For AI agents: A markdown version of this page is available at https://dnd37xeb23o8n.cloudfront.net/stefon.simmons/docs-astro-web-10435/fr/api/latest/experiments/update-metric-sql-model.md. A documentation index is available at /llms.txt.
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Update metric SQL model

PUThttps://api.datadoghq.com/api/v2/experiments/metric-sql-models/{metric_sql_model_id}https://api.us3.datadoghq.com/api/v2/experiments/metric-sql-models/{metric_sql_model_id}https://api.us5.datadoghq.com/api/v2/experiments/metric-sql-models/{metric_sql_model_id}https://api.datadoghq.eu/api/v2/experiments/metric-sql-models/{metric_sql_model_id}https://api.ap1.datadoghq.com/api/v2/experiments/metric-sql-models/{metric_sql_model_id}https://api.ap2.datadoghq.com/api/v2/experiments/metric-sql-models/{metric_sql_model_id}https://api.uk1.datadoghq.com/api/v2/experiments/metric-sql-models/{metric_sql_model_id}https://api.ddog-gov.com/api/v2/experiments/metric-sql-models/{metric_sql_model_id}https://api.us2.ddog-gov.com/api/v2/experiments/metric-sql-models/{metric_sql_model_id}

Présentation

Replace a metric SQL model. This is a destructive full replace: subject types, customer-defined measures, and properties absent from the body are deleted, so send the complete set. Properties are matched by name; changing a property's column, type, or description preserves its ID. column_type is required for every measure and property. Removing a measure or property that an active metric references returns 409 Conflict. Server-generated IDs returned by GET are read-only and can be left in a replayed body. The response reports removals in meta.deleted_subject_types, meta.deleted_measures, and meta.deleted_properties. Certification is read-only. Certified models cannot be replaced through this endpoint.

This endpoint requires the product_analytics_warehouse_model_write permission.

OAuth apps require the product_analytics_warehouse_model_write authorization scope to access this endpoint.

Arguments

Paramètres du chemin

Name
Type
Description
metric_sql_model_id [required]
string

The UUID of the metric SQL model.

Requête

Body Data (required)

Champ
Type
Description
data [required]
object

Metric SQL model resource to create.

Réponse

OK

Updated metric SQL model and its removed entries.

Champ
Type
Description
data [required]
object

JSON:API resource containing the metric SQL model identity and fields.

meta
object

Model entries removed by the update. Empty arrays mean no entries were removed.

Exemple de code

Update metric SQL model
# Path parameters
export metric_sql_model_id="550e8400-e29b-41d4-a716-446655440000"

# Set your Datadog site and credentials
export DD_SITE="datadoghq.com"
# Use a Personal Access Token or Service Access Token
export DD_BEARER_TOKEN="<PERSONAL_ACCESS_TOKEN OR SERVICE_ACCESS_TOKEN>"

curl -X PUT "https://api.${DD_SITE}/api/v2/experiments/metric-sql-models/${metric_sql_model_id}" \
-H "Accept: application/json" \
-H "Content-Type: application/json" \
-H "Authorization: Bearer ${DD_BEARER_TOKEN}" \
-d @- << EOF
{
  "data": {
    "attributes": {
      "date_partition_column": null,
      "description": null,
      "measures": [
        {
          "column_name": "revenue",
          "column_type": "FLOAT",
          "description": null,
          "name": null
        }
      ],
      "name": "Order facts",
      "sql": "SELECT user_id, order_id, item_type, revenue, created_at FROM analytics.orders",
      "subject_types": [
        {
          "column_name": "user_id",
          "subject_type_id": "550e8400-e29b-41d4-a716-446655440010"
        }
      ],
      "timestamp_column": "created_at"
    },
    "type": "metric-sql-models"
  }
}
EOF
# Path parameters
export metric_sql_model_id="550e8400-e29b-41d4-a716-446655440000"

# Set your Datadog site and credentials
export DD_SITE="us3.datadoghq.com"
# Use a Personal Access Token or Service Access Token
export DD_BEARER_TOKEN="<PERSONAL_ACCESS_TOKEN OR SERVICE_ACCESS_TOKEN>"

curl -X PUT "https://api.${DD_SITE}/api/v2/experiments/metric-sql-models/${metric_sql_model_id}" \
-H "Accept: application/json" \
-H "Content-Type: application/json" \
-H "Authorization: Bearer ${DD_BEARER_TOKEN}" \
-d @- << EOF
{
  "data": {
    "attributes": {
      "date_partition_column": null,
      "description": null,
      "measures": [
        {
          "column_name": "revenue",
          "column_type": "FLOAT",
          "description": null,
          "name": null
        }
      ],
      "name": "Order facts",
      "sql": "SELECT user_id, order_id, item_type, revenue, created_at FROM analytics.orders",
      "subject_types": [
        {
          "column_name": "user_id",
          "subject_type_id": "550e8400-e29b-41d4-a716-446655440010"
        }
      ],
      "timestamp_column": "created_at"
    },
    "type": "metric-sql-models"
  }
}
EOF
# Path parameters
export metric_sql_model_id="550e8400-e29b-41d4-a716-446655440000"

