datastore function creates a datastore, which is a repository for
collections of data that are too large to fit in memory. A datastore allows
you to read and process data stored in multiple files on a disk, a remote
location, or a database as a single entity. If the data is too large to fit
in memory, you can manage the incremental import of data, create a
tall array to work with the data, or use the
datastore as an input to
mapreduce for further
processing. For more information, see Getting Started with Datastore.
|Base datastore class|
|Add parallelization support to datastore|
|Add Hadoop file support to datastore|
|File-set object for collection of files in datastore|
|File-reader object for files in a datastore|
A datastore is an object for reading a single file or a collection of files or data.
This example shows how to create a datastore for a large text file containing tabular data, and then read and process the data one chunk at a time or one file at a time.
This example shows how to create a datastore for a collection of images, read the image files, and find the images with the maximum average hue, saturation, and brightness (HSV).
This example shows how to create a datastore for key-value pair data in a MAT-file that is the output of
This example shows how to create a datastore for a Sequence file containing key-value data.
datastore to access remote data in Amazon S3™, Windows Azure® Blob Storage, or HDFS™.
Create a fully customized datastore for your custom or proprietary data.
After implementing your custom datastore, follow this test procedure to qualify your custom datastore.