Import Large Data Programmatically

Import large data from relational database into MATLAB^® workspace using command line

You can use a DatabaseDatastore object to import large data into the MATLAB workspace. To create this object, use the databaseDatastore function. After importing your data into the MATLAB workspace, you can use tall arrays to analyze it. Also, the MapReduce programming technique provides you with greater flexibility in analyzing large data.

To split an SQL query into multiple SQL page queries and import large data in chunks, use the splitsqlquery function. You can access large data by using Database Toolbox™ functions or a parallel pool (requires Parallel Computing Toolbox™).

Functions

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Database Datastore

`databaseDatastore`	Datastore for data in database
`hasdata`	Determine if data in `DatabaseDatastore` is available to read
`preview`	Return subset of data from `DatabaseDatastore`
`read`	Read data in `DatabaseDatastore`
`readall`	Read all data in `DatabaseDatastore`
`reset`	Reset `DatabaseDatastore` to initial state

Split SQL Query

`createConnectionForPool`	Initialize parallel pool using database connection
`splitsqlquery`	Split SQL query using paging

Topics

Working with Large Data Sets
Import and export large data sets that are stored in a database.
Import Large Data Using DatabaseDatastore Object
Create a DatabaseDatastore object for accessing collections of data stored in a relational database.
Analyze Large Data in Database Using Tall Arrays
Find the minimum value in a large data set by using a tall table.
Analyze Large Data in Database Using MapReduce
Write mapper and reducer functions for analyzing large data using a DatabaseDatastore object.