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训练和测试旨在检测洗钱活动的模型

了解如何使用命令行工具在 Anti Money Laundering AI 中执行基本操作在开发机器上或 Google Cloud 控制台中运行。

在本指南中，您将以将 BigQuery 表作为 AML AI 的输入。API 输出包含回测结果和预测结果。这些结果用于分析洗钱结构化资金。

准备工作

登录您的 Google Cloud 账号。如果您是 Google Cloud 新手，请创建一个账号来评估我们的产品在实际场景中的表现。新客户还可获享 $300 赠金，用于运行、测试和部署工作负载。

安装 Google Cloud CLI。

如需初始化 gcloud CLI，请运行以下命令：

gcloud init

Create or select a Google Cloud project.

Create a Google Cloud project:
```
gcloud projects create PROJECT_ID
```
Replace PROJECT_ID with a name for the Google Cloud project you are creating.
Select the Google Cloud project that you created:
```
gcloud config set project PROJECT_ID
```
Replace PROJECT_ID with your Google Cloud project name.

确保您的 Google Cloud 项目已启用结算功能。

Enable the required APIs:

gcloud services enable financialservices.googleapis.com bigquery.googleapis.com cloudkms.googleapis.com bigquerydatatransfer.googleapis.com

为您的 Google 账号创建本地身份验证凭据：

gcloud auth application-default login

向您的 Google 账号授予角色。对以下每个 IAM 角色运行以下命令一次： roles/financialservices.admin

gcloud projects add-iam-policy-binding PROJECT_ID --member="user:EMAIL_ADDRESS" --role=ROLE

将 PROJECT_ID 替换为您的项目 ID。
将 EMAIL_ADDRESS 替换为您的电子邮件地址。
将 ROLE 替换为每个角色。

安装 Google Cloud CLI。

如需初始化 gcloud CLI，请运行以下命令：

gcloud init

Create or select a Google Cloud project.

Create a Google Cloud project:
```
gcloud projects create PROJECT_ID
```
Replace PROJECT_ID with a name for the Google Cloud project you are creating.
Select the Google Cloud project that you created:
```
gcloud config set project PROJECT_ID
```
Replace PROJECT_ID with your Google Cloud project name.

确保您的 Google Cloud 项目已启用结算功能。

Enable the required APIs:

gcloud services enable financialservices.googleapis.com bigquery.googleapis.com cloudkms.googleapis.com bigquerydatatransfer.googleapis.com

为您的 Google 账号创建本地身份验证凭据：

gcloud auth application-default login

向您的 Google 账号授予角色。对以下每个 IAM 角色运行以下命令一次： roles/financialservices.admin

gcloud projects add-iam-policy-binding PROJECT_ID --member="user:EMAIL_ADDRESS" --role=ROLE

将 PROJECT_ID 替换为您的项目 ID。
将 EMAIL_ADDRESS 替换为您的电子邮件地址。
将 ROLE 替换为每个角色。

本指南中的 API 请求使用相同的 Google Cloud 项目和位置和硬编码的资源 ID，使指南更易于理解。资源 ID 遵循 my-resource-type 格式（例如 my-key-ring 和 my-model）。

请确保为本指南定义了以下替换内容：
- PROJECT_ID：您的 Google Cloud 项目 ID IAM 设置
- PROJECT_NUMBER: 与 PROJECT_ID.您可以 IAM 设置页面上的项目编号。
- LOCATION： API 资源的位置；请使用支持的区域
  显示位置
  - us-central1
  - us-east1
  - asia-south1
  - europe-west1
  - europe-west2
  - europe-west4
  - northamerica-northeast1
  - southamerica-east1

创建实例

本部分介绍如何创建实例。AML AI 位于所有其他 AML AI 资源的根目录下。每个实例需要单个关联的客户管理的加密密钥 (CMEK) 用于对由 AML AI 创建的任何数据进行加密。

创建密钥环

如需创建密钥环，请使用 projects.locations.keyRings.create 方法。

REST

如需发送请求，请选择以下方式之一：

curl

注意：以下命令假定您已使用您的用户账号通过运行 gcloud init 或 gcloud auth login 登录 gcloud CLI，或者使用了 Cloud Shell，这会使您自动登录 gcloud CLI。您可以运行 gcloud auth list 来检查当前活跃的账号。

执行以下命令：

curl -X POST \
     -H "Authorization: Bearer $(gcloud auth print-access-token)" \
     -H "Content-Type: application/json; charset=utf-8" \
     -d "" \
     "https://cloudkms.googleapis.com/v1/projects/PROJECT_ID/locations/LOCATION/keyRings?key_ring_id=my-key-ring"

PowerShell

注意：以下命令假定您已使用您的用户账号通过运行 gcloud init 或 gcloud auth login 登录 gcloud CLI。您可以运行 gcloud auth list 来检查当前活跃的账号。

执行以下命令：

$cred = gcloud auth print-access-token
$headers = @{ "Authorization" = "Bearer $cred" }

Invoke-WebRequest `
    -Method POST `
    -Headers $headers `
    -Uri "https://cloudkms.googleapis.com/v1/projects/PROJECT_ID/locations/LOCATION/keyRings?key_ring_id=my-key-ring" | Select-Object -Expand Content

您应该收到类似以下内容的 JSON 响应：

{
  "name": "projects/PROJECT_ID/locations/LOCATION/keyRings/my-key-ring",
  "createTime": CREATE_TIME
}

gcloud

执行以下命令：

Linux、macOS 或 Cloud Shell

gcloud kms keyrings create my-key-ring \
  --location LOCATION

Windows (PowerShell)

gcloud kms keyrings create my-key-ring `
  --location LOCATION

Windows (cmd.exe)

gcloud kms keyrings create my-key-ring ^
  --location LOCATION

您应该会收到空响应：

创建密钥

如需创建密钥，请使用 projects.locations.keyRings.cryptoKeys 方法。

REST

请求 JSON 正文：

{
  "purpose": "ENCRYPT_DECRYPT"
}

如需发送请求，请选择以下方式之一：

curl

将请求正文保存在名为 request.json 的文件中。在终端中运行以下命令，在当前目录中创建或覆盖此文件：

cat > request.json << 'EOF'
{
  "purpose": "ENCRYPT_DECRYPT"
}
EOF

然后，执行以下命令以发送 REST 请求：

curl -X POST \
     -H "Authorization: Bearer $(gcloud auth print-access-token)" \
     -H "Content-Type: application/json; charset=utf-8" \
     -d @request.json \
     "https://cloudkms.googleapis.com/v1/projects/PROJECT_ID/locations/LOCATION/keyRings/my-key-ring/cryptoKeys?crypto_key_id=my-key"

PowerShell

注意：以下命令假定您已使用您的用户账号通过运行 gcloud init 或 gcloud auth login 登录 gcloud CLI。您可以运行 gcloud auth list 来检查当前活跃的账号。

将请求正文保存在名为 request.json 的文件中。在终端中运行以下命令，在当前目录中创建或覆盖此文件：

@'
{
  "purpose": "ENCRYPT_DECRYPT"
}
'@  | Out-File -FilePath request.json -Encoding utf8

然后，执行以下命令以发送 REST 请求：

$cred = gcloud auth print-access-token
$headers = @{ "Authorization" = "Bearer $cred" }

