Modelo do Google Ads para o BigQuery

O modelo do Google Ads para BigQuery é um pipeline em lote que lê relatórios do Google Ads e grava no BigQuery.

Requisitos de pipeline

  • Os IDs das contas do Google Ads a serem usados.
  • A consulta da linguagem de consulta do Google Ads para receber os dados.
  • Credenciais OAuth para a API Google Ads.

Parâmetros do modelo

Parâmetros obrigatórios

Parâmetros opcionais

Executar o modelo

  1. Acesse a página Criar job usando um modelo do Dataflow.
  2. Acesse Criar job usando um modelo
  3. No campo Nome do job, insira um nome exclusivo.
  4. Opcional: em Endpoint regional, selecione um valor no menu suspenso. A região padrão é us-central1.

    Para ver uma lista de regiões em que é possível executar um job do Dataflow, consulte Locais do Dataflow.

  5. No menu suspenso Modelo do Dataflow, selecione the Google Ads to BigQuery template.
  6. Nos campos de parâmetro fornecidos, insira os valores de parâmetro.
  7. Cliquem em Executar job.

No shell ou no terminal, execute o modelo:

gcloud dataflow flex-template run JOB_NAME \
    --template-file-gcs-location=gs://dataflow-templates-REGION_NAME/VERSION/flex/Google_Ads_to_BigQuery \
    --project=PROJECT_ID \
    --region=REGION_NAME \
    --parameters \
       customerIds=CUSTOMER_IDS,\
       query=QUERY,\
       qpsPerWorker=QPS_PER_WORKER,\
       googleAdsClientId=GOOGLE_ADS_CLIENT_ID,\
       googleAdsClientSecret=GOOGLE_ADS_CLIENT_SECRET,\
       googleAdsRefreshToken=GOOGLE_ADS_REFRESH_TOKEN,\
       googleAdsDeveloperToken=GOOGLE_ADS_DEVELOPER_TOKEN,\
       outputTableSpec=OUTPUT_TABLE_SPEC,\

Substitua:

  • JOB_NAME: um nome de job de sua escolha
  • VERSION: a versão do modelo que você quer usar

    Use estes valores:

  • REGION_NAME: a região em que você quer implantar o job do Dataflow, por exemplo, us-central1
  • CUSTOMER_IDS: os IDs das contas do Google Ads.
  • QUERY: a consulta da linguagem de consulta do Google Ads
  • QPS_PER_WORKER: a taxa de solicitação do Google Ads necessária por worker
  • GOOGLE_ADS_CLIENT_ID: o ID do cliente OAuth 2.0 que identifica o aplicativo.
  • GOOGLE_ADS_CLIENT_SECRET: a chave secreta do cliente OAuth 2.0 correspondente ao ID do cliente especificado.
  • GOOGLE_ADS_REFRESH_TOKEN: o token de atualização do OAuth 2.0 a ser usado para se conectar à API Google Ads.
  • GOOGLE_ADS_DEVELOPER_TOKEN: o token de desenvolvedor do Google Ads que será usado para se conectar à API Google Ads.
  • OUTPUT_TABLE_SPEC: a tabela de saída do BigQuery.

Para executar o modelo usando a API REST, envie uma solicitação HTTP POST. Para mais informações sobre a API e os respectivos escopos de autorização, consulte projects.templates.launch.

POST https://dataflow.googleapis.com/v1b3/projects/PROJECT_ID/locations/LOCATION/flexTemplates:launch
{
   "launchParameter": {
     "jobName": "JOB_NAME",
     "parameters": {
       "customerIds": "CUSTOMER_IDS",
       "query": "QUERY",
       "qpsPerWorker": "QPS_PER_WORKER",
       "googleAdsClientId": "GOOGLE_ADS_CLIENT_ID",
       "googleAdsClientSecret": "GOOGLE_ADS_CLIENT_SECRET",
       "googleAdsRefreshToken": "GOOGLE_ADS_REFRESH_TOKEN",
       "googleAdsDeveloperToken": "GOOGLE_ADS_DEVELOPER_TOKEN",
       "outputTableSpec": "OUTPUT_TABLE_SPEC",
     },
     "containerSpecGcsPath": "gs://dataflow-templates-LOCATION/VERSION/flex/Google_Ads_to_BigQuery",
     "environment": { "maxWorkers": "10" }
  }
}

Substitua:

  • PROJECT_ID: o ID do projeto do Google Cloud em que você quer executar o job do Dataflow
  • JOB_NAME: um nome de job de sua escolha
  • VERSION: a versão do modelo que você quer usar

    Use estes valores:

  • LOCATION: a região em que você quer implantar o job do Dataflow, por exemplo, us-central1
  • CUSTOMER_IDS: os IDs das contas do Google Ads.
  • QUERY: a consulta da linguagem de consulta do Google Ads
  • QPS_PER_WORKER: a taxa de solicitação do Google Ads necessária por worker
  • GOOGLE_ADS_CLIENT_ID: o ID do cliente OAuth 2.0 que identifica o aplicativo.
  • GOOGLE_ADS_CLIENT_SECRET: a chave secreta do cliente OAuth 2.0 correspondente ao ID do cliente especificado.
  • GOOGLE_ADS_REFRESH_TOKEN: o token de atualização do OAuth 2.0 a ser usado para se conectar à API Google Ads.
  • GOOGLE_ADS_DEVELOPER_TOKEN: o token de desenvolvedor do Google Ads que será usado para se conectar à API Google Ads.
  • OUTPUT_TABLE_SPEC: a tabela de saída do BigQuery.
Java
/*
 * Copyright (C) 2023 Google LLC
 *
 * Licensed under the Apache License, Version 2.0 (the "License"); you may not
 * use this file except in compliance with the License. You may obtain a copy of
 * the License at
 *
 *   http://www.apache.org/licenses/LICENSE-2.0
 *
 * Unless required by applicable law or agreed to in writing, software
 * distributed under the License is distributed on an "AS IS" BASIS, WITHOUT
 * WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the
 * License for the specific language governing permissions and limitations under
 * the License.
 */
package com.google.cloud.teleport.v2.templates;

import com.google.ads.googleads.v17.services.GoogleAdsRow;
import com.google.cloud.teleport.metadata.Template;
import com.google.cloud.teleport.metadata.TemplateCategory;
import com.google.cloud.teleport.metadata.TemplateParameter;
import com.google.cloud.teleport.v2.options.BigQueryCommonOptions.WriteOptions;
import com.google.cloud.teleport.v2.transforms.BigQueryConverters;
import com.google.cloud.teleport.v2.transforms.GoogleAdsRowToReportRowJsonFn;
import com.google.cloud.teleport.v2.utils.GCSUtils;
import com.google.cloud.teleport.v2.utils.GoogleAdsRateLimitPolicyFactory;
import com.google.cloud.teleport.v2.utils.GoogleAdsUtils;
import com.google.common.collect.ImmutableList;
import java.util.List;
import org.apache.beam.sdk.Pipeline;
import org.apache.beam.sdk.PipelineResult;
import org.apache.beam.sdk.io.gcp.bigquery.BigQueryIO;
import org.apache.beam.sdk.io.gcp.bigquery.BigQueryIO.Write;
import org.apache.beam.sdk.io.gcp.bigquery.BigQueryIO.Write.CreateDisposition;
import org.apache.beam.sdk.io.gcp.bigquery.BigQueryIO.Write.WriteDisposition;
import org.apache.beam.sdk.io.googleads.GoogleAdsIO;
import org.apache.beam.sdk.io.googleads.GoogleAdsOptions;
import org.apache.beam.sdk.options.PipelineOptionsFactory;
import org.apache.beam.sdk.options.Validation;
import org.apache.beam.sdk.transforms.Create;
import org.apache.beam.sdk.transforms.ParDo;
import org.apache.beam.sdk.values.PCollection;
import org.apache.beam.vendor.guava.v32_1_2_jre.com.google.common.base.Strings;
import org.slf4j.Logger;
import org.slf4j.LoggerFactory;

/**
 * A template for writing <a href=
 * "https://developers.google.com/google-ads/api/docs/reporting/overview">Google Ads reports</a> to
 * BigQuery.
 *
 * <p>Nested fields are lifted to top-level fields by replacing the dots in field paths with
 * underscores.
 *
 * <p>Check out <a
 * href="https://github.com/GoogleCloudPlatform/DataflowTemplates/blob/main/v2/README_Google_Ads_to_BigQuery.md">README</a>
 * for instructions on how to use or modify this template.
 */
@Template(
    name = "Google_Ads_to_BigQuery",
    category = TemplateCategory.BATCH,
    displayName = "Google Ads to BigQuery",
    description =
        "The Google Ads to BigQuery template is a batch pipeline that reads Google Ads reports and writes to BigQuery.",
    optionsClass = GoogleAdsToBigQuery.GoogleAdsToBigQueryOptions.class,
    flexContainerName = "google-ads-to-bigquery",
    contactInformation = "https://cloud.google.com/support",
    documentation =
        "https://cloud.google.com/dataflow/docs/guides/templates/provided/google-ads-to-bigquery",
    requirements = {
      "The Google Ads account IDs to use.",
      "The Google Ads Query Language query to obtain information.",
      "OAuth credentials for the Google Ads API."
    },
    preview = true)
public final class GoogleAdsToBigQuery {
  public interface GoogleAdsToBigQueryOptions extends WriteOptions, GoogleAdsOptions {
    @TemplateParameter.Long(
        order = 1,
        optional = true,
        description = "Google Ads manager account ID",
        helpText = "A Google Ads manager account ID to use to access the account IDs.",
        example = "12345")
    Long getLoginCustomerId();

    void setLoginCustomerId(Long loginCustomerId);

    @TemplateParameter.Text(
        order = 2,
        regexes = {"^[0-9]+(,[0-9]+)*$"},
        description = "Google Ads account IDs",
        helpText = "A list of Google Ads account IDs to use to execute the query.",
        example = "12345,67890")
    @Validation.Required
    List<Long> getCustomerIds();

    void setCustomerIds(List<Long> customerIds);

