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README.md
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大数据学习指南
===
>大数据学习指南，从零开始学习大数据开发，包含大数据学习各个阶段资汇总
### [大数据学习or转型的一些建议](https://github.com/Dr11ft/BigDataGuide/blob/master/Docs/%E5%A4%A7%E6%95%B0%E6%8D%AE%E5%AD%A6%E4%B9%A0or%E8%BD%AC%E5%9E%8B.md)
### [GitHub图片不显示解决方案](https://blog.csdn.net/qq_41544550/article/details/106218291)
## 公众号
关注我的公众号：**旧时光大数据**，回复相应关键字，获取更多大数据干货、资料
“大数据学习路线”中我自己看过的视频、文档资料可以直接在公众号获取云盘链接
### 《大数据面试题 V3.0》已出，公众号回复：大数据面试题
<p align="center">
<img src="https://github.com/Dr11ft/BigDataGuide/blob/master/Pics/%E5%85%AC%E4%BC%97%E5%8F%B7%E4%BA%8C%E7%BB%B4%E7%A0%81.jpg" width="200" height="200"/>
<p align="center">
</p>
</p>
概述
---
  1.[大数据简介](https://github.com/Dr11ft/BigDataGuide/blob/master/Docs/%E5%A4%A7%E6%95%B0%E6%8D%AE%E7%AE%80%E4%BB%8B.md)
  2.[大数据相关岗位介绍](https://github.com/Dr11ft/BigDataGuide/blob/master/Docs/%E5%A4%A7%E6%95%B0%E6%8D%AE%E7%9B%B8%E5%85%B3%E5%B2%97%E4%BD%8D%E4%BB%8B%E7%BB%8D.md)
大数据学习路线
---
学习路线中的视频、文档资料可以关注公众号：旧时光大数据，回复相应关键字获取云盘链接
### [大数据学习路线（包含自己看过的视频链接）](https://github.com/Dr11ft/BigDataGuide/blob/master/Docs/%E5%A4%A7%E6%95%B0%E6%8D%AE%E5%AD%A6%E4%B9%A0%E8%B7%AF%E7%BA%BF.md)
编程语言
---
编程语言部分建议先JavaSE，Spark和Flink之前学习Scala，Python看个人或工作，不过有Java基础，Python会快很多（别问我怎么学，问就是使劲拼命学 [ 吃瓜.jpg ]）
### 一、JavaSE（三选一）
  1. [刘意2015版](https://www.bilibili.com/video/BV1pE41167Ye?from=search&seid=15100703070040994669)
  2. [刘意2019版](https://www.bilibili.com/video/BV1gb411F76B?from=search&seid=16116797084076868427)
  3. [尚硅谷宋红康版](https://www.bilibili.com/video/BV1Kb411W75N?from=search&seid=9321658006825735818)
### 二、Scala（二选一）
如果时间短，建议直接看配套Spark的那种三五天的，可以快速了解
  1. [韩顺平老师版](https://www.bilibili.com/video/BV1Mp4y1e7B5?from=search&seid=5450215228532207134)
  2. [清华硕士武晟然老师版](https://www.bilibili.com/video/BV1Mp4y1e7B5?from=search&seid=5450215228532207134)
### 三、Python
推荐黑马的Python视频，通俗易懂，而且文档比较齐全，有Java基础再看Python的话，上手很快
  1. [黑马Python版](https://www.bilibili.com/video/BV1C4411A7ej?from=search&seid=11669436417044703145)
Python文档：
  1. [Python环境搭建与输入输出](https://blog.csdn.net/qq_41544550/article/details/126074237?spm=1001.2014.3001.5501)
  2. [Python运算符与if结构](https://blog.csdn.net/qq_41544550/article/details/126132117?spm=1001.2014.3001.5501)
  3. [Python中的循环结构](https://blog.csdn.net/qq_41544550/article/details/126245387)
