81%E9%9D%A2%E8%AF%95%E9%A2%98.md) 299 | 300 | -----以下是2019年高薪就业及面试题------- 301 | 302 | 1. [高级班学员高薪offer32w，你比他高吗？](https://mp.weixin.qq.com/s?__biz=MzA5ODY0NzgxNA==&mid=2247484774&idx=1&sn=a806ae405cb06f3061010eeec03c80b0&chksm=908f2f0fa7f8a619dc512cd60b313cfd7021d2a6e9c272d84622f35f51af1f77b715019e7c6c&scene=38#wechat_redirect) 303 | 2. [捷报: 高级班学员月薪22K及上周3家offer的面试题](https://mp.weixin.qq.com/s?__biz=MzA5ODY0NzgxNA==&mid=2247484786&idx=1&sn=9acc8eb89ca98f0207ec144c3fff4018&chksm=908f2f1ba7f8a60d2fbbf2afbb15d56506497779fff937add65721304df3f123b7ed63548746&scene=38#wechat_redirect) 304 | 3. [刚出炉的3家大数据面试题(含高级)，你会吗？](https://mp.weixin.qq.com/s?__biz=MzA5ODY0NzgxNA==&mid=2247484831&idx=1&sn=02c8b043f8ed809629af4da5a368d4bf&chksm=908f2ff6a7f8a6e05a2be0e68e06b774638e7ef65bb69390de9cd4e858459ca8d6887ecd7b73&scene=38#wechat_redirect) 305 | 4. [捷报:刚出炉年薪30w的offer和面试题](https://mp.weixin.qq.com/s?__biz=MzA5ODY0NzgxNA==&mid=2247484867&idx=1&sn=9bee69f84ef57ba6e904b95d0d710c67&chksm=908f2faaa7f8a6bc760053d3525c273a7d31e35686f62268993125de65d24062297fe9098b57&scene=38#wechat_redirect) 306 | 5. [捷报:高级班学员年薪37.4W的offer及3家面试题](https://mp.weixin.qq.com/s?__biz=MzA5ODY0NzgxNA==&mid=2247484885&idx=1&sn=0181cb953cf4e7f7244fee5ea7b19e70&chksm=908f2fbca7f8a6aa33a4b6d59126a33a0b1aeee08938b338106cddeeec98d941062de3bc943f&scene=38#wechat_redirect) 307 | 6. [捷报:线下班学员年薪35W的offer及面试题](https://mp.weixin.qq.com/s?__biz=MzA5ODY0NzgxNA==&mid=2247485017&idx=1&sn=bc2d7d96d6b3e260e27578f6eeca612e&chksm=908f2c30a7f8a52605a77ad13a4803f654384245afdb139d66c0ed1402f33ae5611e54387ec3&scene=38#wechat_redirect) 308 | 7. [捷报:上周若泽数据6名学员喜捷offer(含腾讯)](https://mp.weixin.qq.com/s?__biz=MzA5ODY0NzgxNA==&mid=2247485062&idx=1&sn=58ef7071b40d0774b2eacdb02e0dd5b7&chksm=908f2cefa7f8a5f93b31a557d11b259eaaaa125ce858cdefb16a2dbbba088dfb7465e699c67d&scene=38#wechat_redirect) 309 | 8. [捷报:连续2周若泽数据第7-12名学员喜捷offer(含蚂蚁金服)](https://mp.weixin.qq.com/s?__biz=MzA5ODY0NzgxNA==&mid=2247485102&idx=1&sn=4e59ad6dee49be25709f722666847dcb&chksm=908f2cc7a7f8a5d1a3cd34691f01d06a213daceb5da40254899cb5ae0ff8062550e811f6a564&scene=38#wechat_redirect) 310 | 9. [捷报:连续3周若泽数据第13-15名学员喜捷offer(年薪总和108W)](https://mp.weixin.qq.com/s?__biz=MzA5ODY0NzgxNA==&mid=2247485163&idx=1&sn=8189b2ecea579c84773d2ac893f6edef&chksm=908f2c82a7f8a5943ff09be3d5542ef963a14c7e23b67216fef476b53eb201a5d4b3e3bf0515&scene=38#wechat_redirect) 311 | 10. [捷报:连续4周若泽数据第16-19名学员喜捷offer(含面试题)](https://mp.weixin.qq.com/s?