FeatureJoiner

Joins features by combining the attributes and/or geometry of features based on common key attribute values. Performs Left, Inner, and Full joins.

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Typical Uses

Performing simple joins between features, using attribute value(s) as keys

How does it work?

The FeatureJoiner performs simple join operations, much like a SQL join, without requiring knowledge of SQL query construction.

It has two input ports - Left and Right - where two streams of features to be joined are routed into the transformer. One or more attributes are selected to join on.

A Left feature matches a Right feature when every pair of keys specified in the Join On table has the same value. When a match occurs, attributes/geometry from the Left and Right feature are combined, and the combined feature is output to the Joined port.

Join Mode

The Join Mode parameter defines the type of join to be performed, determining which features will be output via the Joined output port.

Join Mode	Joined Output
Inner	Only features that have matching Left and Right pairs.
Left	Features that have matching Left and Right pairs, AND All other unmatched Left features.
Full	Features that have matching Left and Right pairs, AND All unmatched Left and Right features.

Join Behavior

A Joined feature is produced each time a Left feature is matched to a Right feature through its keys. The number of output features produced will depend on whether or not multiple Left and Right features match.

The type of join is determined by the nature of the data used (it is not a parameter). Any of these types of joins may be produced by any of the Join Modes (Inner, Left, or Full).

Cardinality	Description	Output (assuming 1 key value)
1:1	One to One: If each Left feature has a single match among the Right features (for example a single point feature is mapped to an address table via a unique address ID key), this is a 1:1 match and produces a single Joined feature.	1 Left matches 1 Right: 1 Joined Feature output
1:M	One to Many: If each Left feature has multiple matches among the Right features (for example a single address record is mapped to a list of planning applications for that address), this is a 1:M (one-to-many) match and produces a Joined feature for every match that occurs.	1 Left matches 10 Right: 10 Joined Features output
M:1	Many to One: If multiple Left features match a single Right feature record (for example a number of addresses match to the same census data via a postal code field) this is a M:1 (many-to-one) match and produces a Joined feature for every match that occurs	10 Left match 1 Right: 10 Joined Features output
M:N	Many to Many: If multiple Left features match multiple Right features (for example a number of addresses match to a number of records for electrical power outages) this is a M:N (many-to-many) match and produces a Joined feature for every match that occurs.	10 Left match 10 Right: 100 Joined Features output* *When all features have identical key values - all Left match all Right.

Unmatched Features

Features (both Left and Right) that do not find a match are handled according to the Join Mode (Inner, Left, or Full). Both the Left and Full modes will result in some or all unmatched features being output via the Joined port, depending on Mode:

Join Mode	Unmatched Left features output	Unmatched Right features output
Inner	UnjoinedLeft	UnjoinedRight
Left	Joined	UnjoinedRight
Full	Joined	Joined

Usage Notes

FeatureJoiner versus FeatureMerger:
- If the join requirements are simple, FeatureJoiner should give better performance.
- If join requirements are more complex, such as constructing keys, using expressions, naming conflict resolution, consider using the FeatureMerger.
- If you wish to get only one joined feature, regardless of the number of joins (1:M join produces 1 feature with a list of joins, rather than 1 feature for each join as the FeatureJoiner does), use the FeatureMerger.
- The FeatureJoiner does not perform some of the advanced list building or geometry handling operations that the FeatureMerger does, but these may be possible by using the FeatureJoiner plus other transformers.
For complex joins using SQL syntax, or more than two input feature streams, consider using the InlineQuerier.

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

Output Ports

Parameters

Join Mode

Join Mode

Specifies the type of join to perform.

Inner

An Inner join only includes complete joins - features from both Left and Right that have matched. Output is:

Joined: All pairs of Left and Right features that have matching values for the Join On keys, including attributes from both Left and Right matching features.

UnjoinedLeft: Left features that did not find a match.

UnjoinedRight: Right features that did not find a match.

Left

A Left join includes complete joins, plus Left features that did not find matches - that is, all Left features, joined or otherwise. Output is:

Joined: All pairs of Left and Right features that have matching values for the Join On keys, including attributes from both Left and Right matching features.

Additionally, unmatched Left features are output here. They will have the same attribute names added to them as the matched features, but with null values.

UnjoinedLeft: None

UnjoinedRight: Right features that did not find a match.

Full

A Full join includes complete joins, plus Left and Right features that did not find matches - that is, ALL features, joined or otherwise. Output is:

Joined: All pairs of Left and Right features that have matching values for the Join On keys, including attributes from both Left and Right matching features.

Additionally, unmatched Left and Right features are output here. They will have the same attribute names added to them as the matched features, but with null values.

UnjoinedLeft: None

UnjoinedRight: None

Note: To perform a Right join, reverse the Left and Right input connections and use the Left Join Mode.

Attribute Conflict Resolution

When a joined feature receives an attribute with the same name (or a common attribute) from both the left and right features, this specifies which value should be preferred for the Joined output.

Geometry Handling

Specifies what geometry will be used for Joined features.

Use Left: The geometry from the Left input will be used, and the geometry from the Right input will be discarded.

Use Right: The geometry from the Right input will be used, and the geometry from the Left input will be discarded.

Aggregate Left and Right (Enforce Unique Names): The geometry from both the Left and Right inputs will be preserved, and each geometry part will be given a unique name.

Output geometries will retain their original names if already unique.
Unnamed geometries will be named based on their input port (i.e. Left or Right).
Otherwise all geometries from input features will be preserved on Joined output features by renaming geometries to avoid conflicts.
The Right input port will be prepended to conflicting geometry names. The Left geometry names will remain unchanged.
If multiple name conflicts occur, an index will be appended to the name, starting at 2.

Geometry Aggregation Examples

Left Input Geometries	Right Input Geometries	Output Geometries
A	B	A B
Unnamed	Unnamed	Left Right
A	A	A Right_A
A Right_A	A	A Right_A Right_A2

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 - whether entered directly in a parameter or constructed using one of the editors.

Reference

Processing Behavior	Group-Based
Feature Holding	Yes
Dependencies	None
FME Licensing Level	FME Base Edition and above
Aliases
History
Categories	Filters and Joins

FME Knowledge Center

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Examples may contain information licensed under the Open Government Licence – Vancouver

Left	Select the attribute from the Left feature stream to be used as a key.
Right	Select the attribute from the Right feature stream to be used as a key.
Comparison Mode	Specifies how to perform the comparison between Left and Right attribute values. If Automatic or Numeric is specified, an attempt will be made to convert attribute values to numbers before comparing them.

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.
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.
Working with User Parameters	Create your own editable parameters.