  4.[Python数据序列（一）](https://blog.51cto.com/u_15553407/5572403)
  5.[Python中的数据序列（二）](https://blog.51cto.com/u_15553407/5576067)
  6.[Python中的函数](https://blog.51cto.com/u_15553407/5580030)
  7.[Python函数进阶与文件操作](https://blog.51cto.com/u_15553407/5583545)
  8.[Python文件操作与面向对象](https://blog.51cto.com/u_15553407/5587744)
  9.[Python面向对象高级与Python的异常、模块以及包管理](https://blog.51cto.com/u_15553407/5608093)
  10.[Python模块、包与面向对象综合案例](https://blog.51cto.com/u_15553407/5611464)
  11.[Python综合案例](https://blog.51cto.com/u_15553407/5615519)
Linux
---
  [完全分布式集群搭建](https://github.com/Dr11ft/BigDataGuide/blob/master/Hadoop/%E5%88%86%E5%B8%83%E5%BC%8F%E9%9B%86%E7%BE%A4%E6%90%AD%E5%BB%BA.md)
  关于VM、远程登录工具的安装暂时可以参考我的博客，找到相应步骤进行操作即可
  [集群搭建](https://blog.csdn.net/qq_41544550/category_9458240.html)
大数据框架组件
---
### 一、Hadoop
  1.[Hadoop——分布式文件管理系统HDFS](https://github.com/Dr11ft/BigDataGuide/blob/master/Hadoop/HDFS.md)
  2.[Hadoop——HDFS的Shell操作](https://github.com/Dr11ft/BigDataGuide/blob/master/Hadoop/HDFS%E7%9A%84Shell%E6%93%8D%E4%BD%9C.md)
  3.[Hadoop——HDFS的Java API操作](https://github.com/Dr11ft/BigDataGuide/blob/master/Hadoop/HDFS%E7%9A%84Java%20API%E6%93%8D%E4%BD%9C.md)
  4.[Hadoop——分布式计算框架MapReduce](https://github.com/Dr11ft/BigDataGuide/blob/master/Hadoop/MapReduce.md)
  5.[Hadoop——MapReduce案例](https://github.com/Dr11ft/BigDataGuide/blob/master/Hadoop/MapReduce%E6%A1%88%E4%BE%8B.md)
  6.[Hadoop——资源调度器YARN](https://github.com/Dr11ft/BigDataGuide/blob/master/Hadoop/YARN.md)
  7.[Hadoop——Hadoop数据压缩](https://github.com/Dr11ft/BigDataGuide/blob/master/Hadoop/Hadoop%E6%95%B0%E6%8D%AE%E5%8E%8B%E7%BC%A9.md)
### 二、Zookeeper
  1.[Zookeeper——Zookeeper概述](https://github.com/Dr11ft/BigDataGuide/blob/master/Zookeeper/Zookeeper%EF%BC%88%E4%B8%80%EF%BC%89.md)
  2.[Zookeeper——Zookeeper单机和分布式安装](https://github.com/Dr11ft/BigDataGuide/blob/master/Zookeeper/Zookeeper%EF%BC%88%E4%BA%8C%EF%BC%89.md)
  3.[Zookeeper——Zookeeper客户端命令](https://github.com/Dr11ft/BigDataGuide/blob/master/Zookeeper/Zookeeper%EF%BC%88%E4%B8%89%EF%BC%89.md)
  4.[Zookeeper——Zookeeper内部原理](https://github.com/Dr11ft/BigDataGuide/blob/master/Zookeeper/Zookeeper%EF%BC%88%E5%9B%9B%EF%BC%89.md)
  5.[Zookeeper——Zookeeper实战](https://github.com/Dr11ft/BigDataGuide/blob/master/Zookeeper/Zookeeper%EF%BC%88%E4%BA%94%EF%BC%89.md)
