Reference Tables

View and manage Reference Tables in your organization.

POST https://api.ap1.datadoghq.com/api/v2/reference-tables/uploadshttps://api.ap2.datadoghq.com/api/v2/reference-tables/uploadshttps://api.datadoghq.eu/api/v2/reference-tables/uploadshttps://api.ddog-gov.com/api/v2/reference-tables/uploadshttps://api.datadoghq.com/api/v2/reference-tables/uploadshttps://api.us3.datadoghq.com/api/v2/reference-tables/uploadshttps://api.us5.datadoghq.com/api/v2/reference-tables/uploads

개요

Create a reference table upload for bulk data ingestion

요청

Body Data (required)

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항목

유형

설명

data

object

Request data for creating an upload for a file to be ingested into a reference table.

attributes

object

Upload configuration specifying how data is uploaded by the user, and properties of the table to associate the upload with.

headers [required]

[string]

The CSV file headers that define the schema fields, provided in the same order as the columns in the uploaded file.

part_count [required]

int32

Number of parts to split the file into for multipart upload.

part_size [required]

int64

The size of each part in the upload in bytes. All parts except the last one must be at least 5,000,000 bytes.

table_name [required]

string

Name of the table to associate with this upload.

type [required]

enum

Upload resource type. Allowed enum values: upload

default: upload

{
  "data": {
    "attributes": {
      "headers": [
        "field_1",
        "field_2"
      ],
      "part_count": 3,
      "part_size": 10000000,
      "table_name": ""
    },
    "type": "upload"
  }
}

응답

Created

Information about the upload created containing the upload ID and pre-signed URLs to PUT chunks of the CSV file to.

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항목

유형

설명

data

object

Upload ID and attributes of the created upload.

attributes

object

Pre-signed URLs for uploading parts of the file.

part_urls

[string]

The pre-signed URLs for uploading parts. These URLs expire after 5 minutes.

id

string

Unique identifier for this upload. Use this ID when creating the reference table.

type [required]

enum

Upload resource type. Allowed enum values: upload

default: upload

{
  "data": {
    "attributes": {
      "part_urls": []
    },
    "id": "string",
    "type": "upload"
  }
}

Bad Request

API error response.

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항목

유형

설명

errors [required]

[string]

A list of errors.

{
  "errors": [
    "Bad Request"
  ]
}

Forbidden

API error response.

Expand All

항목

유형

설명

errors [required]

[string]

A list of errors.

{
  "errors": [
    "Bad Request"
  ]
}

Too many requests

API error response.

Expand All

항목

유형

설명

errors [required]

[string]

A list of errors.

{
  "errors": [
    "Bad Request"
  ]
}

코드 사례

                  # Curl command
curl -X POST "https://api.ap1.datadoghq.com"https://api.ap2.datadoghq.com"https://api.datadoghq.eu"https://api.ddog-gov.com"https://api.datadoghq.com"https://api.us3.datadoghq.com"https://api.us5.datadoghq.com/api/v2/reference-tables/uploads" \ -H "Accept: application/json" \ -H "Content-Type: application/json" \ -H "DD-API-KEY: ${DD_API_KEY}" \ -H "DD-APPLICATION-KEY: ${DD_APP_KEY}" \ -d @- << EOF { "data": { "attributes": { "headers": [ "field_1", "field_2" ], "part_count": 3, "part_size": 10000000, "table_name": "" }, "type": "upload" } } EOF
"""
Create reference table upload returns "Created" response
"""

from datadog_api_client import ApiClient, Configuration
from datadog_api_client.v2.api.reference_tables_api import ReferenceTablesApi
from datadog_api_client.v2.model.create_upload_request import CreateUploadRequest
from datadog_api_client.v2.model.create_upload_request_data import CreateUploadRequestData
from datadog_api_client.v2.model.create_upload_request_data_attributes import CreateUploadRequestDataAttributes
from datadog_api_client.v2.model.create_upload_request_data_type import CreateUploadRequestDataType

body = CreateUploadRequest(
    data=CreateUploadRequestData(
        attributes=CreateUploadRequestDataAttributes(
            headers=[
                "id",
                "name",
                "value",
            ],
            table_name="test_upload_table_Example-Reference-Table",
            part_count=1,
            part_size=1024,
        ),
        type=CreateUploadRequestDataType.UPLOAD,
    ),
)

configuration = Configuration()
with ApiClient(configuration) as api_client:
    api_instance = ReferenceTablesApi(api_client)
    response = api_instance.create_reference_table_upload(body=body)

    print(response)

Instructions

First install the library and its dependencies and then save the example to example.py and run following commands:

    
DD_SITE="datadoghq.comus3.datadoghq.comus5.datadoghq.comdatadoghq.euap1.datadoghq.comap2.datadoghq.comddog-gov.com" DD_API_KEY="<DD_API_KEY>" DD_APP_KEY="<DD_APP_KEY>" python3 "example.py"
# Create reference table upload returns "Created" response

require "datadog_api_client"
api_instance = DatadogAPIClient::V2::ReferenceTablesAPI.new

body = DatadogAPIClient::V2::CreateUploadRequest.new({
  data: DatadogAPIClient::V2::CreateUploadRequestData.new({
    attributes: DatadogAPIClient::V2::CreateUploadRequestDataAttributes.new({
      headers: [
        "id",
        "name",
        "value",
      ],
      table_name: "test_upload_table_Example-Reference-Table",
      part_count: 1,
      part_size: 1024,
    }),
    type: DatadogAPIClient::V2::CreateUploadRequestDataType::UPLOAD,
  }),
})
p api_instance.create_reference_table_upload(body)

Instructions

First install the library and its dependencies and then save the example to example.rb and run following commands:

    
DD_SITE="datadoghq.comus3.datadoghq.comus5.datadoghq.comdatadoghq.euap1.datadoghq.comap2.datadoghq.comddog-gov.com" DD_API_KEY="<DD_API_KEY>" DD_APP_KEY="<DD_APP_KEY>" rb "example.rb"
// Create reference table upload returns "Created" response

package main

import (
	"context"
	"encoding/json"
	"fmt"
	"os"

	"github.com/DataDog/datadog-api-client-go/v2/api/datadog"
	"github.com/DataDog/datadog-api-client-go/v2/api/datadogV2"
)

func main() {
	body := datadogV2.CreateUploadRequest{
		Data: &datadogV2.CreateUploadRequestData{
			Attributes: &datadogV2.CreateUploadRequestDataAttributes{
				Headers: []string{
					"id",
					"name",
					"value",
				},
				TableName: "test_upload_table_Example-Reference-Table",
				PartCount: 1,
				PartSize:  1024,
			},
			Type: datadogV2.CREATEUPLOADREQUESTDATATYPE_UPLOAD,
		},
	}
	ctx := datadog.NewDefaultContext(context.Background())
	configuration := datadog.NewConfiguration()
	apiClient := datadog.NewAPIClient(configuration)
	api := datadogV2.NewReferenceTablesApi(apiClient)
	resp, r, err := api.CreateReferenceTableUpload(ctx, body)

	if err != nil {
		fmt.Fprintf(os.Stderr, "Error when calling `ReferenceTablesApi.CreateReferenceTableUpload`: %v\n", err)
		fmt.Fprintf(os.Stderr, "Full HTTP response: %v\n", r)
	}

	responseContent, _ := json.MarshalIndent(resp, "", "  ")
	fmt.Fprintf(os.Stdout, "Response from `ReferenceTablesApi.CreateReferenceTableUpload`:\n%s\n", responseContent)
}

Instructions

First install the library and its dependencies and then save the example to main.go and run following commands:

    
DD_SITE="datadoghq.comus3.datadoghq.comus5.datadoghq.comdatadoghq.euap1.datadoghq.comap2.datadoghq.comddog-gov.com" DD_API_KEY="<DD_API_KEY>" DD_APP_KEY="<DD_APP_KEY>" go run "main.go"
// Create reference table upload returns "Created" response

import com.datadog.api.client.ApiClient;
import com.datadog.api.client.ApiException;
import com.datadog.api.client.v2.api.ReferenceTablesApi;
import com.datadog.api.client.v2.model.CreateUploadRequest;
import com.datadog.api.client.v2.model.CreateUploadRequestData;
import com.datadog.api.client.v2.model.CreateUploadRequestDataAttributes;
import com.datadog.api.client.v2.model.CreateUploadRequestDataType;
import com.datadog.api.client.v2.model.CreateUploadResponse;
import java.util.Arrays;

public class Example {
  public static void main(String[] args) {
    ApiClient defaultClient = ApiClient.getDefaultApiClient();
    ReferenceTablesApi apiInstance = new ReferenceTablesApi(defaultClient);

    CreateUploadRequest body =
        new CreateUploadRequest()
            .data(
                new CreateUploadRequestData()
                    .attributes(
                        new CreateUploadRequestDataAttributes()
                            .headers(Arrays.asList("id", "name", "value"))
                            .tableName("test_upload_table_Example-Reference-Table")
                            .partCount(1)
                            .partSize(1024L))
                    .type(CreateUploadRequestDataType.UPLOAD));

    try {
      CreateUploadResponse result = apiInstance.createReferenceTableUpload(body);
      System.out.println(result);
    } catch (ApiException e) {
      System.err.println("Exception when calling ReferenceTablesApi#createReferenceTableUpload");
      System.err.println("Status code: " + e.getCode());
      System.err.println("Reason: " + e.getResponseBody());
      System.err.println("Response headers: " + e.getResponseHeaders());
      e.printStackTrace();
    }
  }
}

Instructions

First install the library and its dependencies and then save the example to Example.java and run following commands:

    
DD_SITE="datadoghq.comus3.datadoghq.comus5.datadoghq.comdatadoghq.euap1.datadoghq.comap2.datadoghq.comddog-gov.com" DD_API_KEY="<DD_API_KEY>" DD_APP_KEY="<DD_APP_KEY>" java "Example.java"
// Create reference table upload returns "Created" response
use datadog_api_client::datadog;
use datadog_api_client::datadogV2::api_reference_tables::ReferenceTablesAPI;
use datadog_api_client::datadogV2::model::CreateUploadRequest;
use datadog_api_client::datadogV2::model::CreateUploadRequestData;
use datadog_api_client::datadogV2::model::CreateUploadRequestDataAttributes;
use datadog_api_client::datadogV2::model::CreateUploadRequestDataType;

#[tokio::main]
async fn main() {
    let body = CreateUploadRequest::new().data(
        CreateUploadRequestData::new(CreateUploadRequestDataType::UPLOAD).attributes(
            CreateUploadRequestDataAttributes::new(
                vec!["id".to_string(), "name".to_string(), "value".to_string()],
                1,
                1024,
                "test_upload_table_Example-Reference-Table".to_string(),
            ),
        ),
    );
    let configuration = datadog::Configuration::new();
    let api = ReferenceTablesAPI::with_config(configuration);
    let resp = api.create_reference_table_upload(body).await;
    if let Ok(value) = resp {
        println!("{:#?}", value);
    } else {
        println!("{:#?}", resp.unwrap_err());
    }
}

Instructions

First install the library and its dependencies and then save the example to src/main.rs and run following commands:

    
DD_SITE="datadoghq.comus3.datadoghq.comus5.datadoghq.comdatadoghq.euap1.datadoghq.comap2.datadoghq.comddog-gov.com" DD_API_KEY="<DD_API_KEY>" DD_APP_KEY="<DD_APP_KEY>" cargo run
/**
 * Create reference table upload returns "Created" response
 */

import { client, v2 } from "@datadog/datadog-api-client";

const configuration = client.createConfiguration();
const apiInstance = new v2.ReferenceTablesApi(configuration);

const params: v2.ReferenceTablesApiCreateReferenceTableUploadRequest = {
  body: {
    data: {
      attributes: {
        headers: ["id", "name", "value"],
        tableName: "test_upload_table_Example-Reference-Table",
        partCount: 1,
        partSize: 1024,
      },
      type: "upload",
    },
  },
};

apiInstance
  .createReferenceTableUpload(params)
  .then((data: v2.CreateUploadResponse) => {
    console.log(
      "API called successfully. Returned data: " + JSON.stringify(data)
    );
  })
  .catch((error: any) => console.error(error));

Instructions

First install the library and its dependencies and then save the example to example.ts and run following commands:

    
DD_SITE="datadoghq.comus3.datadoghq.comus5.datadoghq.comdatadoghq.euap1.datadoghq.comap2.datadoghq.comddog-gov.com" DD_API_KEY="<DD_API_KEY>" DD_APP_KEY="<DD_APP_KEY>" tsc "example.ts"

POST https://api.ap1.datadoghq.com/api/v2/reference-tables/tableshttps://api.ap2.datadoghq.com/api/v2/reference-tables/tableshttps://api.datadoghq.eu/api/v2/reference-tables/tableshttps://api.ddog-gov.com/api/v2/reference-tables/tableshttps://api.datadoghq.com/api/v2/reference-tables/tableshttps://api.us3.datadoghq.com/api/v2/reference-tables/tableshttps://api.us5.datadoghq.com/api/v2/reference-tables/tables

개요

Creates a reference table. You can provide data in two ways:

  1. Call POST /api/v2/reference-tables/upload to get an upload ID. Then, PUT the CSV data (not the file itself) in chunks to each URL in the request body. Finally, call this POST endpoint with upload_id in file_metadata.
  2. Provide access_details in file_metadata pointing to a CSV file in cloud storage.

요청

Body Data (required)

Expand All

항목

유형

설명

data

object

The data object containing the table definition.

attributes

object

Attributes that define the reference table's configuration and properties.

description

string

Optional text describing the purpose or contents of this reference table.

file_metadata

 <oneOf>

Metadata specifying where and how to access the reference table's data file.

Option 1

object

Cloud storage file metadata for create requests. Both access_details and sync_enabled are required.

access_details [required]

object

Cloud storage access configuration for the reference table data file.

aws_detail

object

Amazon Web Services S3 storage access configuration.

aws_account_id [required]

string

AWS account ID where the S3 bucket is located.

aws_bucket_name [required]

string

S3 bucket containing the CSV file.

file_path [required]

string

The relative file path from the S3 bucket root to the CSV file.

azure_detail

object

Azure Blob Storage access configuration.

azure_client_id [required]

string

Azure service principal (application) client ID with permissions to read from the container.

azure_container_name [required]

string

Azure Blob Storage container containing the CSV file.

azure_storage_account_name [required]

string

Azure storage account where the container is located.

azure_tenant_id [required]

string

Azure Active Directory tenant ID.

file_path [required]

string

The relative file path from the Azure container root to the CSV file.

gcp_detail

object

Google Cloud Platform storage access configuration.

file_path [required]

string

The relative file path from the GCS bucket root to the CSV file.

gcp_bucket_name [required]

string

GCP bucket containing the CSV file.

gcp_project_id [required]

string

GCP project ID where the bucket is located.

gcp_service_account_email [required]

string

Service account email with read permissions for the GCS bucket.

sync_enabled [required]

boolean

Whether this table is synced automatically.

Option 2

object

Local file metadata for create requests using the upload ID.

upload_id [required]

string

The upload ID.

schema [required]

object

Schema defining the structure and columns of the reference table.

fields [required]

[object]

The schema fields.

name [required]

string

The field name.

type [required]

enum

The field type for reference table schema fields. Allowed enum values: STRING,INT32

primary_keys [required]

[string]

List of field names that serve as primary keys for the table. Only one primary key is supported, and it is used as an ID to retrieve rows.

source [required]

enum

The source type for creating reference table data. Only these source types can be created through this API. Allowed enum values: LOCAL_FILE,S3,GCS,AZURE

table_name [required]

string

Name to identify this reference table.

tags

[string]

Tags for organizing and filtering reference tables.

type [required]

enum

Reference table resource type. Allowed enum values: reference_table

default: reference_table

{
  "data": {
    "attributes": {
      "description": "string",
      "file_metadata": {
        "access_details": {
          "aws_detail": {
            "aws_account_id": "123456789000",
            "aws_bucket_name": "example-data-bucket",
            "file_path": "reference-tables/users.csv"
          },
          "azure_detail": {
            "azure_client_id": "aaaaaaaa-1111-2222-3333-bbbbbbbbbbbb",
            "azure_container_name": "reference-data",
            "azure_storage_account_name": "examplestorageaccount",
            "azure_tenant_id": "cccccccc-4444-5555-6666-dddddddddddd",
            "file_path": "tables/users.csv"
          },
          "gcp_detail": {
            "file_path": "data/reference_tables/users.csv",
            "gcp_bucket_name": "example-data-bucket",
            "gcp_project_id": "example-gcp-project-12345",
            "gcp_service_account_email": "example-service@example-gcp-project-12345.iam.gserviceaccount.com"
          }
        },
        "sync_enabled": false
      },
      "schema": {
        "fields": [
          {
            "name": "field_1",
            "type": "STRING"
          }
        ],
        "primary_keys": [
          "field_1"
        ]
      },
      "source": "LOCAL_FILE",
      "table_name": "table_1",
      "tags": [
        "tag_1",
        "tag_2"
      ]
    },
    "type": "reference_table"
  }
}

응답

Created

A reference table resource containing its full configuration and state.