    @TemplateParameter.Text(
        order = 3,
        description = "Google Ads Query Language query",
        helpText =
            "The query to use to get the data. See Google Ads Query Language (https://developers.google.com/google-ads/api/docs/query/overview).",
        example = "SELECT campaign.id, campaign.name FROM campaign")
    @Validation.Required
    String getQuery();

    void setQuery(String query);

    @TemplateParameter.Double(
        order = 4,
        description = "Required Google Ads request rate per worker",
        helpText =
            "The rate of query requests per second (QPS) to submit to Google Ads.  "
                + "Divide the desired per pipeline QPS by the maximum number of workers. "
                + "Avoid exceeding per-account or developer token limits. "
                + "See Rate Limits (https://developers.google.com/google-ads/api/docs/best-practices/rate-limits).")
    Double getQpsPerWorker();

    void setQpsPerWorker(Double qpsPerWorker);

    @TemplateParameter.GcsReadFile(
        order = 5,
        optional = true,
        description = "BigQuery Table Schema Path",
        helpText =
            "The Cloud Storage path to the BigQuery schema JSON file. "
                + "If this value is not set, then the schema is inferred "
                + "from the Proto schema.",
        example = "gs://MyBucket/bq_schema.json")
    String getBigQueryTableSchemaPath();

    void setBigQueryTableSchemaPath(String value);

    @TemplateParameter.Text(
        order = 6,
        description = "OAuth 2.0 Client ID identifying the application",
        helpText =
            "The OAuth 2.0 client ID that identifies the application. See Create a client ID and client secret (https://developers.google.com/google-ads/api/docs/oauth/cloud-project#create_a_client_id_and_client_secret).")
    String getGoogleAdsClientId();

    void setGoogleAdsClientId(String clientId);

    @TemplateParameter.Password(
        order = 7,
        groupName = "Source",
        description = "OAuth 2.0 Client Secret for the specified Client ID",
        helpText =
            "The OAuth 2.0 client secret that corresponds to the specified client ID. See Create a client ID and client secret (https://developers.google.com/google-ads/api/docs/oauth/cloud-project#create_a_client_id_and_client_secret).")
    String getGoogleAdsClientSecret();

    void setGoogleAdsClientSecret(String clientSecret);

    @TemplateParameter.Password(
        order = 8,
        description = "OAuth 2.0 Refresh Token for the user connecting to the Google Ads API",
        helpText =
            "The OAuth 2.0 refresh token to use to connect to the Google Ads API. See 2-Step Verification (https://developers.google.com/google-ads/api/docs/oauth/2sv).")
    String getGoogleAdsRefreshToken();

    void setGoogleAdsRefreshToken(String refreshToken);

    @TemplateParameter.Password(
        order = 9,
        description = "Google Ads developer token for the user connecting to the Google Ads API",
        helpText =
            "The Google Ads developer token to use to connect to the Google Ads API. See Obtain a developer token (https://developers.google.com/google-ads/api/docs/get-started/dev-token).")
    String getGoogleAdsDeveloperToken();

    void setGoogleAdsDeveloperToken(String developerToken);
  }

  private static final Logger LOG = LoggerFactory.getLogger(GoogleAdsToBigQuery.class);

  public static void main(String[] args) {
    run(
        PipelineOptionsFactory.fromArgs(args)
            .withValidation()
            .as(GoogleAdsToBigQueryOptions.class));
  }

  public static PipelineResult run(GoogleAdsToBigQueryOptions options) {
    Pipeline pipeline = Pipeline.create(options);
    double qps = options.getQpsPerWorker();
    String query = options.getQuery();

    PCollection<GoogleAdsRow> googleAdsRows =
        pipeline
            .apply(
                Create.of(
                    options.getCustomerIds().stream()
                        .map(Object::toString)
                        .collect(ImmutableList.toImmutableList())))
            .apply(
                GoogleAdsIO.v17()
                    .read()
                    .withDeveloperToken(options.getGoogleAdsDeveloperToken())
                    .withLoginCustomerId(options.getLoginCustomerId())
                    .withQuery(options.getQuery())
                    .withRateLimitPolicy(new GoogleAdsRateLimitPolicyFactory(qps)));

    PCollection<String> reportRows =
        googleAdsRows.apply(ParDo.of(new GoogleAdsRowToReportRowJsonFn(query)));

    Write<String> write =
        BigQueryIO.<String>write()
            .withoutValidation()
            .withWriteDisposition(WriteDisposition.valueOf(options.getWriteDisposition()))
            .withCreateDisposition(CreateDisposition.valueOf(options.getCreateDisposition()))
            .withFormatFunction(BigQueryConverters::convertJsonToTableRow)
            .to(options.getOutputTableSpec());

    String schemaPath = options.getBigQueryTableSchemaPath();

    if (Strings.isNullOrEmpty(schemaPath)) {
      write = write.withSchema(GoogleAdsUtils.createBigQuerySchema(query));
    } else {
      write = write.withJsonSchema(GCSUtils.getGcsFileAsString(schemaPath));
    }

    reportRows.apply("WriteToBigQuery", write);

    return pipeline.run();
  }
}

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