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jiaoqiyuan / 163-bigdate-note

Licence: GPL-3.0 license
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网易云课堂大数据笔记

数据平台综述

  1. 数据管理技术的演化

  2. 学习的方法论

  3. 分布式系统可扩展性


数据存储:HDFS

  1. HDFS架构

  2. HDFS环境搭建

  3. HDFS操作验证

  4. YARN配置

  5. HDFS管理与使用

  6. HDFS高可用性

  7. HDFS联邦

  8. HDFS安全

  9. 压缩与分片

  10. 异常处理


日志解析及计算:MR

  1. MR的应用场景

  2. MR的原理和运行流程

  3. 编写一个MR程序

  4. Hadoop的IO模型-上

  5. Hadoop的IO模型-下

  6. 完整编写Map和Reduce

  7. 灵活配置Configuration

  8. 精准控制Shuffle过程

  9. MR程序的输入

  10. MR程序的输出

  11. 简单好用的计数器

  12. MR实现关联操作

  13. MR参数调优

  14. 数据倾斜

数据获取和预处理:Flume

  1. 日志及日志收集系统介绍

  2. Flume Agent组成

  3. Flume支持的组件类型

  4. Flume基本配置

  5. Flume部署

  6. Flume配置示例

  7. Flume高级配置

  8. 构建复杂日志收集系统

结构化查询:Hive

  1. Hive学习资料

  2. Hive解决了什么问题

  3. Hive擅长什么

  4. Hive结构与数据仓库

  5. 数据模型与元数据

  6. Hive安装与配置

  7. 创建和管理Hive中的数据库

  8. 写一个基本的查询语句

  9. 子查询和关联表

  10. 使用简单函数

  11. 使用聚合函数

  12. 利用正则表达式精确提取信息

  13. 使用窗口函数

  14. 行转列与列转行

  15. 用户自定义函数(UDF)的使用

  16. Hive优化案例

数据获取和预处理:Sqoop

  1. 业务系统数据

  2. 数据同步与传统数据仓库

  3. Sqoop功能与架构

  4. 数据划分

  5. Java Hadoop-client等基础依赖安装

  6. sqoop服务安装

  7. 语法分析

  8. 案例

大数据调度框架:Azkaban

  1. 调度系统背景知识

  2. Azkaban系统介绍

  3. 代码下载、编译、部署

  4. 插件的安装hadoopjava、spark等

  5. 插件的使用要素和DAG设计

  6. 不同调度参数详解

  7. Azkaban任务编写

  8. 如何实现web高可用

  9. 如何提高任务可用性

  10. 如何增加新的插件类型

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