Type Validation Error

Error message

{path}: {detail}; {path}: {detail}; ...

Examples:

price: mean is not compatible with type string
address: primitive config does not match schema type object
events.payload: property 'user_agent' not found in schema

When this error occurs

After the configuration passes structural validation (no duplicate stats, no mixed node types, etc.), the server validates it against the actual schema of the dataset or Rosetta Stone attributes. This error is raised when the configured statistics are incompatible with the field types in the schema. There are four categories of type validation errors:

1. Stat incompatible with field type

A statistic is requested on a column whose type does not support it. Type compatibility rules:

Stat	Compatible types
`value_count`, `null_value_count`, `completeness`	All types
`approx_count_distinct`, `count_distinct`	All types
`histogram`	All types
`mean`, `standard_deviation`	Numeric only (`long`, `double`)
`nan_value_count`	Numeric only (`long`, `double`)
`lower_bound`, `upper_bound`	Ordered types (`long`, `double`, `timestamp_tz`, `string`)

Example: requesting mean on a string column.

{
  "defaults": {
    "enabled_stats": ["value_count"]
  },
  "refresh": { "trigger": "manual" },
  "dataset": {
    "fields": [
      {
        "field_name": "country",
        "enabled_stats": ["value_count", "mean"]
      }
    ]
  }
}

If country is a string column in the dataset schema, the server returns:

country: mean is not compatible with type string

Fix: Remove mean and use stats compatible with strings:

{
  "field_name": "country",
  "enabled_stats": ["value_count", "approx_count_distinct"]
}

2. Shape mismatch between config and schema

The configuration structure does not match the field’s schema type. For example, using primitive config fields (enabled_stats) on an object column, or using non-primitive config fields (properties) on a string column. Example: treating an object column as a primitive.

{
  "defaults": {
    "enabled_stats": ["value_count"]
  },
  "refresh": { "trigger": "manual" },
  "dataset": {
    "fields": [
      {
        "field_name": "address",
        "enabled_stats": ["value_count", "histogram"]
      }
    ]
  }
}

If address is an object column (with children city, zip, state), the server returns:

address: primitive config does not match schema type object

Fix: Use non-primitive config for object columns:

{
  "field_name": "address",
  "self": {
    "enabled_stats": ["null_value_count"]
  },
  "properties": [
    {
      "path": "city",
      "enabled_stats": ["value_count", "histogram"]
    }
  ]
}

The reverse also applies — using object config on a primitive column:

{
  "field_name": "user_id",
  "properties": [
    {
      "path": "name",
      "enabled_stats": ["value_count"]
    }
  ]
}

If user_id is a string, the server returns:

user_id: object config does not match schema type string

3. Unknown property in schema

A property listed in the properties array does not exist in the object’s schema. Example: configuring a non-existent child property.

{
  "defaults": {
    "enabled_stats": ["value_count"]
  },
  "refresh": { "trigger": "manual" },
  "dataset": {
    "fields": [
      {
        "field_name": "address",
        "properties": [
          {
            "path": "city",
            "enabled_stats": ["value_count"]
          },
          {
            "path": "country",
            "enabled_stats": ["value_count"]
          }
        ]
      }
    ]
  }
}

If address has children city, zip, and state but no country, the server returns:

address.country: property 'country' not found in schema

Fix: Remove the property or correct the path to match the schema:

{
  "field_name": "address",
  "properties": [
    {
      "path": "city",
      "enabled_stats": ["value_count"]
    },
    {
      "path": "state",
      "enabled_stats": ["value_count"]
    }
  ]
}

4. Nested type incompatibility

For deeply nested structures (arrays of objects, objects containing arrays), the validation recurses into children. Errors report the full path. Example: requesting mean on a string property inside an array of objects. Consider a dataset with column events of type array<object<name: string, score: double>>.

{
  "defaults": {
    "enabled_stats": ["value_count"]
  },
  "refresh": { "trigger": "manual" },
  "dataset": {
    "fields": [
      {
        "field_name": "events",
        "self": {
          "enabled_stats": ["null_value_count"]
        },
        "items": {
          "properties": [
            {
              "path": "name",
              "enabled_stats": ["value_count", "mean"]
            },
            {
              "path": "score",
              "enabled_stats": ["value_count", "mean"]
            }
          ]
        }
      }
    ]
  }
}

The score field (double) supports mean, but name (string) does not. The server returns:

events.[].name: mean is not compatible with type string

Fix: Remove mean from the string property:

{
  "path": "name",
  "enabled_stats": ["value_count", "approx_count_distinct"]
}

5. Field not found in dataset schema

A field_name in the dataset.fields array does not match any column in the dataset.

{
  "defaults": {
    "enabled_stats": ["value_count"]
  },
  "refresh": { "trigger": "manual" },
  "dataset": {
    "fields": [
      {
        "field_name": "nonexistent_column",
        "enabled_stats": ["value_count"]
      }
    ]
  }
}

nonexistent_column: field 'nonexistent_column' not found in dataset schema

Fix: Verify the column name matches the dataset schema exactly. Column names are case-sensitive.

Multiple errors in one response

The validator reports all errors found, not just the first. Multiple errors are separated by semicolons:

price: mean is not compatible with type string; address: primitive config does not match schema type object; events.[].name: nan_value_count is not compatible with type string

Quick reference: common mistakes

Mistake	Error	Fix
`mean` on a string column	`mean is not compatible with type string`	Use `approx_count_distinct` or `histogram` instead
`nan_value_count` on a non-numeric column	`nan_value_count is not compatible with type boolean`	Remove — NaN only applies to floats
`lower_bound` on a boolean column	`lower_bound is not compatible with type boolean`	Remove — booleans have no meaningful ordering
Flat stats on an object column	`primitive config does not match schema type object`	Use `self` + `properties` instead of `enabled_stats`
Object config on a scalar column	`object config does not match schema type string`	Use `enabled_stats` directly
Non-existent property in `properties`	`property 'x' not found in schema`	Check the schema for correct property names
Non-existent field in `fields`	`field 'x' not found in dataset schema`	Check the dataset schema for correct column names

Mixed Primitive and Non-Primitive Configuration — structural mismatch caught before type validation
Unsupported Statistics for Container Node — self stats limited to null_value_count

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Error message

When this error occurs

1. Stat incompatible with field type

2. Shape mismatch between config and schema

3. Unknown property in schema

4. Nested type incompatibility

5. Field not found in dataset schema

Multiple errors in one response

Quick reference: common mistakes

​Error message

​When this error occurs

​1. Stat incompatible with field type

​2. Shape mismatch between config and schema

​3. Unknown property in schema

​4. Nested type incompatibility

​5. Field not found in dataset schema

​Multiple errors in one response

​Quick reference: common mistakes

​Related errors

Error message

When this error occurs

1. Stat incompatible with field type

2. Shape mismatch between config and schema

3. Unknown property in schema

4. Nested type incompatibility

5. Field not found in dataset schema

Multiple errors in one response

Quick reference: common mistakes

Related errors