Expand All

항목

유형

설명

data

object

The data object containing the reference table configuration and state.

attributes

object

Attributes that define the reference table's configuration and properties.

created_by

string

UUID of the user who created the reference table.

description

string

Optional text describing the purpose or contents of this reference table.

file_metadata

object

Metadata specifying where and how to access the reference table's data file.

For cloud storage tables (S3/GCS/Azure):

  • sync_enabled and access_details will always be present
  • error fields (error_message, error_row_count, error_type) are present only when errors occur

For local file tables:

  • error fields (error_message, error_row_count) are present only when errors occur
  • sync_enabled, access_details are never present

access_details

object

Cloud storage access configuration. Only present for cloud storage sources (S3, GCS, Azure).

aws_detail

object

Amazon Web Services S3 storage access configuration.

aws_account_id

string

AWS account ID where the S3 bucket is located.

aws_bucket_name

string

S3 bucket containing the CSV file.

file_path

string

The relative file path from the S3 bucket root to the CSV file.

azure_detail

object

Azure Blob Storage access configuration.

azure_client_id

string

Azure service principal (application) client ID with permissions to read from the container.

azure_container_name

string

Azure Blob Storage container containing the CSV file.

azure_storage_account_name

string

Azure storage account where the container is located.

azure_tenant_id

string

Azure Active Directory tenant ID.

file_path

string

The relative file path from the Azure container root to the CSV file.

gcp_detail

object

Google Cloud Platform storage access configuration.

file_path

string

The relative file path from the GCS bucket root to the CSV file.

gcp_bucket_name

string

GCP bucket containing the CSV file.

gcp_project_id

string

GCP project ID where the bucket is located.

gcp_service_account_email

string

Service account email with read permissions for the GCS bucket.

error_message

string

The error message returned from the last operation (sync for cloud storage, upload for local file).

error_row_count

int64

The number of rows that failed to process.

error_type

enum

The type of error that occurred during file processing. Only applicable for cloud storage sources. Allowed enum values: TABLE_SCHEMA_ERROR,FILE_FORMAT_ERROR,CONFIGURATION_ERROR,QUOTA_EXCEEDED,CONFLICT_ERROR,VALIDATION_ERROR,STATE_ERROR,OPERATION_ERROR,SYSTEM_ERROR

sync_enabled

boolean

Whether this table is synced automatically from cloud storage. Only applicable for cloud storage sources.

last_updated_by

string

UUID of the user who last updated the reference table.

row_count

int64

The number of successfully processed rows in the reference table.

schema

object

Schema defining the structure and columns of the reference table.

fields [required]

[object]

The schema fields.

name [required]

string

The field name.

type [required]

enum

The field type for reference table schema fields. Allowed enum values: STRING,INT32

primary_keys [required]

[string]

List of field names that serve as primary keys for the table. Only one primary key is supported, and it is used as an ID to retrieve rows.

source

enum

The source type for reference table data. Includes all possible source types that can appear in responses. Allowed enum values: LOCAL_FILE,S3,GCS,AZURE,SERVICENOW,SALESFORCE,DATABRICKS,SNOWFLAKE

status

string

The processing status of the table.

table_name

string

Unique name to identify this reference table. Used in enrichment processors and API calls.

tags

[string]

Tags for organizing and filtering reference tables.

updated_at

string

When the reference table was last updated, in ISO 8601 format.

id

string

Unique identifier for the reference table.

type [required]

enum

Reference table resource type. Allowed enum values: reference_table

default: reference_table

{
  "data": {
    "attributes": {
      "created_by": "00000000-0000-0000-0000-000000000000",
      "description": "example description",
      "file_metadata": {
        "access_details": {
          "aws_detail": {
            "aws_account_id": "123456789000",
            "aws_bucket_name": "my-bucket",
            "file_path": "path/to/file.csv"
          }
        },
        "sync_enabled": true
      },
      "last_updated_by": "00000000-0000-0000-0000-000000000000",
      "row_count": 5,
      "schema": {
        "fields": [
          {
            "name": "id",
            "type": "INT32"
          },
          {
            "name": "name",
            "type": "STRING"
          }
        ],
        "primary_keys": [
          "id"
        ]
      },
      "source": "S3",
      "status": "DONE",
      "table_name": "test_reference_table",
      "tags": [
        "tag1",
        "tag2"
      ],
      "updated_at": "2000-01-01T01:00:00+00:00"
    },
    "id": "00000000-0000-0000-0000-000000000000",
    "type": "reference_table"
  }
}

Bad Request

API error response.

Expand All

항목

유형

설명

errors [required]

[string]

A list of errors.

{
  "errors": [
    "Bad Request"
  ]
}

Forbidden

API error response.

Expand All

항목

유형

설명

errors [required]

[string]

A list of errors.

{
  "errors": [
    "Bad Request"
  ]
}

Too many requests

API error response.

Expand All

항목

유형

설명

errors [required]

[string]

A list of errors.

{
  "errors": [
    "Bad Request"
  ]
}

코드 사례

                  ## Create table from cloud storage (S3)
# 

# Curl command
curl -X POST "https://api.ap1.datadoghq.com"https://api.ap2.datadoghq.com"https://api.datadoghq.eu"https://api.ddog-gov.com"https://api.datadoghq.com"https://api.us3.datadoghq.com"https://api.us5.datadoghq.com/api/v2/reference-tables/tables" \ -H "Accept: application/json" \ -H "Content-Type: application/json" \ -H "DD-API-KEY: ${DD_API_KEY}" \ -H "DD-APPLICATION-KEY: ${DD_APP_KEY}" \ -d @- << EOF { "data": { "attributes": { "description": "Customer reference data synced from S3", "file_metadata": { "access_details": { "aws_detail": { "aws_account_id": "924305315327", "aws_bucket_name": "my-data-bucket", "file_path": "customers.csv" } }, "sync_enabled": true }, "schema": { "fields": [ { "name": "customer_id", "type": "STRING" }, { "name": "customer_name", "type": "STRING" }, { "name": "email", "type": "STRING" } ], "primary_keys": [ "customer_id" ] }, "source": "S3", "table_name": "customer_reference_data", "tags": [ "team:data-platform" ] }, "type": "reference_table" } } EOF
## Create table from local file upload #
# Curl command
curl -X POST "https://api.ap1.datadoghq.com"https://api.ap2.datadoghq.com"https://api.datadoghq.eu"https://api.ddog-gov.com"https://api.datadoghq.com"https://api.us3.datadoghq.com"https://api.us5.datadoghq.com/api/v2/reference-tables/tables" \ -H "Accept: application/json" \ -H "Content-Type: application/json" \ -H "DD-API-KEY: ${DD_API_KEY}" \ -H "DD-APPLICATION-KEY: ${DD_APP_KEY}" \ -d @- << EOF { "data": { "attributes": { "description": "Product catalog uploaded via local file", "file_metadata": { "upload_id": "00000000-0000-0000-0000-000000000000" }, "schema": { "fields": [ { "name": "product_id", "type": "STRING" }, { "name": "product_name", "type": "STRING" }, { "name": "price", "type": "DOUBLE" } ], "primary_keys": [ "product_id" ] }, "source": "LOCAL_FILE", "table_name": "product_catalog", "tags": [ "team:ecommerce" ] }, "type": "reference_table" } } EOF
"""
Create reference table returns "Created" response
"""

from datadog_api_client import ApiClient, Configuration
from datadog_api_client.v2.api.reference_tables_api import ReferenceTablesApi
from datadog_api_client.v2.model.create_table_request import CreateTableRequest
from datadog_api_client.v2.model.create_table_request_data import CreateTableRequestData
from datadog_api_client.v2.model.create_table_request_data_attributes import CreateTableRequestDataAttributes
from datadog_api_client.v2.model.create_table_request_data_attributes_file_metadata_cloud_storage import (
    CreateTableRequestDataAttributesFileMetadataCloudStorage,
)
from datadog_api_client.v2.model.create_table_request_data_attributes_file_metadata_one_of_access_details import (
    CreateTableRequestDataAttributesFileMetadataOneOfAccessDetails,
)
from datadog_api_client.v2.model.create_table_request_data_attributes_file_metadata_one_of_access_details_aws_detail import (
    CreateTableRequestDataAttributesFileMetadataOneOfAccessDetailsAwsDetail,
)
from datadog_api_client.v2.model.create_table_request_data_attributes_file_metadata_one_of_access_details_azure_detail import (
    CreateTableRequestDataAttributesFileMetadataOneOfAccessDetailsAzureDetail,
)
from datadog_api_client.v2.model.create_table_request_data_attributes_file_metadata_one_of_access_details_gcp_detail import (
    CreateTableRequestDataAttributesFileMetadataOneOfAccessDetailsGcpDetail,
)
from datadog_api_client.v2.model.create_table_request_data_attributes_schema import (
    CreateTableRequestDataAttributesSchema,
)
from datadog_api_client.v2.model.create_table_request_data_attributes_schema_fields_items import (
    CreateTableRequestDataAttributesSchemaFieldsItems,
)
from datadog_api_client.v2.model.create_table_request_data_type import CreateTableRequestDataType
from datadog_api_client.v2.model.reference_table_create_source_type import ReferenceTableCreateSourceType
from datadog_api_client.v2.model.reference_table_schema_field_type import ReferenceTableSchemaFieldType

body = CreateTableRequest(
    data=CreateTableRequestData(
        attributes=CreateTableRequestDataAttributes(
            file_metadata=CreateTableRequestDataAttributesFileMetadataCloudStorage(
                access_details=CreateTableRequestDataAttributesFileMetadataOneOfAccessDetails(
                    aws_detail=CreateTableRequestDataAttributesFileMetadataOneOfAccessDetailsAwsDetail(
                        aws_account_id="123456789000",
                        aws_bucket_name="example-data-bucket",
                        file_path="reference-tables/users.csv",
                    ),
                    azure_detail=CreateTableRequestDataAttributesFileMetadataOneOfAccessDetailsAzureDetail(
                        azure_client_id="aaaaaaaa-1111-2222-3333-bbbbbbbbbbbb",
                        azure_container_name="reference-data",
                        azure_storage_account_name="examplestorageaccount",
                        azure_tenant_id="cccccccc-4444-5555-6666-dddddddddddd",
                        file_path="tables/users.csv",
                    ),
                    gcp_detail=CreateTableRequestDataAttributesFileMetadataOneOfAccessDetailsGcpDetail(
                        file_path="data/reference_tables/users.csv",
                        gcp_bucket_name="example-data-bucket",
                        gcp_project_id="example-gcp-project-12345",
                        gcp_service_account_email="example-service@example-gcp-project-12345.iam.gserviceaccount.com",
                    ),
                ),
                sync_enabled=False,
            ),
            schema=CreateTableRequestDataAttributesSchema(
                fields=[
                    CreateTableRequestDataAttributesSchemaFieldsItems(
                        name="field_1",
                        type=ReferenceTableSchemaFieldType.STRING,
                    ),
                ],
                primary_keys=[
                    "field_1",
                ],
            ),
            source=ReferenceTableCreateSourceType.LOCAL_FILE,
            table_name="table_1",
            tags=[
                "tag_1",
                "tag_2",
            ],
        ),
        type=CreateTableRequestDataType.REFERENCE_TABLE,
    ),
)

configuration = Configuration()
with ApiClient(configuration) as api_client:
    api_instance = ReferenceTablesApi(api_client)
    response = api_instance.create_reference_table(body=body)

    print(response)

Instructions

First install the library and its dependencies and then save the example to example.py and run following commands:

    
DD_SITE="datadoghq.comus3.datadoghq.comus5.datadoghq.comdatadoghq.euap1.datadoghq.comap2.datadoghq.comddog-gov.com" DD_API_KEY="<DD_API_KEY>" DD_APP_KEY="<DD_APP_KEY>" python3 "example.py"
# Create reference table returns "Created" response

require "datadog_api_client"
api_instance = DatadogAPIClient::V2::ReferenceTablesAPI.new

body = DatadogAPIClient::V2::CreateTableRequest.new({
  data: DatadogAPIClient::V2::CreateTableRequestData.new({
    attributes: DatadogAPIClient::V2::CreateTableRequestDataAttributes.new({
      file_metadata: DatadogAPIClient::V2::CreateTableRequestDataAttributesFileMetadataCloudStorage.new({
        access_details: DatadogAPIClient::V2::CreateTableRequestDataAttributesFileMetadataOneOfAccessDetails.new({
          aws_detail: DatadogAPIClient::V2::CreateTableRequestDataAttributesFileMetadataOneOfAccessDetailsAwsDetail.new({
            aws_account_id: "123456789000",
            aws_bucket_name: "example-data-bucket",
            file_path: "reference-tables/users.csv",
          }),
          azure_detail: DatadogAPIClient::V2::CreateTableRequestDataAttributesFileMetadataOneOfAccessDetailsAzureDetail.new({
            azure_client_id: "aaaaaaaa-1111-2222-3333-bbbbbbbbbbbb",
            azure_container_name: "reference-data",
            azure_storage_account_name: "examplestorageaccount",
            azure_tenant_id: "cccccccc-4444-5555-6666-dddddddddddd",
            file_path: "tables/users.csv",
          }),
          gcp_detail: DatadogAPIClient::V2::CreateTableRequestDataAttributesFileMetadataOneOfAccessDetailsGcpDetail.new({
            file_path: "data/reference_tables/users.csv",
            gcp_bucket_name: "example-data-bucket",
            gcp_project_id: "example-gcp-project-12345",
            gcp_service_account_email: "example-service@example-gcp-project-12345.iam.gserviceaccount.com",
          }),
        }),
        sync_enabled: false,
      }),
      schema: DatadogAPIClient::V2::CreateTableRequestDataAttributesSchema.new({
        fields: [
          DatadogAPIClient::V2::CreateTableRequestDataAttributesSchemaFieldsItems.new({
            name: "field_1",
            type: DatadogAPIClient::V2::ReferenceTableSchemaFieldType::STRING,
          }),
        ],
        primary_keys: [
          "field_1",
        ],
      }),
      source: DatadogAPIClient::V2::ReferenceTableCreateSourceType::LOCAL_FILE,
      table_name: "table_1",
      tags: [
        "tag_1",
        "tag_2",
      ],
    }),
    type: DatadogAPIClient::V2::CreateTableRequestDataType::REFERENCE_TABLE,
  }),
})
p api_instance.create_reference_table(body)

Instructions

First install the library and its dependencies and then save the example to example.rb and run following commands:

    
DD_SITE="datadoghq.comus3.datadoghq.comus5.datadoghq.comdatadoghq.euap1.datadoghq.comap2.datadoghq.comddog-gov.com" DD_API_KEY="<DD_API_KEY>" DD_APP_KEY="<DD_APP_KEY>" rb "example.rb"
// Create reference table returns "Created" response

package main

import (
	"context"
	"encoding/json"
	"fmt"
	"os"

