Cloud computing

【原创】SAE本地环境与真实环境的差别

其实从刚开始用的时候就发现本地环境和真实环境有不同,导致本地环境我都没怎么用。

1、本地环境的php是32bit版本的,真实环境是64bit的。这是我发现的第一个不相同的地方,就是因为这个,直接导致我的应用绝大部分调试工作都是在把代码上传到服务器后直接在线测试的。因为我做那个应用的时候需要用到64位整数,本地环境不支持。

2、saemysql使用的不同,今天在本地用了一下saemysql,本来以为直接拿以前线上的代码直接在本地环境中运行就可以的,结果发现不行。在线上的版本,只要直接

Hadoop Hbase 升级

Hadoop HDFS 与Hbase升级笔记

由于之前使用了hadoop1.0.2,hbase 使用的是hbase-0.92.1 但是一次事故导致元数据丢失,且修复元数据的类本身有BUG
所以摆在眼前的只有两条路:
1、修改hbase源码重新编译 hbase 修复BUG
2、升级到下一个版本,且这个版本已经修复了此BUG 从release node中看到 0.92.2及以后版本均修复了此bug
  所以决定升级到最新的稳定版 hbase-0.94.3 而此版本的hbase 和hadoop-1.0.4 的兼容性最好,所以hadoop 连带升级到hadoop-1.0.4

1. Hadoop升级步骤:
 (1)停止集群上的所有MR任务,包括Hbase(如果Hbase在使用中,先停掉,接着是zookeeper)
 (2)停止DFS(1、2两步也可以在hbase和zookeeper关闭后使用stop-all.sh脚本直接关闭)
 (3)删除临时数据,即在core-site.xml中设置的hadoop.tmp.dir的value所文件目录下的文件
 (4)备份HDFS元数据

java socket 多线程网络传输多个文件

     由于需要研究了下用 java socket 传输文件,由于需要传输多个文件,因此,采用了多线程设计。客户端每个线程创建一个 socket 连接,每个 socket 连接负责传输一个文件,服务端的ServerSocket每次 accept 一个 socket 连接,创建一个线程用于接收客户端传来的文件。

1、服务端

Resin.io releases experimental support for the Intel Edison

Managing a fleet of IoT devices and deploying code is no easy task. Resin.io changes the workflow by leveraging Git and Docker technology!

How It Works

When you have new code for your end devices, all you need to do is simply perform a "git push". Resin.io builds your code into a Docker container and deploys it onto the device if/when it's online! Below is an image describing the process, found on Resin.io's website:

Ceph Erasure Coding Introduction

Ceph introduction

Ceph, The Future of Storage™, is a massively scalable, open source, software-defined storage system that runs on commodity hardware. Ceph has been developed from the ground up to deliver object, block, and file system storage in a single software platform that is self-managing, self-healing and has no single point of failure. Because of its highly scalable, software defined storage architecture, Ceph is an ideal replacement for legacy storage systems and a powerful storage solution for object and block storage for cloud computing environments.

Optimizing Image resizing example of Intel(R) Integrated Performance Primitives (IPP) with Intel(R) Threading Building Blocks and Intel(R) C++ Compiler

< Overview >

 In this article, we are enabling and using Intel(R) Integrated Performance Primitives(IPP), Intel(R) Threading Building Blocks(TBB) and Intel(R) C++ Compiler(ICC) on Linux ( Ubuntu 14.04 LTS 64bit ). We will build and run one of the examples that comes with IPP and apply TBB and ICC on the example to observe the performance improvement of using Intel(R) System Studio features.

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  • Intel Cluster Ready FAQ: Software vendors (ISVs)

    Why should we join the Intel Cluster Ready program?
    A: By offering registered Intel Cluster Ready applications, you can provide the confidence that applications will run as they should, right away, on certified clusters. Participating in the program will help you increase application adoption, expand application flexibility, and streamline customer support.
    Learn more about the Intel Cluster Ready program

    Q: How do we register an application?

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  • Intel Cluster Ready FAQ: Hardware vendors, system integrators, platform suppliers

    Q: Why should we join the Intel® Cluster Ready program?
    A: By offering certified Intel Cluster Ready systems and certified components, you can give customers greater confidence in deploying and running HPC systems. Participating in the program will help you drive HPC adoption, expand your customer base, and streamline customer support. You will also gain access to the Intel Cluster Checker software tool and the library of pre-certified Intel Cluster Ready system reference designs.

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