# Hierarchical Data

## Content

The `hierarchy` property in a table schema enables hierarchical (tree-structured) data modeling within a single table.
When hierarchy is configured:

* Records are organized into parent–child relationships.
* The table is interpreted as a tree instead of a flat list.
* The hierarchical structure is derived from record data.
* Stored data is not duplicated or transformed.

Hierarchy is a schema-level structural configuration.
It does not introduce cross-table relationships.

## Basic Structure

Hierarchy is defined in the table schema:

```typescript
interface ISchemaOption {
    hierarchy?: IHierarchyOption;
}
```

```typescript
interface IHierarchyOption {
    type: 'Parent' | 'ChildrenPath' | 'Level' | 'Custom';
    column: string;
    outlineColumn?: string | IHierarchyOutlineColumnOptions;
    summaryFields?: { [field: string]: string };
    parse?: (options) => any;
    unparse?: (options) => any;
}
```

The configuration specifies how parent–child relationships are derived from record fields.

## Supported Hierarchy Types

Hierarchy behavior depends on the `type` property.

### Parent Type

Records contain both:

* A primary key field
* A parent reference field

Example data:

```json
[
  { id: 1, parentId: -1 },
  { id: 2, parentId: -1 },
  { id: 3, parentId: 1 }
]
```

Configuration:

```javascript
schema: {
    hierarchy: {
        type: "Parent",
        column: "parentId"
    },
    columns: {
        id: { isPrimaryKey: true },
        parentId: {}
    }
}
```

The `column` identifies the field that references the parent record.
The primary key is required to uniquely identify nodes.

### Level Type

Hierarchy is determined by:

* A level indicator field
* The order of records

Example:

```json
[
  { name: "USA", level: -1 },
  { name: "Texas", level: 0 },
  { name: "Houston", level: 1 }
]
```

Configuration:

```javascript
hierarchy: {
    type: "Level",
    column: "level"
}
```

The level value determines the depth of each record relative to its neighbors.
A primary key is optional but recommended.

### ChildrenPath Type

Records contain nested child collections.
Example:

```json
[
  {
    name: "USA",
    children: [
      { name: "Texas" }
    ]
  }
]
```

Configuration:

```javascript
hierarchy: {
    type: "ChildrenPath",
    column: "children"
}
```

The `column` specifies the property that contains child records.

### Custom Type

Hierarchy is derived from a custom parsing rule.
Example:

```json
[
  { id: "1" },
  { id: "1.1" },
  { id: "1.1.1" }
]
```

Configuration:

```javascript
hierarchy: {
    type: "Custom",
    column: "id",
    parse: function (options) {
        const segments = options.data.id.split(".");
        return segments.slice(0, -1).join(".");
    }
}
```

The `parse` function derives the parent key from each record.
An optional `unparse` function can define how new keys are generated.

## Summary Fields

Hierarchy supports summary fields for parent records.

```javascript
hierarchy: {
    type: "Parent",
    column: "parentId",
    summaryFields: {
        budget: '=SUM(CHILDREN(1,"budget"))'
    }
}
```

Summary fields:

* Apply formulas to parent records
* Are evaluated only when a record has children
* Override editable behavior for summarized fields

These formulas are evaluated during calculation and do not alter stored child values.

## Outline Column

An outline column defines which column visually represents the tree structure when rendered in a compatible view.
It can be specified:

* In `hierarchy.outlineColumn`
* Or at column/view level

When both are defined:

* View-level configuration overrides schema-level settings.

Hierarchy configuration itself does not render UI.
It only provides structural metadata.

## Structural Constraints

Hierarchy modeling may require:

* A primary key (for `Parent` and often `Custom` types)
* A numeric `rowOrder` column for stable reordering (if supported by consuming views)

Hierarchy does not:

* Create cross-table relationships
* Modify remote synchronization semantics
* Duplicate records

It restructures how records are interpreted inside the table.

## Responsibility Boundary

Hierarchy is a schema-level data structure configuration.
It:

* Defines parent–child relationships within a single table
* Influences calculation context and structural interpretation
* Is consumed by views that support hierarchical rendering

View-specific operations (such as expand, collapse, or reordering) are documented separately.
This separation ensures that data structure and UI behavior remain decoupled.