fetch

Import data into MATLAB workspace from execution of SQL statement

Syntax

results = fetch(conn,sqlquery)
results = fetch(conn,sqlquery,opts)
results = fetch(___,Name,Value)
[results,metadata] = fetch(___)

Description

example

results = fetch(conn,sqlquery) returns all rows of data after executing the SQL statement sqlquery for the connection object. fetch imports data in batches.

example

results = fetch(conn,sqlquery,opts) customizes options for importing data from an executed SQL query by using the SQLImportOptions object.

example

results = fetch(___,Name,Value) specifies additional options using one or more name-value pair arguments and any of the previous input argument combinations. For example, 'MaxRows',5 imports five rows of data.

example

[results,metadata] = fetch(___) also returns the metadata table, which contains metadata information about the imported data.

Examples

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Import all product data from a Microsoft® SQL Server® database table into MATLAB® by using the connection object. Then, determine the highest unit cost among products in the table.

Create an ODBC database connection to a Microsoft® SQL Server® database with Windows® authentication. Specify a blank user name and password. The database contains the table productTable.

datasource = 'MS SQL Server Auth';
conn = database(datasource,'','');

Check the database connection. If the Message property is empty, then the connection is successful.

conn.Message
ans =

     []

Import all the data from productTable by using the connection object and SQL query, and display the imported data.

sqlquery = 'SELECT * FROM productTable';
results = fetch(conn,sqlquery)
results =

  15×5 table

    productNumber    stockNumber    supplierNumber    unitCost    productDescription
    _____________    ___________    ______________    ________    __________________

          9          1.2597e+05          1003            13       'Victorian Doll'  
          8          2.1257e+05          1001             5       'Train Set'       
          7          3.8912e+05          1007            16       'Engine Kit'      
          2          4.0031e+05          1002             9       'Painting Set'    
          4          4.0034e+05          1008            21       'Space Cruiser'   
          1          4.0035e+05          1001            14       'Building Blocks' 
          5          4.0046e+05          1005             3       'Tin Soldier'     
          6          4.0088e+05          1004             8       'Sail Boat'       
          3            4.01e+05          1009            17       'Slinky'          
         10          8.8865e+05          1006            24       'Teddy Bear'      
         11          4.0814e+05          1004            11       'Convertible'     
         12          2.1046e+05          1010            22       'Hugsy'           
         13          4.7082e+05          1012            17       'Pancakes'        
         14           5.101e+05          1011            19       'Shawl'           
         15          8.9975e+05          1011            20       'Snacks'          

Determine the highest unit cost for all products in the table.

max(results.unitCost)
ans =

    24

Close the database connection.

close(conn)

Customize import options when importing data from the results of an SQL query on a database. Control the import options by creating an SQLImportOptions object. Then, customize import options for different columns in the SQL query. Import data using the fetch function.

This example uses the employees_database.mat file, which contains the columns first_name, hire_date, and DEPARTMENT_NAME. The example also uses a Microsoft® SQL Server® Version 11.00.2100 database and the Microsoft SQL Server Driver 11.00.5058.

Create an ODBC database connection to a Microsoft SQL Server database with Windows® authentication. Specify a blank user name and password.

datasource = 'MS SQL Server Auth';
conn = database(datasource,'','');

Load employee information into the MATLAB® workspace.

employeedata = load('employees_database.mat');

Create the employees and departments database tables using the employee information.

emps = employeedata.employees;
depts = employeedata.departments;

sqlwrite(conn,'employees',emps)
sqlwrite(conn,'departments',depts)

Create an SQLImportOptions object using an SQL query and the databaseImportOptions function. This query retrieves all information for employees who are sales managers or programmers.

sqlquery = ['SELECT * from employees e join departments d ' ...
    'on (e.department_id = d.department_id) where job_id ' ...
    'in (''IT_PROG'',''SA_MAN'')'];
opts = databaseImportOptions(conn,sqlquery)

Display the current import options for the variables selected in the SelectedVariableNames property of the SQLImportOptions object.

vars = opts.SelectedVariableNames;
varOpts = getoptions(opts,vars)
varOpts = 
    1x16 SQLVariableImportOptions array with properties:

   Variable Options:
                       (1) |          (2) |         (3) |     (4) |            (5) |         (6) |      (7) |      (8) |              (9) |         (10) |            (11) |        (12) |            (13) |              (14) |         (15) |          (16)  
       Name: 'employee_id' | 'first_name' | 'last_name' | 'email' | 'phone_number' | 'hire_date' | 'job_id' | 'salary' | 'commission_pct' | 'manager_id' | 'department_id' | 'temporary' | 'DEPARTMENT_ID' | 'DEPARTMENT_NAME' | 'MANAGER_ID' | 'LOCATION_ID'
       Type:      'double' |       'char' |      'char' |  'char' |         'char' |      'char' |   'char' | 'double' |         'double' |     'double' |        'double' |    'double' |        'double' |            'char' |     'double' |      'double'
  FillValue:         [NaN] |           '' |          '' |      '' |             '' |          '' |       '' |    [NaN] |            [NaN] |        [NaN] |           [NaN] |       [NaN] |           [NaN] |                '' |        [NaN] |         [NaN]

