numpartitions
Class: matlab.io.datastore.Partitionable
Namespace: matlab.io.datastore
Default number of partitions
Syntax
n = numpartitions(ds)
n = numpartitions(ds,pool)
Description
n = numpartitions(
returns the default
number of partitions for datastore ds
)ds
.
n = numpartitions(
returns a reasonable number of partitions to parallelize datastore access over the
parallel pool specified by ds
,pool
)pool
. To parallelize datastore access, you
must have Parallel Computing Toolbox™ installed.
Input Arguments
ds
— Input datastore
matlab.io.Datastore
object
Input datastore, specified as a matlab.io.Datastore
object. To create a Datastore
object, see matlab.io.Datastore
.
pool
— Parallel pool
parallel pool object
Parallel pool, specified as a parallel pool object.
Example: gcp
Examples
Build Datastore with Parallel Processing Support
Build a datastore with parallel processing support and use it to bring your custom or proprietary data into MATLAB®. Then, process the data in a parallel pool.
Create a .m
class definition file that contains the code implementing your custom datastore. You must save this file in your working folder or in a folder that is on the MATLAB® path. The name of the .m
file must be the same as the name of your object constructor function. For example, if you want your constructor function to have the name MyDatastorePar, then the name of the .m
file must be MyDatastorePar.m
. The .m
class definition file must contain the following steps:
Step 1: Inherit from the datastore classes.
Step 2: Define the constructor and the required methods.
Step 3: Define your custom file reading function.
In addition to these steps, define any other properties or methods that you need to process and analyze your data.
%% STEP 1: INHERIT FROM DATASTORE CLASSES classdef MyDatastorePar < matlab.io.Datastore & ... matlab.io.datastore.Partitionable properties(Access = private) CurrentFileIndex double FileSet matlab.io.datastore.DsFileSet end % Property to support saving, loading, and processing of % datastore on different file system machines or clusters. % In addition, define the methods get.AlternateFileSystemRoots() % and set.AlternateFileSystemRoots() in the methods section. properties(Dependent) AlternateFileSystemRoots end %% STEP 2: DEFINE THE CONSTRUCTOR AND THE REQUIRED METHODS methods % Define your datastore constructor function myds = MyDatastorePar(location,altRoots) myds.FileSet = matlab.io.datastore.DsFileSet(location,... 'FileExtensions','.bin', ... 'FileSplitSize',8*1024); myds.CurrentFileIndex = 1; if nargin == 2 myds.AlternateFileSystemRoots = altRoots; end reset(myds); end % Define the hasdata method function tf = hasdata(myds) % Return true if more data is available tf = hasfile(myds.FileSet); end % Define the read method function [data,info] = read(myds) % Read data and information about the extracted data % See also: MyFileReader() if ~hasdata(myds) msgII = ['Use the reset method to reset the datastore ',... 'to the start of the data.']; msgIII = ['Before calling the read method, ',... 'check if data is available to read ',... 'by using the hasdata method.']; error('No more data to read.\n%s\n%s',msgII,msgIII); end fileInfoTbl = nextfile(myds.FileSet); data = MyFileReader(fileInfoTbl); info.Size = size(data); info.FileName = fileInfoTbl.FileName; info.Offset = fileInfoTbl.Offset; % Update CurrentFileIndex for tracking progress if fileInfoTbl.Offset + fileInfoTbl.SplitSize >= ... fileInfoTbl.FileSize myds.CurrentFileIndex = myds.CurrentFileIndex + 1 ; end end % Define the reset method function reset(myds) % Reset to the start of the data reset(myds.FileSet); myds.CurrentFileIndex = 1; end % Define the partition method function subds = partition(myds,n,ii) subds = copy(myds); subds.FileSet = partition(myds.FileSet,n,ii); reset(subds); end % Getter for AlternateFileSystemRoots property function altRoots = get.AlternateFileSystemRoots(myds) altRoots = myds.FileSet.AlternateFileSystemRoots; end % Setter for AlternateFileSystemRoots property function set.AlternateFileSystemRoots(myds,altRoots) try % The DsFileSet object manages AlternateFileSystemRoots % for your datastore myds.FileSet.AlternateFileSystemRoots = altRoots; % Reset the datastore reset(myds); catch ME throw(ME); end end end methods (Hidden = true) % Define the progress method function frac = progress(myds) % Determine percentage of data read from datastore if hasdata(myds) frac = (myds.CurrentFileIndex-1)/... myds.FileSet.NumFiles; else frac = 1; end end end methods(Access = protected) % If you use the FileSet property in the datastore, % then you must define the copyElement method. The % copyElement method allows methods such as readall % and preview to remain stateless function dscopy = copyElement(ds) dscopy = copyElement@matlab.mixin.Copyable(ds); dscopy.FileSet = copy(ds.FileSet); end % Define the maxpartitions method function n = maxpartitions(myds) n = maxpartitions(myds.FileSet); end end end %% STEP 3: IMPLEMENT YOUR CUSTOM FILE READING FUNCTION function data = MyFileReader(fileInfoTbl) % create a reader object using FileName reader = matlab.io.datastore.DsFileReader(fileInfoTbl.FileName); % seek to the offset seek(reader,fileInfoTbl.Offset,'Origin','start-of-file'); % read fileInfoTbl.SplitSize amount of data data = read(reader,fileInfoTbl.SplitSize); end
Your custom datastore is now ready. Use your custom datastore to read and process the data in a parallel pool.
Tips
For your custom datastore implementation, we recommend that you do not implement the
numpartitions
method.
Algorithms
In the default implementation, the number of partitions, n
, is
selected as the minimum between these two values:
Value returned by the
maxpartitions
method on the datastore object.Three times the number of workers available.
Version History
Introduced in R2017b
See Also
matlab.io.datastore.Partitionable
| maxpartitions
| partition
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