__biz=MzA5ODY0NzgxNA==&mid=2247485200&idx=1&sn=68bd4b2464ec6b72ccfdc8addbefc281&chksm=908f2d79a7f8a46fd2902ed076ffd8936c48d0cac2270d1340b22370cfc5ba00e618ca2f004c&scene=38#wechat_redirect) 312 | 11. [捷报:连续5周若泽数据第20-21名学员喜捷offer(含面试题)](https://mp.weixin.qq.com/s?__biz=MzA5ODY0NzgxNA==&mid=2247485251&idx=1&sn=cf40005340e94fc26e4a76e0f33032f4&chksm=908f2d2aa7f8a43cea221286aa4542ee635ce77a90fce5f72db2df46cf7b168deaae5afc7766&scene=38#wechat_redirec) 313 | 314 | ## 课程大纲 315 | 316 | 1. [零基础大数据集训营](http://ruozedata.com/basic.html) 317 | 2. [大数据高级实战班](http://ruozedata.com/advanced.html) 318 | 3. [大数据线下精英班](http://ruozedata.com/line.html) 319 | 320 | -------------------------------------------------------------------- 321 | ### Join us if you have a dream. 322 | 323 | ##### 若泽数据官网: [http://ruozedata.com](http://ruozedata.com) 324 | ##### 免费视频及公开课: [http://ruoze.ke.qq.com](http://ruoze.ke.qq.com) 325 | ##### 扫一扫，学一学: 326 | ![image](https://github.com/Hackeruncle/BigData/blob/master/blog/pic/%E8%8B%A5%E6%B3%BD%E6%95%B0%E6%8D%AE--%E6%89%AB%E6%8F%8F%E5%85%A5%E5%8F%A3.png?raw=true) 327 | 有任何疑问的， 328 | QQ加课程顾问-星星: 1952249535 ， 329 | 或微信(ruoze_star)扫描以上二维码， 邀请进群。 330 | 331 | 332 | 333 | 334 | 335 | 336 | 337 | 338 | 339 | 340 | 341 | -------------------------------------------------------------------------------- /blog/pic/小程序.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/ruozedata/BigData/6b9dcab231ad061ceafa7f92d68c26f6f57bef3f/blog/pic/小程序.png -------------------------------------------------------------------------------- /blog/pic/微信公众号.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/ruozedata/BigData/6b9dcab231ad061ceafa7f92d68c26f6f57bef3f/blog/pic/微信公众号.png -------------------------------------------------------------------------------- /blog/pic/星星.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/ruozedata/BigData/6b9dcab231ad061ceafa7f92d68c26f6f57bef3f/blog/pic/星星.png -------------------------------------------------------------------------------- /blog/pic/若泽数据--扫描入口.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/ruozedata/BigData/6b9dcab231ad061ceafa7f92d68c26f6f57bef3f/blog/pic/若泽数据--扫描入口.png -------------------------------------------------------------------------------- /interview/常见面试题.md: -------------------------------------------------------------------------------- 1 | ## 若泽大数据--内部学员面试题一览 2 | 请花1min，阅读or收藏； 3 | 我们整理内部学员的面试题，当前更新于 20180512。 4 | 5 | 领取大数据实战班和公开课视频，微信关注公众号自动领取 : 6 | [若泽大数据](http://ruozedata.com) 7 | 8 | 9 | ## [20180724] [小伙伴刚出炉的大数据面试题，你们猜猜应该多少K薪水?](https://mp.weixin.qq.com/s?