Speed Up and Deploy MapReduce Using Other Products - MATLAB & Simulink (original) (raw)
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Execution Environment
To use mapreduce with Parallel Computing Toolbox™, MATLAB® Parallel Server™, or MATLAB Compiler™, use the mapreducer configuration function to change the execution environment for mapreduce. This enables you to start small to verify your map and reduce functions, then quickly scale up to run larger calculations.
Running in Parallel
Parallel Computing Toolbox can immediately speed up your mapreduce algorithms by using the full processing power of multicore computers to execute applications with a parallel pool of workers. If you already have Parallel Computing Toolbox installed, then you probably do not need to do anything special to take advantage of these capabilities. For more information about using mapreduce with Parallel Computing Toolbox, see Run mapreduce on a Parallel Pool (Parallel Computing Toolbox).
MATLAB Parallel Server enables you to run the same applications on a remote computer cluster. For more information, including how to configure MATLAB Parallel Server to support Hadoop® clusters, see Tall Arrays and mapreduce (Parallel Computing Toolbox).
Application Deployment
MATLAB Compiler enables you to create standalone mapreduce applications or deployable archives, which you can share with colleagues or deploy to production Hadoop systems.
For more information, see MapReduce Applications on Hadoop Clusters (MATLAB Compiler).