SQL Data Generator
Version - 1.2
Contents
Getting started ................................................................................................... 3
Worked example: setting up data generation ........................................................ 4
About generators ................................................................................................ 9
Generic generators ......................................................................................... 13
Customizing existing generators ....................................................................... 18
Creating new generators ................................................................................. 21
Using existing sources ....................................................................................... 26
Mapping SQL tables or views ............................................................................ 27
Mapping CSV files .......................................................................................... 29
Using the command line interface ..................................................................... 32
Acknowledgements ........................................................................................... 34
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Getting started
SQL Data Generator enables you to populate selected tables and entire databases with
realistic data. You can populate empty tables, or add extra rows to your existing data.
This is useful when you have a table or database that you want to populate, and no live
data that you can use. For example, you may want to create a large database of test data
so that you can perform nunit or performance tests on a new product. Or you may have
live data you do not want to use all of; for example, you may want to replace the data in
a credit card number column with randomly-generated data. With SQL Data Generator,
you can do this by importing some of the data from existing SQL tables or CSV files, while
generating the other columns or tables.
You can use SQL Data Generator to populate SQL Server 2008 and 2008 R2, SQL Server
2005, and SQL Server 2000 databases.
You can use SQL Data Generator to:
Generate data for all supported SQL Server data types, using the standard generators
supplied.
Customize the generators to suit your specific needs.
Create a new generator based on one of the supplied generic data generators.
Technical notes
SQL Data Generator automatically assigns a generator to each column based on
information such as table name, column name, data type, and any constraints; otherwise
the Regular Expressions Generator is assigned.
There are over 80 pre-configured generators, supporting all SQL Server 2008 data types.
These are detailed in the list of generators and the data types they support
(http://downloads.red-gate.com/HelpPDF/SupportedDataTypesByGe nerator.pdf).
You must have administrator privileges for the database that you want to populate.
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Worked example: setting up data generation
This topic provides an overview of how you set up SQL Data Generator to generate data.
You are recommended to back up the database that you are going to populate before you
generate the data; you can then adjust the settings and repeat the data generation if you
are not happy with the results.
To generate data, first create a project by selecting the SQL Server and database you
want to populate. The project also defines some options for the data generation, and you
can specify any number of SQL scripts that you want SQL Generator to run automatically
before or after generating the data.
When you have created a project, the schema of the database you selected is listed in a
tree view in the Tables to populate pane.
You specify the tables that you want to populate by selecting the Populate check box. By
default, these are all selected, but you can change this option in your application options
(accessed from the Tools menu).
To see the creation SQL script for a table, right -click the table or column name in the tree
view and click Show Schema Creation Script.
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When you have selected the Populate check box for a table, you can define how you
want the data to be generated: click the table name in the Tables to populate pane,
and specify the details in the Table generation settings pane.
You can choose to:
create data using generators
SQL Data Generator automatically assigns a generator to each column based on its
table name, column name, data type, and length. If the column has constraints, SQL
Data Generator uses these to set the generator parameters for the column; if the
constraints cannot be complied with in this way, the RegexpGenerator is assigned
instead and an appropriate regular expression is set up. You can change the generator
used by a particular column later if required. For det ailed information, see About
generators.
import data
You can import a table or view from an existing database, or an existing CSV file. SQL
Data Generator maps the columns based on name and data type. If any columns
cannot be mapped, SQL Data Generator assigns a generator. You can change the
mappings later if required. For detailed information, see Mapping SQL tables or views
(page 27) and Mapping CSV files (page 29).
Note that:
foreign keys are automatically assigned the Foreign Key generator; this cannot be
changed to a different generator, but you can customize its settings
columns for which data is auto-generated display Server Assigned in the Generator
box; this cannot be changed
For example, identity columns and computed columns are server assigned.
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In the table generation settings, you can also specify the number of rows that you want
to be generated, and whether you want existing data to be deleted prior to populating the
table.
You can preview the data that will be generated for each table in the Preview pane.
You may see the following icons when the values for a column cannot be previewed prior
to generation:
server-assigned column
foreign key column
computed column or a manual foreign key
column
You may also see warnings or errors in the preview.
