Given Enough MonkeysSome Thoughts on RandomnessJesse Anderson |   CLOUDERA, INSTRUCTOR
Infinite Monkey Theorem2
Million Monkeys Algorithm      Randomly generate a 9 character group                    TOBEORNOT          Does it exist i...
Exponential Growth (aka Big Data)     Odds of finding a group    Contiguous                                              C...
Data Bias?5
Hadoop Scalability                               Percent of Linear Scalability              100              80    Percent...
Business Value of Scalability        Scaling does not require    Adding more computers         massive re-engineering     ...
Going Viral (and taking over the world)      Covered internationally        26,000 unique      in BBC, Wall Street        ...
@jessetanderson
Upcoming SlideShare
Loading in...5
×

Strata 2012 Million Monkeys

200

Published on

Published in: Technology
0 Comments
0 Likes
Statistics
Notes
  • Be the first to comment

  • Be the first to like this

No Downloads
Views
Total Views
200
On Slideshare
0
From Embeds
0
Number of Embeds
1
Actions
Shares
0
Downloads
4
Comments
0
Likes
0
Embeds 0
No embeds

No notes for slide
  • Interesting statistical question. Thought about since Aristotle.Randomness+Resouces+Time=AnythingPossibleNo real monkeys – need virtual monkeys
  • Lucky monkeyThe monkey wears a lot of hats. He generates and then compares.Every work of Shakespeare created. First was A Lover’s Complaint and last was Taming of the ShrewVisualization to find your favorite line from Shakespeare
  • Shakespeare lazy. Heavily influenced English Literature.Big Data isn’t always a huge file. It can be high computation.
  • Creating Shakespeare not a business. Don’t have Shakespeare in your data.If you look hard enough you will find itHumans are not randomYou want to be looking for what’s actually there. Check your assumptionsOperate with scientific method. Form a hypothesis. Test hypothesis against data.Offer what customers are looking for. Not what you think or favorite or new product. Only what your data shows.
  • This is not a map of MT and ID1 to 20 node testingKeep efficiency up RDBMS efficiency in gutter
  • Engineers not spending time coding to scale. Busy adding new features.No code changes for scaling. Took 1.5 months on one computer and 3.5 days on 20 nodesSpending on new computers gives a consistent, linear increase. Compare spending on RDBMS and Hadoop.
  • We like to ask bigger questions.I asked if Shakespeare could be randomly recreated by a bunch of virtual monkeys? The answer is yes.
  • Strata 2012 Million Monkeys

    1. 1. Given Enough MonkeysSome Thoughts on RandomnessJesse Anderson | CLOUDERA, INSTRUCTOR
    2. 2. Infinite Monkey Theorem2
    3. 3. Million Monkeys Algorithm Randomly generate a 9 character group TOBEORNOT Does it exist in Shakespeare? To be, or not to be- that is the question3
    4. 4. Exponential Growth (aka Big Data) Odds of finding a group Contiguous Combinations of characters is 1 in 26 Characters raised to the power of the number of 8 208,827,064,576 contiguous characters 9 5,429,503,678,976 10 141,167,095,653,3764
    5. 5. Data Bias?5
    6. 6. Hadoop Scalability Percent of Linear Scalability 100 80 Percent 60 RDBMS Hadoop 40 20 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 Nodes RDBMS = Relational Database6
    7. 7. Business Value of Scalability Scaling does not require Adding more computers massive re-engineering to cluster gets a and complete rewrites of predictable increase in code computational power and storage SAVE SAVE7
    8. 8. Going Viral (and taking over the world) Covered internationally 26,000 unique in BBC, Wall Street visits from 119 Journal, Wired and countries in Slashdot one day8
    9. 9. @jessetanderson
    1. A particular slide catching your eye?

      Clipping is a handy way to collect important slides you want to go back to later.

    ×