Rules executor transform Icon Rules executor

Description

The Rules Executor allows fields of incoming rows to be executed against a rule set. This may be useful to determine additional information or route rows onto another transform.

Drools is the present rule engine implementation and its rule language can be referenced for use by this transform. Drools documentation

Supported Engines

Hop Engine

Supported

Spark

Maybe Supported

Flink

Maybe Supported

Dataflow

Maybe Supported

Details

For each row processed by the Rules Executor transform each column is converted to a Rules.Column then injected into the rule engine and executed against the rules set. Rules.Column contains four properties:

externalSource: boolean property indicating if this Rules.Column was injected from an external source (a field from a processed row)

name: name of this field

type: type of data stored in payload (one of ValueMetaInterface.typeCodes - Number, String, Integer, Date, Boolean, etc…​)

payload: value of this field

Results are generated by creating Rules.Column objects. The transform is configured to pick up these generated objects by name.

Rules Tab

The Rules tab is where you enter your rule definition or a reference to the rule file..

Option Description

Rules filename

Rules script to execute

Rules result Tab

Rules result tab defines the layout of the Rules output fields.

Option Description

Result column name

Result column type

Example

All Rule Definitions should contain "import org.apache.hop.pipeline.transforms.drools.Rules.Column;" to give access to the Rules.Column class.

For the input row: fica_seed (Integer), hi (String), fica (Integer); three Rules.Column objects will be created in the Rules Engine:

Rules.Row→row (Map) Type Payload

fica_seed

Integer

-3561151667

hi

String

test

fica

Integer

bad

Rules can be defined and applied:

rule "Decline"
    dialect "mvel"
    when
        $fica : Column(name == "fica", payload < 550)

    then
        Column approvalStatus = new Column();
        approvalStatus.name = "approvalStatus"
        approvalStatus.type = String.class
        approvalStatus.payload = "declined"

        Column approvalClassification = new Column();
        approvalClassification.name = "approvalClass"
        approvalClassification.type = String.class
        approvalClassification.payload = "Declined: fica too low"

        insert(approvalStatus);
        insert(approvalClassification);

        System.out.println("Declined");
end

Rules.Column properties can be checked as in the above’s left hand side.

Rules.Column objects can be created for pickup as in the above’s right hand side.

The transform can be told to pickup a generated Rules.Column object by defining the Rules.Column name in the transform’s Results tab. Type conversions can be applied by setting the Result column type as well.