__biz=MzA5ODY0NzgxNA==&mid=2247484172&idx=1&sn=ea93e4156bea13f80d3dc7369cd2ccf5&chksm=908f2965a7f8a073fb5891183962ca6d7f99619a54c7c6272a62fcf4a88c6c311f218e72ae46&scene=38#wechat_redirect) 10 | 11 | ## [20180716] [拿了6个offer的那个臭不要脸，可不可以分一个给我](http://mp.weixin.qq.com/s?__biz=MzA5ODY0NzgxNA==&mid=2247484145&idx=1&sn=d3c1ecc9dee62bc5d5af644f6d2a24af&chksm=908f2898a7f8a18e4104d77b81b419898b9daa39cbcc2d04895c2c3cc4659beebbac72a33041&scene=27#wechat_redirect) 12 | 13 | ## [20180713] [来看看22K的大数据面试题，难吗!](https://mp.weixin.qq.com/s?__biz=MzA5ODY0NzgxNA==&mid=2247484132&idx=1&sn=3f5f72748ec6b55fb9346768aea5d96d&chksm=908f288da7f8a19b96edcefc428768fc0d2001ba21c9a16ff718e94f037f9a946f27531f38bd&scene=38#wechat_redirect) 14 | 15 | ## [20180629] [若泽大数据最强学员来了！](https://mp.weixin.qq.com/s?__biz=MzA5ODY0NzgxNA==&mid=2247484079&idx=1&sn=e3de81b29cedbfdb2e0affffbe7861b7&chksm=908f28c6a7f8a1d07ecce5c15104cbeb6f21b31283a41a94363b64b546164db75901a71d4c8b&scene=27#wechat_redirect) 16 | 17 | ## [20180608] [若泽大数据-高级班二期神秘学员拿下25K高薪offer](http://mp.weixin.qq.com/s?__biz=MzA5ODY0NzgxNA==&mid=2247483983&idx=1&sn=7186cc970a5e51a481c8b85cb1d5908a&chksm=908f2826a7f8a13062c96b298d7dfab8aff40f88c5d3b0407c4455b4aeae5733a75b707058fc&scene=27#wechat_redirect) 18 | 19 | ## [20180531] [深圳某司高薪面试题](https://mp.weixin.qq.com/s?__biz=MzA5ODY0NzgxNA==&mid=2247483956&idx=1&sn=fd2e5c3e09b58e7ad36307984c5ec56a&chksm=908f285da7f8a14bad124ebd6fae9495cd8f10c3b64e4a0803498f38d7f941ed7532f473ea89&scene=38#wechat_redirect) 20 | 21 | ## [20180529] [北京某互联网大数据开发30K面试题](https://mp.weixin.qq.com/s?__biz=MzA5ODY0NzgxNA==&mid=2247483941&idx=1&sn=ebb2eddc92b73234bef5117ea1986167&chksm=908f284ca7f8a15a61e28bf666b4323ca2a41eca6e04bed925a14f0f5781acec013f062f14fc&scene=27#wechat_redirect%22,%20%22source_url%22:%20%22http://www.ruozedata.com) 22 | 23 | ## [20180526] [链家(一面，二面)](https://mp.weixin.qq.com/s?__biz=MzA5ODY0NzgxNA==&mid=2247483933&idx=1&sn=285bf3995aa5c9acedf443b15a1a3cc3&chksm=908f2874a7f8a162f6e1f146901f7366539eccc3704a935f1031471b7bd4e07cc8ede12af67e&scene=38#wechat_redirect) 24 | 25 | ## [20180525] [若泽大数据，带你切实感受一下好友面试大厂的经历](https://mp.weixin.qq.com/s?__biz=MzA5ODY0NzgxNA==&mid=2247483928&idx=1&sn=34ac42cd1f6239a6d333fa4d563ab372&chksm=908f2871a7f8a167a29ad0de154869d48f6c9290297f45cf15a5e863e39f8b01a02141d13589&scene=27#wechat_redirect) 26 | 27 | 28 | ## [20180524] 29 | * 阐述HDFS生成文件的过程 * Hadoop有哪些优化，调优点 * 阐述对Hive分区的理解 * Hive分桶 * 用Spark干过什么 * 你们公司生产的集群规模 * 懂不懂CDH 30 | 31 | ## [20180508] 七牛云面试题 32 | * 快排 33 | * hive和hdfs之间的联系 34 | * inode和文件描述符 35 | * linux指令如何创建文件 36 | * http中header中放入key value 有什么变化 37 | * 