Mapreduce Tutorial Presentation By Sandeep Patil Technological geeks Video 4 Technological geeks Hindi Video 4

1. Hadoop
Development
Series
By Sandeep Patil
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2. Contents
• Traditional Big Data Processing Approach
• Mapreduce I/O
• How Mapper Works
• Reducers tasks
• MapReduce Work Flow
• MapReduce Example
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3. Traditional Approach
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Big
Data
Split Data
Split Data
Split Data
Split Data
grep
grep
grep
grep
Matches
Matches
Matches
Matches
cat All
Matches

4. MapReduce I/O
Mappers input  InputFormat Class  k/v pair
Mappers Output  Developer  k/v pair
Reducers input  Mappers Output  k/v pair
Reducer Output  Developer  k/v pair
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5. How Mapper Works
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250 Mb File
KuchBhi.txt
Block 1 -- > DN1
Block 2 -- > DN2
Number of Mappers == Number of Blocks

6. Reducers Tasks
• Summarization operation
• By Default One reducer
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7. MapReduce
• Map
- Mapper Get Data from input File
- Write business logic to process data
- Write Output
• Reduce
- Get Data From mapper
- Write business logic
- Write output
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8. How Mapper gets Input
• InputFormatClass
• Everything in MapReduce is Key Value Pair
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9. MR in Short
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10. MR Approach
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Big
Data
Split Data
Split Data
Split Data
Split Data
All
Matches
MAP Reduce

11. Next Video
• Will do something practical
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12. Like and Subscribe
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