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Datastore

Read large collections of data

The 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.

Functions

datastoreCreate datastore for large collections of data
TabularTextDatastoreDatastore for tabular text files
SpreadsheetDatastoreDatastore for spreadsheet files
ImageDatastoreDatastore for image data
FileDatastoreDatastore with custom file reader
KeyValueDatastoreDatastore for key-value pair data for use with mapreduce
TallDatastoreDatastore for checkpointing tall arrays
readRead data in datastore
readallRead all data in datastore
previewSubset of data in datastore
partitionPartition a datastore
numpartitionsNumber of datastore partitions
hasdataDetermine if data is available to read
resetReset datastore to initial state

Classes

matlab.io.Datastore Base datastore class
matlab.io.datastore.PartitionableAdd parallelization support to datastore
matlab.io.datastore.HadoopFileBased Add Hadoop file support to datastore
matlab.io.datastore.DsFileSet File-set object for collection of files in datastore
matlab.io.datastore.DsFileReader File-reader object for files in a datastore

Topics

Getting Started with Datastore

A datastore is an object for reading a single file or a collection of files or data.

Read and Analyze Large Tabular Text File

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.

Read and Analyze Image Files

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).

Read and Analyze MAT-File with Key-Value Data

This example shows how to create a datastore for key-value pair data in a MAT-file that is the output of mapreduce.

Read and Analyze Hadoop Sequence File

This example shows how to create a datastore for a Sequence file containing key-value data.

Read Remote Data

Use datastore to access remote data in Amazon S3™, Windows Azure® Blob Storage, or HDFS™.

Develop Custom Datastore

Create a fully customized datastore for your custom or proprietary data.

Testing Guidelines for Custom Datastores

After implementing your custom datastore, follow this test procedure to qualify your custom datastore.

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