系统调用和库函数区别 38 | * http缓冲实现机智 39 | * session cookie  区别 40 | * 进程间通信方式 41 | * jsp本质 42 | * http请求状状态 43 | * get post put remove 44 | * 数据库join  45 | * 数据库引擎 46 | * hibernate和mybiters区别 47 | * jvm垃圾回收 48 | * hive和关系型数据库区别 49 | * hive实现原理 50 | * spark与mr的区别 51 | 52 | ## [20180502] 二三四五面试题 53 | * 画图讲解Spark工作流程，以及在集群上和各个角色的对应关系 54 | * Spark Streaming程序代码更新后如何操作 55 | * 在一个电商网站中，设计一个订单ID生成方案 56 | * spark-submit如何引入外部jar包 57 | * Spark对于OOM从什么角度下手调整 58 | * org.apache.spark.SparkExectption:Task not serializable，这个错误是什么意思？如何解决？哪些场景会出现这错误？ 59 | 60 | ## [20180427] 面试题 61 | * 有10个文件，每个文件1G，每个文件的每一行存放的都是用户的query，每个文件的query都可能重复。要求你按照query的频度排序 62 | * 有一个1G大小的一个文件，里面每一行是一个词，词的大小不超过16字节，内存限制大小是1M。返回频数最高的100个词 63 | 64 | ## [20180426] 美图二面 65 | * ThriftServer的HA如何去实现，能说下实现的思路嘛 66 | * 说下Zookeeper的watch机制是如何实现的嘛？ 67 | * 场景题： 68 | * 现在有1个client，2个server，当我动态加入一台机器，或者删除一台机器，或者某台机器宕机了，client该如何去感知到，说下实现思路(不使用Zookeeper) 69 | * 如何通信，说说具体实现 70 | 71 | 72 | 73 | ## [20180425] 蚂蚁金服编程题 74 | * 编程题A：求一个整数的平方根，不保留小数。 75 | 76 | * 编程题B： 77 | * 1.年/月/日/xxx.jpg ， 文件夹以 这个形式组织。 78 | * 2.新建文件夹，将所有jpg文件拷贝到该文件夹，更名为 年_月_日_xxx.jpg。 79 | * 3.监控文件夹，如果有增加的jpg文件，自动同步到新文件夹。 80 | * 4.jpg文件只增加不删除。 81 | 82 | ## [20180424] 成都某公司面试题 83 | * 谈谈你对HDFS的了解 84 | * Hadoop2.0做了哪些改动 85 | * Spark与MR的区别在哪里 86 | * 知道除了Spark之外的大数据处理框架嘛 87 | * Spark shuffle，说说 88 | * StringBuilder与StringBuffer的区别 89 | * HashMap与Hashtable的区别 90 | * 二叉树的数据结构是什么样的 91 | * 数据库索引的实现原理 92 | * jvm垃圾收集器，挑一种讲讲 93 | 94 | ## [20180423] 美图面试题 95 | * 为什么选择美图，你知道美图地点在哪里嘛 96 | * 介绍下你做的项目吧 97 | * 数据统一管理平台，我挺感兴趣的，你说说吧 98 | * 我大概知道是怎么回事了，java web这块你参与开发了吗 99 | * 你刚刚项目提到了元数据，你能说说hive的元数据管理嘛，对它了解嘛 100 | * 还是hive，你对hive有哪些原理性了解呢 101 | * 知道AST、operator tree这些长什么样吗 102 | * 那你的hive转mr过程是怎么了解的呢？ 103 | * 除了谓词下推，还能说说其它的优化嘛？别说数据倾斜的调优 104 | * jvm了解不，说下垃圾收集算法 105 | * 平常用java和scala语言哪个多点 106 | * 如果我现在要使用map集合，你觉得哪种适合多线程情况下进行访问 107 | * 如何去监控线程 108 | * Spark 出现OOM，你觉得该怎么进行调优呢？不去动jvm的参数 109 | * 你觉得join该怎么优化 110 | * 你对未来的规划是什么？(五年内) 111 | * 你也就是走技术路线咯 112 | 113 | ## [20180421] 北京3+家面试题 114 | #### hadoop面试: 115 | 1、hadoop集群、namenode如何做到数据同步？ 116 | 2、hdfs副本存放策略 117 | 3、HA如何在挂掉一台namenode节点的状态下，自动切换到另一台？ 118 | 4、mapreduce shuffle过程 119 | 5、mapreduce优化 120 | 121 | #### flume面试: 122 | 1、你能二次源码修改支持parquent格式吗？ 123 | 124 | #### sqoop面试: 125 | 1、抽取某个数据库下的某张表+条件 怎么抽取? 126 | 2、sqoop增量导入 127 | 128 | #### hbase面试: 129 | 1、rowkey如何设计 130 | 2、hbase热点问题 131 | 3、协处理器 132 | 4、hbase优化 133 | 5、hbase的二级索引 134 | 135 | #### hive面试: 136 | 1、数据倾斜 137 | 2、hive能加索引吗？ 138 | 139 | #### spark面试: 140 | 1、rdd dataset dataframe 概念 141 | 2、mapflat 142 | 3、spark资源分配 143 | 144 | #### kafka面试: 145 | 1、怎么保证数据零丢失?