Question: BIG DATA & HADOOP The situation is that vector v is too big to fit into the memory. To address this situation, we will need

BIG DATA & HADOOP

The situation is that vector v is too big to fit into the memory. To address this situation, we will need to divide matrix M into vertical stripes, and also divide v into equal number of horizontal stripes:

Your task is to design a mapReduce algorithm and implement the algorithm to divide matrix M into vertical stripes.

Again, matrix M is stored in a file, using (i,j,mij) format. Here is one example matrix,

BIG DATA & HADOOP The situation is that vector v is too

As you can tell, this matrix is 9 x 9, and we would like to break it into 3 vertical stripes (therefore each stripe is 9 x 3). The final result will be 3 separate files, each file holds one stripe from the original matrix.

You will need to submit the following:

a very brief description of your design. The description should be in this format (20 points)

map task: for each , emits ,

reduce task:

your source code (30 points)

a screen shot showing the command you use to start your job (5 points)

a screen shot showing the result of your submitted job, should be something look like this (5 points)

hint: you will need to write a customer partitioner, something like this:

public static class MatrixConvertorPartitioner extends Partitioner

This is how it should look

big to fit into the memory. To address this situation, we will

** If answered before September 11, 2018 at 10:30 EST, I will send $25 to your paypal/cashapp/venmo **

)1 2 4 8 4 3 5 1 8 6 7 1 6 8 2 236 1871328236458567171828 1 8-328236458567171828 )1 2 4 8 4 3 5 1 8 6 7 1 6 8 2 236 1871328236458567171828 1 8-328236458567171828

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