### 三、Hive
  1.[Hive——Hive概述](https://github.com/Dr11ft/BigDataGuide/blob/master/Hive/1%E3%80%81Hive%E6%A6%82%E8%BF%B0.md)
  2.[Hive——Hive数据类型](https://github.com/Dr11ft/BigDataGuide/blob/master/Hive/2%E3%80%81Hive%E6%95%B0%E6%8D%AE%E7%B1%BB%E5%9E%8B.md)
  3.[Hive——Hive DDL数据定义](https://github.com/Dr11ft/BigDataGuide/blob/master/Hive/3%E3%80%81Hive%20DDL%E6%95%B0%E6%8D%AE.md)
  4.[Hive——Hive DML数据操作](https://github.com/Dr11ft/BigDataGuide/blob/master/Hive/4%E3%80%81Hive%20DML%E6%95%B0%E6%8D%AE%E6%93%8D%E4%BD%9C.md)
  5.[Hive——Hive查询](https://github.com/Dr11ft/BigDataGuide/blob/master/Hive/5%E3%80%81Hive%E6%9F%A5%E8%AF%A2.md)
  6.[Hive——Hive函数](https://github.com/MoRan1607/BigDataGuide/blob/master/Hive/6%E3%80%81Hive%E5%87%BD%E6%95%B0.md)
  7.[Hive——Hive压缩和存储](https://github.com/MoRan1607/BigDataGuide/blob/master/Hive/7%E3%80%81Hive%E5%8E%8B%E7%BC%A9%E5%92%8C%E5%AD%98%E5%82%A8.md)
  8.[Hive——Hive实战：统计影音视频网站的常规指标](https://github.com/MoRan1607/BigDataGuide/blob/master/Hive/8%E3%80%81Hive%E5%AE%9E%E6%88%98%EF%BC%9A%E7%BB%9F%E8%AE%A1%E5%BD%B1%E9%9F%B3%E8%A7%86%E9%A2%91%E7%BD%91%E7%AB%99%E7%9A%84%E5%B8%B8%E8%A7%84%E6%8C%87%E6%A0%87.md)
  9.[Hive——Hive分区表和分桶表](https://github.com/MoRan1607/BigDataGuide/blob/master/Hive/9%E3%80%81%E5%88%86%E5%8C%BA%E8%A1%A8%E5%92%8C%E5%88%86%E6%A1%B6%E8%A1%A8.md)
  10.[Hive——Hive调优](https://github.com/MoRan1607/BigDataGuide/blob/master/Hive/10%E3%80%81Hive%E4%BC%81%E4%B8%9A%E7%BA%A7%E8%B0%83%E4%BC%98.md)
### 四、Flume
  1.[Flume——Flume概述](https://github.com/Dr11ft/BigDataGuide/blob/master/Flume/1%E3%80%81Flume%E6%A6%82%E8%BF%B0.md)
  2.[Flume——Flume实践操作](https://github.com/Dr11ft/BigDataGuide/blob/master/Flume/2%E3%80%81Flume%E5%AE%9E%E8%B7%B5%E6%93%8D%E4%BD%9C.md)
  3.[Flume——Flume案例](https://github.com/Dr11ft/BigDataGuide/blob/master/Flume/3%E3%80%81Flume%E6%A1%88%E4%BE%8B.md)
### 五、Kafka
  1.[Kafka——Kafka概述](https://github.com/Dr11ft/BigDataGuide/blob/master/Kafka/1%E3%80%81Kafka%E6%A6%82%E8%BF%B0.md)
  2.[Kafka——Kafka深入解析](https://github.com/Dr11ft/BigDataGuide/blob/master/Kafka/2%E3%80%81Kafka%E6%B7%B1%E5%85%A5%E8%A7%A3%E6%9E%90.md)
  3.[Kafka——Kafka API操作实践](https://github.com/Dr11ft/BigDataGuide/blob/master/Kafka/3%E3%80%81Kafka%20API%E6%93%8D%E4%BD%9C%E5%AE%9E%E8%B7%B5.md)
  3.[Kafka——Kafka对接Flume实践](https://github.com/Dr11ft/BigDataGuide/blob/master/Kafka/4%E3%80%81Flume%E5%AF%B9%E6%8E%A5Kafka%E5%AE%9E%E8%B7%B5%E6%93%8D%E4%BD%9C.md)