# Set your Datadog site and credentials
export DD_SITE="us5.datadoghq.com"
# Use a Personal Access Token or Service Access Token
export DD_BEARER_TOKEN="<PERSONAL_ACCESS_TOKEN OR SERVICE_ACCESS_TOKEN>"

curl -X PUT "https://api.${DD_SITE}/api/v2/experiments/metric-sql-models/${metric_sql_model_id}" \
-H "Accept: application/json" \
-H "Content-Type: application/json" \
-H "Authorization: Bearer ${DD_BEARER_TOKEN}" \
-d @- << EOF
{
  "data": {
    "attributes": {
      "date_partition_column": null,
      "description": null,
      "measures": [
        {
          "column_name": "revenue",
          "column_type": "FLOAT",
          "description": null,
          "name": null
        }
      ],
      "name": "Order facts",
      "sql": "SELECT user_id, order_id, item_type, revenue, created_at FROM analytics.orders",
      "subject_types": [
        {
          "column_name": "user_id",
          "subject_type_id": "550e8400-e29b-41d4-a716-446655440010"
        }
      ],
      "timestamp_column": "created_at"
    },
    "type": "metric-sql-models"
  }
}
EOF
# Path parameters
export metric_sql_model_id="550e8400-e29b-41d4-a716-446655440000"

# Set your Datadog site and credentials
export DD_SITE="datadoghq.eu"
# Use a Personal Access Token or Service Access Token
export DD_BEARER_TOKEN="<PERSONAL_ACCESS_TOKEN OR SERVICE_ACCESS_TOKEN>"

curl -X PUT "https://api.${DD_SITE}/api/v2/experiments/metric-sql-models/${metric_sql_model_id}" \
-H "Accept: application/json" \
-H "Content-Type: application/json" \
-H "Authorization: Bearer ${DD_BEARER_TOKEN}" \
-d @- << EOF
{
  "data": {
    "attributes": {
      "date_partition_column": null,
      "description": null,
      "measures": [
        {
          "column_name": "revenue",
          "column_type": "FLOAT",
          "description": null,
          "name": null
        }
      ],
      "name": "Order facts",
      "sql": "SELECT user_id, order_id, item_type, revenue, created_at FROM analytics.orders",
      "subject_types": [
        {
          "column_name": "user_id",
          "subject_type_id": "550e8400-e29b-41d4-a716-446655440010"
        }
      ],
      "timestamp_column": "created_at"
    },
    "type": "metric-sql-models"
  }
}
EOF
# Path parameters
export metric_sql_model_id="550e8400-e29b-41d4-a716-446655440000"

# Set your Datadog site and credentials
export DD_SITE="ap1.datadoghq.com"
# Use a Personal Access Token or Service Access Token
export DD_BEARER_TOKEN="<PERSONAL_ACCESS_TOKEN OR SERVICE_ACCESS_TOKEN>"

curl -X PUT "https://api.${DD_SITE}/api/v2/experiments/metric-sql-models/${metric_sql_model_id}" \
-H "Accept: application/json" \
-H "Content-Type: application/json" \
-H "Authorization: Bearer ${DD_BEARER_TOKEN}" \
-d @- << EOF
{
  "data": {
    "attributes": {
      "date_partition_column": null,
      "description": null,
      "measures": [
        {
          "column_name": "revenue",
          "column_type": "FLOAT",
          "description": null,
          "name": null
        }
      ],
      "name": "Order facts",
      "sql": "SELECT user_id, order_id, item_type, revenue, created_at FROM analytics.orders",
      "subject_types": [
        {
          "column_name": "user_id",
          "subject_type_id": "550e8400-e29b-41d4-a716-446655440010"
        }
      ],
      "timestamp_column": "created_at"
    },
    "type": "metric-sql-models"
  }
}
EOF
# Path parameters
export metric_sql_model_id="550e8400-e29b-41d4-a716-446655440000"

