Hadoop on Windows Azure: Visualizing Data

We are currently experimenting with a 32-node Apache Hadoop cluster on Windows Azure.  The setup includes a web-based interactive JavaScript console, which lets you put data into HDFS, launch MapReduce jobs, and also visualize results with HTML5 charts – and it’s very easy to use.

Using our in-house tools, we generated a report showing what keywords on Twitter were recently used in conjunction with the word “xbox”, and what user platforms were used to Tweet about “xbox”:


In this example, we’ve exported data that’s shown on either side of the screen as tab-delimited text files:

  • xbox_tweets_keywords.txt
  • xbox_tweets_platforms.txt

The files are then uploaded to HDFS using fs.put() command in the JavaScript console – which lets you upload a file from your desktop:

js> fs.put()

File uploaded.


We verify that both data files have been uploaded:

js> #ls

Found 3 items

drwxr-xr-x   – itrend supergroup          0 2012-01-15 06:48 /user/itrend/.oink

-rw-r–r–   3 itrend supergroup        895 2012-01-15 08:39 /user/itrend/xbox_tweets_keywords.txt

-rw-r–r–   3 itrend supergroup        244 2012-01-15 08:28 /user/itrend/xbox_tweets_platforms.txt

Once the file is in the HDFS, we can read its contents:

js> file = fs.read(“xbox_tweets_platforms.txt”)

411 web

229 twitter for iphone

142 twitterfeed

130 twitter for android

117 mobile web

98 raptr

58 tweetdeck

58 echofon

50 twitter for blackberry

47 txt

33 google

29 kit link

26 dlvr.it

25 slickdeals

25 xbox

21 bersocial for blackberry

301 Other

… and parse the tab-delimited data (just showing the top few data nodes here for simplicity):

js> data = parse(file.data, “Tweets:integer, Platform”)


    0: {

        Tweets: “411”

        Platform: “web”


    1: {

        Tweets: “229”

        Platform: “twitter for iphone”


    2: {

        Tweets: “142”

        Platform: “twitterfeed”




Prepare for charting:

js> options = { title: “Twitter User Platforms”, orientation: 25, x: “Platform”, y: “Tweets” }


    title: “Twitter User Platforms”

    orientation: 25

    x: “Platform”

    y: “Tweets”


Then, generate a bar graph:

js> graph.bar(data, options)


… followed by a pie chart:

js> graph.pie(data, options)


Similar process is used for the keyword data (this sampling clearly needs a different visualization mechanism):


Next week, we will be posting a more interesting example.

by Michael Alatortsev



Technologist, parallel entrepreneur. Interests: travel, photography, big data, analytics, predictive modeling.

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2 comments on “Hadoop on Windows Azure: Visualizing Data
  1. Michael Alatortsev says:

    Yury, I wasn’t sure 32 nodes was going to cut it. The spreadsheet was 17 x 2, that’s 34 cells. But it all worked out in the end!

  2. Adrianne says:

    Out the door i along these lines mechanism. But about
    time it’s began to tire. I did find a method to surprise the tissues back, good as new.

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