	"github.com/DataDog/datadog-api-client-go/v2/api/datadog"
	"github.com/DataDog/datadog-api-client-go/v2/api/datadogV2"
)

func main() {
	body := datadogV2.CreateTableRequest{
		Data: &datadogV2.CreateTableRequestData{
			Attributes: &datadogV2.CreateTableRequestDataAttributes{
				FileMetadata: &datadogV2.CreateTableRequestDataAttributesFileMetadata{
					CreateTableRequestDataAttributesFileMetadataCloudStorage: &datadogV2.CreateTableRequestDataAttributesFileMetadataCloudStorage{
						AccessDetails: datadogV2.CreateTableRequestDataAttributesFileMetadataOneOfAccessDetails{
							AwsDetail: &datadogV2.CreateTableRequestDataAttributesFileMetadataOneOfAccessDetailsAwsDetail{
								AwsAccountId:  "123456789000",
								AwsBucketName: "example-data-bucket",
								FilePath:      "reference-tables/users.csv",
							},
							AzureDetail: &datadogV2.CreateTableRequestDataAttributesFileMetadataOneOfAccessDetailsAzureDetail{
								AzureClientId:           "aaaaaaaa-1111-2222-3333-bbbbbbbbbbbb",
								AzureContainerName:      "reference-data",
								AzureStorageAccountName: "examplestorageaccount",
								AzureTenantId:           "cccccccc-4444-5555-6666-dddddddddddd",
								FilePath:                "tables/users.csv",
							},
							GcpDetail: &datadogV2.CreateTableRequestDataAttributesFileMetadataOneOfAccessDetailsGcpDetail{
								FilePath:               "data/reference_tables/users.csv",
								GcpBucketName:          "example-data-bucket",
								GcpProjectId:           "example-gcp-project-12345",
								GcpServiceAccountEmail: "example-service@example-gcp-project-12345.iam.gserviceaccount.com",
							},
						},
						SyncEnabled: false,
					}},
				Schema: datadogV2.CreateTableRequestDataAttributesSchema{
					Fields: []datadogV2.CreateTableRequestDataAttributesSchemaFieldsItems{
						{
							Name: "field_1",
							Type: datadogV2.REFERENCETABLESCHEMAFIELDTYPE_STRING,
						},
					},
					PrimaryKeys: []string{
						"field_1",
					},
				},
				Source:    datadogV2.REFERENCETABLECREATESOURCETYPE_LOCAL_FILE,
				TableName: "table_1",
				Tags: []string{
					"tag_1",
					"tag_2",
				},
			},
			Type: datadogV2.CREATETABLEREQUESTDATATYPE_REFERENCE_TABLE,
		},
	}
	ctx := datadog.NewDefaultContext(context.Background())
	configuration := datadog.NewConfiguration()
	apiClient := datadog.NewAPIClient(configuration)
	api := datadogV2.NewReferenceTablesApi(apiClient)
	resp, r, err := api.CreateReferenceTable(ctx, body)

	if err != nil {
		fmt.Fprintf(os.Stderr, "Error when calling `ReferenceTablesApi.CreateReferenceTable`: %v\n", err)
		fmt.Fprintf(os.Stderr, "Full HTTP response: %v\n", r)
	}

	responseContent, _ := json.MarshalIndent(resp, "", "  ")
	fmt.Fprintf(os.Stdout, "Response from `ReferenceTablesApi.CreateReferenceTable`:\n%s\n", responseContent)
}

Instructions

First install the library and its dependencies and then save the example to main.go and run following commands:

    
DD_SITE="datadoghq.comus3.datadoghq.comus5.datadoghq.comdatadoghq.euap1.datadoghq.comap2.datadoghq.comddog-gov.com" DD_API_KEY="<DD_API_KEY>" DD_APP_KEY="<DD_APP_KEY>" go run "main.go"
// Create reference table returns "Created" response

import com.datadog.api.client.ApiClient;
import com.datadog.api.client.ApiException;
import com.datadog.api.client.v2.api.ReferenceTablesApi;
import com.datadog.api.client.v2.model.CreateTableRequest;
import com.datadog.api.client.v2.model.CreateTableRequestData;
import com.datadog.api.client.v2.model.CreateTableRequestDataAttributes;
import com.datadog.api.client.v2.model.CreateTableRequestDataAttributesFileMetadata;
import com.datadog.api.client.v2.model.CreateTableRequestDataAttributesFileMetadataCloudStorage;
import com.datadog.api.client.v2.model.CreateTableRequestDataAttributesFileMetadataOneOfAccessDetails;
import com.datadog.api.client.v2.model.CreateTableRequestDataAttributesFileMetadataOneOfAccessDetailsAwsDetail;
import com.datadog.api.client.v2.model.CreateTableRequestDataAttributesFileMetadataOneOfAccessDetailsAzureDetail;
import com.datadog.api.client.v2.model.CreateTableRequestDataAttributesFileMetadataOneOfAccessDetailsGcpDetail;
import com.datadog.api.client.v2.model.CreateTableRequestDataAttributesSchema;
import com.datadog.api.client.v2.model.CreateTableRequestDataAttributesSchemaFieldsItems;
import com.datadog.api.client.v2.model.CreateTableRequestDataType;
import com.datadog.api.client.v2.model.ReferenceTableCreateSourceType;
import com.datadog.api.client.v2.model.ReferenceTableSchemaFieldType;
import com.datadog.api.client.v2.model.TableResultV2;
import java.util.Arrays;
import java.util.Collections;

public class Example {
  public static void main(String[] args) {
    ApiClient defaultClient = ApiClient.getDefaultApiClient();
    ReferenceTablesApi apiInstance = new ReferenceTablesApi(defaultClient);

    CreateTableRequest body =
        new CreateTableRequest()
            .data(
                new CreateTableRequestData()
                    .attributes(
                        new CreateTableRequestDataAttributes()
                            .fileMetadata(
                                new CreateTableRequestDataAttributesFileMetadata(
                                    new CreateTableRequestDataAttributesFileMetadataCloudStorage()
                                        .accessDetails(
                                            new CreateTableRequestDataAttributesFileMetadataOneOfAccessDetails()
                                                .awsDetail(
                                                    new CreateTableRequestDataAttributesFileMetadataOneOfAccessDetailsAwsDetail()
                                                        .awsAccountId("123456789000")
                                                        .awsBucketName("example-data-bucket")
                                                        .filePath("reference-tables/users.csv"))
                                                .azureDetail(
                                                    new CreateTableRequestDataAttributesFileMetadataOneOfAccessDetailsAzureDetail()
                                                        .azureClientId(
                                                            "aaaaaaaa-1111-2222-3333-bbbbbbbbbbbb")
                                                        .azureContainerName("reference-data")
                                                        .azureStorageAccountName(
                                                            "examplestorageaccount")
                                                        .azureTenantId(
                                                            "cccccccc-4444-5555-6666-dddddddddddd")
                                                        .filePath("tables/users.csv"))
                                                .gcpDetail(
                                                    new CreateTableRequestDataAttributesFileMetadataOneOfAccessDetailsGcpDetail()
                                                        .filePath("data/reference_tables/users.csv")
                                                        .gcpBucketName("example-data-bucket")
                                                        .gcpProjectId("example-gcp-project-12345")
                                                        .gcpServiceAccountEmail(
                                                            "example-service@example-gcp-project-12345.iam.gserviceaccount.com")))
                                        .syncEnabled(false)))
                            .schema(
                                new CreateTableRequestDataAttributesSchema()
                                    .fields(
                                        Collections.singletonList(
                                            new CreateTableRequestDataAttributesSchemaFieldsItems()
                                                .name("field_1")
                                                .type(ReferenceTableSchemaFieldType.STRING)))
                                    .primaryKeys(Collections.singletonList("field_1")))
                            .source(ReferenceTableCreateSourceType.LOCAL_FILE)
                            .tableName("table_1")
                            .tags(Arrays.asList("tag_1", "tag_2")))
                    .type(CreateTableRequestDataType.REFERENCE_TABLE));

    try {
      TableResultV2 result = apiInstance.createReferenceTable(body);
      System.out.println(result);
    } catch (ApiException e) {
      System.err.println("Exception when calling ReferenceTablesApi#createReferenceTable");
      System.err.println("Status code: " + e.getCode());
      System.err.println("Reason: " + e.getResponseBody());
      System.err.println("Response headers: " + e.getResponseHeaders());
      e.printStackTrace();
    }
  }
}

Instructions

First install the library and its dependencies and then save the example to Example.java and run following commands:

    
DD_SITE="datadoghq.comus3.datadoghq.comus5.datadoghq.comdatadoghq.euap1.datadoghq.comap2.datadoghq.comddog-gov.com" DD_API_KEY="<DD_API_KEY>" DD_APP_KEY="<DD_APP_KEY>" java "Example.java"
// Create reference table returns "Created" response
use datadog_api_client::datadog;
use datadog_api_client::datadogV2::api_reference_tables::ReferenceTablesAPI;
use datadog_api_client::datadogV2::model::CreateTableRequest;
use datadog_api_client::datadogV2::model::CreateTableRequestData;
use datadog_api_client::datadogV2::model::CreateTableRequestDataAttributes;
use datadog_api_client::datadogV2::model::CreateTableRequestDataAttributesFileMetadata;
use datadog_api_client::datadogV2::model::CreateTableRequestDataAttributesFileMetadataCloudStorage;
use datadog_api_client::datadogV2::model::CreateTableRequestDataAttributesFileMetadataOneOfAccessDetails;
use datadog_api_client::datadogV2::model::CreateTableRequestDataAttributesFileMetadataOneOfAccessDetailsAwsDetail;
use datadog_api_client::datadogV2::model::CreateTableRequestDataAttributesFileMetadataOneOfAccessDetailsAzureDetail;
use datadog_api_client::datadogV2::model::CreateTableRequestDataAttributesFileMetadataOneOfAccessDetailsGcpDetail;
use datadog_api_client::datadogV2::model::CreateTableRequestDataAttributesSchema;
use datadog_api_client::datadogV2::model::CreateTableRequestDataAttributesSchemaFieldsItems;
use datadog_api_client::datadogV2::model::CreateTableRequestDataType;
use datadog_api_client::datadogV2::model::ReferenceTableCreateSourceType;
use datadog_api_client::datadogV2::model::ReferenceTableSchemaFieldType;

#[tokio::main]
async fn main() {
    let body =
        CreateTableRequest
        ::new().data(
            CreateTableRequestData::new(
                CreateTableRequestDataType::REFERENCE_TABLE,
            ).attributes(
                CreateTableRequestDataAttributes::new(
                    CreateTableRequestDataAttributesSchema::new(
                        vec![
                            CreateTableRequestDataAttributesSchemaFieldsItems::new(
                                "field_1".to_string(),
                                ReferenceTableSchemaFieldType::STRING,
                            )
                        ],
                        vec!["field_1".to_string()],
                    ),
                    ReferenceTableCreateSourceType::LOCAL_FILE,
                    "table_1".to_string(),
                )
                    .file_metadata(
                        CreateTableRequestDataAttributesFileMetadata
                        ::CreateTableRequestDataAttributesFileMetadataCloudStorage(
                            Box::new(
                                CreateTableRequestDataAttributesFileMetadataCloudStorage::new(
                                    CreateTableRequestDataAttributesFileMetadataOneOfAccessDetails::new()
                                        .aws_detail(
                                            CreateTableRequestDataAttributesFileMetadataOneOfAccessDetailsAwsDetail
                                            ::new(
                                                "123456789000".to_string(),
                                                "example-data-bucket".to_string(),
                                                "reference-tables/users.csv".to_string(),
                                            ),
                                        )
                                        .azure_detail(
                                            CreateTableRequestDataAttributesFileMetadataOneOfAccessDetailsAzureDetail
                                            ::new(
                                                "aaaaaaaa-1111-2222-3333-bbbbbbbbbbbb".to_string(),
                                                "reference-data".to_string(),
                                                "examplestorageaccount".to_string(),
                                                "cccccccc-4444-5555-6666-dddddddddddd".to_string(),
                                                "tables/users.csv".to_string(),
                                            ),
                                        )
                                        .gcp_detail(
                                            CreateTableRequestDataAttributesFileMetadataOneOfAccessDetailsGcpDetail
                                            ::new(
                                                "data/reference_tables/users.csv".to_string(),
                                                "example-data-bucket".to_string(),
                                                "example-gcp-project-12345".to_string(),
                                                "example-service@example-gcp-project-12345.iam.gserviceaccount.com".to_string(),
                                            ),
                                        ),
                                    false,
                                ),
                            ),
                        ),
                    )
                    .tags(vec!["tag_1".to_string(), "tag_2".to_string()]),
            ),
        );
    let configuration = datadog::Configuration::new();
    let api = ReferenceTablesAPI::with_config(configuration);
    let resp = api.create_reference_table(body).await;
    if let Ok(value) = resp {
        println!("{:#?}", value);
    } else {
        println!("{:#?}", resp.unwrap_err());
    }
}

Instructions

First install the library and its dependencies and then save the example to src/main.rs and run following commands:

    
DD_SITE="datadoghq.comus3.datadoghq.comus5.datadoghq.comdatadoghq.euap1.datadoghq.comap2.datadoghq.comddog-gov.com" DD_API_KEY="<DD_API_KEY>" DD_APP_KEY="<DD_APP_KEY>" cargo run
/**
 * Create reference table returns "Created" response
 */

import { client, v2 } from "@datadog/datadog-api-client";

const configuration = client.createConfiguration();
const apiInstance = new v2.ReferenceTablesApi(configuration);

const params: v2.ReferenceTablesApiCreateReferenceTableRequest = {
  body: {
    data: {
      attributes: {
        fileMetadata: {
          accessDetails: {
            awsDetail: {
              awsAccountId: "123456789000",
              awsBucketName: "example-data-bucket",
              filePath: "reference-tables/users.csv",
            },
            azureDetail: {
              azureClientId: "aaaaaaaa-1111-2222-3333-bbbbbbbbbbbb",
              azureContainerName: "reference-data",
              azureStorageAccountName: "examplestorageaccount",
              azureTenantId: "cccccccc-4444-5555-6666-dddddddddddd",
              filePath: "tables/users.csv",
            },
            gcpDetail: {
              filePath: "data/reference_tables/users.csv",
              gcpBucketName: "example-data-bucket",
              gcpProjectId: "example-gcp-project-12345",
              gcpServiceAccountEmail:
                "example-service@example-gcp-project-12345.iam.gserviceaccount.com",
            },
          },
          syncEnabled: false,
        },
        schema: {
          fields: [
            {
              name: "field_1",
              type: "STRING",
            },
          ],
          primaryKeys: ["field_1"],
        },
        source: "LOCAL_FILE",
        tableName: "table_1",
        tags: ["tag_1", "tag_2"],
      },
      type: "reference_table",
    },
  },
};

apiInstance
  .createReferenceTable(params)
  .then((data: v2.TableResultV2) => {
    console.log(
      "API called successfully. Returned data: " + JSON.stringify(data)
    );
  })
  .catch((error: any) => console.error(error));

Instructions

First install the library and its dependencies and then save the example to example.ts and run following commands:

    
DD_SITE="datadoghq.comus3.datadoghq.comus5.datadoghq.comdatadoghq.euap1.datadoghq.comap2.datadoghq.comddog-gov.com" DD_API_KEY="<DD_API_KEY>" DD_APP_KEY="<DD_APP_KEY>" tsc "example.ts"

GET https://api.ap1.datadoghq.com/api/v2/reference-tables/tableshttps://api.ap2.datadoghq.com/api/v2/reference-tables/tableshttps://api.datadoghq.eu/api/v2/reference-tables/tableshttps://api.ddog-gov.com/api/v2/reference-tables/tableshttps://api.datadoghq.com/api/v2/reference-tables/tableshttps://api.us3.datadoghq.com/api/v2/reference-tables/tableshttps://api.us5.datadoghq.com/api/v2/reference-tables/tables

개요

List all reference tables in this organization.

인수

쿼리 문자열

이름

유형

설명

page[limit]

integer

Number of tables to return.

page[offset]

integer

Number of tables to skip for pagination.

sort

enum

Sort field and direction for the list of reference tables. Use field name for ascending, prefix with “-” for descending.
Allowed enum values: updated_at, table_name, status, -updated_at, -table_name, -status

filter[status]

string

Filter by table status.

filter[table_name][exact]

string

Filter by exact table name match.

filter[table_name][contains]

string

Filter by table name containing substring.

응답

OK

List of reference tables.

Expand All

항목

유형

설명

data [required]

[object]

The reference tables.

attributes

object

Attributes that define the reference table's configuration and properties.

created_by

string

UUID of the user who created the reference table.

description

string

Optional text describing the purpose or contents of this reference table.

file_metadata

object

Metadata specifying where and how to access the reference table's data file.

