Hadoop的 “ 生态圈 ”

相关热门搜索：hive 查看数据库命令

大数据标签:hadoop hdfs mapreduce hbase hive mahout zookeeper sqoop flume bigdata

Hadoop生态系统的图谱，详细的列举了在Hadoop这个生态系统中出现的各种数据工具。

* 这一切，都起源自Web数据爆炸时代的来临
* 数据抓取系统 － Nutch
* 海量数据怎么存，当然是用分布式文件系统 － HDFS
* 数据怎么用呢，分析，处理
* MapReduce框架，让你编写代码来实现对大数据的分析工作
* 非结构化数据（日志）收集处理 － fuse,webdav, chukwa, flume, Scribe
* 数据导入到HDFS中，至此RDBSM也可以加入HDFS的狂欢了     － Hiho, sqoop
* MapReduce太麻烦，好吧，让你用熟悉的方式来操作Hadoop里的数据     – Pig, Hive, Jaql
* 让你的数据可见 － drilldown, Intellicus用高级语言管理你的任务流 – oozie, Cascading
* Hadoop当然也有自己的监控管理工具 – Hue, karmasphere, eclipse plugin, cacti, ganglia
* 数据序列化处理与任务调度 – Avro, Zookeeper
* 更多构建在Hadoop上层的服务 – Mahout, Elastic map Reduce
* OLTP存储系统 – Hbase

* How did it all start- huge data on the     web!
* Nutch     built to crawl this web data
* Huge     data had to saved- HDFS was born!
* How to use this data?
* Map reduce framework built for coding     and running analytics – java, any language-streaming/pipes
* How to get in unstructured     data – Web logs, Click streams, Apache logs, Server logs  – fuse,webdav, chukwa, flume,     Scribe
* Hiho and sqoop for loading data into     HDFS – RDBMS can join the Hadoop band wagon!
* High level interfaces required over low     level map reduce programming– Pig, Hive, Jaql
* BI tools with advanced UI     reporting- drilldown etc- Intellicus
* Workflow tools over Map-Reduce     processes and High level languages
* Monitor and manage hadoop, run     jobs/hive, view HDFS – high level view- Hue, karmasphere, eclipse plugin,     cacti, ganglia
* Support frameworks- Avro     (Serialization), Zookeeper (Coordination)
* More High level interfaces/uses-     Mahout, Elastic map Reduce
* OLTP- also possible – Hbase

*

大数据系列hadoop,hdfs相关文章：