# Set your Datadog site and credentials
export DD_SITE="ap2.datadoghq.com"
# Use a Personal Access Token or Service Access Token
export DD_BEARER_TOKEN="<PERSONAL_ACCESS_TOKEN OR SERVICE_ACCESS_TOKEN>"

curl -X PUT "https://api.${DD_SITE}/api/v2/experiments/metric-sql-models/${metric_sql_model_id}" \
-H "Accept: application/json" \
-H "Content-Type: application/json" \
-H "Authorization: Bearer ${DD_BEARER_TOKEN}" \
-d @- << EOF
{
  "data": {
    "attributes": {
      "date_partition_column": null,
      "description": null,
      "measures": [
        {
          "column_name": "revenue",
          "column_type": "FLOAT",
          "description": null,
          "name": null
        }
      ],
      "name": "Order facts",
      "sql": "SELECT user_id, order_id, item_type, revenue, created_at FROM analytics.orders",
      "subject_types": [
        {
          "column_name": "user_id",
          "subject_type_id": "550e8400-e29b-41d4-a716-446655440010"
        }
      ],
      "timestamp_column": "created_at"
    },
    "type": "metric-sql-models"
  }
}
EOF
# Path parameters
export metric_sql_model_id="550e8400-e29b-41d4-a716-446655440000"

# Set your Datadog site and credentials
export DD_SITE="uk1.datadoghq.com"
# Use a Personal Access Token or Service Access Token
export DD_BEARER_TOKEN="<PERSONAL_ACCESS_TOKEN OR SERVICE_ACCESS_TOKEN>"

curl -X PUT "https://api.${DD_SITE}/api/v2/experiments/metric-sql-models/${metric_sql_model_id}" \
-H "Accept: application/json" \
-H "Content-Type: application/json" \
-H "Authorization: Bearer ${DD_BEARER_TOKEN}" \
-d @- << EOF
{
  "data": {
    "attributes": {
      "date_partition_column": null,
      "description": null,
      "measures": [
        {
          "column_name": "revenue",
          "column_type": "FLOAT",
          "description": null,
          "name": null
        }
      ],
      "name": "Order facts",
      "sql": "SELECT user_id, order_id, item_type, revenue, created_at FROM analytics.orders",
      "subject_types": [
        {
          "column_name": "user_id",
          "subject_type_id": "550e8400-e29b-41d4-a716-446655440010"
        }
      ],
      "timestamp_column": "created_at"
    },
    "type": "metric-sql-models"
  }
}
EOF
# Path parameters
export metric_sql_model_id="550e8400-e29b-41d4-a716-446655440000"

# Set your Datadog site and credentials
export DD_SITE="ddog-gov.com"
# Use a Personal Access Token or Service Access Token
export DD_BEARER_TOKEN="<PERSONAL_ACCESS_TOKEN OR SERVICE_ACCESS_TOKEN>"

curl -X PUT "https://api.${DD_SITE}/api/v2/experiments/metric-sql-models/${metric_sql_model_id}" \
-H "Accept: application/json" \
-H "Content-Type: application/json" \
-H "Authorization: Bearer ${DD_BEARER_TOKEN}" \
-d @- << EOF
{
  "data": {
    "attributes": {
      "date_partition_column": null,
      "description": null,
      "measures": [
        {
          "column_name": "revenue",
          "column_type": "FLOAT",
          "description": null,
          "name": null
        }
      ],
      "name": "Order facts",
      "sql": "SELECT user_id, order_id, item_type, revenue, created_at FROM analytics.orders",
      "subject_types": [
        {
          "column_name": "user_id",
          "subject_type_id": "550e8400-e29b-41d4-a716-446655440010"
        }
      ],
      "timestamp_column": "created_at"
    },
    "type": "metric-sql-models"
  }
}
EOF
# Path parameters
export metric_sql_model_id="550e8400-e29b-41d4-a716-446655440000"

# Set your Datadog site and credentials
export DD_SITE="us2.ddog-gov.com"
# Use a Personal Access Token or Service Access Token
export DD_BEARER_TOKEN="<PERSONAL_ACCESS_TOKEN OR SERVICE_ACCESS_TOKEN>"

curl -X PUT "https://api.${DD_SITE}/api/v2/experiments/metric-sql-models/${metric_sql_model_id}" \
-H "Accept: application/json" \
-H "Content-Type: application/json" \
-H "Authorization: Bearer ${DD_BEARER_TOKEN}" \
-d @- << EOF
{
  "data": {
    "attributes": {
      "date_partition_column": null,
      "description": null,
      "measures": [
        {
          "column_name": "revenue",
          "column_type": "FLOAT",
          "description": null,
          "name": null
        }
      ],
      "name": "Order facts",
      "sql": "SELECT user_id, order_id, item_type, revenue, created_at FROM analytics.orders",
      "subject_types": [
        {
          "column_name": "user_id",
          "subject_type_id": "550e8400-e29b-41d4-a716-446655440010"
        }
      ],
      "timestamp_column": "created_at"
    },
    "type": "metric-sql-models"
  }
}
EOF