### 六、HBase
  1.[HBase——HBase概述](https://github.com/Dr11ft/BigDataGuide/blob/master/HBase/1%E3%80%81HBase%E6%A6%82%E8%BF%B0.md)
  2.[HBase——HBase数据结构](https://github.com/Dr11ft/BigDataGuide/blob/master/HBase/2%E3%80%81HBase%E6%95%B0%E6%8D%AE%E7%BB%93%E6%9E%84.md)
  3.[HBase——HBase Shell操作](https://github.com/Dr11ft/BigDataGuide/blob/master/HBase/3%E3%80%81HBase%20Shell%E6%93%8D%E4%BD%9C.md)
  4.[HBase——HBase API实践操作](https://github.com/Dr11ft/BigDataGuide/blob/master/HBase/4%E3%80%81HBase%20API%E5%AE%9E%E8%B7%B5%E6%93%8D%E4%BD%9C.md)
### 七、Spark
#### Spark基础
  1.[Spark基础——Spark的诞生](https://github.com/Dr11ft/BigDataGuide/blob/master/Spark/1%E3%80%81Spark%E7%9A%84%E8%AF%9E%E7%94%9F.md)
  2.[Spark基础——Spark概述](https://github.com/Dr11ft/BigDataGuide/blob/master/Spark/2%E3%80%81Spark%E6%A6%82%E8%BF%B0.md)
  3.[Spark基础——Spark运行模式](https://github.com/Dr11ft/BigDataGuide/blob/master/Spark/3%E3%80%81Spark%E8%BF%90%E8%A1%8C%E6%A8%A1%E5%BC%8F.md)
  4.[Spark基础——案例实践](https://github.com/Dr11ft/BigDataGuide/blob/master/Spark/2%E3%80%81Spark%E6%A6%82%E8%BF%B0.md)
#### Spark Core
  1.[Spark Core——RDD概述](https://github.com/Dr11ft/BigDataGuide/blob/master/Spark/Spark%20Core/1%E3%80%81RDD%E6%A6%82%E8%BF%B0.md)
  2.[Spark Core——RDD编程（一）](https://github.com/Dr11ft/BigDataGuide/blob/master/Spark/Spark%20Core/2%E3%80%81RDD%E7%BC%96%E7%A8%8B%EF%BC%88%E4%B8%80%EF%BC%89.md)
  3.[Spark Core——RDD编程（二）](https://github.com/Dr11ft/BigDataGuide/blob/master/Spark/Spark%20Core/3%E3%80%81RDD%E7%BC%96%E7%A8%8B%EF%BC%882%EF%BC%89.md)
  4.[Spark Core——键值对RDD数据分区器](https://github.com/Dr11ft/BigDataGuide/blob/master/Spark/Spark%20Core/4%E3%80%81%E9%94%AE%E5%80%BC%E5%AF%B9RDD%E6%95%B0%E6%8D%AE%E5%88%86%E5%8C%BA%E5%99%A8.md)
  5.[Spark Core——数据读取与保存](https://github.com/Dr11ft/BigDataGuide/blob/master/Spark/Spark%20Core/5%E3%80%81%E6%95%B0%E6%8D%AE%E8%AF%BB%E5%8F%96%E4%B8%8E%E4%BF%9D%E5%AD%98.md)
#### Spark SQL
  1.[Spark SQL——Spaek SQL概述](https://github.com/Dr11ft/BigDataGuide/blob/master/Spark/Spark%20SQL/1%E3%80%81Spark%20SQL%E6%A6%82%E8%BF%B0.md)
  2.[Spark SQL——Spaek SQL编程](https://github.com/Dr11ft/BigDataGuide/blob/master/Spark/Spark%20SQL/2%E3%80%81Spark%20SQL%E7%BC%96%E7%A8%8B.md)