Invoke-WebRequest `
    -Method POST `
    -Headers $headers `
    -ContentType: "application/json; charset=utf-8" `
    -InFile request.json `
    -Uri "https://cloudkms.googleapis.com/v1/projects/PROJECT_ID/locations/LOCATION/keyRings/my-key-ring/cryptoKeys?crypto_key_id=my-key" | Select-Object -Expand Content

您应该收到类似以下内容的 JSON 响应：

{
  "name": "projects/PROJECT_ID/locations/LOCATION/keyRings/my-key-ring/cryptoKeys/my-key",
  "primary": {
    "name": "projects/PROJECT_ID/locations/LOCATION/keyRings/my-key-ring/cryptoKeys/my-key/cryptoKeyVersions/1",
    "state": "ENABLED",
    "createTime": CREATE_TIME,
    "protectionLevel": "SOFTWARE",
    "algorithm": "GOOGLE_SYMMETRIC_ENCRYPTION",
    "generateTime": GENERATE_TIME
  },
  "purpose": "ENCRYPT_DECRYPT",
  "createTime": CREATE_TIME,
  "versionTemplate": {
    "protectionLevel": "SOFTWARE",
    "algorithm": "GOOGLE_SYMMETRIC_ENCRYPTION"
  },
  "destroyScheduledDuration": "86400s"
}

gcloud

在使用下面的命令数据之前，请先进行以下替换：

LOCATION：密钥环的位置；请使用支持的区域
显示位置
- us-central1
- us-east1
- asia-south1
- europe-west1
- europe-west2
- europe-west4
- northamerica-northeast1
- southamerica-east1

执行以下命令：

Linux、macOS 或 Cloud Shell

gcloud kms keys create my-key \
  --keyring my-key-ring \
  --location LOCATION \
  --purpose "encryption"

Windows (PowerShell)

gcloud kms keys create my-key `
  --keyring my-key-ring `
  --location LOCATION `
  --purpose "encryption"

Windows (cmd.exe)

gcloud kms keys create my-key ^
  --keyring my-key-ring ^
  --location LOCATION ^
  --purpose "encryption"

您应该会收到空响应：

使用 API 创建实例

如需创建实例，请使用 projects.locations.instances.create 方法。

请求 JSON 正文：

{
  "kmsKey": "projects/PROJECT_ID/locations/LOCATION/keyRings/my-key-ring/cryptoKeys/my-key"
}

如需发送请求，请选择以下方式之一：

curl

将请求正文保存在名为 request.json 的文件中。在终端中运行以下命令，在当前目录中创建或覆盖此文件：

cat > request.json << 'EOF'
{
  "kmsKey": "projects/PROJECT_ID/locations/LOCATION/keyRings/my-key-ring/cryptoKeys/my-key"
}
EOF

然后，执行以下命令以发送 REST 请求：

curl -X POST \
     -H "Authorization: Bearer $(gcloud auth print-access-token)" \
     -H "Content-Type: application/json; charset=utf-8" \
     -d @request.json \
     "https://financialservices.googleapis.com/v1/projects/PROJECT_ID/locations/LOCATION/instances?instance_id=my-instance"

PowerShell

注意：以下命令假定您已使用您的用户账号通过运行 gcloud init 或 gcloud auth login 登录 gcloud CLI。您可以运行 gcloud auth list 来检查当前活跃的账号。

将请求正文保存在名为 request.json 的文件中。在终端中运行以下命令，在当前目录中创建或覆盖此文件：

@'
{
  "kmsKey": "projects/PROJECT_ID/locations/LOCATION/keyRings/my-key-ring/cryptoKeys/my-key"
}
'@  | Out-File -FilePath request.json -Encoding utf8

然后，执行以下命令以发送 REST 请求：

$cred = gcloud auth print-access-token
$headers = @{ "Authorization" = "Bearer $cred" }

Invoke-WebRequest `
    -Method POST `
    -Headers $headers `
    -ContentType: "application/json; charset=utf-8" `
    -InFile request.json `
    -Uri "https://financialservices.googleapis.com/v1/projects/PROJECT_ID/locations/LOCATION/instances?instance_id=my-instance" | Select-Object -Expand Content

您应该收到类似以下内容的 JSON 响应：

{
  "name": "projects/PROJECT_ID/locations/LOCATION/operations/OPERATION_ID",
  "metadata": {
    "@type": "type.googleapis.com/google.cloud.financialservices.v1.OperationMetadata",
    "createTime": CREATE_TIME,
    "target": "projects/PROJECT_ID/locations/LOCATION/instances/my-instance",
    "verb": "create",
    "requestedCancellation": false,
    "apiVersion": "v1"
  },
  "done": false
}

如果成功，响应正文将包含一个长时间运行的操作包含可用于检索当前状态的异步操作。复制返回的 OPERATION_ID（在接下来的）中使用部分。

查看结果

使用 projects.locations.operations.get 方法来检查实例是否已创建。如果响应包含 "done": false，重复该命令，直到响应包含 "done": true。

本指南中的操作可能需要几分钟到几小时才能完成。您必须等到某项操作完成后，才能继续本指南中的操作因为 API 将某些方法的输出用作其他方法的输入。

在使用任何请求数据之前，请先进行以下替换：

OPERATION_ID：操作的标识符

如需发送请求，请选择以下方式之一：

curl

执行以下命令：

curl -X GET \
     -H "Authorization: Bearer $(gcloud auth print-access-token)" \
     "https://financialservices.googleapis.com/v1/projects/PROJECT_ID/locations/LOCATION/operations/OPERATION_ID"

PowerShell

注意：以下命令假定您已使用您的用户账号通过运行 gcloud init 或 gcloud auth login 登录 gcloud CLI。您可以运行 gcloud auth list 来检查当前活跃的账号。

执行以下命令：

$cred = gcloud auth print-access-token
$headers = @{ "Authorization" = "Bearer $cred" }

Invoke-WebRequest `
    -Method GET `
    -Headers $headers `
    -Uri "https://financialservices.googleapis.com/v1/projects/PROJECT_ID/locations/LOCATION/operations/OPERATION_ID" | Select-Object -Expand Content

您应该收到类似以下内容的 JSON 响应：

{
  "name": "projects/PROJECT_ID/locations/LOCATION/operations/OPERATION_ID",
  "metadata": {
    "@type": "type.googleapis.com/google.cloud.financialservices.v1.OperationMetadata",
    "createTime": CREATE_TIME,
    "endTime": END_TIME,
    "target": "projects/PROJECT_ID/locations/LOCATION/instances/my-instance",
    "verb": "create",
    "requestedCancellation": false,
    "apiVersion": "v1"
  },
  "done": true,
  "response": {
    "@type": "type.googleapis.com/google.cloud.financialservices.v1.Instance",
    "name": "projects/PROJECT_ID/locations/LOCATION/instances/my-instance",
    "createTime": CREATE_TIME,
    "updateTime": UPDATE_TIME,
    "kmsKey": "projects/KMS_PROJECT_ID/locations/LOCATION/keyRings/my-key-ring/cryptoKeys/my-key",
    "state": "ACTIVE"
  }
}

