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Coded-TeraSort
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Coded-TeraSort
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# Coded-TeraSort Utilizing in-network coding to trade extra computations for more communication bandwidth in a distributed sorting algorithm ([TeraSort](http://sortbenchmark.org/YahooHadoop.pdf)). The paper for this project is available at https://arxiv.org/abs/1702.04850. ## Requirements - C/C++ compiler (g++) - OpenMPI library ## Usage ### Input File A file containing data to be sorted must be placed in the `input` directory. Note that the format of the data points follows standard TeraSort input data. Each record contains a 10-byte key and a 90-byte value. An input file can be generated by [TeraSort Example](http://hadoop.apache.org/docs/r2.8.0/api/org/apache/hadoop/examples/terasort/package-summary.html). ### TeraSort Execution Specify in `Configuration.h`: - `numReducer`: number of distributed computing nodes - `inputPath`: a path to the input file Run `make` to compile `TeraSort`. Run `./Splitter` to split the input data points. Run `mpirun -np 4 ./TeraSort`. The above execution creates 3 computing processes and 1 master process to sorts data according to TeraSort algorithm. All processes are local. ### Coded-TeraSort Execution Specify in `CodedConfiguration.h`: - `numReducer`: number of distributed computing nodes - `load`: number of nodes on which each data point is processed (computation load) - `numInput` is set to be equal to (`numReducer` choose `load`) - `inputPath`: a path to the input file Run `make` to compile `CodedTeraSort`. Run `./Splitter code` to split the input data points. Run `mpirun -np 4 ./CodedTeraSort`. The above execution creates 3 computing processes and 1 master process to sorts data according to CodedTeraSort algorithm. All processes are local.
