> ## Documentation Index
> Fetch the complete documentation index at: https://docs.datris.ai/llms.txt
> Use this file to discover all available pages before exploring further.

# JSON/XML Schema Validation

> Validate data against JSON/XML schemas

Schema validation checks incoming JSON or XML files against a formal schema definition before processing. This catches structural issues, missing required fields, and type mismatches early in the pipeline.

## Requirements

* The source file must be JSON or XML format.
* The validation schema file must be stored in MinIO in the `{environment}-config` bucket under `validation-schema/{filename}`.

## Configuration

Set the `validationSchema` field in the `dataQuality` block to the filename of the schema. The pipeline resolves the file from the MinIO config bucket at `{environment}-config/validation-schema/{filename}`.

```json theme={null}
{
  "pipelineName": "product_catalog",
  "sourceFileFormat": "JSON",
  "dataQuality": {
    "validationSchema": "product_catalog_schema.json"
  }
}
```

## Example Schema

Validation uses the Everit `org.everit.json.schema` library (1.5.1), which implements **JSON Schema Draft 4 only**. The `$schema` URI is ignored, and Draft 07-only keywords (`const`, `if`/`then`/`else`, `propertyNames`, numeric `exclusiveMinimum`/`exclusiveMaximum` as values) are silently ignored rather than enforced. Write schemas to the Draft 4 specification.

A JSON Schema file stored in MinIO at `{environment}-config/validation-schema/product_catalog_schema.json`:

```json theme={null}
{
  "$schema": "http://json-schema.org/draft-04/schema#",
  "type": "object",
  "required": ["product_id", "name", "price"],
  "properties": {
    "product_id": {
      "type": "string",
      "pattern": "^PRD-[0-9]{6}$"
    },
    "name": {
      "type": "string",
      "minLength": 1
    },
    "price": {
      "type": "number",
      "minimum": 0
    },
    "tags": {
      "type": "array",
      "items": { "type": "string" }
    }
  }
}
```

## Behavior

1. The pipeline loads the schema file from the configured path in the environment's config bucket.
2. Each record in the source file is validated against the schema.
3. If any record fails validation, the file is rejected and processing stops.
4. Validation errors are logged with details about which fields failed and why.

## When to Use

Use schema validation when you need to enforce a strict contract on the structure of incoming JSON or XML data. This is particularly useful when data is provided by external systems where you do not control the format directly.