Personal_3.MapReduce An Introduction - Map Reduce - Ghana -...

Map Reduce
- an overview
-
Ghana

AGENDA

Comparison of Hadoop with other
systems

RDBMS

Grid Computing
•
Map Reduce - An Introduction
• Word count – default
•
Word count – custom

AGENDA
•
Understanding MapReduce
•
Map Reduce - An Introduction
•
Word count – default
• Word count – custom

Why not RDBMS

Seek time improving slowly than read/write
time

Map Reduce

Programming model to process large
datasets

Supported languages for MR

Java
 Ruby

Python

C++

Understanding MapReduce

Start with WORDCOUNT example

“Do as I say, not as I do”
Word Count
As 2
Do 2
I 2
Not 2
Say 1

Understanding MapReduce
pseudo
code
define wordCount as Map<String,long>;
for each document in documentSet {
T = tokenize(document);
for each token in T {
wordCount[token]++;
}
}

Understanding MapReduce
-
pseudo code

Spam filter

Millions of emails

Word count for analysis

Working from a single computer is time
consuming

Rewrite the program to count form
multiple machines