When you have set the table-level parameters, you can check the settings for each
column in the table, and customize them if required. To select a column for
customization, click the name of the column in the Tables to populate pane, or click the
column in the Preview pane.
When you are happy with the settings for all the columns that you want to populate, click
Generate Data. An action plan provides a summary of the data generation for you to
review before you generate.
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Scripts
You can run SQL scripts before or after the data generation. For example, you could use
scripts to add custom data to the database. SQL Data Generator can run these scripts
automatically.
You set up the scripts you want to run in the Project Configuration dialog box (click
Edit Project and select the Scripts tab).
You can link to external script files, or you can embed scripts by typing in the Project
Configuration dialog box, (or a combination of the two). Scripts are run in the order in
which you list them in the project configuration.
If a script that is run before generation fails, the generation process is stopped.
If a script that is run after data generation fails, the process continues with the next
script.
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Warnings and errors
When you are setting up the tables and columns that you want to populate, SQL Data
Generator displays warning and error messages to inform you when there may be a
problem with the data generation.
Errors prevent you from selecting
Generate Data. For example,
an error is displayed if there are circular dependencies.
Warnings inform you when a problem may arise during data
generation. The problem does not prevent you from generating data,
but it may stop the data generation for a particular table. For
example, a warning is displayed if you have chosen to delete rows in
a table, but another table references it.
Information messages provide you with information about issues
that you may want to rectify, but which will not prevent data
generation. For example, you may see an information message if
SQL Data Generator cannot create enough rows for the preview.
To see the details of an error or warning, hover your mouse pointer over the icon to
display a tooltip, or click the column name to see the details in the Column generation
settings pane.
Refreshing the schema
When you open a project, if the database schema has c hanged since you created the
project, the schema that has changed is flagged with
in the Tables to populate pane.
For example, a changed column is indicated by
and a changed primary key column is
indicated by
.
To clear the flags, click
Refresh Schema.
You can also click
Refresh Schema to see any changes that have been made to the
schema since you opened it. Click
Refresh Schema again to clear the flags.
Command line
When you have set up a SQL Data Generator project, you can use the command line to
Chapter
run the project. For more information, see Using the command line interface.
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About generators
SQL Data Generator uses generators to creat e the data for the tables that you choose to
populate. Different generators are used to create different types of values, and to enable
you to define specific parameters for the values.
When you select a column in the Tables to populate pane, Generators lists only the
generators that create data of the same data type as the column. For example, if the
column type is int, only generators that create integer values are available in the list.
SQL Data Generator provides a number of pre-defined generators, such as FirstName,
WorkingAge, Country, and so on. These generators are grouped by subject area in the
Generator list. You can change the settings for these generators as required.
In addition, SQL Data Generator provides some non-specific generators for you t o
customize:
SQL Type lists a generator for each SQL data type (except CLR)
Generic lists some basic generators
For information about the generic generators, see Generic generators.
For full details about customizing generators, see Customizing generators.
For information about how you can create your own generators, see Creating new
generators.
Data types supported by the supplied generators
To see a matrix of the data types that are supported by the supplied generators, see the
table of supported data types by generator (PDF) (http://downloads.redgate.com/HelpPDF/SupportedDataTypesByGenerator.pdf )
Uniqueness
Many of the generators have a Set unique setting. When this check box is selected, SQL
Data Generator makes the values that are generated for the column unique.
If the column schema has a uniqueness constraint (such as a unique index or primary
key), Set unique is selected by default. However, you can override the uniqueness for
the column by clearing the check box. For example, you may want to do this if the
uniqueness constraint applies across multiple columns, and you know that another of the
columns is unique. A warning is displayed, but you can proceed with the generation.
Generators that do not offer the Set unique option are not available for columns that
have a uniqueness constraint, except for the SQL statement generator.
If Set unique is selected but there are not enough unique values to display in the
preview, a warning is displayed. However, you can proceed with the generation. (Note
that you can change the number of values to be displayed in the preview by changing
your application options, which are available from the Tools menu.)
