1.hadoop

MapReduce工作原理
https://blog.csdn.net/tanggao1314/article/details/51275812

MapReduce运行原理详解
http://blog.csdn.net/u011007180/article/details/52434382

MapReduce 框架 Yarn 详解
https://www.ibm.com/developerworks/cn/opensource/os-cn-hadoop-yarn/

MapReduce框架的架构
http://dongxicheng.org/mapreduce-nextgen/nextgen-mapreduce-introduction/

NameNode 高可用 (High Availability) 实现解析
https://www.ibm.com/developerworks/cn/opensource/os-cn-hadoop-name-node/

HDFS精华文章汇总
https://blog.csdn.net/androidlushangderen/article/details/78700392

理解Hadoop YARN架构
https://blog.csdn.net/bingduanlbd/article/details/51880019

YARN架构设计详解
https://www.cnblogs.com/wcwen1990/p/6737985.html

2.zk

分布式服务框架 Zookeeper
https://www.ibm.com/developerworks/cn/opensource/os-cn-zookeeper/index.html

Zookeeper内部分析
https://blog.csdn.net/tang06211015/article/details/51921428

Zookeeper的功能以及工作原理
https://www.cnblogs.com/felixzh/p/5869212.html

3.hive

hive 源码解析之代码整体结构
https://www.xuebuyuan.com/2181081.html

Hive原理及查询优化
https://blog.csdn.net/lw_ghy/article/details/51469753

Hive性能优化上的一些总结
https://blog.csdn.net/mrlevo520/article/details/76339075

4.hbase

HBase 官方文档中文版
http://abloz.com/hbase/book.html

深入理解HBase的系统架构
https://blog.csdn.net/Yaokai_AssultMaster/article/details/72877127

HBase 常用Shell命令
https://www.cnblogs.com/nexiyi/p/hbase_shell.html

Hbase开发实例
https://www.cnblogs.com/fangdai/p/5991620.html

• 定位一条记录所属region
• 查看一个region的数据量
• 查看一个Cell的所有版本
  https://blog.csdn.net/javajxz008/article/details/51913533

HBase Rowkey设计
https://blog.csdn.net/u014091123/article/details/73163088

HBase写入的各种方式总结汇总
https://blog.csdn.net/shudaqi2010/article/details/88653796

5.spark

DataFrame操作
https://www.cnblogs.com/nucdy/p/6541564.html

RDD操作详解
https://blog.csdn.net/zhaojw_420/article/details/53261965

SparkSQL操作Hive Table
https://blog.csdn.net/zhao897426182/article/details/78435234/

park/spark-sql处理schema数据
https://www.cnblogs.com/kangoroo/p/6891540.html

Spark数据倾斜治理
http://www.jasongj.com/spark/skew/

Dataset中Actions、function、transformations
https://blog.csdn.net/legotime/article/details/52562796

Dataset中structField、structType、schame
https://blog.csdn.net/legotime/article/details/52643243

Spark 共享变量：广播变量、累加器
https://blog.csdn.net/wangpei1949/article/details/83335273

DataFrame新增一列的四种方法
https://www.cnblogs.com/itboys/p/9762808.html

Spark SQL将数据写入Mysql表的一些坑
https://blog.csdn.net/dai451954706/article/details/52840011/

Spark 动态资源分配(Dynamic Resource Allocation) 解析
http://idcbgp.cn/article/267186

6.flink

Flink架构、原理与部署测试
https://blog.csdn.net/jdoouddm7i/article/details/62039337

广播流 Broadcast State用例
https://cloud.tencent.com/developer/article/1378332

Flink中的状态管理
云栖社区： https://yq.aliyun.com/articles/225623#
https://ci.apache.org/projects/flink/flink-docs-release-1.6/dev/stream/state/state.html

WaterMark 水位
简书:https://www.jianshu.com/p/9db56f81fa2a

Flink 中 timeWindow 滚动窗口边界和数据延迟问题调研
https://blog.csdn.net/xsdxs/article/details/82415450

Window Join
https://blog.csdn.net/xsdxs/article/details/82750254

flink-SQL解析JSON格式数据
http://www.mamicode.com/info-detail-2644620.html

Flink UDF实例
https://www.jianshu.com/p/5dc2cab91c78

source function
https://cloud.tencent.com/developer/article/1366981

Flink 网络流控和反压剖析
https://yq.aliyun.com/articles/725982/

7.杂项

KUDU 介绍
https://www.jianshu.com/p/93c602b637a4

Azkaban介绍
https://blog.csdn.net/clypm/article/details/79076801

elasticsearch 常见查询及聚合的JAVA API
https://blog.csdn.net/majun_guang/article/details/81103623

Kafka 架构原理
https://blog.csdn.net/u013256816/article/details/71091774

为什么不建议在 HBase 中使用过多的列族
https://blog.csdn.net/bingdianone/article/details/86062506

logstash过滤器插件filter详解及实例
https://www.cnblogs.com/FengGeBlog/p/10305318.html