  3.[Spark SQL——Spaek SQL数据的加载与保存](https://github.com/Dr11ft/BigDataGuide/blob/master/Spark/Spark%20SQL/3%E3%80%81Spark%20SQL%E6%95%B0%E6%8D%AE%E7%9A%84%E5%8A%A0%E8%BD%BD%E4%B8%8E%E4%BF%9D%E5%AD%98.md)
  4.[Spark SQL——Spaek SQL实战](https://github.com/Dr11ft/BigDataGuide/blob/master/Spark/Spark%20SQL/4%E3%80%81Spark%20SQL%E5%AE%9E%E6%88%98.md)
#### Spark Streaming
  1.[Spark Streaming——Spark Streaming概述](https://github.com/Dr11ft/BigDataGuide/blob/master/Spark/Spark%20Streaming/1%E3%80%81Spark%20Streaming%E6%A6%82%E8%BF%B0.md)
  2.[Spark Streaming——Dstream基础](https://github.com/Dr11ft/BigDataGuide/blob/master/Spark/Spark%20Streaming/2%E3%80%81Dstream%E5%9F%BA%E7%A1%80.md)
  3.[Spark Streaming——Dstream的转换&输出](https://github.com/Dr11ft/BigDataGuide/blob/master/Spark/Spark%20Streaming/3%E3%80%81Dstream%E7%9A%84%E8%BD%AC%E6%8D%A2%26%E8%BE%93%E5%87%BA.md)
### 八、Flink
  1.[Flink——Flink核心概述](https://github.com/Dr11ft/BigDataGuide/blob/master/Flink/1%E3%80%81Flink%E6%A6%82%E8%BF%B0.md)
  2.[Flink——Flink部署](https://github.com/Dr11ft/BigDataGuide/blob/master/Flink/2%E3%80%81Flink%E9%83%A8%E7%BD%B2.md)
  3.[Flink——Flink运行架构](https://github.com/Dr11ft/BigDataGuide/blob/master/Flink/3、Flink运行架构.md)
  4.[Flink——Flink流处理API](https://github.com/Dr11ft/BigDataGuide/blob/master/Flink/4%E3%80%81Flink%E6%B5%81%E5%A4%84%E7%90%86API.md)
  5.[Flink——Flink中的Window](https://github.com/Dr11ft/BigDataGuide/blob/master/Flink/5%E3%80%81Flink%E4%B8%AD%E7%9A%84Window.md)
  6.[Flink——时间语义与Wartermark](https://github.com/Dr11ft/BigDataGuide/blob/master/Flink/6、时间语义与Wartermark.md)
  7.[Flink——ProcessFunction API（底层API）](https://github.com/Dr11ft/BigDataGuide/blob/master/Flink/7%E3%80%81ProcessFunction%20API%EF%BC%88%E5%BA%95%E5%B1%82API%EF%BC%89.md)
  8.[Flink——状态编程和容错机制](https://github.com/Dr11ft/BigDataGuide/blob/master/Flink/8%E3%80%81%E7%8A%B6%E6%80%81%E7%BC%96%E7%A8%8B%E5%92%8C%E5%AE%B9%E9%94%99%E6%9C%BA%E5%88%B6.md)
  9.[Flink——Table API 与SQL](https://github.com/Dr11ft/BigDataGuide/blob/master/Flink/9%E3%80%81Table%20API%20%E4%B8%8ESQL.md)
  10.[Flink——Flink CEP](https://github.com/Dr11ft/BigDataGuide/blob/master/Flink/10%E3%80%81Flink%20CEP.md)
数据仓库
---
  [数据仓库总结](https://zhuanlan.zhihu.com/p/371365562)
大数据项目
---
  **基本上选择三到四个即可，B站直接搜索项目名字，都有视频**
  **详细说明公众号回复“大数据项目”即可**
<p align="center">
<img src="https://github.com/Dr11ft/BigDataGuide/blob/master/Pics/%E7%94%B5%E5%AD%90%E4%B9%A6%26%E9%A1%B9%E7%9B%AE/%E5%A4%A7%E6%95%B0%E6%8D%AE%E9%A1%B9%E7%9B%AE%E6%B6%89%E5%8F%8A%E6%A1%86%E6%9E%B6%E7%BB%84%E4%BB%B6.jpg"/>