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Check constraints
When SQL Data Generator automatically assigns generators to the columns in a new
project or new schema, it sets the generator parameters to take account of any check
constraints.
However, it is not always possible to set the generator parameters appropriately. When
you generate data, if the values generated do not comply with a check constraint, data
generation for that table is stopped and an error is reported.
You can set up the project so that check constraints are not enforced when the data is
generated. To do this, clear the Enforce check constraints check box in the project
configuration options (click
Edit Project and select the Options tab).
Foreign keys
When SQL Data Generator automatically assigns generators to the columns in a new
project or new schema, the Foreign Key generator is assigned to all columns that have
foreign key constraints.
You cannot change the generator, but you can change the settings for the Foreign Key
generator.
In the example below, Table 2 Column 1 references Table 1 Column A, and Table 2
Column 2 references Table 3 Column a.
SQL Data Generator assigns the Foreign Key generator to Column 1 and Column 2. You
can change the settings for these columns individually.
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For a composite foreign key, the generator settings are the same for each of the
columns; if you change the settings on one column, they are automatically changed on
the others. In the example below, changing the generator settings for Column 2 in Table
2 also changes the settings for columns 1 and 3.
Similarly, if two or more composite foreign keys overlap, the generator settings are the
same for each of the foreign keys. In the example below, changing the generator settings
for Column 4 in Table 2 also changes the settings for Columns 1, 2, and 3 in Table 2.
In addition, when two composite foreign keys overlap, for the overlapping column(s) SQL
Data Generator uses values that appear in both referenced tables; that is, if a value
appears in one referenced table but not in the other, that value will not appear in the
generated data. In the example above, only values that appear in both Table 1 Column C
and Table 3 Column c will be used for Table 2 Column 3.
A NULL value in a composite foreign key is NULL across all of the columns in the foreign
key.
SQL Data Generator cannot display preview values f or the Foreign Key generator;
displayed instead.
is
Foreign Key (manual) generator
You can create a single-column foreign key by using the Foreign Key (manual) generator,
which is available under the SQL Types category.
There is no restriction on the data type of the column you select. However, if possible,
you should select a column with the same data type. If you select a column with a
different data type, SQL Data Generator attempts to convert the values when the data is
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generated; if SQL Data Generator is unable to convert the data, the data generation may
fail.
You cannot create a self-referential foreign key using this generator.
SQL Data Generator cannot display preview values for the Foreign Key (manual)
generator;
is displayed instead.
Dependencies
SQL Data Generator takes dependencies into account when defining the order in which
tables will be generated.
If there are any circular dependencies,
is displayed next to the relevant columns in the
Tables to populate pane, and
Generate Data is not available.
Generating XML
There are a number of ways in which you can generator XML values:
use the XML generator to generator XML strings
use the RegExGenerator and write a regular expression that obeys the XML definition
use the File Import generator to import XML files
use the SQL Statement generator to retrieve values from another database that
contains schema-validated XML
Generating real numbers
When you use the real SQL type generator, if you set Min or Max to be a large value,
sequential distribution will not produce sequential values because the increment cannot
be set high enough.
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Generic generators
SQL Data Generator provides the following generators in the Generic category for you to
customize:
CSV (page 13)
File List (page 14)
SQL Statement
Text Shuffler (page 16)
File Import (page 13)
RegexpGenerator
Weighted List (page 17)
Information about each of these generators is provided below.
For information about how to customize the generators, see Customizing existing
generators.
Data types supported by the supplied generators
To see a matrix of the data types that are supported by the supplied generators, see the
table of supported data types by generator (PDF file) (http://downloads.redgate.com/HelpPDF/SupportedDataTypesByGenerator.pdf )
CSV generator
Use the CSV generator when you want to import data from a CSV file into a single
column. (If you want to import data from a CSV file into an entire table or multiple
columns in a table, you can use the Use existing data source table generation setting
instead; for details, see Mapping CSV files (page 29).)
Click Browse to select the CSV file you want to use; you then specify the delimiters to be
used when importing the data, and select the column in the CSV file that you want to
import.