授予对 CMEK 密钥的访问权限

该 API 会自动在您的项目中创建一个服务账号。服务账号需要访问 CMEK 密钥，以便使用该密钥进行加密和对底层数据进行解密。授予对密钥的访问权限。

gcloud kms keys add-iam-policy-binding "projects/PROJECT_ID/locations/LOCATION/keyRings/my-key-ring/cryptoKeys/my-key" \
  --keyring "projects/PROJECT_ID/locations/LOCATION/keyRings/my-key-ring" \
  --location "LOCATION" \
  --member "serviceAccount:service-PROJECT_NUMBER@gcp-sa-financialservices.iam.gserviceaccount.com" \
  --role="roles/cloudkms.cryptoKeyEncrypterDecrypter" \
  --project="PROJECT_ID"

创建 BigQuery 数据集

本部分介绍如何创建输入和输出 BigQuery 数据集，然后将样本银行数据复制到输入数据集中。

创建输出数据集

运行以下命令创建数据集 AML 流水线输出的接收对象

bq mk \
  --location=LOCATION \
  --project_id=PROJECT_ID \
  my_bq_output_dataset

创建输入数据集

运行以下命令以创建数据集以复制示例银行表。

bq mk \
  --location=LOCATION \
  --project_id=PROJECT_ID \
  my_bq_input_dataset

复制示例数据集

示例银行数据以 BigQuery 公共数据集。图例该数据集的特征包括：

10 万个政党
核心时间范围为 2020 年 1 月 1 日至 2023 年 1 月 1 日；额外 24 个月的回溯期数据
每月 300 个负风险案例和 20 个正风险案例
具有以下属性的风险案例： <ph type="x-smartling-placeholder">
- 一半的正风险案例都与设计活动有关，发生在“AML_PROCESS_START”事件之前的两个月内
- 另一半会涵盖收款金额最高的各方在AML_PROCESS_START事件发生前的两个月内
- 负例是随机生成的
- 另一方面，生成风险案例的可能性为 0.1% （例如，某个为正数的随机方、结构化活动或收入最高，并且报告为负）

运行以下命令，将示例银行数据复制到输入中数据集。

bq mk --transfer_config \
  --project_id="PROJECT_ID" \
  --data_source=cross_region_copy \
  --target_dataset="my_bq_input_dataset" \
  --display_name="Copy the AML sample dataset." \
  --schedule=None \
  --params='{
    "source_project_id":"bigquery-public-data",
    "source_dataset_id":"aml_ai_input_dataset",
    "overwrite_destination_table":"true"
  }'

在 Google Cloud 控制台中打开 BigQuery。

开始 Google Cloud 控制台
在探索器窗格中查找并展开输入数据集。数次后几分钟后，您应该会看到输入数据集中的表。您还可以查看转移状态方法是从 BigQuery 导航菜单中选择数据传输 菜单。AML 架构在 AML 输入数据模型中定义。

授予对 BigQuery 数据集的访问权限

该 API 会自动在您的项目中创建一个服务账号。服务账号需要访问 BigQuery 输入和输出数据集。

在以下设备上安装 jq：开发机器。如果您无法在开发机器上安装 jq，则可以使用 Cloud Shell 或其他方法授予对资源的访问权限详情请参阅 BigQuery 文档。
运行以下命令，授予对输入数据集及其表格。

# Request the current access permissions on the BigQuery dataset and store them in a temp file.
bq show --format=prettyjson "PROJECT_ID:my_bq_input_dataset" | jq '.access+=[{"role":"READER","userByEmail":"service-PROJECT_NUMBER@gcp-sa-financialservices.iam.gserviceaccount.com" }]'> /tmp/mydataset.json
# Update the BigQuery dataset access permissions using the temp file.
bq update --source /tmp/mydataset.json "PROJECT_ID:my_bq_input_dataset"

# Grant the API read access to the BigQuery table if the table is provided.
for table in party_registration party account_party_link transaction risk_case_event party_supplementary_data
do
   [ -n table ] && bq add-iam-policy-binding \
     --member="serviceAccount:service-PROJECT_NUMBER@gcp-sa-financialservices.iam.gserviceaccount.com" --role="roles/bigquery.dataViewer" \
     PROJECT_ID:my_bq_input_dataset.${table}
done

运行以下命令以授予对输出数据集的写入权限。

# Request the current access permissions on the BigQuery dataset and store them in a temp file.
bq show --format=prettyjson "PROJECT_ID:my_bq_output_dataset" | jq '.access+=[{"role":"roles/bigquery.dataEditor","userByEmail":"service-PROJECT_NUMBER@gcp-sa-financialservices.iam.gserviceaccount.com" }]'> /tmp/mydataset.json
# Update the BigQuery dataset access permissions using the temp file.
bq update --source /tmp/mydataset.json "PROJECT_ID:my_bq_output_dataset"

创建 AML AI 数据集

创建 AML AI 数据集以指定输入要使用的 BigQuery 数据集表和时间范围。

如需创建数据集，请使用 projects.locations.instances.datasets.create 方法。

请求 JSON 正文：

{
  "tableSpecs": {
    "party": "bq://PROJECT_ID.my_bq_input_dataset.party",
    "account_party_link": "bq://PROJECT_ID.my_bq_input_dataset.account_party_link",
    "transaction": "bq://PROJECT_ID.my_bq_input_dataset.transaction",
    "risk_case_event": "bq://PROJECT_ID.my_bq_input_dataset.risk_case_event",
    "party_supplementary_data": "bq://PROJECT_ID.my_bq_input_dataset.party_supplementary_data"
  },
  "dateRange": {
    "startTime": "2020-01-01T00:00:0.00Z",
    "endTime": "2023-01-01T00:00:0.00Z"
  },
  "timeZone": {
    "id": "UTC"
  }
}

如需发送请求，请选择以下方式之一：

curl

将请求正文保存在名为 request.json 的文件中。在终端中运行以下命令，在当前目录中创建或覆盖此文件：

cat > request.json << 'EOF'
{
  "tableSpecs": {
    "party": "bq://PROJECT_ID.my_bq_input_dataset.party",
    "account_party_link": "bq://PROJECT_ID.my_bq_input_dataset.account_party_link",
    "transaction": "bq://PROJECT_ID.my_bq_input_dataset.transaction",
    "risk_case_event": "bq://PROJECT_ID.my_bq_input_dataset.risk_case_event",
    "party_supplementary_data": "bq://PROJECT_ID.my_bq_input_dataset.party_supplementary_data"
  },
  "dateRange": {
    "startTime": "2020-01-01T00:00:0.00Z",
    "endTime": "2023-01-01T00:00:0.00Z"
  },
  "timeZone": {
    "id": "UTC"
  }
}
EOF

然后，执行以下命令以发送 REST 请求：

curl -X POST \
     -H "Authorization: Bearer $(gcloud auth print-access-token)" \
     -H "Content-Type: application/json; charset=utf-8" \
     -d @request.json \
     "https://financialservices.googleapis.com/v1/projects/PROJECT_ID/locations/LOCATION/instances/my-instance/datasets?dataset_id=my-dataset"

PowerShell

注意：以下命令假定您已使用您的用户账号通过运行 gcloud init 或 gcloud auth login 登录 gcloud CLI。您可以运行 gcloud auth list 来检查当前活跃的账号。