	To access sub-properties of each variable, use getoptions

Change the data types for the hire_date, DEPARTMENT_NAME, and first_name variables using the setoptions function. Then, display the updated import options. Because hire_date stores date and time data, change the data type of this variable to datetime. Because DEPARTMENT_NAME designates a finite set of repeating values, change the data type of this variable to categorical. Also, change the name of this variable to lowercase. Because first_name stores text data, change the data type of this variable to string.

opts = setoptions(opts,'hire_date','Type','datetime');
opts = setoptions(opts,'DEPARTMENT_NAME','Name','department_name', ...
    'Type','categorical');
opts = setoptions(opts,'first_name','Type','string');

vars = opts.SelectedVariableNames;
varOpts = getoptions(opts,vars)
varOpts = 
    1x16 SQLVariableImportOptions array with properties:

   Variable Options:
                       (1) |          (2) |         (3) |     (4) |            (5) |         (6) |      (7) |      (8) |              (9) |         (10) |            (11) |        (12) |            (13) |              (14) |         (15) |          (16)  
       Name: 'employee_id' | 'first_name' | 'last_name' | 'email' | 'phone_number' | 'hire_date' | 'job_id' | 'salary' | 'commission_pct' | 'manager_id' | 'department_id' | 'temporary' | 'DEPARTMENT_ID' | 'department_name' | 'MANAGER_ID' | 'LOCATION_ID'
       Type:      'double' |     'string' |      'char' |  'char' |         'char' |  'datetime' |   'char' | 'double' |         'double' |     'double' |        'double' |    'double' |        'double' |     'categorical' |     'double' |      'double'
  FillValue:           NaN |    <missing> |          '' |      '' |             '' |         NaT |       '' |      NaN |              NaN |          NaN |             NaN |         NaN |             NaN |       <undefined> |          NaN |           NaN

	To access sub-properties of each variable, use getoptions

Select the three modified variables using the SelectVariableNames property.

opts.SelectedVariableNames = {'first_name','hire_date','department_name'};

Import and display the results of the SQL query using the fetch function.

employees_data = fetch(conn,sqlquery,opts)
employees_data=10×3 table
    first_name          hire_date          department_name
    ___________    ____________________    _______________

    "Alexander"    03-Jan-2006 00:00:00         IT        
    "Bruce"        21-May-2007 00:00:00         IT        
    "David"        25-Jun-2005 00:00:00         IT        
    "Valli"        05-Feb-2006 00:00:00         IT        
    "Diana"        07-Feb-2007 00:00:00         IT        
    "John"         01-Oct-2004 00:00:00         Sales     
    "Karen"        05-Jan-2005 00:00:00         Sales     
    "Alberto"      10-Mar-2005 00:00:00         Sales     
    "Gerald"       15-Oct-2007 00:00:00         Sales     
    "Eleni"        29-Jan-2008 00:00:00         Sales     

Delete the employees and departments database tables using the execute function.

execute(conn,'DROP TABLE employees')
execute(conn,'DROP TABLE departments')

Close the database connection.

close(conn)

Specify the data return format and the number of imported rows for the results of an SQL query. Import data using an SQL query and the fetch function.

This example uses a Microsoft® SQL Server® Version 11.00.2100 database and the Microsoft SQL Server Driver 11.00.5058.

Create an ODBC database connection to a Microsoft SQL Server database with Windows® authentication. Specify a blank user name and password.

datasource = 'MS SQL Server Auth';
conn = database(datasource,'','');

Load patient information into the MATLAB® workspace.

patients = readtable('patients.xls');

Create the patients database table using the patient information.

tablename = 'patients';
sqlwrite(conn,tablename,patients)

Select all data from the patients database table and import five rows from the table as a structure. Use the 'DataReturnFormat' name-value pair argument to specify returning the result data as a structure. Also, use the 'MaxRows' name-value pair argument to specify five rows. Display the imported data.

sqlquery = ['SELECT * FROM ' tablename];
results = fetch(conn,sqlquery,'DataReturnFormat','structure', ...
    'MaxRows',5)
results = struct with fields:
                    LastName: {5×1 cell}
                      Gender: {5×1 cell}
                         Age: [5×1 double]
                    Location: {5×1 cell}
                      Height: [5×1 double]
                      Weight: [5×1 double]
                      Smoker: [5×1 double]
                    Systolic: [5×1 double]
                   Diastolic: [5×1 double]
    SelfAssessedHealthStatus: {5×1 cell}

Delete the patients database table using the execute function.

sqlquery = ['DROP TABLE ' tablename];
execute(conn,sqlquery)

Close the database connection.

close(conn)

Import product data from a Microsoft® SQL Server® database into MATLAB® by using an ODBC connection and a variable in the SQL SELECT statement.