Note that when you select Shuffle data, changing the Seed value in the CSV generator
settings changes only the position of any null values.
File Import generator
Use the File Import generator to import the contents of files in a specified folder.
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For example, if you specify a folder containing a number of images, each image is
imported into a new row. You can specify a search string to identify the files within the
specified folder you want to use.
If you specify large files, or if you specify a large number of files, performance will be
reduced.
File List generator
Use the File List generator to import values from a text file.
You must first create a text file containing the list of values, with each value on a new
line. The values will be imported from the list in a random order. You can then browse to
this file when you select the File List generator.
If you have a very long list of values, you may want to consider creating a CSV file with
the list of values and then importing the values using the CSV generator (page 29) to
import the values.
Regexp generator
Use the Regexp generator to define the generated data using a regular expression.
In the basic syntax, most characters are treated as literals (for example, a generates
"a"). Below is a list of syntax elements.
Syntax
Example
Generates
ordinary chars
bob
bob
[chars]character
set
[A-Z0- 9]
eg. 5 or G
individual chars
[FM]
F or M
initial ] in char
set
[]]
]
[x-y] range
[0-9]
eg. 3 or 9
complement
[^abc]
eg. d or #
* zero or more
abc*
eg. abcccccc or
ab
+ 1 or more
abc+
eg. abcccc or abc
? Include or not
abc?
ab or abc
(regexp) grouping
(abc)*d
eg., abcabcd or d
{num} repeat
a{4}
aaaa
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{min,max} repeat
a{2,3}
aa or aaa
{min,} at least
min repeats
a{3,}
eg. aaa or
aaaaaaaaaa
() empty string
()
| alternatives
Yes|No
Yes or No
Empty Alternative
(|some- |often)time
eg. some-time or
time
Escapes:
Syntax
Generates
\xdd hex char (8- bit)
eg. \x21 generates !
\udddd hex unicode
eg. \u0021 generates !
\\
\
\.
.
\^
^
\$
$
\{
{
\[
[
\]
\]
\(
(
\|
|
\)
)
\*
*
\+
+
\?
?
\a
alarm character
\b
backspace
\d
digit
\e
escape
\f
formfeed
\n
newline
\t
tab
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\r
carriage return
\s
space
\v
vertical tab
\w
[A-Za- z_0-9]
Use $"file_name" to import a text file containing a list of values.
Use $[column_name] to import the values from another column in the same table. Note
that when you import values from another column:
for repeating values, you must specify a fixed range of repetitions using {1,10}; you
cannot use * when you import values from a column
changing the Seed value in the RegexpGenerator settings changes only the position
of any null values; to shuffle the order of the values, use the settings on the
referenced column
you should not select Set unique in the RegexpGenerator settings, because only one
row will be generated
You can use the buttons below the Regular Expression box to add snippets of code, file
lists, and table columns.
SQL Statement generator
Use the SQL Statement generator to define data to import from an external database
using a SQL statement. If you want to import data from an external database into a an
entire table or multiple columns in a table, you can use the Use existing data source
table generation setting instead; for details, see Mapping SQL tables or views (page 27).
Click Edit to specify the database and the SQL statement. The SQL statement must select
a single column of values which are of the correct data type.
If the column you are populating has a unique constraint, you must ensure that the SQL
statement returns unique values; if it does not, the data generation will fail.
Note that when you select Shuffle data, changing the Seed value in the SQL Statement
settings changes only the position of any null values.
Text Shuffler generator
Use the Text Shuffler generator when you want to create values that contain words
randomly selected from a pre-defined list. For example, you may want to use this to
check the performance of a full text index.
You can type the text, or you can import it from a text file. You are recommended to us e
text that contains a high variety of words that are similar to your real data.
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SQL Data Generator shuffles the text using the spaces as delimiters for the words.
Therefore, if there is punctuation in the text, this will be included in the values.
Weighted List generator
Use this generator when you want to specify the percentage for the number of
occurrences of each value in the column. For example, you may want to use this to check
that your indexing strategy will work on the table.
