gcmr

Get current mapreducer configuration

Syntax

mr = gcmr

mr = gcmr('nocreate')

Description

mr = gcmr returns an object representing the current global execution environment for mapreduce.

• If no global execution environment exists, then gcmr calls mapreducer to set the global execution environment to be the default.

• If a global execution environment currently exists, then gcmr returns the last visible MapReducer object created.

  When you create a MapReducer object using mapreducer, the object sets the global execution environment. The global execution environment persists even if the object representing it is later deleted.

• If the global execution environment is deleted or invalid, then gcmr returns the next visible MapReducer object available. For example, delete(gcmr) deletes the current global execution environment.

The gcmr function defines the global execution environment for mapreduce, and is most likely used with Parallel Computing Toolbox™, MATLAB^® Parallel Server™, or MATLAB Compiler™.

If you do not specify a configuration to use in your call to mapreduce, then by default mapreduce uses the configuration returned (or generated) by gcmr.

mr = gcmr('nocreate') returns the current global execution environment for mapreduce, if one already exists. If no global execution environment exists, then gcmr returns [].

Tips

• If you have Parallel Computing Toolbox, see the mapreducer (Parallel Computing Toolbox) function reference page for related information.

• If you have MATLAB Compiler, see the mapreducer (MATLAB Compiler) function reference page for related information.

Extended Capabilities

Automatic Parallel Support

Accelerate code by automatically running computation in parallel using Parallel Computing Toolbox™.

If you have Parallel Computing Toolbox installed, when you use gcmr, MATLAB automatically opens a parallel pool of workers on your local machine. Control parallel behavior with the parallel preferences, including scaling up to a cluster.

For details, see Run mapreduce on a Parallel Pool (Parallel Computing Toolbox) or Use Tall Arrays on a Parallel Pool (Parallel Computing Toolbox). For more general information about parallel computing, see Run MATLAB Functions with Automatic Parallel Support (Parallel Computing Toolbox).

Version History

Introduced in R2014b