Rule Splitter

The Rule Splitter Component is used to divide datasets into smaller, more manageable subsets based on user-defined conditions. This enables targeted downstream processing, such as filtering customer records by demographics, segmenting transactions by value, or routing events by conditional logic.

Key Capabilities

• Split incoming data into 1–7 subsets.

• Define rule-based conditions on columns to control how records are distributed.

• Supports multiple comparison operators including BETWEEN and LIKE.

• Automatically maps outputs to events for easy pipeline integration.

Configuration Overview

All Rule Splitter configurations are organized into the following sections:

• Basic Information

• Meta Information

• Resource Configuration

Configuring Meta Information

Number of Outputs

• Specify the total number of data subsets to create (range: 1–7).

Event Relation

• Out Event: Automatically mapped based on the number of outputs selected.

• Ensure the component is connected to the same number of downstream events as the configured outputs.

Conditions

Define the rules used to split the data. Each rule consists of the following fields:

• Column Name – The input column on which the condition will be applied.

• Condition – Select a condition from the supported list:

  • > (Greater than)

  • < (Less than)

  • >= (Greater than or equal to)

  • <= (Less than or equal to)

  • == (Equal to)

  • != (Not equal to)

  • BETWEEN (Within a range)

  • LIKE (Pattern matching, e.g., text contains)

• Value – The reference value or range for comparison.

• Datatype – Specify the datatype of the column (e.g., String, Integer, Date).

Rule Condition

• When multiple column conditions are defined, select how they should be combined:

  • AND – All conditions must be true.

  • OR – Any one of the conditions must be true.

Usage Notes

• The Copy/Paste option is disabled for the Rule Splitter Component.

  • You cannot duplicate the component inside a pipeline.

  • Create new instances manually if multiple Rule Splitters are required.

Example Use Cases

• Split customer transactions into high-value (>1000) and low-value (<=1000) subsets.

• Separate records by region using the LIKE condition (e.g., "Region LIKE 'US%'").

• Segment orders by date range with the BETWEEN operator.