<p align="center">
</p>
</p>
面试题
---
### [大数据面试题 V3.0](https://mp.weixin.qq.com/s/hMcuDEkzH49rfSmGWy_GRg)
#### 一、Hadoop
##### 1、Hadoop基础
[介绍下Hadoop](https://blog.csdn.net/qq_41544550/article/details/123031348)
##### 2、HDFS
[HDFS读写流程](https://blog.csdn.net/qq_41544550/article/details/103113335)
##### 3、MapReduce
[介绍下MapReduce](https://blog.csdn.net/qq_41544550/article/details/123674103)
[MapReduce优缺点](https://github.com/MoRan1607/BigDataGuide/blob/master/%E9%9D%A2%E8%AF%95/Hadoop%E9%9D%A2%E8%AF%95%E9%A2%98%E6%80%BB%E7%BB%93/Hadoop/MapReduce%E4%BC%98%E7%BC%BA%E7%82%B9.md)
##### 4、YARN
[介绍下YARN](https://blog.csdn.net/qq_41544550/article/details/123826496?spm=1001.2014.3001.5501)
#### 二、Zookeeper
[介绍下Zookeeper是什么？](https://blog.csdn.net/qq_41544550/article/details/123148663)
[Zookeeper有什么作用？优缺点？有什么应用场景？](https://blog.csdn.net/qq_41544550/article/details/123148688)
#### 三、Hive
[说下为什么要使用Hive？Hive的优缺点？Hive的作用是什么？](https://blog.csdn.net/qq_41544550/article/details/123333839)
#### 四、Flume
[介绍下Flume](https://blog.csdn.net/qq_41544550/article/details/123451528?spm=1001.2014.3001.5501)
#### 五、Kafka
[介绍下Kafka，Kafka的作用？Kafka的组件？适用场景？](https://blog.csdn.net/qq_41544550/article/details/123534948)
#### 六、HBase
[介绍下HBase架构](https://blog.csdn.net/qq_41544550/article/details/123583361)
#### 七、Spark
[说下对RDD的理解？RDD特点、算子？](https://github.com/MoRan1607/BigDataGuide/blob/master/%E9%9D%A2%E8%AF%95/Spark%E9%9D%A2%E8%AF%95%E9%A2%98%E6%95%B4%E7%90%86/Spark/Pics/%E8%AF%B4%E4%B8%8B%E5%AF%B9RDD%E7%9A%84%E7%90%86%E8%A7%A3%EF%BC%9FRDD%E7%89%B9%E7%82%B9%E3%80%81%E7%AE%97%E5%AD%90/%E8%AF%B4%E4%B8%8B%E5%AF%B9RDD%E7%9A%84%E7%90%86%E8%A7%A3%EF%BC%9FRDD%E7%89%B9%E7%82%B9%E3%80%81%E7%AE%97%E5%AD%90.md)
[Spark小文件问题](https://github.com/MoRan1607/BigDataGuide/blob/master/%E9%9D%A2%E8%AF%95/Spark%E9%9D%A2%E8%AF%95%E9%A2%98%E6%95%B4%E7%90%86/Spark/Spark%E5%B0%8F%E6%96%87%E4%BB%B6%E9%97%AE%E9%A2%98/Spark%E5%B0%8F%E6%96%87%E4%BB%B6%E9%97%AE%E9%A2%98.md)
---
### 大数据面试 V1.0
#### 一、Hadoop
  1.[Hadoop面试题总结（一）](https://github.com/Dr11ft/BigDataGuide/blob/master/%E9%9D%A2%E8%AF%95/Hadoop%E9%9D%A2%E8%AF%95%E9%A2%98%E6%80%BB%E7%BB%93/Hadoop%E9%9D%A2%E8%AF%95%E9%A2%98%E6%80%BB%E7%BB%93%EF%BC%88%E4%B8%80%EF%BC%89.md)
