Menu
I try to build a code for page rank algorithm, and in that the main complexity is to solve matrix multiplication efficiently, but I didn't understand how this task be perform, I read some papers on that, but that is beyond of my range. I didn't understand the concept that he apply. So, can you give me a concept behind mapper and reducer function for matrix multiplication. Thanks in advance.
I read this link
325
Matrix multiplication in MapReduceIf A=[a_{ij}] is an m\times n matrix and B=[b_{ij}] is an n\times p matrix, C=[c_{ij}], the product of AB, is an m\times p matrix where each element c_{ij} is calculated as.
In linear algebra, the Strassen algorithm, named after Volker Strassen, is an algorithm for matrix multiplication. It is faster than the standard matrix multiplication algorithm for large matrices, with a better asymptotic complexity, although the naive algorithm is often better for smaller matrices.
In mathematics, particularly in linear algebra, matrix multiplication is a binary operation that produces a matrix from two matrices. For matrix multiplication, the number of columns in the first matrix must be equal to the number of rows in the second matrix.
We can multiply two matrices in java using binary * operator and executing another loop. A matrix is also known as array of arrays. We can add, subtract and multiply matrices. In case of matrix multiplication, one row element of first matrix is multiplied by all columns of second matrix.
The idea is that you can break matrix multiplication into subproblems with something like the Strassen Algorithm and then send those subproblems to a bunch of different computers. Once those subproblems are finished the summing together of the different subproblems into the matrix itsself can also be handled with. The key to using Mapreduce is that all of the subproblems can basically be computed in parallel, which is... what Mapreduce is for.
167
Couple of frameworks like Apache Hama have implementation of the PageRank. Apache Giraph also has support for Pagerank.
MapReduce is not well suited for PageRank, so Google published Pregel paper for large scale graph computing.
26
If you love us? You can donate to us via Paypal or buy me a coffee so we can maintain and grow! Thank you!
Donate Us With
