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Filter

The Filter node keeps only the rows that match a field condition. It removes rows that do not match, reducing the dataset.

Configuration

PropertyTypeDefaultDescription
fieldstring--Required. The field name to test.
operatorstringeqThe comparison operator.
valuestring--The value to compare against (not used for empty and not_empty).

Operators

OperatorNameDescription
eqEqualsString equality: field == value
neqNot equalsString inequality: field != value
gtGreater thanNumeric comparison: field > value
ltLess thanNumeric comparison: field < value
gteGreater or equalNumeric comparison: field >= value
lteLess or equalNumeric comparison: field <= value
containsContainsSubstring match: field contains value
not_emptyNot emptyField is not null and not empty string
emptyEmptyField is null or empty string

Input

Accepts an array of rows.

Output

Returns a filtered array of rows containing only the rows where the condition is true. The output preserves the original row structure.

How It Works

The node iterates over each input row and evaluates the condition:

  • String operators (eq, neq, contains): Both the field value and comparison value are cast to strings.
  • Numeric operators (gt, lt, gte, lte): Both values are cast to floats.
  • Existence operators (empty, not_empty): Only check if the field is null or empty string.

Example Use Cases

Keep only active items

field: "status"
operator: "eq"
value: "active"

Filter high-value orders

field: "total"
operator: "gte"
value: "100"

Remove rows with missing emails

field: "email"
operator: "not_empty"

Search by keyword

field: "title"
operator: "contains"
value: "widget"

Chaining filters

Connect multiple Filter nodes in sequence for AND logic:

Table Query --> Filter (status = "active") --> Filter (price > 50) --> Result

TIP

For complex filtering with full expression support, use the If/Else node instead. The Filter node is simpler and faster for single-field conditions.

TIP

When possible, use the whereField / whereOp / whereValue options on source nodes (Table Query, Post Query) to filter at the database level. The Filter node operates on in-memory data, which is less efficient for large datasets.