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Customizing existing generators
You can customize the generators in the following ways:
change the settings for each column
for generators that use lists, create a custom list of values
Changing the settings
When you select a generator for a column, you can customize the gene rator by changing
the default settings.
For example, in the Personal category, Working Age is pre-configured to have a minimum
value of 18 and a maximum value of 65. However, in your company the minimum age
may be 21, so you can change this value in Min.
Similarly, if you have selected the Title generator, you may want to add the title Prof. To
do this, you can edit the expression in Regular expression. Change:
Mr|((Mrs|Miss|Ms)|Dr)(\.?)
To:
Mr|((Mrs|Miss|Ms)|Dr|Prof)(\.?)
For more information about regular expression generators, see RegexpGenerator.
This is a good way to customize a generator for an individual column.
Creating custom lists
Some of the generators use lists of values (dictionaries) to supply the data. For example,
First Name (Female) uses the list NamesFirstFemale.txt
The lists are located in:
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Program Files\Red Gate\SQL Data Generator 1\Config
You can create your own lists by creating a text file with each value on a new line. You
can then amend the generator settings so that it uses your file. For example, for First
Name (Female), click Browse... to select your file. Alternatively, you can use the generic
File List generator.
For generators that use regular expressions such as Full Names, edit the regular
expression to specify the name of the new text file.
For more information about regular expression generators, see RegexpGenerator.
Creating a custom generator
You may find that you want to make the same customizations for a number of columns.
In this case, you can customize a generator and add it to the list of available generators
so that you can re-use it.
To do this, find the SQL type or generic generator that you want to base the custom
generator on, and then find its corresponding .xml file in:
Program Files\Red Gate\SQL Data Generator 1\UserExample\Config
Create a copy of the .xml file and name it appropriately, then edit the contents to specify
the properties as required.
The example below shows the code for the Working Age generator which generates
random integers between 18 and 65. It is based on Int32Generator.xml:
<?xml version="1.0" encoding="iso-8859-1"?>
<generators>
<generator
/* Specify the class. */
type="RedGate.SQLDataGenerator.Generators.Number.
Int32Generator"
/* The name and description to be displayed
in the generators list, */
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/* and its category */
name="Working Age"
description="29,30,35,18..."
category="Personal">
/* Set the properties for the generator. */
<property name="MinValue">18</property>
<property name="MaxValue">65</property>
/* Specify the columns that match, and their score. */
<matches field="Age" score="50"/>
/* Define the data types for which the generator
is valid. */
<type type="Int64"/>
<type type="Int32"/>
<type type="Int16"/>
<type type="Byte"/>
</generator>
SQL Data Generator uses the matches field string when it allocates the generators to
columns. You can specify a regular expression search string. You then specify a score; if
more than one generator matches a particular column, SQL Data Generator uses the one
with the highest score.
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Creating new generators
You may want to create a new generator if the supplied generators do not meet your
requirements and you cannot customize them to suit your needs.
To write your own generator, you must be proficient at a .NET 2.0 language, have a good
understanding of .NET, and have access to SQL Data Generator on your computer.
The procedure is summarized below:
1. In Microsoft Visual Studio, create a Class Library .NET project.
2. Add references to RedGate.SQLDataGenerator.Engine and
RedGate.SQLCompare.Engine
3. Create a public class that implements IGenerator.
4. Add the class attributes.
5. Implement the constructor.
6. Implement the method GetEnumerator.
7. Copy the output DLL to:
Program Files\Red Gate\SQL Data Generator\Generators
Example Microsoft ® Visual Studio® 2005 project files are provided in:
Program Files\Red Gate\SQL Data Generator\UserExample\Generator
The examples are written in C#. If you want to build the projects, you must first reset the
project references for the SQL Compare Engine and the SQL Data Compare Engine. You
may also want to change the output path. When you have built the project, copy the
output DLL to:
Program Files\Red Gate\SQL Data Generator\Generators
Architecture
A simple diagram of the architecture is shown below.
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The SQL Data Generator engine defines a series of interfaces. Each interface is very
lightweight.