将请求正文保存在名为 request.json 的文件中。在终端中运行以下命令，在当前目录中创建或覆盖此文件：

@'
{
  "tableSpecs": {
    "party": "bq://PROJECT_ID.my_bq_input_dataset.party",
    "account_party_link": "bq://PROJECT_ID.my_bq_input_dataset.account_party_link",
    "transaction": "bq://PROJECT_ID.my_bq_input_dataset.transaction",
    "risk_case_event": "bq://PROJECT_ID.my_bq_input_dataset.risk_case_event",
    "party_supplementary_data": "bq://PROJECT_ID.my_bq_input_dataset.party_supplementary_data"
  },
  "dateRange": {
    "startTime": "2020-01-01T00:00:0.00Z",
    "endTime": "2023-01-01T00:00:0.00Z"
  },
  "timeZone": {
    "id": "UTC"
  }
}
'@  | Out-File -FilePath request.json -Encoding utf8

然后，执行以下命令以发送 REST 请求：

$cred = gcloud auth print-access-token
$headers = @{ "Authorization" = "Bearer $cred" }

Invoke-WebRequest `
    -Method POST `
    -Headers $headers `
    -ContentType: "application/json; charset=utf-8" `
    -InFile request.json `
    -Uri "https://financialservices.googleapis.com/v1/projects/PROJECT_ID/locations/LOCATION/instances/my-instance/datasets?dataset_id=my-dataset" | Select-Object -Expand Content

您应该收到类似以下内容的 JSON 响应：

{
  "name": "projects/PROJECT_ID/locations/LOCATION/operations/OPERATION_ID",
  "metadata": {
    "@type": "type.googleapis.com/google.cloud.financialservices.v1.OperationMetadata",
    "createTime": CREATE_TIME,
    "target": "projects/PROJECT_ID/locations/LOCATION/instances/my-instance/datasets/my-dataset",
    "verb": "create",
    "requestedCancellation": false,
    "apiVersion": "v1"
  },
  "done": false
}

您可以使用新的操作操作 ID。（对于本 guide.)

创建引擎配置

创建 AML AI 引擎配置以进行自动调整设置超参数。引擎版本已发布且对应于不同的模型逻辑（例如，定位是零售业务线还是商业业务线）。

如需创建引擎配置，请使用 projects.locations.instances.engineConfigs.create 方法。

请求 JSON 正文：

{
  "engineVersion": "projects/PROJECT_ID/locations/LOCATION/instances/my-instance/engineVersions/aml-commercial.default.v004.000.202312-000",
  "tuning": {
    "primaryDataset": "projects/PROJECT_ID/locations/LOCATION/instances/my-instance/datasets/my-dataset",
    "endTime": "2021-07-01T00:00:00Z",
  },
  "performanceTarget": {
    "partyInvestigationsPerPeriodHint": "30"
  }
}

如需发送请求，请选择以下方式之一：

curl

将请求正文保存在名为 request.json 的文件中。在终端中运行以下命令，在当前目录中创建或覆盖此文件：

cat > request.json << 'EOF'
{
  "engineVersion": "projects/PROJECT_ID/locations/LOCATION/instances/my-instance/engineVersions/aml-commercial.default.v004.000.202312-000",
  "tuning": {
    "primaryDataset": "projects/PROJECT_ID/locations/LOCATION/instances/my-instance/datasets/my-dataset",
    "endTime": "2021-07-01T00:00:00Z",
  },
  "performanceTarget": {
    "partyInvestigationsPerPeriodHint": "30"
  }
}
EOF

然后，执行以下命令以发送 REST 请求：

curl -X POST \
     -H "Authorization: Bearer $(gcloud auth print-access-token)" \
     -H "Content-Type: application/json; charset=utf-8" \
     -d @request.json \
     "https://financialservices.googleapis.com/v1/projects/PROJECT_ID/locations/LOCATION/instances/my-instance/engineConfigs?engine_config_id=my-engine-config"

PowerShell

注意：以下命令假定您已使用您的用户账号通过运行 gcloud init 或 gcloud auth login 登录 gcloud CLI。您可以运行 gcloud auth list 来检查当前活跃的账号。

将请求正文保存在名为 request.json 的文件中。在终端中运行以下命令，在当前目录中创建或覆盖此文件：

@'
{
  "engineVersion": "projects/PROJECT_ID/locations/LOCATION/instances/my-instance/engineVersions/aml-commercial.default.v004.000.202312-000",
  "tuning": {
    "primaryDataset": "projects/PROJECT_ID/locations/LOCATION/instances/my-instance/datasets/my-dataset",
    "endTime": "2021-07-01T00:00:00Z",
  },
  "performanceTarget": {
    "partyInvestigationsPerPeriodHint": "30"
  }
}
'@  | Out-File -FilePath request.json -Encoding utf8

然后，执行以下命令以发送 REST 请求：

$cred = gcloud auth print-access-token
$headers = @{ "Authorization" = "Bearer $cred" }

Invoke-WebRequest `
    -Method POST `
    -Headers $headers `
    -ContentType: "application/json; charset=utf-8" `
    -InFile request.json `
    -Uri "https://financialservices.googleapis.com/v1/projects/PROJECT_ID/locations/LOCATION/instances/my-instance/engineConfigs?engine_config_id=my-engine-config" | Select-Object -Expand Content

您应该收到类似以下内容的 JSON 响应：

{
  "name": "projects/PROJECT_ID/locations/LOCATION/operations/OPERATION_ID",
  "metadata": {
    "@type": "type.googleapis.com/google.cloud.financialservices.v1.OperationMetadata",
    "createTime": CREATE_TIME,
    "target": "projects/PROJECT_ID/locations/LOCATION/instances/my-instance/engineConfigs/my-engine-config",
    "verb": "create",
    "requestedCancellation": false,
    "apiVersion": "v1"
  },
  "done": false
}

创建模型

创建 AML AI 模型以启动 AML 训练流水线。

如需创建模型，请使用 projects.locations.instances.models.create 方法。

请求 JSON 正文：

{
    "engineConfig": "projects/PROJECT_ID/locations/LOCATION/instances/my-instance/engineConfigs/my-engine-config",
    "primaryDataset": "projects/PROJECT_ID/locations/LOCATION/instances/my-instance/datasets/my-dataset",
    "endTime": "2021-07-01T00:00:00Z"
}

如需发送请求，请选择以下方式之一：

curl

将请求正文保存在名为 request.json 的文件中。在终端中运行以下命令，在当前目录中创建或覆盖此文件：

cat > request.json << 'EOF'
{
    "engineConfig": "projects/PROJECT_ID/locations/LOCATION/instances/my-instance/engineConfigs/my-engine-config",
    "primaryDataset": "projects/PROJECT_ID/locations/LOCATION/instances/my-instance/datasets/my-dataset",
    "endTime": "2021-07-01T00:00:00Z"
}
EOF

然后，执行以下命令以发送 REST 请求：

curl -X POST \
     -H "Authorization: Bearer $(gcloud auth print-access-token)" \
     -H "Content-Type: application/json; charset=utf-8" \
     -d @request.json \
     "https://financialservices.googleapis.com/v1/projects/PROJECT_ID/locations/LOCATION/instances/my-instance/models?model_id=my-model"