For cloud storage tables (S3/GCS/Azure):

  • sync_enabled and access_details will always be present
  • error fields (error_message, error_row_count, error_type) are present only when errors occur

For local file tables:

  • error fields (error_message, error_row_count) are present only when errors occur
  • sync_enabled, access_details are never present

access_details

object

Cloud storage access configuration. Only present for cloud storage sources (S3, GCS, Azure).

aws_detail

object

Amazon Web Services S3 storage access configuration.

aws_account_id

string

AWS account ID where the S3 bucket is located.

aws_bucket_name

string

S3 bucket containing the CSV file.

file_path

string

The relative file path from the S3 bucket root to the CSV file.

azure_detail

object

Azure Blob Storage access configuration.

azure_client_id

string

Azure service principal (application) client ID with permissions to read from the container.

azure_container_name

string

Azure Blob Storage container containing the CSV file.

azure_storage_account_name

string

Azure storage account where the container is located.

azure_tenant_id

string

Azure Active Directory tenant ID.

file_path

string

The relative file path from the Azure container root to the CSV file.

gcp_detail

object

Google Cloud Platform storage access configuration.

file_path

string

The relative file path from the GCS bucket root to the CSV file.

gcp_bucket_name

string

GCP bucket containing the CSV file.

gcp_project_id

string

GCP project ID where the bucket is located.

gcp_service_account_email

string

Service account email with read permissions for the GCS bucket.

error_message

string

The error message returned from the last operation (sync for cloud storage, upload for local file).

error_row_count

int64

The number of rows that failed to process.

error_type

enum

The type of error that occurred during file processing. Only applicable for cloud storage sources. Allowed enum values: TABLE_SCHEMA_ERROR,FILE_FORMAT_ERROR,CONFIGURATION_ERROR,QUOTA_EXCEEDED,CONFLICT_ERROR,VALIDATION_ERROR,STATE_ERROR,OPERATION_ERROR,SYSTEM_ERROR

sync_enabled

boolean

Whether this table is synced automatically from cloud storage. Only applicable for cloud storage sources.

last_updated_by

string

UUID of the user who last updated the reference table.

row_count

int64

The number of successfully processed rows in the reference table.

schema

object

Schema defining the structure and columns of the reference table.

fields [required]

[object]

The schema fields.

name [required]

string

The field name.

type [required]

enum

The field type for reference table schema fields. Allowed enum values: STRING,INT32

primary_keys [required]

[string]

List of field names that serve as primary keys for the table. Only one primary key is supported, and it is used as an ID to retrieve rows.

source

enum

The source type for reference table data. Includes all possible source types that can appear in responses. Allowed enum values: LOCAL_FILE,S3,GCS,AZURE,SERVICENOW,SALESFORCE,DATABRICKS,SNOWFLAKE

status

string

The processing status of the table.

table_name

string

Unique name to identify this reference table. Used in enrichment processors and API calls.

tags

[string]

Tags for organizing and filtering reference tables.

updated_at

string

When the reference table was last updated, in ISO 8601 format.

id

string

Unique identifier for the reference table.

type [required]

enum

Reference table resource type. Allowed enum values: reference_table

default: reference_table

{
  "data": [
    {
      "attributes": {
        "created_by": "00000000-0000-0000-0000-000000000000",
        "description": "example description",
        "file_metadata": {
          "access_details": {},
          "error_message": "",
          "error_row_count": 0,
          "upload_id": "00000000-0000-0000-0000-000000000000"
        },
        "last_updated_by": "",
        "row_count": 5,
        "schema": {
          "fields": [
            {
              "name": "id",
              "type": "INT32"
            },
            {
              "name": "name",
              "type": "STRING"
            }
          ],
          "primary_keys": [
            "id"
          ]
        },
        "source": "LOCAL_FILE",
        "status": "DONE",
        "table_name": "test_reference_table",
        "tags": [
          "tag1",
          "tag2"
        ],
        "updated_at": "2000-01-01T01:00:00+00:00"
      },
      "id": "00000000-0000-0000-0000-000000000000",
      "type": "reference_table"
    },
    {
      "attributes": {
        "created_by": "00000000-0000-0000-0000-000000000000",
        "description": "example description",
        "file_metadata": {
          "access_details": {
            "aws_detail": {
              "aws_account_id": "test-account-id",
              "aws_bucket_name": "test-bucket",
              "file_path": "test_rt.csv"
            }
          },
          "error_message": "",
          "error_row_count": 0,
          "sync_enabled": true
        },
        "last_updated_by": "00000000-0000-0000-0000-000000000000",
        "row_count": 5,
        "schema": {
          "fields": [
            {
              "name": "location",
              "type": "STRING"
            },
            {
              "name": "file_name",
              "type": "STRING"
            }
          ],
          "primary_keys": [
            "location"
          ]
        },
        "source": "S3",
        "status": "DONE",
        "table_name": "test_reference_table_2",
        "tags": [
          "test_tag1",
          "tag2",
          "3"
        ],
        "updated_at": "2000-01-01T01:00:00+00:00"
      },
      "id": "00000000-0000-0000-0000-000000000000",
      "type": "reference_table"
    }
  ]
}

Forbidden

API error response.

Expand All

항목

유형

설명

errors [required]

[string]

A list of errors.

{
  "errors": [
    "Bad Request"
  ]
}

Too many requests

API error response.

Expand All

항목

유형

설명

errors [required]

[string]

A list of errors.

{
  "errors": [
    "Bad Request"
  ]
}

코드 사례

                  # Curl command
curl -X GET "https://api.ap1.datadoghq.com"https://api.ap2.datadoghq.com"https://api.datadoghq.eu"https://api.ddog-gov.com"https://api.datadoghq.com"https://api.us3.datadoghq.com"https://api.us5.datadoghq.com/api/v2/reference-tables/tables" \ -H "Accept: application/json" \ -H "DD-API-KEY: ${DD_API_KEY}" \ -H "DD-APPLICATION-KEY: ${DD_APP_KEY}"
"""
List tables returns "OK" response
"""

from datadog_api_client import ApiClient, Configuration
from datadog_api_client.v2.api.reference_tables_api import ReferenceTablesApi

configuration = Configuration()
with ApiClient(configuration) as api_client:
    api_instance = ReferenceTablesApi(api_client)
    response = api_instance.list_tables()

    print(response)

Instructions

First install the library and its dependencies and then save the example to example.py and run following commands:

    
DD_SITE="datadoghq.comus3.datadoghq.comus5.datadoghq.comdatadoghq.euap1.datadoghq.comap2.datadoghq.comddog-gov.com" DD_API_KEY="<DD_API_KEY>" DD_APP_KEY="<DD_APP_KEY>" python3 "example.py"
# List tables returns "OK" response

require "datadog_api_client"
api_instance = DatadogAPIClient::V2::ReferenceTablesAPI.new
p api_instance.list_tables()

Instructions

First install the library and its dependencies and then save the example to example.rb and run following commands:

    
DD_SITE="datadoghq.comus3.datadoghq.comus5.datadoghq.comdatadoghq.euap1.datadoghq.comap2.datadoghq.comddog-gov.com" DD_API_KEY="<DD_API_KEY>" DD_APP_KEY="<DD_APP_KEY>" rb "example.rb"
// List tables returns "OK" response

package main

import (
	"context"
	"encoding/json"
	"fmt"
	"os"

	"github.com/DataDog/datadog-api-client-go/v2/api/datadog"
	"github.com/DataDog/datadog-api-client-go/v2/api/datadogV2"
)

func main() {
	ctx := datadog.NewDefaultContext(context.Background())
	configuration := datadog.NewConfiguration()
	apiClient := datadog.NewAPIClient(configuration)
	api := datadogV2.NewReferenceTablesApi(apiClient)
	resp, r, err := api.ListTables(ctx, *datadogV2.NewListTablesOptionalParameters())

	if err != nil {
		fmt.Fprintf(os.Stderr, "Error when calling `ReferenceTablesApi.ListTables`: %v\n", err)
		fmt.Fprintf(os.Stderr, "Full HTTP response: %v\n", r)
	}

	responseContent, _ := json.MarshalIndent(resp, "", "  ")
	fmt.Fprintf(os.Stdout, "Response from `ReferenceTablesApi.ListTables`:\n%s\n", responseContent)
}

Instructions

First install the library and its dependencies and then save the example to main.go and run following commands:

    
DD_SITE="datadoghq.comus3.datadoghq.comus5.datadoghq.comdatadoghq.euap1.datadoghq.comap2.datadoghq.comddog-gov.com" DD_API_KEY="<DD_API_KEY>" DD_APP_KEY="<DD_APP_KEY>" go run "main.go"
// List tables returns "OK" response

import com.datadog.api.client.ApiClient;
import com.datadog.api.client.ApiException;
import com.datadog.api.client.v2.api.ReferenceTablesApi;
import com.datadog.api.client.v2.model.TableResultV2Array;

public class Example {
  public static void main(String[] args) {
    ApiClient defaultClient = ApiClient.getDefaultApiClient();
    ReferenceTablesApi apiInstance = new ReferenceTablesApi(defaultClient);

    try {
      TableResultV2Array result = apiInstance.listTables();
      System.out.println(result);
    } catch (ApiException e) {
      System.err.println("Exception when calling ReferenceTablesApi#listTables");
      System.err.println("Status code: " + e.getCode());
      System.err.println("Reason: " + e.getResponseBody());
      System.err.println("Response headers: " + e.getResponseHeaders());
      e.printStackTrace();
    }
  }
}

Instructions

First install the library and its dependencies and then save the example to Example.java and run following commands:

    
DD_SITE="datadoghq.comus3.datadoghq.comus5.datadoghq.comdatadoghq.euap1.datadoghq.comap2.datadoghq.comddog-gov.com" DD_API_KEY="<DD_API_KEY>" DD_APP_KEY="<DD_APP_KEY>" java "Example.java"
// List tables returns "OK" response
use datadog_api_client::datadog;
use datadog_api_client::datadogV2::api_reference_tables::ListTablesOptionalParams;
use datadog_api_client::datadogV2::api_reference_tables::ReferenceTablesAPI;

#[tokio::main]
async fn main() {
    let configuration = datadog::Configuration::new();
    let api = ReferenceTablesAPI::with_config(configuration);
    let resp = api.list_tables(ListTablesOptionalParams::default()).await;
    if let Ok(value) = resp {
        println!("{:#?}", value);
    } else {
        println!("{:#?}", resp.unwrap_err());
    }
}

Instructions

First install the library and its dependencies and then save the example to src/main.rs and run following commands:

    
DD_SITE="datadoghq.comus3.datadoghq.comus5.datadoghq.comdatadoghq.euap1.datadoghq.comap2.datadoghq.comddog-gov.com" DD_API_KEY="<DD_API_KEY>" DD_APP_KEY="<DD_APP_KEY>" cargo run
/**
 * List tables returns "OK" response
 */

import { client, v2 } from "@datadog/datadog-api-client";

const configuration = client.createConfiguration();
const apiInstance = new v2.ReferenceTablesApi(configuration);

apiInstance
  .listTables()
  .then((data: v2.TableResultV2Array) => {
    console.log(
      "API called successfully. Returned data: " + JSON.stringify(data)
    );
  })
  .catch((error: any) => console.error(error));

Instructions

First install the library and its dependencies and then save the example to example.ts and run following commands:

    
DD_SITE="datadoghq.comus3.datadoghq.comus5.datadoghq.comdatadoghq.euap1.datadoghq.comap2.datadoghq.comddog-gov.com" DD_API_KEY="<DD_API_KEY>" DD_APP_KEY="<DD_APP_KEY>" tsc "example.ts"

GET https://api.ap1.datadoghq.com/api/v2/reference-tables/tables/{id}https://api.ap2.datadoghq.com/api/v2/reference-tables/tables/{id}https://api.datadoghq.eu/api/v2/reference-tables/tables/{id}https://api.ddog-gov.com/api/v2/reference-tables/tables/{id}https://api.datadoghq.com/api/v2/reference-tables/tables/{id}https://api.us3.datadoghq.com/api/v2/reference-tables/tables/{id}https://api.us5.datadoghq.com/api/v2/reference-tables/tables/{id}

개요

Get a reference table by ID

인수

경로 파라미터

이름

유형

설명

id [required]

string

Unique identifier of the reference table to retrieve

응답

OK

A reference table resource containing its full configuration and state.

Expand All

항목

유형

설명

data

object

The data object containing the reference table configuration and state.

attributes

object

Attributes that define the reference table's configuration and properties.

created_by

string

UUID of the user who created the reference table.

description

string

Optional text describing the purpose or contents of this reference table.

file_metadata

object

Metadata specifying where and how to access the reference table's data file.

For cloud storage tables (S3/GCS/Azure):

  • sync_enabled and access_details will always be present
  • error fields (error_message, error_row_count, error_type) are present only when errors occur

For local file tables:

  • error fields (error_message, error_row_count) are present only when errors occur
  • sync_enabled, access_details are never present

access_details

object

Cloud storage access configuration. Only present for cloud storage sources (S3, GCS, Azure).

aws_detail

object

Amazon Web Services S3 storage access configuration.

aws_account_id

string

AWS account ID where the S3 bucket is located.

aws_bucket_name

string

S3 bucket containing the CSV file.

file_path

string

The relative file path from the S3 bucket root to the CSV file.

azure_detail

object

Azure Blob Storage access configuration.

azure_client_id

string

Azure service principal (application) client ID with permissions to read from the container.

azure_container_name

string

Azure Blob Storage container containing the CSV file.

azure_storage_account_name

string

Azure storage account where the container is located.

azure_tenant_id

string

Azure Active Directory tenant ID.

file_path

string

The relative file path from the Azure container root to the CSV file.

gcp_detail

object

Google Cloud Platform storage access configuration.

file_path

string

The relative file path from the GCS bucket root to the CSV file.

gcp_bucket_name

string

GCP bucket containing the CSV file.

gcp_project_id

string

GCP project ID where the bucket is located.

gcp_service_account_email

string

Service account email with read permissions for the GCS bucket.

error_message

string

The error message returned from the last operation (sync for cloud storage, upload for local file).

error_row_count

int64

The number of rows that failed to process.

error_type

enum

The type of error that occurred during file processing. Only applicable for cloud storage sources. Allowed enum values: TABLE_SCHEMA_ERROR,FILE_FORMAT_ERROR,CONFIGURATION_ERROR,QUOTA_EXCEEDED,CONFLICT_ERROR,VALIDATION_ERROR,STATE_ERROR,OPERATION_ERROR,SYSTEM_ERROR

sync_enabled

boolean

Whether this table is synced automatically from cloud storage. Only applicable for cloud storage sources.

last_updated_by

string

UUID of the user who last updated the reference table.

row_count

int64

The number of successfully processed rows in the reference table.

schema

object

Schema defining the structure and columns of the reference table.

fields [required]

[object]

The schema fields.

name [required]

string

The field name.

type [required]

enum

The field type for reference table schema fields. Allowed enum values: STRING,INT32

primary_keys [required]

[string]

List of field names that serve as primary keys for the table. Only one primary key is supported, and it is used as an ID to retrieve rows.

source

enum

The source type for reference table data. Includes all possible source types that can appear in responses. Allowed enum values: LOCAL_FILE,S3,GCS,AZURE,SERVICENOW,SALESFORCE,DATABRICKS,SNOWFLAKE

status

string

The processing status of the table.

table_name

string

Unique name to identify this reference table. Used in enrichment processors and API calls.

tags

[string]

Tags for organizing and filtering reference tables.

updated_at

string

When the reference table was last updated, in ISO 8601 format.

id

string

Unique identifier for the reference table.

type [required]

enum

Reference table resource type. Allowed enum values: reference_table

default: reference_table

{
  "data": {
    "attributes": {
      "created_by": "00000000-0000-0000-0000-000000000000",
      "description": "example description",
      "file_metadata": {
        "access_details": {
          "aws_detail": {
            "aws_account_id": "123456789000",
            "aws_bucket_name": "my-bucket",
            "file_path": "path/to/file.csv"
          }
        },
        "sync_enabled": true
      },
      "last_updated_by": "00000000-0000-0000-0000-000000000000",
      "row_count": 5,
      "schema": {
        "fields": [
          {
            "name": "id",
            "type": "INT32"
          },
          {
            "name": "name",
            "type": "STRING"
          }
        ],
        "primary_keys": [
          "id"
        ]
      },
      "source": "S3",
      "status": "DONE",
      "table_name": "test_reference_table",
      "tags": [
        "tag1",
        "tag2"
      ],
      "updated_at": "2000-01-01T01:00:00+00:00"
    },
    "id": "00000000-0000-0000-0000-000000000000",
    "type": "reference_table"
  }
}

Forbidden

API error response.

Expand All

항목

유형

설명

errors [required]

[string]

A list of errors.

{
  "errors": [
    "Bad Request"
  ]
}

Not Found

API error response.

Expand All

항목

유형

설명

errors [required]

[string]

A list of errors.

{
  "errors": [
    "Bad Request"
  ]
}

Too many requests

API error response.

Expand All

항목

유형

설명

errors [required]

[string]

A list of errors.