A generator must implement a series of interfaces in order that the engine considers it to
be a generator. At startup, a specified folder is scanned for DLLs. Each DLL is loaded in
turn, and reflection is used to check whether any public classes implement these
interfaces. If they do, the class is considered to be a generator and is made accessible to
the rest of the system.
By default, parameters for the generator are displayed in a standard Microsoft Grid
Control. To override this default functionality, implement interfaces IGeneratorUIStyle
and IGeneratorUI. See the FullDemo project for an example.
Basic interface: IGenerator
The IGenerator interface must be implemented for your class to be considered a
generator.
The IGenerator interface is defined as:
namespace RedGate.SQLDataGenerator.Engine.Generators
{
public interface IGenerator
{
IEnumerator GetEnumerator
GenerationSession session);
}
}
You must also implement a special constructor that takes a single parameter of type
GeneratorParameters. This parameter describes the SQL field in the Table that is being
assigned. If necessary, your code can throw exceptions and so on.
To display your generator in the graphical user interface (GUI), you must add a simple
Generator attribute to your class. The following example code produces random values
between 0 and 1024 for the 8 times table.
namespace Basic
{
[Generator(typeof(int), "Generic", "8 times table",
"8, 16, 0, 256, ...")]
public class Basic : IGenerator
{
public Basic(GeneratorParameters parameters)
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{
}
public System.Collections.IEnumerator GetEnumerator
(GenerationSession session)
{
Random r = new Random(0);
while (true)
{
yield return r.Next(0, 1024) * 8;
}
}
}
}
The Generator attribute defines the type of .NET result, the Category that the generator
is to be placed in, and the name and desc ription to be displayed in the GUI. It must be
defined only once per class.
SQL Data Generator assigns the SQL data type that corresponds to the specified type of
.NET result. To create a generator that supports multiple SQL data types, add
SupportSQLType. SQL Data Generator will add SQL data types based on SqlTypes defined
in the SQL Compare engine.
Note that you must ensure that the class is public, and the Generator class exists.
Constructor
GeneratorParameters provides access to the field. This enables your code to verify that
lengths and types are consistent.
GetEnumerator
The easiest way to implement this code is by using the Yield statement; the above
example never runs out of values. However, it is not always possible to do this. The
engine is designed to cater for a limited number of values from the GetEnumerator. If
necessary, the GetEnumerator can throw exceptions.
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Interface: ISeedableGenerator
This interface enables the generator to specify a seed. The generator can then generate
random data that is different each time.
The ISeedableGenerator is defined as:
public interface ISeedableGenerator
{
int Seed { get; set; }
}
Use public bool Unique { get { return m_Unique; } set { m_Unique = value; } }the seed
to initialize the Random class in the GetEnumerator.
The engine will automatically give a value to Seed at initialization. Each column will have
its own seed, therefore the same generator can be assigned multiple times within a table
and different values will be produced for each column.
A typical implementation is:
public int Seed
{
get { return m_Seed; }
set { m_Seed = value; }
}
For a complete example, see:
UserExample\Generator\Seedable\Seedable.cs
Interface: IUniqueableGenerator
This interface enables the generator to specify whether the data generated is unique so
that the generator can then generate a unique value.
The IUniqueableGenerator is defined as follows:
public interface IUniqueableGenerator
{
bool Unique { get; set; }
}
A typical implementation is:
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public bool Unique
{
get { return m_Unique; }
set { m_Unique = value; }
}
For a complete example, see:
UserExample\Generator\Uniqueable\Uniqueable.cs
The generator can now be assigned to unique fields. The engine automatically configures
the Unique flag as on when the generator is assigned.
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Using existing sources
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Mapping SQL tables or views
You can populate an entire table, or multiple columns in a table, by mapping to another
SQL table or view. For example, this may be useful if you want to import master data or
lookup data into your schema.
With the table selected in Tables to populate, click Use existing data source, select
SQL Table or View and click Browse.
You can then select the SQL Server and database, and the table you want to use from the
Select SQL Table or View wizard. When you click Finish on the wizard, SQL Data
Generator matches columns in the two t ables based on data type and column name.