PowerShell

注意：以下命令假定您已使用您的用户账号通过运行 gcloud init 或 gcloud auth login 登录 gcloud CLI。您可以运行 gcloud auth list 来检查当前活跃的账号。

将请求正文保存在名为 request.json 的文件中。在终端中运行以下命令，在当前目录中创建或覆盖此文件：

@'
{
    "engineConfig": "projects/PROJECT_ID/locations/LOCATION/instances/my-instance/engineConfigs/my-engine-config",
    "primaryDataset": "projects/PROJECT_ID/locations/LOCATION/instances/my-instance/datasets/my-dataset",
    "endTime": "2021-07-01T00:00:00Z"
}
'@  | Out-File -FilePath request.json -Encoding utf8

然后，执行以下命令以发送 REST 请求：

$cred = gcloud auth print-access-token
$headers = @{ "Authorization" = "Bearer $cred" }

Invoke-WebRequest `
    -Method POST `
    -Headers $headers `
    -ContentType: "application/json; charset=utf-8" `
    -InFile request.json `
    -Uri "https://financialservices.googleapis.com/v1/projects/PROJECT_ID/locations/LOCATION/instances/my-instance/models?model_id=my-model" | Select-Object -Expand Content

您应该收到类似以下内容的 JSON 响应：

{
  "name": "projects/PROJECT_ID/locations/LOCATION/operations/OPERATION_ID",
  "metadata": {
    "@type": "type.googleapis.com/google.cloud.financialservices.v1.OperationMetadata",
    "createTime": CREATE_TIME,
    "target": "projects/PROJECT_ID/locations/LOCATION/instances/my-instance/models/my-model",
    "verb": "create",
    "requestedCancellation": false,
    "apiVersion": "v1"
  },
  "done": false
}

创建回测结果

回测预测使用基于现有历史数据训练好的模型。创建数据集中最近 12 个月的回测结果；这些月不是训练数据。

如需创建回测结果，请使用 projects.locations.instances.backtestResults.create 方法。

请求 JSON 正文：

{
    "model": "projects/PROJECT_ID/locations/LOCATION/instances/my-instance/models/my-model",
    "dataset": "projects/PROJECT_ID/locations/LOCATION/instances/my-instance/datasets/my-dataset",
    "endTime": "2023-01-01T00:00:00Z",
    "backtestPeriods": 12,
    "performanceTarget": {
      "partyInvestigationsPerPeriodHint": "150"
    }
}

如需发送请求，请选择以下方式之一：

curl

将请求正文保存在名为 request.json 的文件中。在终端中运行以下命令，在当前目录中创建或覆盖此文件：

cat > request.json << 'EOF'
{
    "model": "projects/PROJECT_ID/locations/LOCATION/instances/my-instance/models/my-model",
    "dataset": "projects/PROJECT_ID/locations/LOCATION/instances/my-instance/datasets/my-dataset",
    "endTime": "2023-01-01T00:00:00Z",
    "backtestPeriods": 12,
    "performanceTarget": {
      "partyInvestigationsPerPeriodHint": "150"
    }
}
EOF

然后，执行以下命令以发送 REST 请求：

curl -X POST \
     -H "Authorization: Bearer $(gcloud auth print-access-token)" \
     -H "Content-Type: application/json; charset=utf-8" \
     -d @request.json \
     "https://financialservices.googleapis.com/v1/projects/PROJECT_ID/locations/LOCATION/instances/my-instance/backtestResults?backtest_result_id=my-backtest-results"

PowerShell

注意：以下命令假定您已使用您的用户账号通过运行 gcloud init 或 gcloud auth login 登录 gcloud CLI。您可以运行 gcloud auth list 来检查当前活跃的账号。

将请求正文保存在名为 request.json 的文件中。在终端中运行以下命令，在当前目录中创建或覆盖此文件：

@'
{
    "model": "projects/PROJECT_ID/locations/LOCATION/instances/my-instance/models/my-model",
    "dataset": "projects/PROJECT_ID/locations/LOCATION/instances/my-instance/datasets/my-dataset",
    "endTime": "2023-01-01T00:00:00Z",
    "backtestPeriods": 12,
    "performanceTarget": {
      "partyInvestigationsPerPeriodHint": "150"
    }
}
'@  | Out-File -FilePath request.json -Encoding utf8

然后，执行以下命令以发送 REST 请求：

$cred = gcloud auth print-access-token
$headers = @{ "Authorization" = "Bearer $cred" }

Invoke-WebRequest `
    -Method POST `
    -Headers $headers `
    -ContentType: "application/json; charset=utf-8" `
    -InFile request.json `
    -Uri "https://financialservices.googleapis.com/v1/projects/PROJECT_ID/locations/LOCATION/instances/my-instance/backtestResults?backtest_result_id=my-backtest-results" | Select-Object -Expand Content

您应该收到类似以下内容的 JSON 响应：

{
  "name": "projects/PROJECT_ID/locations/LOCATION/operations/OPERATION_ID",
  "metadata": {
    "@type": "type.googleapis.com/google.cloud.financialservices.v1.OperationMetadata",
    "createTime": CREATE_TIME,
    "target": "projects/PROJECT_ID/locations/LOCATION/instances/my-instance/backtestResults/my-backtest-results",
    "verb": "create",
    "requestedCancellation": false,
    "apiVersion": "v1"
  },
  "done": false
}

导出回测结果元数据

如需从回测结果中导出元数据，请使用 projects.locations.instances.backtestResults.exportMetadata 方法。

请求 JSON 正文：

{
  "structuredMetadataDestination": {
    "tableUri": "bq://PROJECT_ID.my_bq_output_dataset.my_backtest_results_metadata",
    "writeDisposition": "WRITE_TRUNCATE"
  }
}

如需发送请求，请选择以下方式之一：

curl

将请求正文保存在名为 request.json 的文件中。在终端中运行以下命令，在当前目录中创建或覆盖此文件：

cat > request.json << 'EOF'
{
  "structuredMetadataDestination": {
    "tableUri": "bq://PROJECT_ID.my_bq_output_dataset.my_backtest_results_metadata",
    "writeDisposition": "WRITE_TRUNCATE"
  }
}
EOF

然后，执行以下命令以发送 REST 请求：

curl -X POST \
     -H "Authorization: Bearer $(gcloud auth print-access-token)" \
     -H "Content-Type: application/json; charset=utf-8" \
     -d @request.json \
     "https://financialservices.googleapis.com/v1/projects/PROJECT_ID/locations/LOCATION/instances/my-instance/backtestResults/my-backtest-results:exportMetadata"

PowerShell

注意：以下命令假定您已使用您的用户账号通过运行 gcloud init 或 gcloud auth login 登录 gcloud CLI。您可以运行 gcloud auth list 来检查当前活跃的账号。

将请求正文保存在名为 request.json 的文件中。在终端中运行以下命令，在当前目录中创建或覆盖此文件：

@'
{
  "structuredMetadataDestination": {
    "tableUri": "bq://PROJECT_ID.my_bq_output_dataset.my_backtest_results_metadata",
    "writeDisposition": "WRITE_TRUNCATE"
  }
}
'@  | Out-File -FilePath request.json -Encoding utf8

