A Hadoop Primer

•

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sogrady

A simple introduction to Hadoop talk given to the Maine Java Users' Group February 15, 2011.

Technologie

Project Architecture

Source: Running Hadoop On Ubuntu Linux, Michael G. Noll, 8.8.07

12

“The big issue is not that everyone will
suddenly operate at petabyte scale; a lot of
folks do not have that much data.

The more important topics are the specifics
of the storage and processing infrastructure
and what approaches best suit each
problem.”
- Bradford Cross, Flightcaster/Woven

20

“build Amazon's product search indices”
“build the recommender system for behavioral targeting”
“ETL style processing and statistics generation”
“information extraction & search”
“searching and analysis of millions of rental bookings”
“we use Hadoop to summarize of user's tracking data”
“we use Hadoop to store ad serving logs”
“the freedom to query the data in an ad-hoc manner”
“generating web graphs on 100 nodes”
“we use Hadoop for batch-processing large RDF datasets”
“facial similarity and recognition across large datasets“
“We are using Hadoop and Nutch to crawl Blog posts”
“Used for ETL & data analysis on terascale datasets”
Source: http://wiki.apache.org/hadoop/PoweredBy

24

Crawling Largeish
Unstructured Datasets

30

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A Hadoop Primer

1. A Hadoop Primer Feb 2011 10.20.2005

2. http://redmonk.com/public/hadoop.pdf 2

3. The Background 3

4. October, 2003 4

5. December, 2004 5

6. Map::Reduce 6

7. Job::Map Reduce::Output 7

8. Counting Shakespeare 8

9. The Birth of Hadoop 9

10. 10

11. 11

12. Project Architecture Source: Running Hadoop On Ubuntu Linux, Michael G. Noll, 8.8.07 12

13. Project Traction 13

14. Employment Potential 14

15. Hadoop Users 15

16. Why Hadoop? 16

17. More Machines = More Faster 17

18. The reason everyone knows 18

19. BIG DATA 19

20. “The big issue is not that everyone will suddenly operate at petabyte scale; a lot of folks do not have that much data. The more important topics are the specifics of the storage and processing infrastructure and what approaches best suit each problem.” - Bradford Cross, Flightcaster/Woven 20

21. The reason not everyone knows 21

22. ru d U st tu e Data n r c 22

23. What Hadoop Is 23

24. “build Amazon's product search indices” “build the recommender system for behavioral targeting” “ETL style processing and statistics generation” “information extraction & search” “searching and analysis of millions of rental bookings” “we use Hadoop to summarize of user's tracking data” “we use Hadoop to store ad serving logs” “the freedom to query the data in an ad-hoc manner” “generating web graphs on 100 nodes” “we use Hadoop for batch-processing large RDF datasets” “facial similarity and recognition across large datasets“ “We are using Hadoop and Nutch to crawl Blog posts” “Used for ETL & data analysis on terascale datasets” Source: http://wiki.apache.org/hadoop/PoweredBy 24

25. What Hadoop Isn't 25

26. A relational database killer No Yes 26

27. Beyond Hadoop 27

28. The Hadoop Ecosystem 28

29. What We Use Hadoop For 29

30. Crawling Largeish Unstructured Datasets 30

31. Like 1.3M StackOverflow Questions 31

32. Or 1.7M HackerNews Entries 32

33. Or Years of Apache Log Files 33

34. How to Get Started 34

35. We use Cloudera 35

36. Mostly because it's easy 36