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基于 hadoop 文件系统以及 Hbase 的微博系统








     以基于Hbase的hadoop为数据库,实现用户发布微博和,关注用户及等功能,涉及到Hbase表结构设计,相应实现的Java API等一些内容。使用hbase作为微博系统的数据存储平台有如下好处:根据微博系统的特点,微博用户数量庞大,且关注和被关注数据严重不相等,这些特点刚好可以通过hbase分布式处理数据的一些特性得以满足,如果使用旧的关系数据库可能对一个单独的服务器要求非常之高。





Smart Baby Monitor with Intel® Edison and Ubidots

Intel Edison is small enough for wearables. It gives lot of flexibility to developers through the languages and programming environment it offers and it has integrated Wi-Fi and Bluetooth that makes it ideal for a wearable. Now a days there are many wearables in market for different purposes, so why not we make one for babies. With increase in nuclear families there is no one to guide the new parents about their new born baby. They are always worried about their baby regarding his health, temperature, environment etc. Babies need to be monitored 24*7 which is not always possible as in some families both the parents are working, sometimes they have to do lots of household chores and other issue is sleep also hence in these cases parents need a Smart Baby Monitoring System that can help them to keep track on baby’s health and alert them if any irregular activity happens.

My Reality Moment. Why Did I Ever Agree to Do This?

When I first took this job of leading our scripting languages area, the Reality Moment struck when I had my first real look at the challenges of dynamic languages. For example, if you compare two strings in a program, we have some new instructions in the processor which can make these go very fast. But unfortunately, if you compare two strings in PHP, you first need to determine if the strings could be interpreted as numbers. If so, you need to treat them as numbers.

Making the Dead Rise, and Other Impossible Tasks

My current job is to lead our company's work on dynamic server languages, such as performance optimization and feature enabling. Besides PHP and HHVM, we want to improve Python. There is a huge amount of Python code in use out there, for example running OpenStack, Swift, DropBox and many others. What I didn't realize when I took the job was that much of this use is in a "dead" language.

The JITter Conundrum - Just in Time for Your Traffic Jam

In interpreted languages, it just takes longer to get stuff done - I earlier gave the example where the Python source code a = b + c would result in a BINARY_ADD byte code which takes 78 machine instructions to do the add, but it's a single native ADD instruction if run in compiled language like C or C++. How can we speed this up? Or as the performance expert would say, how do I decrease pathlength while keeping CPI in check? There is one common short cut around this traffic jam of interpreted languages. If you were going to run this line of code repeatedly, say in a loop, why not translate it into the super-efficient machine code version?
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