  2.[Hadoop面试题总结（二）——HDFS](https://github.com/Dr11ft/BigDataGuide/blob/master/%E9%9D%A2%E8%AF%95/Hadoop%E9%9D%A2%E8%AF%95%E9%A2%98%E6%80%BB%E7%BB%93/Hadoop%E9%9D%A2%E8%AF%95%E9%A2%98%E6%80%BB%E7%BB%93%EF%BC%88%E4%BA%8C%EF%BC%89%E2%80%94%E2%80%94HDFS.md)
  3.[Hadoop面试题总结（三）——MapReduce](https://github.com/Dr11ft/BigDataGuide/blob/master/%E9%9D%A2%E8%AF%95/Hadoop%E9%9D%A2%E8%AF%95%E9%A2%98%E6%80%BB%E7%BB%93/Hadoop%E9%9D%A2%E8%AF%95%E9%A2%98%E6%80%BB%E7%BB%93%EF%BC%88%E4%B8%89%EF%BC%89%E2%80%94%E2%80%94MapReduce.md)
  4.[Hadoop面试题总结（四）——YARN](https://github.com/Dr11ft/BigDataGuide/blob/master/%E9%9D%A2%E8%AF%95/Hadoop%E9%9D%A2%E8%AF%95%E9%A2%98%E6%80%BB%E7%BB%93/Hadoop%E9%9D%A2%E8%AF%95%E9%A2%98%E6%80%BB%E7%BB%93%EF%BC%88%E5%9B%9B%EF%BC%89%E2%80%94%E2%80%94YARN.md)
  5.[Hadoop面试题总结（五）——优化问题](https://github.com/Dr11ft/BigDataGuide/blob/master/%E9%9D%A2%E8%AF%95/Hadoop%E9%9D%A2%E8%AF%95%E9%A2%98%E6%80%BB%E7%BB%93/Hadoop%E9%9D%A2%E8%AF%95%E9%A2%98%E6%80%BB%E7%BB%93%EF%BC%88%E4%BA%94%EF%BC%89%E2%80%94%E2%80%94%E4%BC%98%E5%8C%96%E9%97%AE%E9%A2%98.md)
#### 二、Zookeeper
  1.[Zookeeper面试题总结（一）](
https://github.com/Dr11ft/BigDataGuide/blob/master/%E9%9D%A2%E8%AF%95/Zookeeper%E9%9D%A2%E8%AF%95%E9%A2%98%E6%80%BB%E7%BB%93/Zookeeper.md)
#### 三、Hive
  1.[Hive面试题总结（一）](https://github.com/Dr11ft/BigDataGuide/blob/master/%E9%9D%A2%E8%AF%95/Hive%E9%9D%A2%E8%AF%95%E9%A2%98%E6%80%BB%E7%BB%93/Hive%EF%BC%88%E4%B8%80%EF%BC%89.md)
  2.[Hive面试题总结（二）](https://github.com/Dr11ft/BigDataGuide/blob/master/%E9%9D%A2%E8%AF%95/Hive%E9%9D%A2%E8%AF%95%E9%A2%98%E6%80%BB%E7%BB%93/Hive%EF%BC%88%E4%BA%8C%EF%BC%89.md)
#### 四、HBase
  1.[HBase面试题总结（一）](https://github.com/Dr11ft/BigDataGuide/blob/master/%E9%9D%A2%E8%AF%95/HBase%E9%9D%A2%E8%AF%95%E9%A2%98%E6%95%B4%E7%90%86/HBase.md)
#### 五、Flume
  1.[Flume面试题总结（一）](https://github.com/Dr11ft/BigDataGuide/blob/master/%E9%9D%A2%E8%AF%95/Flume%E9%9D%A2%E8%AF%95%E9%A2%98%E6%95%B4%E7%90%86/Flume.md)
#### 六、Kafka
  1.[Kafka面试题总结（一）](https://github.com/Dr11ft/BigDataGuide/blob/master/%E9%9D%A2%E8%AF%95/Kafka%E9%9D%A2%E8%AF%95%E9%A2%98%E6%95%B4%E7%90%86/Kafka%EF%BC%88%E4%B8%80%EF%BC%89.md)
  2.[Kafka面试题总结（二）](https://github.com/Dr11ft/BigDataGuide/blob/master/%E9%9D%A2%E8%AF%95/Kafka%E9%9D%A2%E8%AF%95%E9%A2%98%E6%95%B4%E7%90%86/Kafka%EF%BC%88%E4%BA%8C%EF%BC%89.md)