{
  "errors": [
    "Bad Request"
  ]
}

코드 사례

                  # Path parameters
export id="CHANGE_ME"
# Curl command
curl -X GET "https://api.ap1.datadoghq.com"https://api.ap2.datadoghq.com"https://api.datadoghq.eu"https://api.ddog-gov.com"https://api.datadoghq.com"https://api.us3.datadoghq.com"https://api.us5.datadoghq.com/api/v2/reference-tables/tables/${id}" \ -H "Accept: application/json" \ -H "DD-API-KEY: ${DD_API_KEY}" \ -H "DD-APPLICATION-KEY: ${DD_APP_KEY}"
"""
Get table returns "OK" response
"""

from datadog_api_client import ApiClient, Configuration
from datadog_api_client.v2.api.reference_tables_api import ReferenceTablesApi

configuration = Configuration()
with ApiClient(configuration) as api_client:
    api_instance = ReferenceTablesApi(api_client)
    response = api_instance.get_table(
        id="id",
    )

    print(response)

Instructions

First install the library and its dependencies and then save the example to example.py and run following commands:

    
DD_SITE="datadoghq.comus3.datadoghq.comus5.datadoghq.comdatadoghq.euap1.datadoghq.comap2.datadoghq.comddog-gov.com" DD_API_KEY="<DD_API_KEY>" DD_APP_KEY="<DD_APP_KEY>" python3 "example.py"
# Get table returns "OK" response

require "datadog_api_client"
api_instance = DatadogAPIClient::V2::ReferenceTablesAPI.new
p api_instance.get_table("id")

Instructions

First install the library and its dependencies and then save the example to example.rb and run following commands:

    
DD_SITE="datadoghq.comus3.datadoghq.comus5.datadoghq.comdatadoghq.euap1.datadoghq.comap2.datadoghq.comddog-gov.com" DD_API_KEY="<DD_API_KEY>" DD_APP_KEY="<DD_APP_KEY>" rb "example.rb"
// Get table returns "OK" response

package main

import (
	"context"
	"encoding/json"
	"fmt"
	"os"

	"github.com/DataDog/datadog-api-client-go/v2/api/datadog"
	"github.com/DataDog/datadog-api-client-go/v2/api/datadogV2"
)

func main() {
	ctx := datadog.NewDefaultContext(context.Background())
	configuration := datadog.NewConfiguration()
	apiClient := datadog.NewAPIClient(configuration)
	api := datadogV2.NewReferenceTablesApi(apiClient)
	resp, r, err := api.GetTable(ctx, "id")

	if err != nil {
		fmt.Fprintf(os.Stderr, "Error when calling `ReferenceTablesApi.GetTable`: %v\n", err)
		fmt.Fprintf(os.Stderr, "Full HTTP response: %v\n", r)
	}

	responseContent, _ := json.MarshalIndent(resp, "", "  ")
	fmt.Fprintf(os.Stdout, "Response from `ReferenceTablesApi.GetTable`:\n%s\n", responseContent)
}

Instructions

First install the library and its dependencies and then save the example to main.go and run following commands:

    
DD_SITE="datadoghq.comus3.datadoghq.comus5.datadoghq.comdatadoghq.euap1.datadoghq.comap2.datadoghq.comddog-gov.com" DD_API_KEY="<DD_API_KEY>" DD_APP_KEY="<DD_APP_KEY>" go run "main.go"
// Get table returns "OK" response

import com.datadog.api.client.ApiClient;
import com.datadog.api.client.ApiException;
import com.datadog.api.client.v2.api.ReferenceTablesApi;
import com.datadog.api.client.v2.model.TableResultV2;

public class Example {
  public static void main(String[] args) {
    ApiClient defaultClient = ApiClient.getDefaultApiClient();
    ReferenceTablesApi apiInstance = new ReferenceTablesApi(defaultClient);

    try {
      TableResultV2 result = apiInstance.getTable("id");
      System.out.println(result);
    } catch (ApiException e) {
      System.err.println("Exception when calling ReferenceTablesApi#getTable");
      System.err.println("Status code: " + e.getCode());
      System.err.println("Reason: " + e.getResponseBody());
      System.err.println("Response headers: " + e.getResponseHeaders());
      e.printStackTrace();
    }
  }
}

Instructions

First install the library and its dependencies and then save the example to Example.java and run following commands:

    
DD_SITE="datadoghq.comus3.datadoghq.comus5.datadoghq.comdatadoghq.euap1.datadoghq.comap2.datadoghq.comddog-gov.com" DD_API_KEY="<DD_API_KEY>" DD_APP_KEY="<DD_APP_KEY>" java "Example.java"
// Get table returns "OK" response
use datadog_api_client::datadog;
use datadog_api_client::datadogV2::api_reference_tables::ReferenceTablesAPI;

#[tokio::main]
async fn main() {
    let configuration = datadog::Configuration::new();
    let api = ReferenceTablesAPI::with_config(configuration);
    let resp = api.get_table("id".to_string()).await;
    if let Ok(value) = resp {
        println!("{:#?}", value);
    } else {
        println!("{:#?}", resp.unwrap_err());
    }
}

Instructions

First install the library and its dependencies and then save the example to src/main.rs and run following commands:

    
DD_SITE="datadoghq.comus3.datadoghq.comus5.datadoghq.comdatadoghq.euap1.datadoghq.comap2.datadoghq.comddog-gov.com" DD_API_KEY="<DD_API_KEY>" DD_APP_KEY="<DD_APP_KEY>" cargo run
/**
 * Get table returns "OK" response
 */

import { client, v2 } from "@datadog/datadog-api-client";

const configuration = client.createConfiguration();
const apiInstance = new v2.ReferenceTablesApi(configuration);

const params: v2.ReferenceTablesApiGetTableRequest = {
  id: "id",
};

apiInstance
  .getTable(params)
  .then((data: v2.TableResultV2) => {
    console.log(
      "API called successfully. Returned data: " + JSON.stringify(data)
    );
  })
  .catch((error: any) => console.error(error));

Instructions

First install the library and its dependencies and then save the example to example.ts and run following commands:

    
DD_SITE="datadoghq.comus3.datadoghq.comus5.datadoghq.comdatadoghq.euap1.datadoghq.comap2.datadoghq.comddog-gov.com" DD_API_KEY="<DD_API_KEY>" DD_APP_KEY="<DD_APP_KEY>" tsc "example.ts"

GET https://api.ap1.datadoghq.com/api/v2/reference-tables/tables/{id}/rowshttps://api.ap2.datadoghq.com/api/v2/reference-tables/tables/{id}/rowshttps://api.datadoghq.eu/api/v2/reference-tables/tables/{id}/rowshttps://api.ddog-gov.com/api/v2/reference-tables/tables/{id}/rowshttps://api.datadoghq.com/api/v2/reference-tables/tables/{id}/rowshttps://api.us3.datadoghq.com/api/v2/reference-tables/tables/{id}/rowshttps://api.us5.datadoghq.com/api/v2/reference-tables/tables/{id}/rows

개요

Get reference table rows by their primary key values.

인수

경로 파라미터

이름

유형

설명

id [required]

string

Unique identifier of the reference table to get rows from

쿼리 문자열

이름

유형

설명

row_id [required]

array

List of row IDs (primary key values) to retrieve from the reference table.

응답

Some or all requested rows were found.

List of rows from a reference table query.

Expand All

항목

유형

설명

data [required]

[object]

The rows.

attributes

object

Column values for this row in the reference table.

values

object

Key-value pairs representing the row data, where keys are field names from the schema.

id

string

Row identifier, corresponding to the primary key value.

type [required]

enum

Row resource type. Allowed enum values: row

default: row

{
  "data": [
    {
      "attributes": {
        "values": {}
      },
      "id": "string",
      "type": "row"
    }
  ]
}

Forbidden

API error response.

Expand All

항목

유형

설명

errors [required]

[string]

A list of errors.

{
  "errors": [
    "Bad Request"
  ]
}

Not Found

API error response.

Expand All

항목

유형

설명

errors [required]

[string]

A list of errors.

{
  "errors": [
    "Bad Request"
  ]
}

Too many requests

API error response.

Expand All

항목

유형

설명

errors [required]

[string]

A list of errors.

{
  "errors": [
    "Bad Request"
  ]
}

코드 사례

                  # Path parameters
export id="table-123"
# Required query arguments
export row_id_0="row_id_0"
export row_id_1="row_id_1"
# Curl command
curl -X GET "https://api.ap1.datadoghq.com"https://api.ap2.datadoghq.com"https://api.datadoghq.eu"https://api.ddog-gov.com"https://api.datadoghq.com"https://api.us3.datadoghq.com"https://api.us5.datadoghq.com/api/v2/reference-tables/tables/${id}/rows?row_id=${row_id_0}&row_id=${row_id_1}" \ -H "Accept: application/json" \ -H "DD-API-KEY: ${DD_API_KEY}" \ -H "DD-APPLICATION-KEY: ${DD_APP_KEY}"
"""
Get rows by id returns "Some or all requested rows were found." response
"""

from datadog_api_client import ApiClient, Configuration
from datadog_api_client.v2.api.reference_tables_api import ReferenceTablesApi

configuration = Configuration()
with ApiClient(configuration) as api_client:
    api_instance = ReferenceTablesApi(api_client)
    response = api_instance.get_rows_by_id(
        id="id",
        row_id=[],
    )

    print(response)

Instructions

First install the library and its dependencies and then save the example to example.py and run following commands:

    
DD_SITE="datadoghq.comus3.datadoghq.comus5.datadoghq.comdatadoghq.euap1.datadoghq.comap2.datadoghq.comddog-gov.com" DD_API_KEY="<DD_API_KEY>" DD_APP_KEY="<DD_APP_KEY>" python3 "example.py"
# Get rows by id returns "Some or all requested rows were found." response

require "datadog_api_client"
api_instance = DatadogAPIClient::V2::ReferenceTablesAPI.new
p api_instance.get_rows_by_id("id", [])

Instructions

First install the library and its dependencies and then save the example to example.rb and run following commands:

    
DD_SITE="datadoghq.comus3.datadoghq.comus5.datadoghq.comdatadoghq.euap1.datadoghq.comap2.datadoghq.comddog-gov.com" DD_API_KEY="<DD_API_KEY>" DD_APP_KEY="<DD_APP_KEY>" rb "example.rb"
// Get rows by id returns "Some or all requested rows were found." response

package main

import (
	"context"
	"encoding/json"
	"fmt"
	"os"

	"github.com/DataDog/datadog-api-client-go/v2/api/datadog"
	"github.com/DataDog/datadog-api-client-go/v2/api/datadogV2"
)

func main() {
	ctx := datadog.NewDefaultContext(context.Background())
	configuration := datadog.NewConfiguration()
	apiClient := datadog.NewAPIClient(configuration)
	api := datadogV2.NewReferenceTablesApi(apiClient)
	resp, r, err := api.GetRowsByID(ctx, "id", []string{})

	if err != nil {
		fmt.Fprintf(os.Stderr, "Error when calling `ReferenceTablesApi.GetRowsByID`: %v\n", err)
		fmt.Fprintf(os.Stderr, "Full HTTP response: %v\n", r)
	}

	responseContent, _ := json.MarshalIndent(resp, "", "  ")
	fmt.Fprintf(os.Stdout, "Response from `ReferenceTablesApi.GetRowsByID`:\n%s\n", responseContent)
}

Instructions

First install the library and its dependencies and then save the example to main.go and run following commands:

    
DD_SITE="datadoghq.comus3.datadoghq.comus5.datadoghq.comdatadoghq.euap1.datadoghq.comap2.datadoghq.comddog-gov.com" DD_API_KEY="<DD_API_KEY>" DD_APP_KEY="<DD_APP_KEY>" go run "main.go"
// Get rows by id returns "Some or all requested rows were found." response

import com.datadog.api.client.ApiClient;
import com.datadog.api.client.ApiException;
import com.datadog.api.client.v2.api.ReferenceTablesApi;
import com.datadog.api.client.v2.model.TableRowResourceArray;
import java.util.Arrays;

public class Example {
  public static void main(String[] args) {
    ApiClient defaultClient = ApiClient.getDefaultApiClient();
    ReferenceTablesApi apiInstance = new ReferenceTablesApi(defaultClient);

    try {
      TableRowResourceArray result =
          apiInstance.getRowsByID("table-123", Arrays.asList("row1", "row2"));
      System.out.println(result);
    } catch (ApiException e) {
      System.err.println("Exception when calling ReferenceTablesApi#getRowsByID");
      System.err.println("Status code: " + e.getCode());
      System.err.println("Reason: " + e.getResponseBody());
      System.err.println("Response headers: " + e.getResponseHeaders());
      e.printStackTrace();
    }
  }
}

Instructions

First install the library and its dependencies and then save the example to Example.java and run following commands:

    
DD_SITE="datadoghq.comus3.datadoghq.comus5.datadoghq.comdatadoghq.euap1.datadoghq.comap2.datadoghq.comddog-gov.com" DD_API_KEY="<DD_API_KEY>" DD_APP_KEY="<DD_APP_KEY>" java "Example.java"
// Get rows by id returns "Some or all requested rows were found." response
use datadog_api_client::datadog;
use datadog_api_client::datadogV2::api_reference_tables::ReferenceTablesAPI;

#[tokio::main]
async fn main() {
    let configuration = datadog::Configuration::new();
    let api = ReferenceTablesAPI::with_config(configuration);
    let resp = api.get_rows_by_id("id".to_string(), vec![]).await;
    if let Ok(value) = resp {
        println!("{:#?}", value);
    } else {
        println!("{:#?}", resp.unwrap_err());
    }
}

Instructions

First install the library and its dependencies and then save the example to src/main.rs and run following commands:

    
DD_SITE="datadoghq.comus3.datadoghq.comus5.datadoghq.comdatadoghq.euap1.datadoghq.comap2.datadoghq.comddog-gov.com" DD_API_KEY="<DD_API_KEY>" DD_APP_KEY="<DD_APP_KEY>" cargo run
/**
 * Get rows by id returns "Some or all requested rows were found." response
 */

import { client, v2 } from "@datadog/datadog-api-client";

const configuration = client.createConfiguration();
const apiInstance = new v2.ReferenceTablesApi(configuration);

const params: v2.ReferenceTablesApiGetRowsByIDRequest = {
  id: "id",
  rowId: [],
};

apiInstance
  .getRowsByID(params)
  .then((data: v2.TableRowResourceArray) => {
    console.log(
      "API called successfully. Returned data: " + JSON.stringify(data)
    );
  })
  .catch((error: any) => console.error(error));

Instructions

First install the library and its dependencies and then save the example to example.ts and run following commands:

    
DD_SITE="datadoghq.comus3.datadoghq.comus5.datadoghq.comdatadoghq.euap1.datadoghq.comap2.datadoghq.comddog-gov.com" DD_API_KEY="<DD_API_KEY>" DD_APP_KEY="<DD_APP_KEY>" tsc "example.ts"

PATCH https://api.ap1.datadoghq.com/api/v2/reference-tables/tables/{id}https://api.ap2.datadoghq.com/api/v2/reference-tables/tables/{id}https://api.datadoghq.eu/api/v2/reference-tables/tables/{id}https://api.ddog-gov.com/api/v2/reference-tables/tables/{id}https://api.datadoghq.com/api/v2/reference-tables/tables/{id}https://api.us3.datadoghq.com/api/v2/reference-tables/tables/{id}https://api.us5.datadoghq.com/api/v2/reference-tables/tables/{id}

개요

Update a reference table by ID. You can update the table’s data, description, and tags. Note: The source type cannot be changed after table creation. For data updates: For existing tables of type source:LOCAL_FILE, call POST api/v2/reference-tables/uploads first to get an upload ID, then PUT chunks of CSV data to each provided URL, and finally call this PATCH endpoint with the upload_id in file_metadata. For existing tables with source: types of S3, GCS, or AZURE, provide updated access_details in file_metadata pointing to a CSV file in the same type of cloud storage.

인수

경로 파라미터

이름

유형

설명

id [required]

string

Unique identifier of the reference table to update

요청

Body Data (required)

Expand All

항목

유형

설명

data

object

The data object containing the partial table definition updates.

attributes

object

Attributes that define the updates to the reference table's configuration and properties.

description

string

Optional text describing the purpose or contents of this reference table.

file_metadata

 <oneOf>

Metadata specifying where and how to access the reference table's data file.

Option 1

object

Cloud storage file metadata for patch requests. Allows partial updates of access_details and sync_enabled.

access_details

object

Cloud storage access configuration for the reference table data file.

aws_detail

object

Amazon Web Services S3 storage access configuration.

aws_account_id

string

AWS account ID where the S3 bucket is located.

aws_bucket_name

string

S3 bucket containing the CSV file.

file_path

string

The relative file path from the S3 bucket root to the CSV file.

azure_detail

object

Azure Blob Storage access configuration.

azure_client_id

string

Azure service principal (application) client ID with permissions to read from the container.

azure_container_name

string

Azure Blob Storage container containing the CSV file.

azure_storage_account_name

string

Azure storage account where the container is located.

azure_tenant_id

string

Azure Active Directory tenant ID.

file_path

string

The relative file path from the Azure container root to the CSV file.

gcp_detail

object

Google Cloud Platform storage access configuration.

file_path

string

The relative file path from the GCS bucket root to the CSV file.

gcp_bucket_name

string

GCP bucket containing the CSV file.

gcp_project_id

string

GCP project ID where the bucket is located.

gcp_service_account_email

string

Service account email with read permissions for the GCS bucket.

sync_enabled

boolean

Whether this table is synced automatically.