Create an ODBC database connection to a Microsoft® SQL Server® database with Windows® authentication. Specify a blank user name and password. The database contains the table productTable.

datasource = 'MS SQL Server Auth';
conn = database(datasource,'','');

Check the database connection. If the Message property is empty, then the connection is successful.

conn.Message
ans =

     []

Select all the data from productTable by specifying the product description as a variable. Import the data from the executed query using the fetch function.

The SQL SELECT statement uses square brackets to concatenate the two character vectors. To create the pair of single quotation marks that appears in the SQL SELECT statement, specify two sets of four single quotation marks around productdesc. The outer two marks delineate the next character vector for concatenation. The two inner marks denote a quotation mark inside a character vector.

productdesc = 'Painting Set';
sqlquery = ['SELECT * FROM productTable ' ...
    'WHERE productDescription = ' '''' productdesc ''''];
results = fetch(conn,sqlquery)
results =

  1×5 table

    productNumber    stockNumber    supplierNumber    unitCost    productDescription
    _____________    ___________    ______________    ________    __________________

          2          4.0031e+05          1002            9          'Painting Set'  

Instead of a variable, use the character vector 'Slinky' to import data.

sqlquery = ['SELECT * FROM productTable ' ...
    'WHERE productDescription = ' '''Slinky'''];
results = fetch(conn,sqlquery)
results =

  1×5 table

    productNumber    stockNumber    supplierNumber    unitCost    productDescription
    _____________    ___________    ______________    ________    __________________

          3           4.01e+05           1009            17            'Slinky'     

Close the database connection.

close(conn)

Retrieve metadata information when importing data from an SQL query. Import data using the fetch function and explore the metadata information by using dot notation.

This example uses the outages.csv file, which contains outage data. Also, the example uses a Microsoft® SQL Server® Version 11.00.2100 database and the Microsoft SQL Server Driver 11.00.5058.

Create a database connection to a Microsoft SQL Server database with Windows® authentication. Specify a blank user name and password.

datasource = "MS SQL Server Auth";
conn = database(datasource,"","");

Load outage information into the MATLAB® workspace.

outages = readtable("outages.csv");

Create the outages database table using the outage information.

tablename = "outages";
sqlwrite(conn,tablename,outages)

Import the data into the MATLAB workspace and return metadata information about the imported data.

sqlquery = "SELECT * FROM outages";
[results,metadata] = fetch(conn,sqlquery);

View the names of the variables in the imported data.

metadata.Properties.RowNames
ans = 6×1 cell array
    {'Region'         }
    {'OutageTime'     }
    {'Loss'           }
    {'Customers'      }
    {'RestorationTime'}
    {'Cause'          }

View the data type of each variable in the imported data.

metadata.VariableType
ans = 6×1 cell array
    {'char'  }
    {'char'  }
    {'double'}
    {'double'}
    {'char'  }
    {'char'  }

View the missing data value for each variable in the imported data.

metadata.FillValue
ans = 6×1 cell array
    {0×0 char}
    {0×0 char}
    {[   NaN]}
    {[   NaN]}
    {0×0 char}
    {0×0 char}

View the indices of the missing data for each variable in the imported data.

metadata.MissingRows
ans = 6×1 cell array
    {  0×1 double}
    {  0×1 double}
    {604×1 double}
    {328×1 double}
    { 29×1 double}
    {  0×1 double}

Display the first eight rows of the imported data that contain missing restoration time. data contains restoration time in the fifth variable. Use the numeric indices to find the rows with missing data.

index = metadata.MissingRows{5,1};
nullrestoration = results(index,:);
head(nullrestoration)
ans=8×6 table
      Region              OutageTime             Loss     Customers     RestorationTime          Cause       
    ___________    _________________________    ______    __________    _______________    __________________

    'SouthEast'    '2003-01-23 00:49:00.000'    530.14    2.1204e+05          ''           'winter storm'    
    'NorthEast'    '2004-09-18 05:54:00.000'         0             0          ''           'equipment fault' 
    'MidWest'      '2002-04-20 16:46:00.000'     23141           NaN          ''           'unknown'         
    'NorthEast'    '2004-09-16 19:42:00.000'      4718           NaN          ''           'unknown'         
    'SouthEast'    '2005-09-14 15:45:00.000'    1839.2    3.4144e+05          ''           'severe storm'    
    'SouthEast'    '2004-08-17 17:34:00.000'     624.1    1.7879e+05          ''           'severe storm'    
    'SouthEast'    '2006-01-28 23:13:00.000'    498.78           NaN          ''           'energy emergency'
    'West'         '2003-06-20 18:22:00.000'         0             0          ''           'energy emergency'

Delete the outages database table using the execute function.

sqlstr = "DROP TABLE ";
sqlquery = strcat(sqlstr,tablename);
execute(conn,sqlquery)

Close the database connection.

close(conn)

Input Arguments

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Database connection, specified as a connection object created with the database function.