然后，执行以下命令以发送 REST 请求：

$cred = gcloud auth print-access-token
$headers = @{ "Authorization" = "Bearer $cred" }

Invoke-WebRequest `
    -Method POST `
    -Headers $headers `
    -ContentType: "application/json; charset=utf-8" `
    -InFile request.json `
    -Uri "https://financialservices.googleapis.com/v1/projects/PROJECT_ID/locations/LOCATION/instances/my-instance/backtestResults/my-backtest-results:exportMetadata" | Select-Object -Expand Content

您应该收到类似以下内容的 JSON 响应：

{
  "name": "projects/PROJECT_ID/locations/LOCATION/operations/OPERATION_ID",
  "metadata": {
    "@type": "type.googleapis.com/google.cloud.financialservices.v1.OperationMetadata",
    "createTime": CREATE_TIME,
    "target": "projects/PROJECT_ID/locations/LOCATION/instances/my-instance/backtestResults/my-backtest-results",
    "verb": "exportMetadata",
    "requestedCancellation": false,
    "apiVersion": "v1"
  },
  "done": false
}

在 Google Cloud 控制台中打开 BigQuery。

开始 Google Cloud 控制台
在探索器窗格中查找并展开输出数据集。
选择表，然后点击预览。
找到名为 ObservedRecallValues 的行。
假设您每月的调查能力为 120 人。找到使用 "partyInvestigationsPerPeriod": "120" 来召回值对象。对于如果将调查范围限定为有风险的各方，可采用以下示例值得分高于 0.53，那么您应该研究 120 个新每月举行一次聚会。在回测期间（即 2022 年），您会能够识别先前系统识别到的 86% 的案例（可能旧系统未能识别的其他问题）。
```
{
  "recallValues": [
    ...
    {
      "partyInvestigationsPerPeriod": "105",
      "recallValue": 0.8142077,
      "scoreThreshold": 0.6071321
    },
    {
      "partyInvestigationsPerPeriod": "120",
      "recallValue": 0.863388,
      "scoreThreshold": 0.5339603
    },
    {
      "partyInvestigationsPerPeriod": "135",
      "recallValue": 0.89071035,
      "scoreThreshold": 0.4739899
    },
    ...
  ]
}
```

导入注册方

在创建预测结果之前，您需要导入已注册的各方（即数据集中的客户）。

要导入注册方，请使用 projects.locations.instances.importRegisteredParties 方法。

请求 JSON 正文：

{
  "partyTables": [
     "bq://PROJECT_ID.my_bq_input_dataset.party_registration"
  ],
  "mode": "REPLACE",
  "lineOfBusiness": "COMMERCIAL"
}

如需发送请求，请选择以下方式之一：

curl

将请求正文保存在名为 request.json 的文件中。在终端中运行以下命令，在当前目录中创建或覆盖此文件：

cat > request.json << 'EOF'
{
  "partyTables": [
     "bq://PROJECT_ID.my_bq_input_dataset.party_registration"
  ],
  "mode": "REPLACE",
  "lineOfBusiness": "COMMERCIAL"
}
EOF

然后，执行以下命令以发送 REST 请求：

curl -X POST \
     -H "Authorization: Bearer $(gcloud auth print-access-token)" \
     -H "Content-Type: application/json; charset=utf-8" \
     -d @request.json \
     "https://financialservices.googleapis.com/v1/projects/PROJECT_ID/locations/LOCATION/instances/my-instance:importRegisteredParties"

PowerShell

注意：以下命令假定您已使用您的用户账号通过运行 gcloud init 或 gcloud auth login 登录 gcloud CLI。您可以运行 gcloud auth list 来检查当前活跃的账号。

将请求正文保存在名为 request.json 的文件中。在终端中运行以下命令，在当前目录中创建或覆盖此文件：

@'
{
  "partyTables": [
     "bq://PROJECT_ID.my_bq_input_dataset.party_registration"
  ],
  "mode": "REPLACE",
  "lineOfBusiness": "COMMERCIAL"
}
'@  | Out-File -FilePath request.json -Encoding utf8

然后，执行以下命令以发送 REST 请求：

$cred = gcloud auth print-access-token
$headers = @{ "Authorization" = "Bearer $cred" }

Invoke-WebRequest `
    -Method POST `
    -Headers $headers `
    -ContentType: "application/json; charset=utf-8" `
    -InFile request.json `
    -Uri "https://financialservices.googleapis.com/v1/projects/PROJECT_ID/locations/LOCATION/instances/my-instance:importRegisteredParties" | Select-Object -Expand Content

您应该收到类似以下内容的 JSON 响应：

{
  "name": "projects/PROJECT_ID/locations/LOCATION/operations/OPERATION_ID",
  "metadata": {
    "@type": "type.googleapis.com/google.cloud.financialservices.v1.OperationMetadata",
    "createTime": CREATE_TIME,
    "target": "projects/PROJECT_ID/locations/LOCATION/instances/my-instance",
    "verb": "importRegisteredParties",
    "requestedCancellation": false,
    "apiVersion": "v1"
  },
  "done": false
}

操作完成后，您应该会看到 10,000 方。

创建预测结果

在数据集中创建最近 12 个月的预测结果；这些月没有用于训练。

要创建预测结果，请使用 projects.locations.instances.predictionResults.create 方法。

请求 JSON 正文：

{
    "model": "projects/PROJECT_ID/locations/LOCATION/instances/my-instance/models/my-model",
    "dataset": "projects/PROJECT_ID/locations/LOCATION/instances/my-instance/datasets/my-dataset",
    "endTime": "2023-01-01T00:00:00Z",
    "predictionPeriods": "12",
    "outputs": {
      "predictionDestination": {
        "tableUri": "bq://PROJECT_ID.my_bq_output_dataset.my_prediction_results",
        "writeDisposition": "WRITE_TRUNCATE"
      },
      "explainabilityDestination": {
        "tableUri": "bq://PROJECT_ID.my_bq_output_dataset.my_prediction_results_explainability",
        "writeDisposition": "WRITE_TRUNCATE"
      }
    }
}

如需发送请求，请选择以下方式之一：

curl

将请求正文保存在名为 request.json 的文件中。在终端中运行以下命令，在当前目录中创建或覆盖此文件：

cat > request.json << 'EOF'
{
    "model": "projects/PROJECT_ID/locations/LOCATION/instances/my-instance/models/my-model",
    "dataset": "projects/PROJECT_ID/locations/LOCATION/instances/my-instance/datasets/my-dataset",
    "endTime": "2023-01-01T00:00:00Z",
    "predictionPeriods": "12",
    "outputs": {
      "predictionDestination": {
        "tableUri": "bq://PROJECT_ID.my_bq_output_dataset.my_prediction_results",
        "writeDisposition": "WRITE_TRUNCATE"
      },
      "explainabilityDestination": {
        "tableUri": "bq://PROJECT_ID.my_bq_output_dataset.my_prediction_results_explainability",
        "writeDisposition": "WRITE_TRUNCATE"
      }
    }
}
EOF

