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Bigdata Blog | 大数据技术博客

小米大数据团队,专注于大数据的存储与计算平台。

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Bigdata Blog | 大数据技术博客 | bigdata-blog.net Reviews
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小米大数据团队,专注于大数据的存储与计算平台。
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1 Bigdata
2 大数据,分布式系统,Hadoop
3 HDFS
4 YARN
5 MapReduce
6 HBase
7 ZooKeeper
8 Spark
9 Storm
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bigdata blog,大数据技术博客,跳至内容,hbase,文件系统,计算框架,zookeeper,十分钟开发hbase应用,发表回复,本文将介绍如何在十分钟内跑起你的hbase应用,继续阅读 →,本条目发布于,属于 hbase,作者是 chendihao,hfile和hlog的回收机制,正常回收流程,hbase数据主要存储在分布式文件系统上hfile和hlog文件中,当小的hfile过多的时候,会将多个小的hfile压缩形成一个大的hfile,作者是 liushaohui,hbase社区开发faq
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Bigdata Blog | 大数据技术博客 | bigdata-blog.net Reviews

https://bigdata-blog.net

小米大数据团队,专注于大数据的存储与计算平台。

INTERNAL PAGES

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1

HBase行数统计Bigdata Blog | Bigdata Blog

http://bigdata-blog.net/2013/11/15/hbase行数统计

另一解决方案是使用MapReduce,HBase自身提供了org.apache.hadoop.hbase.mapreduce.RowCounter类,可以方便地在命令行调用进行统计,但执行效率仍难以达到我们的需求。 开发时还发现rowCount必须指定colum family,于是找到相应的issue并backport到0.94(详见 Reference[4]. 实践也发现每次rpc调用时间都比正常操作长很多,所以务必将hbase.rpc.timeout设置为Integer.MAX VALUE,才能保证程序不会因为rpc超时而退出。 1]Coprocessor Introduction http:/ blogs.apache.org/hbase/entry/coprocessor introduction. 2]HBase Aggregation Example http:/ michaelmorello.blogspot.jp/2012/01/row-count-hbase-aggregation-example.html. Hive SQL优化之 Count Distinct.

2

YehangjunBigdata Blog | Bigdata Blog

http://bigdata-blog.net/author/yehangjun

目前为止团队已经提交了超过130个改进,其中”new write ahead log threading model”和”reverse scanners”是HBase 0.98.0版本发布时被重点提到的 四大改进. 谢良和冯宏华受邀做了题目为”HBase at Xiaomi”的演讲,主要分享了HBase在小米的使用情况,遇到的问题和所做的改进,以及下一步的改进计划。 点击这里下载ppt HBase at Xiaomi HBaseCon 2014.

3

HBase在小米的应用与扩展Bigdata Blog | Bigdata Blog

http://bigdata-blog.net/2013/12/24/hbase在小米的应用与扩展

BDTC 2013的ppt: HBase在小米的应用与扩展 – BDTC 2013. 小米HBase实践@2013 hadoop中国技术峰会 →.

4

文件系统 | Bigdata Blog

http://bigdata-blog.net/category/文件系统

5

十分钟开发HBase应用Bigdata Blog | Bigdata Blog

http://bigdata-blog.net/2014/12/03/十分钟开发hbase应用

Docker run -d - net=host tobegit3hub/standalone-hbase-0.94. Docker run -i -t - net=host tobegit3hub/smoke-hbase. Apt-get install docker.io. Docker run -i -t - net=host - privileged -v /:/host tobegit3hub/jde. 当然这还需要你对Hadoop和Docker有基本的了解,容器是个很好的概念 Escape Dependency Hell ,已经广泛应用到Google的生产环境上了,希望大家继续关注:-).

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