#### 七、Spark
  1.[Spark面试题总结（一）](https://github.com/Dr11ft/BigDataGuide/blob/master/%E9%9D%A2%E8%AF%95/Spark%E9%9D%A2%E8%AF%95%E9%A2%98%E6%95%B4%E7%90%86/Spark%EF%BC%88%E4%B8%80%EF%BC%89.md)
  2.[Spark面试题总结（二）](https://github.com/Dr11ft/BigDataGuide/blob/master/%E9%9D%A2%E8%AF%95/Spark%E9%9D%A2%E8%AF%95%E9%A2%98%E6%95%B4%E7%90%86/Spark%EF%BC%88%E4%BA%8C%EF%BC%89.md)
  3.[Spark面试题总结（三）](https://github.com/Dr11ft/BigDataGuide/blob/master/%E9%9D%A2%E8%AF%95/Spark%E9%9D%A2%E8%AF%95%E9%A2%98%E6%95%B4%E7%90%86/Spark%EF%BC%88%E4%B8%89%EF%BC%89.md)
  4.[Spark面试题总结（四）](https://github.com/Dr11ft/BigDataGuide/blob/master/%E9%9D%A2%E8%AF%95/Spark%E9%9D%A2%E8%AF%95%E9%A2%98%E6%95%B4%E7%90%86/Spark%EF%BC%88%E5%9B%9B%EF%BC%89.md)
  **Spark性能优化：**
  5.[Spark面试题总结（五）——几种常见的数据倾斜情况及调优方式](https://github.com/Dr11ft/BigDataGuide/blob/master/%E9%9D%A2%E8%AF%95/Spark%E9%9D%A2%E8%AF%95%E9%A2%98%E6%95%B4%E7%90%86/Spark%E8%B0%83%E4%BC%98/%E6%95%B0%E6%8D%AE%E5%80%BE%E6%96%9C.md)
  6.[Spark面试题总结（六）——Shuffle配置调优](https://github.com/Dr11ft/BigDataGuide/blob/master/%E9%9D%A2%E8%AF%95/Spark%E9%9D%A2%E8%AF%95%E9%A2%98%E6%95%B4%E7%90%86/Spark%E8%B0%83%E4%BC%98/Shuffle%E9%85%8D%E7%BD%AE%E8%B0%83%E4%BC%98.md)
  7.[Spark面试题总结（七）——程序开发调优](https://github.com/Dr11ft/BigDataGuide/blob/master/%E9%9D%A2%E8%AF%95/Spark%E9%9D%A2%E8%AF%95%E9%A2%98%E6%95%B4%E7%90%86/Spark%E8%B0%83%E4%BC%98/%E7%A8%8B%E5%BA%8F%E5%BC%80%E5%8F%91%E8%B0%83%E4%BC%98.md)
  8.[Spark面试题总结（八）——运行资源调优](https://github.com/Dr11ft/BigDataGuide/blob/master/%E9%9D%A2%E8%AF%95/Spark%E9%9D%A2%E8%AF%95%E9%A2%98%E6%95%B4%E7%90%86/Spark%E8%B0%83%E4%BC%98/%E8%B5%84%E6%BA%90%E8%B0%83%E4%BC%98.md)
大数据&后端书籍
---
  **图片上的PDF书籍在公众号回复关键字“大数据书籍”或“Java书籍”自行进百度云盘群保存即可**
####   大数据书籍
<p align="center">
<img src="https://github.com/Dr11ft/BigDataGuide/blob/master/Pics/%E7%94%B5%E5%AD%90%E4%B9%A6%26%E9%A1%B9%E7%9B%AE/%E5%A4%A7%E6%95%B0%E6%8D%AE%E4%B9%A6%E6%9E%B6.png"/>
<p align="center">
</p>
</p>
####   后端书籍
<p align="center">
<img src="https://github.com/Dr11ft/BigDataGuide/blob/master/Pics/%E7%94%B5%E5%AD%90%E4%B9%A6%26%E9%A1%B9%E7%9B%AE/Java%E5%90%8E%E7%AB%AF%E4%B9%A6%E6%9E%B6.png"/>
<p align="center">
</p>
</p>
## 交流群
交流群建好了，进群的小伙伴可以加我微信：**MoRan1607，备注：GitHub**
<p align="center">
<img src="https://github.com/Dr11ft/BigDataGuide/blob/master/Pics/%E5%BE%AE%E4%BF%A1.jpg" width="200" height="200"/>
<p align="center">
</p>
</p>