Option 2

object

Local file metadata for patch requests using upload ID.

upload_id [required]

string

The upload ID.

schema

object

Schema defining the updates to the structure and columns of the reference table. Schema fields cannot be deleted or renamed.

fields [required]

[object]

The schema fields.

name [required]

string

The field name.

type [required]

enum

The field type for reference table schema fields. Allowed enum values: STRING,INT32

primary_keys [required]

[string]

List of field names that serve as primary keys for the table. Only one primary key is supported, and it is used as an ID to retrieve rows. Primary keys cannot be changed after table creation.

sync_enabled

boolean

Whether this table is synced automatically.

tags

[string]

Tags for organizing and filtering reference tables.

type [required]

enum

Reference table resource type. Allowed enum values: reference_table

default: reference_table

{
  "data": {
    "attributes": {
      "description": "example description",
      "file_metadata": {
        "access_details": {
          "aws_detail": {
            "aws_account_id": "123456789000",
            "aws_bucket_name": "example-data-bucket",
            "file_path": "reference-tables/users.csv"
          },
          "azure_detail": {
            "azure_client_id": "aaaaaaaa-1111-2222-3333-bbbbbbbbbbbb",
            "azure_container_name": "reference-data",
            "azure_storage_account_name": "examplestorageaccount",
            "azure_tenant_id": "cccccccc-4444-5555-6666-dddddddddddd",
            "file_path": "tables/users.csv"
          },
          "gcp_detail": {
            "file_path": "data/reference_tables/users.csv",
            "gcp_bucket_name": "example-data-bucket",
            "gcp_project_id": "example-gcp-project-12345",
            "gcp_service_account_email": "example-service@example-gcp-project-12345.iam.gserviceaccount.com"
          }
        },
        "sync_enabled": false
      },
      "schema": {
        "fields": [
          {
            "name": "field_1",
            "type": "STRING"
          }
        ],
        "primary_keys": [
          "field_1"
        ]
      },
      "sync_enabled": false,
      "tags": [
        "tag_1",
        "tag_2"
      ]
    },
    "type": "reference_table"
  }
}

응답

OK

Bad Request

API error response.

Expand All

항목

유형

설명

errors [required]

[string]

A list of errors.

{
  "errors": [
    "Bad Request"
  ]
}

Forbidden

API error response.

Expand All

항목

유형

설명

errors [required]

[string]

A list of errors.

{
  "errors": [
    "Bad Request"
  ]
}

Too many requests

API error response.

Expand All

항목

유형

설명

errors [required]

[string]

A list of errors.

{
  "errors": [
    "Bad Request"
  ]
}

코드 사례

                  # Path parameters
export id="CHANGE_ME"
# Curl command
curl -X PATCH "https://api.ap1.datadoghq.com"https://api.ap2.datadoghq.com"https://api.datadoghq.eu"https://api.ddog-gov.com"https://api.datadoghq.com"https://api.us3.datadoghq.com"https://api.us5.datadoghq.com/api/v2/reference-tables/tables/${id}" \ -H "Accept: application/json" \ -H "Content-Type: application/json" \ -H "DD-API-KEY: ${DD_API_KEY}" \ -H "DD-APPLICATION-KEY: ${DD_APP_KEY}" \ -d @- << EOF { "data": { "attributes": { "schema": { "fields": [ { "name": "field_1", "type": "STRING" } ], "primary_keys": [ "field_1" ] } }, "type": "reference_table" } } EOF
"""
Update reference table returns "OK" response
"""

from datadog_api_client import ApiClient, Configuration
from datadog_api_client.v2.api.reference_tables_api import ReferenceTablesApi
from datadog_api_client.v2.model.patch_table_request import PatchTableRequest
from datadog_api_client.v2.model.patch_table_request_data import PatchTableRequestData
from datadog_api_client.v2.model.patch_table_request_data_attributes import PatchTableRequestDataAttributes
from datadog_api_client.v2.model.patch_table_request_data_attributes_file_metadata_cloud_storage import (
    PatchTableRequestDataAttributesFileMetadataCloudStorage,
)
from datadog_api_client.v2.model.patch_table_request_data_attributes_file_metadata_one_of_access_details import (
    PatchTableRequestDataAttributesFileMetadataOneOfAccessDetails,
)
from datadog_api_client.v2.model.patch_table_request_data_attributes_file_metadata_one_of_access_details_aws_detail import (
    PatchTableRequestDataAttributesFileMetadataOneOfAccessDetailsAwsDetail,
)
from datadog_api_client.v2.model.patch_table_request_data_attributes_schema import PatchTableRequestDataAttributesSchema
from datadog_api_client.v2.model.patch_table_request_data_attributes_schema_fields_items import (
    PatchTableRequestDataAttributesSchemaFieldsItems,
)
from datadog_api_client.v2.model.patch_table_request_data_type import PatchTableRequestDataType
from datadog_api_client.v2.model.reference_table_schema_field_type import ReferenceTableSchemaFieldType

body = PatchTableRequest(
    data=PatchTableRequestData(
        attributes=PatchTableRequestDataAttributes(
            description="this is a cloud table generated via a cloud bucket sync",
            file_metadata=PatchTableRequestDataAttributesFileMetadataCloudStorage(
                access_details=PatchTableRequestDataAttributesFileMetadataOneOfAccessDetails(
                    aws_detail=PatchTableRequestDataAttributesFileMetadataOneOfAccessDetailsAwsDetail(
                        aws_account_id="test-account-id",
                        aws_bucket_name="test-bucket",
                        file_path="test_rt.csv",
                    ),
                ),
                sync_enabled=True,
            ),
            schema=PatchTableRequestDataAttributesSchema(
                fields=[
                    PatchTableRequestDataAttributesSchemaFieldsItems(
                        name="id",
                        type=ReferenceTableSchemaFieldType.INT32,
                    ),
                    PatchTableRequestDataAttributesSchemaFieldsItems(
                        name="name",
                        type=ReferenceTableSchemaFieldType.STRING,
                    ),
                ],
                primary_keys=[
                    "id",
                ],
            ),
            sync_enabled=False,
            tags=[
                "test_tag",
            ],
        ),
        type=PatchTableRequestDataType.REFERENCE_TABLE,
    ),
)

configuration = Configuration()
with ApiClient(configuration) as api_client:
    api_instance = ReferenceTablesApi(api_client)
    api_instance.update_reference_table(id="id", body=body)

Instructions

First install the library and its dependencies and then save the example to example.py and run following commands:

    
DD_SITE="datadoghq.comus3.datadoghq.comus5.datadoghq.comdatadoghq.euap1.datadoghq.comap2.datadoghq.comddog-gov.com" DD_API_KEY="<DD_API_KEY>" DD_APP_KEY="<DD_APP_KEY>" python3 "example.py"
# Update reference table returns "OK" response

require "datadog_api_client"
api_instance = DatadogAPIClient::V2::ReferenceTablesAPI.new

body = DatadogAPIClient::V2::PatchTableRequest.new({
  data: DatadogAPIClient::V2::PatchTableRequestData.new({
    attributes: DatadogAPIClient::V2::PatchTableRequestDataAttributes.new({
      description: "this is a cloud table generated via a cloud bucket sync",
      file_metadata: DatadogAPIClient::V2::PatchTableRequestDataAttributesFileMetadataCloudStorage.new({
        access_details: DatadogAPIClient::V2::PatchTableRequestDataAttributesFileMetadataOneOfAccessDetails.new({
          aws_detail: DatadogAPIClient::V2::PatchTableRequestDataAttributesFileMetadataOneOfAccessDetailsAwsDetail.new({
            aws_account_id: "test-account-id",
            aws_bucket_name: "test-bucket",
            file_path: "test_rt.csv",
          }),
        }),
        sync_enabled: true,
      }),
      schema: DatadogAPIClient::V2::PatchTableRequestDataAttributesSchema.new({
        fields: [
          DatadogAPIClient::V2::PatchTableRequestDataAttributesSchemaFieldsItems.new({
            name: "id",
            type: DatadogAPIClient::V2::ReferenceTableSchemaFieldType::INT32,
          }),
          DatadogAPIClient::V2::PatchTableRequestDataAttributesSchemaFieldsItems.new({
            name: "name",
            type: DatadogAPIClient::V2::ReferenceTableSchemaFieldType::STRING,
          }),
        ],
        primary_keys: [
          "id",
        ],
      }),
      sync_enabled: false,
      tags: [
        "test_tag",
      ],
    }),
    type: DatadogAPIClient::V2::PatchTableRequestDataType::REFERENCE_TABLE,
  }),
})
p api_instance.update_reference_table("id", body)

Instructions

First install the library and its dependencies and then save the example to example.rb and run following commands:

    
DD_SITE="datadoghq.comus3.datadoghq.comus5.datadoghq.comdatadoghq.euap1.datadoghq.comap2.datadoghq.comddog-gov.com" DD_API_KEY="<DD_API_KEY>" DD_APP_KEY="<DD_APP_KEY>" rb "example.rb"
// Update reference table returns "OK" response

package main

import (
	"context"
	"fmt"
	"os"

	"github.com/DataDog/datadog-api-client-go/v2/api/datadog"
	"github.com/DataDog/datadog-api-client-go/v2/api/datadogV2"
)

func main() {
	body := datadogV2.PatchTableRequest{
		Data: &datadogV2.PatchTableRequestData{
			Attributes: &datadogV2.PatchTableRequestDataAttributes{
				Description: datadog.PtrString("this is a cloud table generated via a cloud bucket sync"),
				FileMetadata: &datadogV2.PatchTableRequestDataAttributesFileMetadata{
					PatchTableRequestDataAttributesFileMetadataCloudStorage: &datadogV2.PatchTableRequestDataAttributesFileMetadataCloudStorage{
						AccessDetails: &datadogV2.PatchTableRequestDataAttributesFileMetadataOneOfAccessDetails{
							AwsDetail: &datadogV2.PatchTableRequestDataAttributesFileMetadataOneOfAccessDetailsAwsDetail{
								AwsAccountId:  datadog.PtrString("test-account-id"),
								AwsBucketName: datadog.PtrString("test-bucket"),
								FilePath:      datadog.PtrString("test_rt.csv"),
							},
						},
						SyncEnabled: datadog.PtrBool(true),
					}},
				Schema: &datadogV2.PatchTableRequestDataAttributesSchema{
					Fields: []datadogV2.PatchTableRequestDataAttributesSchemaFieldsItems{
						{
							Name: "id",
							Type: datadogV2.REFERENCETABLESCHEMAFIELDTYPE_INT32,
						},
						{
							Name: "name",
							Type: datadogV2.REFERENCETABLESCHEMAFIELDTYPE_STRING,
						},
					},
					PrimaryKeys: []string{
						"id",
					},
				},
				SyncEnabled: datadog.PtrBool(false),
				Tags: []string{
					"test_tag",
				},
			},
			Type: datadogV2.PATCHTABLEREQUESTDATATYPE_REFERENCE_TABLE,
		},
	}
	ctx := datadog.NewDefaultContext(context.Background())
	configuration := datadog.NewConfiguration()
	apiClient := datadog.NewAPIClient(configuration)
	api := datadogV2.NewReferenceTablesApi(apiClient)
	r, err := api.UpdateReferenceTable(ctx, "id", body)

	if err != nil {
		fmt.Fprintf(os.Stderr, "Error when calling `ReferenceTablesApi.UpdateReferenceTable`: %v\n", err)
		fmt.Fprintf(os.Stderr, "Full HTTP response: %v\n", r)
	}
}

Instructions

First install the library and its dependencies and then save the example to main.go and run following commands:

    
DD_SITE="datadoghq.comus3.datadoghq.comus5.datadoghq.comdatadoghq.euap1.datadoghq.comap2.datadoghq.comddog-gov.com" DD_API_KEY="<DD_API_KEY>" DD_APP_KEY="<DD_APP_KEY>" go run "main.go"
// Update reference table returns "OK" response

import com.datadog.api.client.ApiClient;
import com.datadog.api.client.ApiException;
import com.datadog.api.client.v2.api.ReferenceTablesApi;
import com.datadog.api.client.v2.model.PatchTableRequest;
import com.datadog.api.client.v2.model.PatchTableRequestData;
import com.datadog.api.client.v2.model.PatchTableRequestDataAttributes;
import com.datadog.api.client.v2.model.PatchTableRequestDataAttributesFileMetadata;
import com.datadog.api.client.v2.model.PatchTableRequestDataAttributesFileMetadataCloudStorage;
import com.datadog.api.client.v2.model.PatchTableRequestDataAttributesFileMetadataOneOfAccessDetails;
import com.datadog.api.client.v2.model.PatchTableRequestDataAttributesFileMetadataOneOfAccessDetailsAwsDetail;
import com.datadog.api.client.v2.model.PatchTableRequestDataAttributesSchema;
import com.datadog.api.client.v2.model.PatchTableRequestDataAttributesSchemaFieldsItems;
import com.datadog.api.client.v2.model.PatchTableRequestDataType;
import com.datadog.api.client.v2.model.ReferenceTableSchemaFieldType;
import java.util.Arrays;
import java.util.Collections;

public class Example {
  public static void main(String[] args) {
    ApiClient defaultClient = ApiClient.getDefaultApiClient();
    ReferenceTablesApi apiInstance = new ReferenceTablesApi(defaultClient);

    PatchTableRequest body =
        new PatchTableRequest()
            .data(
                new PatchTableRequestData()
                    .attributes(
                        new PatchTableRequestDataAttributes()
                            .description("this is a cloud table generated via a cloud bucket sync")
                            .fileMetadata(
                                new PatchTableRequestDataAttributesFileMetadata(
                                    new PatchTableRequestDataAttributesFileMetadataCloudStorage()
                                        .accessDetails(
                                            new PatchTableRequestDataAttributesFileMetadataOneOfAccessDetails()
                                                .awsDetail(
                                                    new PatchTableRequestDataAttributesFileMetadataOneOfAccessDetailsAwsDetail()
                                                        .awsAccountId("test-account-id")
                                                        .awsBucketName("test-bucket")
                                                        .filePath("test_rt.csv")))
                                        .syncEnabled(true)))
                            .schema(
                                new PatchTableRequestDataAttributesSchema()
                                    .fields(
                                        Arrays.asList(
                                            new PatchTableRequestDataAttributesSchemaFieldsItems()
                                                .name("id")
                                                .type(ReferenceTableSchemaFieldType.INT32),
                                            new PatchTableRequestDataAttributesSchemaFieldsItems()
                                                .name("name")
                                                .type(ReferenceTableSchemaFieldType.STRING)))
                                    .primaryKeys(Collections.singletonList("id")))
                            .syncEnabled(false)
                            .tags(Collections.singletonList("test_tag")))
                    .type(PatchTableRequestDataType.REFERENCE_TABLE));

    try {
      apiInstance.updateReferenceTable("id", body);
    } catch (ApiException e) {
      System.err.println("Exception when calling ReferenceTablesApi#updateReferenceTable");
      System.err.println("Status code: " + e.getCode());
      System.err.println("Reason: " + e.getResponseBody());
      System.err.println("Response headers: " + e.getResponseHeaders());
      e.printStackTrace();
    }
  }
}

Instructions

First install the library and its dependencies and then save the example to Example.java and run following commands:

    
DD_SITE="datadoghq.comus3.datadoghq.comus5.datadoghq.comdatadoghq.euap1.datadoghq.comap2.datadoghq.comddog-gov.com" DD_API_KEY="<DD_API_KEY>" DD_APP_KEY="<DD_APP_KEY>" java "Example.java"
// Update reference table returns "OK" response
use datadog_api_client::datadog;
use datadog_api_client::datadogV2::api_reference_tables::ReferenceTablesAPI;
use datadog_api_client::datadogV2::model::PatchTableRequest;
use datadog_api_client::datadogV2::model::PatchTableRequestData;
use datadog_api_client::datadogV2::model::PatchTableRequestDataAttributes;
use datadog_api_client::datadogV2::model::PatchTableRequestDataAttributesFileMetadata;
use datadog_api_client::datadogV2::model::PatchTableRequestDataAttributesFileMetadataCloudStorage;
use datadog_api_client::datadogV2::model::PatchTableRequestDataAttributesFileMetadataOneOfAccessDetails;
use datadog_api_client::datadogV2::model::PatchTableRequestDataAttributesFileMetadataOneOfAccessDetailsAwsDetail;
use datadog_api_client::datadogV2::model::PatchTableRequestDataAttributesSchema;
use datadog_api_client::datadogV2::model::PatchTableRequestDataAttributesSchemaFieldsItems;
use datadog_api_client::datadogV2::model::PatchTableRequestDataType;
use datadog_api_client::datadogV2::model::ReferenceTableSchemaFieldType;