SQL statement, specified as a character vector or string scalar. The SQL statement can be any valid SQL statement, including nested queries. The SQL statement can be a stored procedure, such as {call sp_name (parm1,parm2,...)}. For stored procedures that return one or more result sets, use fetch function. For procedures that return output arguments, use runstoredprocedure.

For information about the SQL query language, see the SQL Tutorial.

Data Types: char | string

Database import options, specified as an SQLImportOptions object.

Name-Value Pair Arguments

Specify optional comma-separated pairs of Name,Value arguments. Name is the argument name and Value is the corresponding value. Name must appear inside quotes. You can specify several name and value pair arguments in any order as Name1,Value1,...,NameN,ValueN.

Example: results = fetch(conn,sqlquery,'MaxRows',50,'DataReturnFormat','structure') imports 50 rows of data as a structure.

Maximum number of rows to return, specified as the comma-separated pair consisting of 'MaxRows' and a positive numeric scalar. By default, the fetch function returns all rows from the executed SQL query. Use this name-value pair argument to limit the number of rows imported into MATLAB®.

Example: 'MaxRows',10

Data Types: double

Data return format, specified as the comma-separated pair consisting of 'DataReturnFormat' and one of these values:

  • 'table'

  • 'cellarray'

  • 'numeric'

  • 'structure'

Use the 'DataReturnFormat' name-value pair argument to specify the data type of the result data results. To specify integer classes for numeric data, use the opts input argument.

You can specify these values using character vectors or string scalars.

Example: 'DataReturnFormat','cellarray' imports data as a cell array.

Output Arguments

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Result data, returned as a table, cell array, structure, or numeric matrix. The result data contains all rows of data from the executed SQL statement by default.

Use the 'MaxRows' name-value pair argument to specify the number of rows of data to import. Use the 'DataReturnFormat' name-value pair argument to specify the data type of the result data.

When the executed SQL statement does not return any rows, the result data is an empty table.

Metadata information, returned as a table with these variables.

Variable NameVariable DescriptionVariable Data Type

VariableType

Data type of each variable in the imported data

Cell array of character vectors

FillValue

Value of missing data for each variable in the imported data

Cell array of missing data values

MissingRows

Indices for each occurrence of missing data in each variable of the imported data

Cell array of numeric indices

By default, the fetch function imports text data as a character vector and numeric data as a double. FillValue is an empty character array (for text data) or NaN (for numeric data) by default. To change the missing data value to another value, use the SQLImportOptions object.

The RowNames property of the metadata table contains the names of the variables in the imported data.

Limitations

The name-value pair argument 'MaxRows' has these limitations:

  • If you are using Microsoft® Access™, the native ODBC interface is not supported.

  • Not all database drivers support setting the maximum number of rows before query execution. For an unsupported driver, modify your SQL query to limit the maximum number of rows to return. The SQL syntax varies with the driver. For details, consult the driver documentation.

Tips

  • The order of records in your database does not remain constant. Sort data using the SQL ORDER BY command in your sqlquery statement.

  • For Microsoft Excel®, tables in sqlquery are Excel worksheets. By default, some worksheet names include a $ symbol. To select data from a worksheet with this name format, use an SQL statement of the form SELECT * FROM "Sheet1$" (or 'Sheet1$').

  • Before you modify database tables, ensure that the database is not open for editing. If you try to edit the database while it is open, you receive this MATLAB error:

    [Vendor][ODBC Driver] The database engine could not lock 
    table 'TableName' because it is already in use by 
    another person or process.
  • The PostgreSQL database management system supports multidimensional fields, but SQL SELECT statements fail when retrieving these fields unless you specify an index.

  • Some databases require that you include a symbol, such as #, before and after a date in a query, as follows:

    execute(conn,'SELECT * FROM mydb WHERE mydate > #03/05/2005#')
  • Executing the fetch function with the opts input argument and the 'DataReturnFormat' name-value pair argument set to the 'numeric' value has no effect. A corresponding warning message appears in the Command Window.

Alternative Functionality

App

The fetch function imports data using the command line. To import data interactively, use the Database Explorer app.

Compatibility Considerations

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Behavior changed in R2018b

Behavior changed in R2018b

Introduced in R2006b