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

POSThttps://api.datadoghq.com/api/v2/experiments/metric-sql-modelshttps://api.us3.datadoghq.com/api/v2/experiments/metric-sql-modelshttps://api.us5.datadoghq.com/api/v2/experiments/metric-sql-modelshttps://api.datadoghq.eu/api/v2/experiments/metric-sql-modelshttps://api.ap1.datadoghq.com/api/v2/experiments/metric-sql-modelshttps://api.ap2.datadoghq.com/api/v2/experiments/metric-sql-modelshttps://api.uk1.datadoghq.com/api/v2/experiments/metric-sql-modelshttps://api.ddog-gov.com/api/v2/experiments/metric-sql-modelshttps://api.us2.ddog-gov.com/api/v2/experiments/metric-sql-models

概要

Create a metric SQL model. Requires at least one subject type, whose subject_type_id must already exist for the organization (list them with GET /api/v2/experiments/subject-types). The model is created against the organization's warehouse connection, which is resolved server-side. Only customer-defined measures belong in measures. The response provides unique_subject_count_measure_id for each subject type and event_count_measure_id for use in metric aggregations. column_type is required for every measure and property. Certification is read-only and cannot be changed 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.

リクエスト

Body Data (required)

フィールド
タイプ
説明
data [required]
object

Metric SQL model resource to create.

応答

Created

Response containing the metric SQL model.

フィールド
タイプ
説明
data [required]
object

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

コード例

Create metric SQL model
# 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 POST "https://api.${DD_SITE}/api/v2/experiments/metric-sql-models" \
-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
# 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 POST "https://api.${DD_SITE}/api/v2/experiments/metric-sql-models" \
-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
# 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 POST "https://api.${DD_SITE}/api/v2/experiments/metric-sql-models" \
-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
# 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 POST "https://api.${DD_SITE}/api/v2/experiments/metric-sql-models" \
-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
# 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 POST "https://api.${DD_SITE}/api/v2/experiments/metric-sql-models" \
-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
# 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 POST "https://api.${DD_SITE}/api/v2/experiments/metric-sql-models" \
-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
# 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 POST "https://api.${DD_SITE}/api/v2/experiments/metric-sql-models" \
-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
# 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 POST "https://api.${DD_SITE}/api/v2/experiments/metric-sql-models" \
-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
# 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 POST "https://api.${DD_SITE}/api/v2/experiments/metric-sql-models" \
-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