然后，执行以下命令以发送 REST 请求：

curl -X POST \
     -H "Authorization: Bearer $(gcloud auth print-access-token)" \
     -H "Content-Type: application/json; charset=utf-8" \
     -d @request.json \
     "https://financialservices.googleapis.com/v1/projects/PROJECT_ID/locations/LOCATION/instances/my-instance/predictionResults?prediction_result_id=my-prediction-results"

PowerShell

注意：以下命令假定您已使用您的用户账号通过运行 gcloud init 或 gcloud auth login 登录 gcloud CLI。您可以运行 gcloud auth list 来检查当前活跃的账号。

将请求正文保存在名为 request.json 的文件中。在终端中运行以下命令，在当前目录中创建或覆盖此文件：

@'
{
    "model": "projects/PROJECT_ID/locations/LOCATION/instances/my-instance/models/my-model",
    "dataset": "projects/PROJECT_ID/locations/LOCATION/instances/my-instance/datasets/my-dataset",
    "endTime": "2023-01-01T00:00:00Z",
    "predictionPeriods": "12",
    "outputs": {
      "predictionDestination": {
        "tableUri": "bq://PROJECT_ID.my_bq_output_dataset.my_prediction_results",
        "writeDisposition": "WRITE_TRUNCATE"
      },
      "explainabilityDestination": {
        "tableUri": "bq://PROJECT_ID.my_bq_output_dataset.my_prediction_results_explainability",
        "writeDisposition": "WRITE_TRUNCATE"
      }
    }
}
'@  | Out-File -FilePath request.json -Encoding utf8

然后，执行以下命令以发送 REST 请求：

$cred = gcloud auth print-access-token
$headers = @{ "Authorization" = "Bearer $cred" }

Invoke-WebRequest `
    -Method POST `
    -Headers $headers `
    -ContentType: "application/json; charset=utf-8" `
    -InFile request.json `
    -Uri "https://financialservices.googleapis.com/v1/projects/PROJECT_ID/locations/LOCATION/instances/my-instance/predictionResults?prediction_result_id=my-prediction-results" | Select-Object -Expand Content

您应该收到类似以下内容的 JSON 响应：

{
  "name": "projects/PROJECT_ID/locations/LOCATION/operations/OPERATION_ID",
  "metadata": {
    "@type": "type.googleapis.com/google.cloud.financialservices.v1.OperationMetadata",
    "createTime": CREATE_TIME,
    "target": "projects/PROJECT_ID/locations/LOCATION/instances/my-instance/predictionResults/my-prediction-results",
    "verb": "create",
    "requestedCancellation": false,
    "apiVersion": "v1"
  },
  "done": false
}

在 Google Cloud 控制台中分析单个结构设计案例

在 Google Cloud 控制台中打开 BigQuery。确保 SQL 工作区。

开始 Google Cloud 控制台
BigQuery 页面包含三个主要部分：
- BigQuery 导航菜单
- 浏览器窗格
- “详细信息”窗格
在详细信息窗格中，点击编写新查询以打开查询编辑器。
将以下 SQL 语句复制到编辑器中，然后点击运行。
```
SELECT *
FROM `PROJECT_ID.my_bq_input_dataset.transaction`
WHERE account_id = '1E60OAUNKP84WDKB' AND DATE_TRUNC(book_time, MONTH) = "2022-08-01"
ORDER by book_time
```
此对账单会在 2022 年 8 月检查账号 ID 1E60OAUNKP84WDKB。这个账号已关联至方 ID EGS4NJD38JZ8NTL8。您可以 AccountPartyLink 表格，针对指定账号 ID 进行衡量。

交易数据显示了针对这看起来很可疑
将以下 SQL 语句复制到编辑器中，然后点击运行。
```
SELECT *
FROM `PROJECT_ID.my_bq_input_dataset.risk_case_event`
WHERE party_id = 'EGS4NJD38JZ8NTL8'
```
此语句表明存在导致此退出。风险案例在可疑活动两个月后开始。
将以下 SQL 语句复制到编辑器中，然后点击运行。
```
SELECT *
FROM `PROJECT_ID.my_bq_output_dataset.my_prediction_results`
WHERE party_id = 'EGS4NJD38JZ8NTL8'
ORDER BY risk_period_end_time
```
通过查看预测结果，您可以看到一方的风险得分从接近于零（注意指数值）跳到个月后。您的结果可能与条结果。

风险得分并非概率，风险评分应始终为是相对于其他风险得分进行评估的。例如，一个看起来很小的值，在其他风险得分较低的情况下则可以视为正例。

将以下 SQL 语句复制到编辑器中，然后点击运行。

SELECT *
FROM `PROJECT_ID.my_bq_output_dataset.my_prediction_results_explainability`
WHERE party_id = 'EGS4NJD38JZ8NTL8'
AND risk_period_end_time = '2022-10-01'

通过检查可解释性结果，您可以看到正确的特征得分最高。

预测的可解释性结果。

清理

为避免因本页面中使用的资源导致您的 Google Cloud 账号产生费用，请删除包含这些资源的 Google Cloud 项目。

删除预测结果

要删除预测结果，请使用 projects.locations.instances.predictionResults.delete 方法。

如需发送请求，请选择以下方式之一：

curl

执行以下命令：

curl -X DELETE \
     -H "Authorization: Bearer $(gcloud auth print-access-token)" \
     "https://financialservices.googleapis.com/v1/projects/PROJECT_ID/locations/LOCATION/instances/my-instance/predictionResults/my-prediction-results"

PowerShell

注意：以下命令假定您已使用您的用户账号通过运行 gcloud init 或 gcloud auth login 登录 gcloud CLI。您可以运行 gcloud auth list 来检查当前活跃的账号。

执行以下命令：

$cred = gcloud auth print-access-token
$headers = @{ "Authorization" = "Bearer $cred" }

Invoke-WebRequest `
    -Method DELETE `
    -Headers $headers `
    -Uri "https://financialservices.googleapis.com/v1/projects/PROJECT_ID/locations/LOCATION/instances/my-instance/predictionResults/my-prediction-results" | Select-Object -Expand Content

您应该收到类似以下内容的 JSON 响应：

{
  "name": "projects/PROJECT_ID/locations/LOCATION/operations/OPERATION_ID",
  "metadata": {
    "@type": "type.googleapis.com/google.cloud.financialservices.v1.OperationMetadata",
    "createTime": CREATE_TIME,
    "target": "projects/PROJECT_ID/locations/LOCATION/instances/my-instance/predictionResults/my-prediction-results",
    "verb": "delete",
    "requestedCancellation": false,
    "apiVersion": "v1"
  },
  "done": false
}

删除回测结果

要删除回测结果，请使用 projects.locations.instances.backtestResults.delete 方法。

如需发送请求，请选择以下方式之一：

curl

执行以下命令：

curl -X DELETE \
     -H "Authorization: Bearer $(gcloud auth print-access-token)" \
     "https://financialservices.googleapis.com/v1/projects/PROJECT_ID/locations/LOCATION/instances/my-instance/backtestResults/my-backtest-results"

PowerShell

注意：以下命令假定您已使用您的用户账号通过运行 gcloud init 或 gcloud auth login 登录 gcloud CLI。您可以运行 gcloud auth list 来检查当前活跃的账号。

执行以下命令：

$cred = gcloud auth print-access-token
$headers = @{ "Authorization" = "Bearer $cred" }