和spark streaming结合说说看？ 146 | 2、怎么解决数据重复问题？ 147 | 3、某个kafka节点挂掉对生产和消费有影响吗？ 148 | 4、生产大于消费 lag产生大量的滞后怎么解决？ 149 | 150 | #### 数据库面试: 151 | 1、btree 152 | 2、索引 153 | 3、拉链表 154 | 155 | #### shell面试: 156 | 1、如何查找在Linux目录下的某个文本里的包含相关内容的操作? 157 | 158 | ## [20180420] 蚂蚁金服面试题 159 | * 小文件的合并 160 | * MR与Spark的区别 161 | * 关注哪些名人的博客 162 | * 对大数据领域有什么自己的见解 163 | * 平常怎么学习大数据的 164 | * StringBuilder与StringBuffer的区别 165 | * HashMap与Hashtable的区别 166 | * 谈谈你对树的理解 167 | * 数据库索引的实现 168 | * jvm的内存模型 169 | * jvm的垃圾收集器 170 | * jvm的垃圾收集算法 171 | * HDFS架构 172 | * HDFS读写流程 173 | * Hadoop3.0做了哪些改进 174 | * 谈谈YARN 175 | * 为什么项目选择使用Spark，你觉得Spark的优点在哪里 176 | * 了解Flink与Storm嘛，他们与Spark Streaming的区别在哪里 177 | * 1TB文件，取重复的词，top5指定的资源的场景下，如何快速统计出来 178 | 179 | 180 | ## [20180419] 网易大数据面试题 181 | * 说说项目 182 | * Spark哪部分用得好，如何调优 183 | * Java哪部分了解比较好 184 | * 聊聊并发，并发实现方法，volatile关键字说说 185 | * HashMap的底层原理 186 | * 为什么要重写hashcode和equals 187 | * 说说jvm 188 | * 各个垃圾收集器运用在什么情形 189 | * jvm调优 190 | * 说说io 191 | * 为什么考虑转行呢？是因为原专业不好就业吗？ 192 | 193 | ## [20180418] 数据挖掘面试题 194 | * Java字符串拼接StringBuffer和+=区别 195 | * Scala map和foreach区别 196 | * Spark groupByKey和reduceByKey区别 197 | * Spark将数据写MySQL要注意什么 198 | * Spark repartition和coalesce函数的区别 199 | * 梯度下降、随机梯度下降、mini batch 梯度下降的区别 200 | * SVM原理 201 | * SVM中为什么要转成对偶问题 202 | * SVM在分类时怎么选择合适的核函数 203 | * 特征共线性问题 204 | * Hive外表和内表的区别 205 | * 求解字符串的所有的回文子串 206 | * 贝叶斯定理 207 | * 人员画像 208 | * 推荐系统 svd knn 209 | 210 | 211 | 212 | ## [20180417] 213 | 214 | * 自我介绍 215 | * 最近一个项目的架构，你所负责的模块 216 | * 谈谈你对Spark的理解 217 | * 在这个项目中，你觉得你做的模板中出彩的地方与哪些 218 | * Spark作业提交的流程 219 | * 在工作中使用Spark遇到了哪些问题，如何解决的，请举3个例子 220 | * 谈谈你对JVM的了解 221 | 222 | 223 | -------------------------------------------------------------------------------- /share/公开课列表.md: -------------------------------------------------------------------------------- 1 | ## 腾讯课堂公开课: 2 | [1.大数据入门](https://ke.qq.com/course/235161?tuin=11cffd50) 3 | [2.Spark零基础到实战第二期](https://ke.qq.com/course/246389?tuin=11cffd50) 4 | [3.基于Spark的某互联网直播平台大数据分析项目实战](https://ke.qq.com/course/258137?tuin=11cffd50) 5 | 6 | ###### 每周公开课1次，详情单击，查看课程目录，值得看一看； 7 | 8 | 领取大数据实战班和公开课视频，微信关注公众号自动领取 : 9 | [若泽大数据](http://ruozedata.com) 10 | 11 | 12 | ## 空军一号: 13 | * 前面1年的分享，没有记录下来 14 | * .......... 15 | * .......... 16 | * [20180413] 五哥(Airflow) & 二舅哥(CBoard BI数据可视化) 17 | * [20180420] YJ(TiDB) 18 | * [20180511] 于博(Tableau如何做大数据可视化) 19 | 20 | ## GIT fork 21 | --------------------------------------------------------------------------------