Any columns in the table for which SQL Data Generator does not find a match will have a
generator assigned to them instead. However, you can still map the schema column to a
column in the external SQL table as long as the data types match:
1. Select the column in the Tables to populate pane.
2. Click the Generator list.
The list displays the table name, with any columns for which the data types match.
3. Click the name of the column you want to use.
Similarly, if SQL Data Generator maps a schema column to an external SQL table column
but you do not want to use it, you can select a different generator for that column.
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If you want to define data to import from an external database using a SQL statement,
use the SQL Statement generator.
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Mapping CSV files
You can populate an entire table, or multiple columns in a table, by mapping an imported
CSV file to the table. For example, this may be useful if you want to import master data
or lookup data into your schema.
With the table selected in Tables to populate, click Use existing data source, select
CSV File and click Browse.
You can then select the file, and define the import settings.
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SQL Data Generator matches columns in the CSV file to columns in the table based on
data type and column name. If the data type and/or column name for a column in t he
CSV file is not the same as in the table, you can specify these in the data import settings.
When you click Finish, SQL Data Generator maps the columns.
Any columns in the table for which SQL Data Generator does not find a match will have a
generator assigned to them instead. However, you can still map the schema column to a
column in the CSV file as long as the data types match:
1. Select the column in the Tables to populate pane.
2. Click the Generator list.
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The list displays the CSV file path, with any columns for which the data types match.
3. Click the name of the column you want to use.
Similarly, if SQL Data Generator maps a schema column to a CSV file column but you do
not want to use it, you can select a different generator for that column.
If you want to import data from a single column in a CSV file into a single column in a
table, use the CSV generator.
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Using the command line interface
SQL Data Generator provides a command line interface for you to use with SQL Data
Generator projects that you have already created using the graphical user interface.
This topic describes how to use the basic features of the command line.
Getting help from the command line
To display help, enter:
SQLDataGenerator /help
This displays a brief description, and help on all the command line switches.
For more detailed help enter:
SQLDataGenerator /help /verbose
This displays a detailed description of each switch and the values it can accept (where
applicable), and all exit codes. To output the help in HTML format, enter:
SQLDataGenerator /help /verbose /html
Entering a command
When you enter a command line, the order of switches is unimportant. You are
recommended to follow the Microsoft convention of separating a switch from its values
using a colon as shown below.
/out:output.txt
(You can separate a switch that accepts a single value from its value using a space, but
this is not recommended.) Values that include spaces must be delimited by double
quotation marks ( " ). For example:
/out:"c:\output file.txt"
Aliases
Many of the switches have an alias. The alias provides a convenient short -hand way to
specify the switch. For example, /? is the alias for the /help switch, and /v is the alias for
the /verbose switch. Note that switches and aliases are not case-sensitive.
/verbose and /quiet switches
The standard output mode prints basic information about what the tool is doing while it is
executing. You can specify verbose and quiet modes using the /verbose and /quiet
switches, respectively: in verbose mode, detailed output is printed; in quiet mode, output
is printed only if an error occurs.
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Redirecting command output
Output from all commands can be redirected to a file by one of several methods:
Use the /out switch to specify the file to which you want output directed:
SQLDataGenerator ... /out:outputlog.txt
where outputlog.txt is the name of the file. If the file exists already, you must also
use the /force switch to force the tool to overwrite the file, otherwise an error will
occur.
Use the output redirection features that are provided by the shell in which you are
executing the command.
From the standard command prompt provided by Windows, you can redirect output to
a file as follows:
SQLDataGenerator ... > outputlog.txt
Note that the redirection operator ( > ) and file name must be the last items on the
command line. If the specified file exists already, it will be overwritten. To append
output from the tool to an existing file, for example to append to a log without losing
the data already present in the log, enter the following:
SQLDataGenerator ... >> existinglog.txt
If you are scripting using a language such as VBScript, JScript, PHP, Perl, or Python,
or if you want to access the tool from Web pages using ASP.NET, refer to the
documentation for the language.
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Acknowledgements
This product contains software that is Copyright 1995 - 2005 Jean-loup Gailly and Mark
Adler.
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© 2021