SQLCreator

Generates FME features and/or schemas from the results of a SQL query executed against a database. One FME feature is created for each row of the results of the SQL query.

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Typical Uses

Extract database records as FME features according to a SQL statement
Add features from a database mid-translation
Execute a database join

How does it work?

The SQLCreator executes a SQL statement against a database. It has no input ports, and so (unlike the SQLExecutor) is not reliant on incoming features to trigger the statement - rather, the query is run one time only.

SQL statements are constructed within the transformer, using the appropriate syntax for the database in use. Spatial queries are supported if the database supports spatial predicates.

One feature is output for each row of the query results, via the Result port.

A single schema feature may also be produced if supported by the database.

Examples

Example: Creating features from a SELECT statement

In this example, we will create a set of features by querying a PostGIS database, which has a table containing addresses with point geometry. We will use a SELECT statement that extracts a subset of the data based on postal code.

A SQLCreator is placed in the workspace.

In the parameters dialog, the Database Connection is selected (or defined, if not previously saved).

A SQL statement is constructed in the SQL Statement parameter, using the built-in editor. The syntax matches the database being used.

There is a convenient shortcut in the editor - by right-clicking on a table (or column) name under Database Tables, you can create a quick statement based on SELECT and more to start editing from.

In this case, we are selecting all of the records in the PostalAddress table that have a postal code starting with V6E.

By default, the output has hidden attributes. Choose the ones you wish to include in the Attributes to Expose parameter.

The query results are extracted, including geometry.

Note that only attributes which were exposed are visible in the Table View.

Usage Notes

If the database supports spatial predicates, spatial queries may be used.
The SchemaScanner may also be useful as an alternative for producing schemas.
The SQLCreator can only be used on SQL-enabled data sources. To use SQL with non-SQL data, consider the InlineQuerier.
If all the data to be queried already exists in a SQL-capable data source, it is generally most efficient to use the SQLCreator or SQLExecutor, as the queries and filtering of the data is executed directly by the database before it enters the FME environment.
For simple joins of one database table to features, the DatabaseJoiner may be more efficient (if the key field(s) are indexed). The DatabaseJoiner does not require knowledge of SQL.

Choosing a Feature Joining Method

Many transformers can perform data joining based on matching attributes, expressions and/or geometry. When choosing one for a specific joining task, considerations include the complexity of the join, data format, indexing, conflict handling, and desired results. Some transformers use SQL syntax, and some access external databases directly. They may or may not support list attribute reading and creation.

Generally, choosing the one that is most specific to the task you need to accomplish will provide the optimal performance results. If there is more than one way to do it (which is frequently the case), time spent on performance testing alternate methods may be worthwhile. Performance may vary greatly depending on the existence of key indexes when reading external tables (as opposed to features already in the workspace).

Joining Transformers Comparison Matrix

Transformer	Match By	Uses SQL Statements	Can Create List	Input Type	Notable	Description
FeatureJoiner	Attributes	No	No	Features	Best performance for simple joins on attribute values Cannot create lists - represents multiple joins as multiple output features Cannot use constructed keys or expressions	Joins features by combining the attributes and/or geometry of features based on common key attribute values. Performs the equivalent of Inner, Left, and Full SQL joins.
FeatureMerger	Attributes	No	Yes	Features	Can use expressions as keys (constructed keys) Can create lists – represents multiple joins as a list on a single feature Cannot match on geometry	Merges the attributes and/or geometry of one set of features onto another set of features, based on matching key attribute values and expressions.
ListBasedFeatureMerger	List Attribute to Single Attribute	No	Yes	Features	Only joining transformer to use all list attribute contents as keys (others may use one specific value in a list, but not the entire list)	Merges the attributes and/or geometry of one set of features onto another set of features, based on matching list attribute values with key attribute values and expressions.
InlineQuerier	SQL query	Yes	No	Features	Use SQL on non-SQL data Allows multiple join/SQL statements, and so can replace multiple transformers with one	Creates a set of SQLite database tables from incoming features, executes SQL queries against them, and outputs the results as features.
SQLCreator	SQL query	Yes	No	External DB	Best if all features already in SQL-capable source Read an external DB table mid-translation	Generates FME features from the results of a SQL query executed once against a database. One FME feature is created for each row of the results of the SQL query.
SQLExecutor	SQL query	Yes	No	External DB	Best for complex joins between features and SQL-capable source Read an external DB table mid-translation	Executes SQL queries against a database. One query is issued to the database for each initiating feature that enters the transformer. Both the initiating features and the results of the query may be output as features.
DatabaseJoiner	Attributes	No	Yes	External DB and Features	Best for simple joins between features and a database table Very efficient if keys indexed, and caches data locally Read an external DB table mid-translation Non-blocking	Joins attributes from an external table to features already in a workspace, based on a common key or keys. SQL knowledge not required. Non-blocking transformer.
Matcher	Geometry and/or Attributes	No	Yes	Features	The only one of these methods that can use geometry as key for matching Can look for attribute differences Uses geometry, not spatial relationships	Detects features that are matches of each other. Features are declared to match when they have matching geometry, matching attribute values, or both. A list of attributes which must differ between the features may also be specified. If matching on attributes only (not geometry), using the FeatureMerger or another method will give better performance.