#[tokio::main]
async fn main() {
    let body =
        PatchTableRequest
        ::new().data(
            PatchTableRequestData::new(
                PatchTableRequestDataType::REFERENCE_TABLE,
            ).attributes(
                PatchTableRequestDataAttributes::new()
                    .description("this is a cloud table generated via a cloud bucket sync".to_string())
                    .file_metadata(
                        PatchTableRequestDataAttributesFileMetadata
                        ::PatchTableRequestDataAttributesFileMetadataCloudStorage(
                            Box::new(
                                PatchTableRequestDataAttributesFileMetadataCloudStorage::new()
                                    .access_details(
                                        PatchTableRequestDataAttributesFileMetadataOneOfAccessDetails
                                        ::new().aws_detail(
                                            PatchTableRequestDataAttributesFileMetadataOneOfAccessDetailsAwsDetail
                                            ::new()
                                                .aws_account_id("test-account-id".to_string())
                                                .aws_bucket_name("test-bucket".to_string())
                                                .file_path("test_rt.csv".to_string()),
                                        ),
                                    )
                                    .sync_enabled(true),
                            ),
                        ),
                    )
                    .schema(
                        PatchTableRequestDataAttributesSchema::new(
                            vec![
                                PatchTableRequestDataAttributesSchemaFieldsItems::new(
                                    "id".to_string(),
                                    ReferenceTableSchemaFieldType::INT32,
                                ),
                                PatchTableRequestDataAttributesSchemaFieldsItems::new(
                                    "name".to_string(),
                                    ReferenceTableSchemaFieldType::STRING,
                                )
                            ],
                            vec!["id".to_string()],
                        ),
                    )
                    .sync_enabled(false)
                    .tags(vec!["test_tag".to_string()]),
            ),
        );
    let configuration = datadog::Configuration::new();
    let api = ReferenceTablesAPI::with_config(configuration);
    let resp = api.update_reference_table("id".to_string(), body).await;
    if let Ok(value) = resp {
        println!("{:#?}", value);
    } else {
        println!("{:#?}", resp.unwrap_err());
    }
}

Instructions

First install the library and its dependencies and then save the example to src/main.rs and run following commands:

    
DD_SITE="datadoghq.comus3.datadoghq.comus5.datadoghq.comdatadoghq.euap1.datadoghq.comap2.datadoghq.comddog-gov.com" DD_API_KEY="<DD_API_KEY>" DD_APP_KEY="<DD_APP_KEY>" cargo run
/**
 * Update reference table returns "OK" response
 */

import { client, v2 } from "@datadog/datadog-api-client";

const configuration = client.createConfiguration();
const apiInstance = new v2.ReferenceTablesApi(configuration);

const params: v2.ReferenceTablesApiUpdateReferenceTableRequest = {
  body: {
    data: {
      attributes: {
        description: "this is a cloud table generated via a cloud bucket sync",
        fileMetadata: {
          accessDetails: {
            awsDetail: {
              awsAccountId: "test-account-id",
              awsBucketName: "test-bucket",
              filePath: "test_rt.csv",
            },
          },
          syncEnabled: true,
        },
        schema: {
          fields: [
            {
              name: "id",
              type: "INT32",
            },
            {
              name: "name",
              type: "STRING",
            },
          ],
          primaryKeys: ["id"],
        },
        syncEnabled: false,
        tags: ["test_tag"],
      },
      type: "reference_table",
    },
  },
  id: "id",
};

apiInstance
  .updateReferenceTable(params)
  .then((data: any) => {
    console.log(
      "API called successfully. Returned data: " + JSON.stringify(data)
    );
  })
  .catch((error: any) => console.error(error));

Instructions

First install the library and its dependencies and then save the example to example.ts and run following commands:

    
DD_SITE="datadoghq.comus3.datadoghq.comus5.datadoghq.comdatadoghq.euap1.datadoghq.comap2.datadoghq.comddog-gov.com" DD_API_KEY="<DD_API_KEY>" DD_APP_KEY="<DD_APP_KEY>" tsc "example.ts"

DELETE https://api.ap1.datadoghq.com/api/v2/reference-tables/tables/{id}https://api.ap2.datadoghq.com/api/v2/reference-tables/tables/{id}https://api.datadoghq.eu/api/v2/reference-tables/tables/{id}https://api.ddog-gov.com/api/v2/reference-tables/tables/{id}https://api.datadoghq.com/api/v2/reference-tables/tables/{id}https://api.us3.datadoghq.com/api/v2/reference-tables/tables/{id}https://api.us5.datadoghq.com/api/v2/reference-tables/tables/{id}

개요

Delete a reference table by ID

인수

경로 파라미터

이름

유형

설명

id [required]

string

Unique identifier of the reference table to delete

응답

OK

Forbidden

API error response.

Expand All

항목

유형

설명

errors [required]

[string]

A list of errors.

{
  "errors": [
    "Bad Request"
  ]
}

Not Found

API error response.

Expand All

항목

유형

설명

errors [required]

[string]

A list of errors.

{
  "errors": [
    "Bad Request"
  ]
}

Too many requests

API error response.

Expand All

항목

유형

설명

errors [required]

[string]

A list of errors.

{
  "errors": [
    "Bad Request"
  ]
}

코드 사례

                  # Path parameters
export id="CHANGE_ME"
# Curl command
curl -X DELETE "https://api.ap1.datadoghq.com"https://api.ap2.datadoghq.com"https://api.datadoghq.eu"https://api.ddog-gov.com"https://api.datadoghq.com"https://api.us3.datadoghq.com"https://api.us5.datadoghq.com/api/v2/reference-tables/tables/${id}" \ -H "Accept: application/json" \ -H "DD-API-KEY: ${DD_API_KEY}" \ -H "DD-APPLICATION-KEY: ${DD_APP_KEY}"
"""
Delete table returns "OK" response
"""

from datadog_api_client import ApiClient, Configuration
from datadog_api_client.v2.api.reference_tables_api import ReferenceTablesApi

configuration = Configuration()
with ApiClient(configuration) as api_client:
    api_instance = ReferenceTablesApi(api_client)
    api_instance.delete_table(
        id="id",
    )

Instructions

First install the library and its dependencies and then save the example to example.py and run following commands:

    
DD_SITE="datadoghq.comus3.datadoghq.comus5.datadoghq.comdatadoghq.euap1.datadoghq.comap2.datadoghq.comddog-gov.com" DD_API_KEY="<DD_API_KEY>" DD_APP_KEY="<DD_APP_KEY>" python3 "example.py"
# Delete table returns "OK" response

require "datadog_api_client"
api_instance = DatadogAPIClient::V2::ReferenceTablesAPI.new
p api_instance.delete_table("id")

Instructions

First install the library and its dependencies and then save the example to example.rb and run following commands:

    
DD_SITE="datadoghq.comus3.datadoghq.comus5.datadoghq.comdatadoghq.euap1.datadoghq.comap2.datadoghq.comddog-gov.com" DD_API_KEY="<DD_API_KEY>" DD_APP_KEY="<DD_APP_KEY>" rb "example.rb"
// Delete table returns "OK" response

package main

import (
	"context"
	"fmt"
	"os"

	"github.com/DataDog/datadog-api-client-go/v2/api/datadog"
	"github.com/DataDog/datadog-api-client-go/v2/api/datadogV2"
)

func main() {
	ctx := datadog.NewDefaultContext(context.Background())
	configuration := datadog.NewConfiguration()
	apiClient := datadog.NewAPIClient(configuration)
	api := datadogV2.NewReferenceTablesApi(apiClient)
	r, err := api.DeleteTable(ctx, "id")

	if err != nil {
		fmt.Fprintf(os.Stderr, "Error when calling `ReferenceTablesApi.DeleteTable`: %v\n", err)
		fmt.Fprintf(os.Stderr, "Full HTTP response: %v\n", r)
	}
}

Instructions

First install the library and its dependencies and then save the example to main.go and run following commands:

    
DD_SITE="datadoghq.comus3.datadoghq.comus5.datadoghq.comdatadoghq.euap1.datadoghq.comap2.datadoghq.comddog-gov.com" DD_API_KEY="<DD_API_KEY>" DD_APP_KEY="<DD_APP_KEY>" go run "main.go"
// Delete table returns "OK" response

import com.datadog.api.client.ApiClient;
import com.datadog.api.client.ApiException;
import com.datadog.api.client.v2.api.ReferenceTablesApi;

public class Example {
  public static void main(String[] args) {
    ApiClient defaultClient = ApiClient.getDefaultApiClient();
    ReferenceTablesApi apiInstance = new ReferenceTablesApi(defaultClient);

    try {
      apiInstance.deleteTable("id");
    } catch (ApiException e) {
      System.err.println("Exception when calling ReferenceTablesApi#deleteTable");
      System.err.println("Status code: " + e.getCode());
      System.err.println("Reason: " + e.getResponseBody());
      System.err.println("Response headers: " + e.getResponseHeaders());
      e.printStackTrace();
    }
  }
}

Instructions

First install the library and its dependencies and then save the example to Example.java and run following commands:

    
DD_SITE="datadoghq.comus3.datadoghq.comus5.datadoghq.comdatadoghq.euap1.datadoghq.comap2.datadoghq.comddog-gov.com" DD_API_KEY="<DD_API_KEY>" DD_APP_KEY="<DD_APP_KEY>" java "Example.java"
// Delete table returns "OK" response
use datadog_api_client::datadog;
use datadog_api_client::datadogV2::api_reference_tables::ReferenceTablesAPI;

#[tokio::main]
async fn main() {
    let configuration = datadog::Configuration::new();
    let api = ReferenceTablesAPI::with_config(configuration);
    let resp = api.delete_table("id".to_string()).await;
    if let Ok(value) = resp {
        println!("{:#?}", value);
    } else {
        println!("{:#?}", resp.unwrap_err());
    }
}

Instructions

First install the library and its dependencies and then save the example to src/main.rs and run following commands:

    
DD_SITE="datadoghq.comus3.datadoghq.comus5.datadoghq.comdatadoghq.euap1.datadoghq.comap2.datadoghq.comddog-gov.com" DD_API_KEY="<DD_API_KEY>" DD_APP_KEY="<DD_APP_KEY>" cargo run
/**
 * Delete table returns "OK" response
 */

import { client, v2 } from "@datadog/datadog-api-client";

const configuration = client.createConfiguration();
const apiInstance = new v2.ReferenceTablesApi(configuration);

const params: v2.ReferenceTablesApiDeleteTableRequest = {
  id: "id",
};

apiInstance
  .deleteTable(params)
  .then((data: any) => {
    console.log(
      "API called successfully. Returned data: " + JSON.stringify(data)
    );
  })
  .catch((error: any) => console.error(error));

Instructions

First install the library and its dependencies and then save the example to example.ts and run following commands:

    
DD_SITE="datadoghq.comus3.datadoghq.comus5.datadoghq.comdatadoghq.euap1.datadoghq.comap2.datadoghq.comddog-gov.com" DD_API_KEY="<DD_API_KEY>" DD_APP_KEY="<DD_APP_KEY>" tsc "example.ts"

POST https://api.ap1.datadoghq.com/api/v2/reference-tables/tables/{id}/rowshttps://api.ap2.datadoghq.com/api/v2/reference-tables/tables/{id}/rowshttps://api.datadoghq.eu/api/v2/reference-tables/tables/{id}/rowshttps://api.ddog-gov.com/api/v2/reference-tables/tables/{id}/rowshttps://api.datadoghq.com/api/v2/reference-tables/tables/{id}/rowshttps://api.us3.datadoghq.com/api/v2/reference-tables/tables/{id}/rowshttps://api.us5.datadoghq.com/api/v2/reference-tables/tables/{id}/rows

개요

Create or update rows in a Reference Table by their primary key values. If a row with the specified primary key exists, it is updated; otherwise, a new row is created.

인수

경로 파라미터

이름

유형

설명

id [required]

string

Unique identifier of the reference table to upsert rows into

요청

Body Data (required)

Expand All

항목

유형

설명

data [required]

[object]

attributes

object

Attributes containing row data values for row creation or update operations.

values [required]

object

Key-value pairs representing row data, where keys are field names from the schema.

<any-key>

id [required]

string

type [required]

enum

Row resource type. Allowed enum values: row

default: row

{
  "data": [
    {
      "attributes": {
        "values": {
          "<any-key>": "undefined"
        }
      },
      "id": "primary_key_value",
      "type": "row"
    }
  ]
}

응답

Rows created or updated successfully

Bad Request

API error response.

Expand All

항목

유형

설명

errors [required]

[string]

A list of errors.

{
  "errors": [
    "Bad Request"
  ]
}

Forbidden

API error response.

Expand All

항목

유형

설명

errors [required]

[string]

A list of errors.

{
  "errors": [
    "Bad Request"
  ]
}

Not Found

API error response.

Expand All

항목

유형

설명

errors [required]

[string]

A list of errors.

{
  "errors": [
    "Bad Request"
  ]
}

Too many requests

API error response.

Expand All

항목

유형

설명

errors [required]

[string]

A list of errors.

{
  "errors": [
    "Bad Request"
  ]
}

Internal Server Error

API error response.

Expand All

항목

유형

설명

errors [required]

[string]

A list of errors.

{
  "errors": [
    "Bad Request"
  ]
}

코드 사례

                  # Path parameters
export id="CHANGE_ME"
# Curl command
curl -X POST "https://api.ap1.datadoghq.com"https://api.ap2.datadoghq.com"https://api.datadoghq.eu"https://api.ddog-gov.com"https://api.datadoghq.com"https://api.us3.datadoghq.com"https://api.us5.datadoghq.com/api/v2/reference-tables/tables/${id}/rows" \ -H "Accept: application/json" \ -H "Content-Type: application/json" \ -H "DD-API-KEY: ${DD_API_KEY}" \ -H "DD-APPLICATION-KEY: ${DD_APP_KEY}" \ -d @- << EOF { "data": [ { "attributes": { "values": {} }, "id": "primary_key_value", "type": "row" } ] } EOF
"""
Upsert rows returns "Rows created or updated successfully" response
"""

from datadog_api_client import ApiClient, Configuration
from datadog_api_client.v2.api.reference_tables_api import ReferenceTablesApi
from datadog_api_client.v2.model.batch_upsert_rows_request_array import BatchUpsertRowsRequestArray
from datadog_api_client.v2.model.batch_upsert_rows_request_data import BatchUpsertRowsRequestData
from datadog_api_client.v2.model.batch_upsert_rows_request_data_attributes import BatchUpsertRowsRequestDataAttributes
from datadog_api_client.v2.model.table_row_resource_data_type import TableRowResourceDataType

body = BatchUpsertRowsRequestArray(
    data=[
        BatchUpsertRowsRequestData(
            attributes=BatchUpsertRowsRequestDataAttributes(
                values=dict(
                    example_key_value="primary_key_value",
                    name="row_name",
                ),
            ),
            id="primary_key_value",
            type=TableRowResourceDataType.ROW,
        ),
    ],
)

configuration = Configuration()
with ApiClient(configuration) as api_client:
    api_instance = ReferenceTablesApi(api_client)
    api_instance.upsert_rows(id="id", body=body)

Instructions

First install the library and its dependencies and then save the example to example.py and run following commands:

    
DD_SITE="datadoghq.comus3.datadoghq.comus5.datadoghq.comdatadoghq.euap1.datadoghq.comap2.datadoghq.comddog-gov.com" DD_API_KEY="<DD_API_KEY>" DD_APP_KEY="<DD_APP_KEY>" python3 "example.py"
# Upsert rows returns "Rows created or updated successfully" response

require "datadog_api_client"
api_instance = DatadogAPIClient::V2::ReferenceTablesAPI.new

body = DatadogAPIClient::V2::BatchUpsertRowsRequestArray.new({
  data: [
    DatadogAPIClient::V2::BatchUpsertRowsRequestData.new({
      attributes: DatadogAPIClient::V2::BatchUpsertRowsRequestDataAttributes.new({
        values: {
          example_key_value: "primary_key_value", name: "row_name",
        },
      }),
      id: "primary_key_value",
      type: DatadogAPIClient::V2::TableRowResourceDataType::ROW,
    }),
  ],
})
p api_instance.upsert_rows("id", body)

Instructions

First install the library and its dependencies and then save the example to example.rb and run following commands:

    
DD_SITE="datadoghq.comus3.datadoghq.comus5.datadoghq.comdatadoghq.euap1.datadoghq.comap2.datadoghq.comddog-gov.com" DD_API_KEY="<DD_API_KEY>" DD_APP_KEY="<DD_APP_KEY>" rb "example.rb"
// Upsert rows returns "Rows created or updated successfully" response

package main

import (
	"context"
	"fmt"
	"os"