Invoke-WebRequest `
    -Method DELETE `
    -Headers $headers `
    -Uri "https://financialservices.googleapis.com/v1/projects/PROJECT_ID/locations/LOCATION/instances/my-instance/backtestResults/my-backtest-results" | Select-Object -Expand Content

您应该收到类似以下内容的 JSON 响应：

{
  "name": "projects/PROJECT_ID/locations/LOCATION/operations/OPERATION_ID",
  "metadata": {
    "@type": "type.googleapis.com/google.cloud.financialservices.v1.OperationMetadata",
    "createTime": CREATE_TIME,
    "target": "projects/PROJECT_ID/locations/LOCATION/instances/my-instance/backtestResults/my-backtest-results",
    "verb": "delete",
    "requestedCancellation": false,
    "apiVersion": "v1"
  },
  "done": false
}

删除模型

如需删除模型，请使用 projects.locations.instances.models.delete 方法。

如需发送请求，请选择以下方式之一：

curl

执行以下命令：

curl -X DELETE \
     -H "Authorization: Bearer $(gcloud auth print-access-token)" \
     "https://financialservices.googleapis.com/v1/projects/PROJECT_ID/locations/LOCATION/instances/my-instance/models/my-model"

PowerShell

注意：以下命令假定您已使用您的用户账号通过运行 gcloud init 或 gcloud auth login 登录 gcloud CLI。您可以运行 gcloud auth list 来检查当前活跃的账号。

执行以下命令：

$cred = gcloud auth print-access-token
$headers = @{ "Authorization" = "Bearer $cred" }

Invoke-WebRequest `
    -Method DELETE `
    -Headers $headers `
    -Uri "https://financialservices.googleapis.com/v1/projects/PROJECT_ID/locations/LOCATION/instances/my-instance/models/my-model" | Select-Object -Expand Content

您应该收到类似以下内容的 JSON 响应：

{
  "name": "projects/PROJECT_ID/locations/LOCATION/operations/OPERATION_ID",
  "metadata": {
    "@type": "type.googleapis.com/google.cloud.financialservices.v1.OperationMetadata",
    "createTime": CREATE_TIME,
    "target": "projects/PROJECT_ID/locations/LOCATION/instances/my-instance/models/my-model",
    "verb": "delete",
    "requestedCancellation": false,
    "apiVersion": "v1"
  },
  "done": false
}

删除引擎配置

如需删除引擎配置，请使用 projects.locations.instances.engineConfigs.delete 方法。

如需发送请求，请选择以下方式之一：

curl

执行以下命令：

curl -X DELETE \
     -H "Authorization: Bearer $(gcloud auth print-access-token)" \
     "https://financialservices.googleapis.com/v1/projects/PROJECT_ID/locations/LOCATION/instances/my-instance/engineConfigs/my-engine-config"

PowerShell

注意：以下命令假定您已使用您的用户账号通过运行 gcloud init 或 gcloud auth login 登录 gcloud CLI。您可以运行 gcloud auth list 来检查当前活跃的账号。

执行以下命令：

$cred = gcloud auth print-access-token
$headers = @{ "Authorization" = "Bearer $cred" }

Invoke-WebRequest `
    -Method DELETE `
    -Headers $headers `
    -Uri "https://financialservices.googleapis.com/v1/projects/PROJECT_ID/locations/LOCATION/instances/my-instance/engineConfigs/my-engine-config" | Select-Object -Expand Content

您应该收到类似以下内容的 JSON 响应：

{
  "name": "projects/PROJECT_ID/locations/LOCATION/operations/OPERATION_ID",
  "metadata": {
    "@type": "type.googleapis.com/google.cloud.financialservices.v1.OperationMetadata",
    "createTime": CREATE_TIME,
    "target": "projects/PROJECT_ID/locations/LOCATION/instances/my-instance/engineConfigs/my-engine-config",
    "verb": "delete",
    "requestedCancellation": false,
    "apiVersion": "v1"
  },
  "done": false
}

删除数据集

如需删除数据集，请使用 projects.locations.instances.datasets.delete 方法。

如需发送请求，请选择以下方式之一：

curl

执行以下命令：

curl -X DELETE \
     -H "Authorization: Bearer $(gcloud auth print-access-token)" \
     "https://financialservices.googleapis.com/v1/projects/PROJECT_ID/locations/LOCATION/instances/my-instance/datasets/my-dataset"

PowerShell

注意：以下命令假定您已使用您的用户账号通过运行 gcloud init 或 gcloud auth login 登录 gcloud CLI。您可以运行 gcloud auth list 来检查当前活跃的账号。

执行以下命令：

$cred = gcloud auth print-access-token
$headers = @{ "Authorization" = "Bearer $cred" }

Invoke-WebRequest `
    -Method DELETE `
    -Headers $headers `
    -Uri "https://financialservices.googleapis.com/v1/projects/PROJECT_ID/locations/LOCATION/instances/my-instance/datasets/my-dataset" | Select-Object -Expand Content

您应该收到类似以下内容的 JSON 响应：

{
  "name": "projects/PROJECT_ID/locations/LOCATION/operations/OPERATION_ID",
  "metadata": {
    "@type": "type.googleapis.com/google.cloud.financialservices.v1.OperationMetadata",
    "createTime": CREATE_TIME,
    "target": "projects/PROJECT_ID/locations/LOCATION/instances/my-instance/datasets/my-dataset",
    "verb": "delete",
    "requestedCancellation": false,
    "apiVersion": "v1"
  },
  "done": false
}

删除实例

如需删除实例，请使用 projects.locations.instances.delete 方法。

如需发送请求，请选择以下方式之一：

curl

执行以下命令：

curl -X DELETE \
     -H "Authorization: Bearer $(gcloud auth print-access-token)" \
     "https://financialservices.googleapis.com/v1/projects/PROJECT_ID/locations/LOCATION/instances/my-instance"

PowerShell

注意：以下命令假定您已使用您的用户账号通过运行 gcloud init 或 gcloud auth login 登录 gcloud CLI。您可以运行 gcloud auth list 来检查当前活跃的账号。

执行以下命令：

$cred = gcloud auth print-access-token
$headers = @{ "Authorization" = "Bearer $cred" }

Invoke-WebRequest `
    -Method DELETE `
    -Headers $headers `
    -Uri "https://financialservices.googleapis.com/v1/projects/PROJECT_ID/locations/LOCATION/instances/my-instance" | Select-Object -Expand Content

您应该收到类似以下内容的 JSON 响应：

{
  "name": "projects/PROJECT_ID/locations/LOCATION/operations/OPERATION_ID",
  "metadata": {
    "@type": "type.googleapis.com/google.cloud.financialservices.v1.OperationMetadata",
    "createTime": CREATE_TIME,
    "target": "projects/PROJECT_ID/locations/LOCATION/instances/my-instance",
    "verb": "delete",
    "requestedCancellation": false,
    "apiVersion": "v1"
  },
  "done": false
}

删除 BigQuery 数据集

bq rm -r -f -d PROJECT_ID:my_bq_input_dataset
bq rm -r -f -d PROJECT_ID:my_bq_output_dataset

后续步骤

如需了解关键概念，请参阅概览
查看参考文档