Configuration

Input Ports

The SQLCreator has no input ports.

Output Ports

Parameters

Database

Format	Select a database format.
Dataset/Connection	According to chosen format, select a dataset or use/configure a database connection.
Parameters	Format-specific parameters
Coord. System	The coordinate system of the database being connected to, as well as the coordinate system of the Result output features. Leave as default (Read from source) or use a selection from the Coordinate System Gallery.

General

SQL Statement

Specify the SQL query using the text editor.

Multiple SQL commands can be delimited by a character specified using the keyword FME_SQL_DELIMITER, embedded at the very beginning of the SQL statement. The single character immediately following this keyword will be used to split the SQL which will then be sent to the database for execution. (Note: Include a space before the character.)

An individual statement may be preceded with a single hyphen, indicating that errors should be ignored.

Note: Some database formats support comments with /* ... */ or double hyphens (--).

The following example contains two SQL commands where errors from the first command will be ignored:

FME_SQL_DELIMITER ;

-SELECT * FROM TABLEA;

SELECT * FROM TABLEB;

Attributes to Expose

Enter the names of attributes to expose on the features created by the query. The attributes will be output in the same sequence as specified in the list.

Note: By default, the attributes of the resulting features are hidden. You can specify which attributes to expose by entering the attribute names. Click the browse button next to the Attributes to Expose parameter. You can also use a SQL statement to populate the list by pressing “Populate from SQL Query…” and entering a SQL query. The columns from the first matching feature will be used to populate the attributes list.

Schema/Data Features

Features to Read

Select the type of features to read and output:

Schema and Data Features	Read schema and query results.
Data Features	Read query results only.
Schema Features	Read schema only.

Editing Transformer Parameters

Using a set of menu options, transformer parameters can be assigned by referencing other elements in the workspace. More advanced functions, such as an advanced editor and an arithmetic editor, are also available in some transformers. To access a menu of these options, click beside the applicable parameter. For more information, see Transformer Parameter Menu Options.

Defining Values

There are several ways to define a value for use in a Transformer. The simplest is to simply type in a value or string, which can include functions of various types such as attribute references, math and string functions, and workspace parameters. There are a number of tools and shortcuts that can assist in constructing values, generally available from the drop-down context menu adjacent to the value field.

How to Set Parameter Values

Using the Text Editor

The Text Editor provides a convenient way to construct text strings (including regular expressions) from various data sources, such as attributes, parameters, and constants, where the result is used directly inside a parameter.

Text Editor

Using the Arithmetic Editor

The Arithmetic Editor provides a convenient way to construct math expressions from various data sources, such as attributes, parameters, and feature functions, where the result is used directly inside a parameter.

Arithmetic Editor

Conditional Values

Set values depending on one or more test conditions that either pass or fail.

Parameter Condition Definition Dialog

Content

Expressions and strings can include a number of functions, characters, parameters, and more.

When setting values - whether entered directly in a parameter or constructed using one of the editors - strings and expressions containing String, Math, Date/Time or FME Feature Functions will have those functions evaluated. Therefore, the names of these functions (in the form @<function_name>) should not be used as literal string values.

Content Types

String Functions	These functions manipulate and format strings.
Special Characters	A set of control characters is available in the Text Editor.
Math Functions	Math functions are available in both editors.
Date/Time Functions	Date and time functions are available in the Text Editor.
Math Operators	These operators are available in the Arithmetic Editor.
FME Feature Functions	These return primarily feature-specific values.
FME Parameters	FME and workspace-specific parameters may be used.
Creating and Modifying User Parameters	Create your own editable parameters.

Dialog Options - Tables

Transformers with table-style parameters have additional tools for populating and manipulating values.

Table Tools

Row Reordering

Enabled once you have clicked on a row item. Choices include:

Add a row
Remove a row
Move current row up one
Move current row down one
Move current row to top
Move current row to bottom

Cut, Copy, and Paste

Enabled once you have clicked on a row item. Choices include:

Cut a row - delete and copy to clipboard
Copy a row to the clipboard
Paste a row from the clipboard

Cut, copy, and paste may be used within a transformer, or between transformers.

Filter

Start typing a string, and the matrix will only display rows matching those characters. Searches all columns. This only affects the display of attributes within the transformer - it does not alter which attributes are output.

Import

Import populates the table with a set of new attributes read from a dataset. Specific application varies between transformers.

Reset/Refresh

Generally resets the table to its initial state, and may provide additional options to remove invalid entries. Behavior varies between transformers.

Note: Not all tools are available in all transformers.

Reference

Processing Behavior	Not applicable
Feature Holding	Not applicable
Dependencies	Format-dependent - may require third-party drivers for some formats
Aliases
History

FME Community

The FME Community is the place for demos, how-tos, articles, FAQs, and more. Get answers to your questions, learn from other users, and suggest, vote, and comment on new features.

Search for all results about the SQLCreator on the FME Community.

Examples may contain information licensed under the Open Government Licence – Vancouver and/or the Open Government Licence – Canada.