	"github.com/DataDog/datadog-api-client-go/v2/api/datadog"
	"github.com/DataDog/datadog-api-client-go/v2/api/datadogV2"
)

func main() {
	body := datadogV2.BatchUpsertRowsRequestArray{
		Data: []datadogV2.BatchUpsertRowsRequestData{
			{
				Attributes: &datadogV2.BatchUpsertRowsRequestDataAttributes{
					Values: map[string]interface{}{
						"example_key_value": "primary_key_value",
						"name":              "row_name",
					},
				},
				Id:   "primary_key_value",
				Type: datadogV2.TABLEROWRESOURCEDATATYPE_ROW,
			},
		},
	}
	ctx := datadog.NewDefaultContext(context.Background())
	configuration := datadog.NewConfiguration()
	apiClient := datadog.NewAPIClient(configuration)
	api := datadogV2.NewReferenceTablesApi(apiClient)
	r, err := api.UpsertRows(ctx, "id", body)

	if err != nil {
		fmt.Fprintf(os.Stderr, "Error when calling `ReferenceTablesApi.UpsertRows`: %v\n", err)
		fmt.Fprintf(os.Stderr, "Full HTTP response: %v\n", r)
	}
}

Instructions

First install the library and its dependencies and then save the example to main.go and run following commands:

    
DD_SITE="datadoghq.comus3.datadoghq.comus5.datadoghq.comdatadoghq.euap1.datadoghq.comap2.datadoghq.comddog-gov.com" DD_API_KEY="<DD_API_KEY>" DD_APP_KEY="<DD_APP_KEY>" go run "main.go"
// Upsert rows returns "Rows created or updated successfully" response

import com.datadog.api.client.ApiClient;
import com.datadog.api.client.ApiException;
import com.datadog.api.client.v2.api.ReferenceTablesApi;
import com.datadog.api.client.v2.model.BatchUpsertRowsRequestArray;
import com.datadog.api.client.v2.model.BatchUpsertRowsRequestData;
import com.datadog.api.client.v2.model.BatchUpsertRowsRequestDataAttributes;
import com.datadog.api.client.v2.model.TableRowResourceDataType;
import java.util.Collections;
import java.util.Map;

public class Example {
  public static void main(String[] args) {
    ApiClient defaultClient = ApiClient.getDefaultApiClient();
    ReferenceTablesApi apiInstance = new ReferenceTablesApi(defaultClient);

    BatchUpsertRowsRequestArray body =
        new BatchUpsertRowsRequestArray()
            .data(
                Collections.singletonList(
                    new BatchUpsertRowsRequestData()
                        .attributes(
                            new BatchUpsertRowsRequestDataAttributes()
                                .values(
                                    Map.ofEntries(
                                        Map.entry("example_key_value", "primary_key_value"),
                                        Map.entry("name", "row_name"))))
                        .id("primary_key_value")
                        .type(TableRowResourceDataType.ROW)));

    try {
      apiInstance.upsertRows("id", body);
    } catch (ApiException e) {
      System.err.println("Exception when calling ReferenceTablesApi#upsertRows");
      System.err.println("Status code: " + e.getCode());
      System.err.println("Reason: " + e.getResponseBody());
      System.err.println("Response headers: " + e.getResponseHeaders());
      e.printStackTrace();
    }
  }
}

Instructions

First install the library and its dependencies and then save the example to Example.java and run following commands:

    
DD_SITE="datadoghq.comus3.datadoghq.comus5.datadoghq.comdatadoghq.euap1.datadoghq.comap2.datadoghq.comddog-gov.com" DD_API_KEY="<DD_API_KEY>" DD_APP_KEY="<DD_APP_KEY>" java "Example.java"
// Upsert rows returns "Rows created or updated successfully" response
use datadog_api_client::datadog;
use datadog_api_client::datadogV2::api_reference_tables::ReferenceTablesAPI;
use datadog_api_client::datadogV2::model::BatchUpsertRowsRequestArray;
use datadog_api_client::datadogV2::model::BatchUpsertRowsRequestData;
use datadog_api_client::datadogV2::model::BatchUpsertRowsRequestDataAttributes;
use datadog_api_client::datadogV2::model::TableRowResourceDataType;
use serde_json::Value;
use std::collections::BTreeMap;

#[tokio::main]
async fn main() {
    let body = BatchUpsertRowsRequestArray::new(vec![BatchUpsertRowsRequestData::new(
        "primary_key_value".to_string(),
        TableRowResourceDataType::ROW,
    )
    .attributes(BatchUpsertRowsRequestDataAttributes::new(BTreeMap::from([
        (
            "example_key_value".to_string(),
            Value::from("primary_key_value"),
        ),
        ("name".to_string(), Value::from("row_name")),
    ])))]);
    let configuration = datadog::Configuration::new();
    let api = ReferenceTablesAPI::with_config(configuration);
    let resp = api.upsert_rows("id".to_string(), body).await;
    if let Ok(value) = resp {
        println!("{:#?}", value);
    } else {
        println!("{:#?}", resp.unwrap_err());
    }
}

Instructions

First install the library and its dependencies and then save the example to src/main.rs and run following commands:

    
DD_SITE="datadoghq.comus3.datadoghq.comus5.datadoghq.comdatadoghq.euap1.datadoghq.comap2.datadoghq.comddog-gov.com" DD_API_KEY="<DD_API_KEY>" DD_APP_KEY="<DD_APP_KEY>" cargo run
/**
 * Upsert rows returns "Rows created or updated successfully" response
 */

import { client, v2 } from "@datadog/datadog-api-client";

const configuration = client.createConfiguration();
const apiInstance = new v2.ReferenceTablesApi(configuration);

const params: v2.ReferenceTablesApiUpsertRowsRequest = {
  body: {
    data: [
      {
        attributes: {
          values: {
            example_key_value: "primary_key_value",
            name: "row_name",
          },
        },
        id: "primary_key_value",
        type: "row",
      },
    ],
  },
  id: "id",
};

apiInstance
  .upsertRows(params)
  .then((data: any) => {
    console.log(
      "API called successfully. Returned data: " + JSON.stringify(data)
    );
  })
  .catch((error: any) => console.error(error));

Instructions

First install the library and its dependencies and then save the example to example.ts and run following commands:

    
DD_SITE="datadoghq.comus3.datadoghq.comus5.datadoghq.comdatadoghq.euap1.datadoghq.comap2.datadoghq.comddog-gov.com" DD_API_KEY="<DD_API_KEY>" DD_APP_KEY="<DD_APP_KEY>" tsc "example.ts"

DELETE https://api.ap1.datadoghq.com/api/v2/reference-tables/tables/{id}/rowshttps://api.ap2.datadoghq.com/api/v2/reference-tables/tables/{id}/rowshttps://api.datadoghq.eu/api/v2/reference-tables/tables/{id}/rowshttps://api.ddog-gov.com/api/v2/reference-tables/tables/{id}/rowshttps://api.datadoghq.com/api/v2/reference-tables/tables/{id}/rowshttps://api.us3.datadoghq.com/api/v2/reference-tables/tables/{id}/rowshttps://api.us5.datadoghq.com/api/v2/reference-tables/tables/{id}/rows

개요

Delete multiple rows from a Reference Table by their primary key values.

인수

경로 파라미터

이름

유형

설명

id [required]

string

Unique identifier of the reference table to delete rows from

요청

Body Data (required)

Expand All

항목

유형

설명

data [required]

[object]

id [required]

string

type [required]

enum

Row resource type. Allowed enum values: row

default: row

{
  "data": [
    {
      "id": "primary_key_value",
      "type": "row"
    }
  ]
}

응답

Rows deleted successfully

Bad Request

API error response.

Expand All

항목

유형

설명

errors [required]

[string]

A list of errors.

{
  "errors": [
    "Bad Request"
  ]
}

Forbidden

API error response.

Expand All

항목

유형

설명

errors [required]

[string]

A list of errors.

{
  "errors": [
    "Bad Request"
  ]
}

Not Found

API error response.

Expand All

항목

유형

설명

errors [required]

[string]

A list of errors.

{
  "errors": [
    "Bad Request"
  ]
}

Too many requests

API error response.

Expand All

항목

유형

설명

errors [required]

[string]

A list of errors.

{
  "errors": [
    "Bad Request"
  ]
}

Internal Server Error

API error response.

Expand All

항목

유형

설명

errors [required]

[string]

A list of errors.

{
  "errors": [
    "Bad Request"
  ]
}

코드 사례

                  # Path parameters
export id="CHANGE_ME"
# Curl command
curl -X DELETE "https://api.ap1.datadoghq.com"https://api.ap2.datadoghq.com"https://api.datadoghq.eu"https://api.ddog-gov.com"https://api.datadoghq.com"https://api.us3.datadoghq.com"https://api.us5.datadoghq.com/api/v2/reference-tables/tables/${id}/rows" \ -H "Accept: application/json" \ -H "Content-Type: application/json" \ -H "DD-API-KEY: ${DD_API_KEY}" \ -H "DD-APPLICATION-KEY: ${DD_APP_KEY}" \ -d @- << EOF { "data": [ { "id": "primary_key_value", "type": "row" } ] } EOF
"""
Delete rows returns "Rows deleted successfully" response
"""

from datadog_api_client import ApiClient, Configuration
from datadog_api_client.v2.api.reference_tables_api import ReferenceTablesApi
from datadog_api_client.v2.model.batch_delete_rows_request_array import BatchDeleteRowsRequestArray
from datadog_api_client.v2.model.batch_delete_rows_request_data import BatchDeleteRowsRequestData
from datadog_api_client.v2.model.table_row_resource_data_type import TableRowResourceDataType

body = BatchDeleteRowsRequestArray(
    data=[
        BatchDeleteRowsRequestData(
            id="primary_key_value",
            type=TableRowResourceDataType.ROW,
        ),
    ],
)

configuration = Configuration()
with ApiClient(configuration) as api_client:
    api_instance = ReferenceTablesApi(api_client)
    api_instance.delete_rows(id="id", body=body)

Instructions

First install the library and its dependencies and then save the example to example.py and run following commands:

    
DD_SITE="datadoghq.comus3.datadoghq.comus5.datadoghq.comdatadoghq.euap1.datadoghq.comap2.datadoghq.comddog-gov.com" DD_API_KEY="<DD_API_KEY>" DD_APP_KEY="<DD_APP_KEY>" python3 "example.py"
# Delete rows returns "Rows deleted successfully" response

require "datadog_api_client"
api_instance = DatadogAPIClient::V2::ReferenceTablesAPI.new

body = DatadogAPIClient::V2::BatchDeleteRowsRequestArray.new({
  data: [
    DatadogAPIClient::V2::BatchDeleteRowsRequestData.new({
      id: "primary_key_value",
      type: DatadogAPIClient::V2::TableRowResourceDataType::ROW,
    }),
  ],
})
p api_instance.delete_rows("id", body)

Instructions

First install the library and its dependencies and then save the example to example.rb and run following commands:

    
DD_SITE="datadoghq.comus3.datadoghq.comus5.datadoghq.comdatadoghq.euap1.datadoghq.comap2.datadoghq.comddog-gov.com" DD_API_KEY="<DD_API_KEY>" DD_APP_KEY="<DD_APP_KEY>" rb "example.rb"
// Delete rows returns "Rows deleted successfully" response

package main

import (
	"context"
	"fmt"
	"os"

	"github.com/DataDog/datadog-api-client-go/v2/api/datadog"
	"github.com/DataDog/datadog-api-client-go/v2/api/datadogV2"
)

func main() {
	body := datadogV2.BatchDeleteRowsRequestArray{
		Data: []datadogV2.BatchDeleteRowsRequestData{
			{
				Id:   "primary_key_value",
				Type: datadogV2.TABLEROWRESOURCEDATATYPE_ROW,
			},
		},
	}
	ctx := datadog.NewDefaultContext(context.Background())
	configuration := datadog.NewConfiguration()
	apiClient := datadog.NewAPIClient(configuration)
	api := datadogV2.NewReferenceTablesApi(apiClient)
	r, err := api.DeleteRows(ctx, "id", body)

	if err != nil {
		fmt.Fprintf(os.Stderr, "Error when calling `ReferenceTablesApi.DeleteRows`: %v\n", err)
		fmt.Fprintf(os.Stderr, "Full HTTP response: %v\n", r)
	}
}

Instructions

First install the library and its dependencies and then save the example to main.go and run following commands:

    
DD_SITE="datadoghq.comus3.datadoghq.comus5.datadoghq.comdatadoghq.euap1.datadoghq.comap2.datadoghq.comddog-gov.com" DD_API_KEY="<DD_API_KEY>" DD_APP_KEY="<DD_APP_KEY>" go run "main.go"
// Delete rows returns "Rows deleted successfully" response

import com.datadog.api.client.ApiClient;
import com.datadog.api.client.ApiException;
import com.datadog.api.client.v2.api.ReferenceTablesApi;
import com.datadog.api.client.v2.model.BatchDeleteRowsRequestArray;
import com.datadog.api.client.v2.model.BatchDeleteRowsRequestData;
import com.datadog.api.client.v2.model.TableRowResourceDataType;
import java.util.Collections;

public class Example {
  public static void main(String[] args) {
    ApiClient defaultClient = ApiClient.getDefaultApiClient();
    ReferenceTablesApi apiInstance = new ReferenceTablesApi(defaultClient);

    BatchDeleteRowsRequestArray body =
        new BatchDeleteRowsRequestArray()
            .data(
                Collections.singletonList(
                    new BatchDeleteRowsRequestData()
                        .id("primary_key_value")
                        .type(TableRowResourceDataType.ROW)));

    try {
      apiInstance.deleteRows("id", body);
    } catch (ApiException e) {
      System.err.println("Exception when calling ReferenceTablesApi#deleteRows");
      System.err.println("Status code: " + e.getCode());
      System.err.println("Reason: " + e.getResponseBody());
      System.err.println("Response headers: " + e.getResponseHeaders());
      e.printStackTrace();
    }
  }
}

Instructions

First install the library and its dependencies and then save the example to Example.java and run following commands:

    
DD_SITE="datadoghq.comus3.datadoghq.comus5.datadoghq.comdatadoghq.euap1.datadoghq.comap2.datadoghq.comddog-gov.com" DD_API_KEY="<DD_API_KEY>" DD_APP_KEY="<DD_APP_KEY>" java "Example.java"
// Delete rows returns "Rows deleted successfully" response
use datadog_api_client::datadog;
use datadog_api_client::datadogV2::api_reference_tables::ReferenceTablesAPI;
use datadog_api_client::datadogV2::model::BatchDeleteRowsRequestArray;
use datadog_api_client::datadogV2::model::BatchDeleteRowsRequestData;
use datadog_api_client::datadogV2::model::TableRowResourceDataType;

#[tokio::main]
async fn main() {
    let body = BatchDeleteRowsRequestArray::new(vec![BatchDeleteRowsRequestData::new(
        "primary_key_value".to_string(),
        TableRowResourceDataType::ROW,
    )]);
    let configuration = datadog::Configuration::new();
    let api = ReferenceTablesAPI::with_config(configuration);
    let resp = api.delete_rows("id".to_string(), body).await;
    if let Ok(value) = resp {
        println!("{:#?}", value);
    } else {
        println!("{:#?}", resp.unwrap_err());
    }
}

Instructions

First install the library and its dependencies and then save the example to src/main.rs and run following commands:

    
DD_SITE="datadoghq.comus3.datadoghq.comus5.datadoghq.comdatadoghq.euap1.datadoghq.comap2.datadoghq.comddog-gov.com" DD_API_KEY="<DD_API_KEY>" DD_APP_KEY="<DD_APP_KEY>" cargo run
/**
 * Delete rows returns "Rows deleted successfully" response
 */

import { client, v2 } from "@datadog/datadog-api-client";

const configuration = client.createConfiguration();
const apiInstance = new v2.ReferenceTablesApi(configuration);

const params: v2.ReferenceTablesApiDeleteRowsRequest = {
  body: {
    data: [
      {
        id: "primary_key_value",
        type: "row",
      },
    ],
  },
  id: "id",
};

apiInstance
  .deleteRows(params)
  .then((data: any) => {
    console.log(
      "API called successfully. Returned data: " + JSON.stringify(data)
    );
  })
  .catch((error: any) => console.error(error));

Instructions

First install the library and its dependencies and then save the example to example.ts and run following commands:

    
DD_SITE="datadoghq.comus3.datadoghq.comus5.datadoghq.comdatadoghq.euap1.datadoghq.comap2.datadoghq.comddog-gov.com" DD_API_KEY="<DD_API_KEY>" DD_APP_KEY="<DD_APP_KEY>" tsc "example.ts"