| # -*- coding: utf-8 -*- | |
| import os | |
| import sys | |
| import StringIO | |
| sys.path.append("/Users/ikbear/Code/Qiniu/SDK/python-sdk/") | |
| # @gist import_io | |
| import qiniu.io | |
| # @endgist | |
| import qiniu.conf |
| # -*- coding: utf-8 -*- | |
| import os | |
| import sys | |
| import StringIO | |
| # @gist import_io | |
| import qiniu.io | |
| # @endgist | |
| import qiniu.conf | |
| # @gist import_rs |
| package main | |
| import ( | |
| "encoding/base64" | |
| "fmt" | |
| "io/ioutil" | |
| "net/http" | |
| gourl "net/url" | |
| "qbox.us/api" | |
| "qbox.us/digest_auth" |
| # to install the latest stable version: | |
| brew install scala --with-docs | |
| # to install scala-2.10.0-RC1: | |
| brew install https://raw.github.com/gist/3939012/scala.rb --with-docs | |
| # to switch versions (from https://github.com/mxcl/homebrew/wiki/External-Commands): | |
| brew switch scala 2.9.2 | |
| brew switch scala 2.10.0-RC1 |
Ideas are cheap. Make a prototype, sketch a CLI session, draw a wireframe. Discussions around concrete examples, not handy-waving abstractions. Don't say you did something, provide a URL that proves it.
Nothing is real until it's being used by a real user. This doesn't mean you make a prototype in the morning and blog about it in the evening. It means you find one person you believe your product will help and try to get them to use it.
| #!/usr/bin/env ruby | |
| require 'thor' | |
| require 'rest_client' | |
| require 'base64' | |
| require 'qiniu-rs' | |
| class QiniuUploader < Thor | |
| desc "upload", "Upload a file to qiniu cloud storage" | |
| def upload | |
| bucket = 'mybucket' |
A friend asked me for a few pointers to interesting, mostly recent papers on data warehousing and "big data" database systems, with an eye towards real-world deployments. I figured I'd share the list. While it's biased and rather incomplete but maybe of interest to someone. While many are obvious choices (I've omitted several, like MapReduce), I think there are a few underappreciated gems.
###Dataflow Engines:
Dryad--general-purpose distributed parallel dataflow engine
http://research.microsoft.com/en-us/projects/dryad/eurosys07.pdf
Spark--in memory dataflow
http://www.cs.berkeley.edu/~matei/papers/2012/nsdi_spark.pdf
Delete all containers
$ docker ps -q -a | xargs docker rm
-q prints only the container IDs -a prints all containers
Notice that it uses xargs to issue a remove container command for each container ID
| docker run -v /var/run/docker.sock:/var/run/docker.sock -v /var/lib/docker:/var/lib/docker --rm martin/docker-cleanup-volumes |
| # Gemfile | |
| gem 'redis', '~> 3.0.1' |