Amazon Ads Import Integration DSP Report

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This integration enables the configuration of Amazon Ads reports and allows you to ingest the content of those reports directly into Treasure Data.

Prerequisites

• Basic Knowledge of Treasure Data
• Basic knowledge of Amazon Ads

Requirements and Limitations

• Amazon Ads report metrics and data are controlled by Amazon Ads.

• This integration only triggers a report that is already configured in Amazon Ads.

Static IP Address of Treasure Data

The static IP address of Treasure Data is the access point and source of the linkage for this Integration. To determine the static IP address, contact your Customer Success representative or technical support.

Import Amazon Ads reports via TD Console

Create Authentication

Your first step is to create a new authentication with a set of credentials.

1. Select Integrations Hub.
2. Select Catalog.
3. Search for your Amazon Ads in the Catalog; hover your mouse over the icon and select Create Authentication.

4. Ensure that the Credentials tab is selected and then enter the OAuth connection credential for the integration. 5. Select Continue. 6. Enter a name for your authentication, and then select Done.

Create a Source

After the authentication becomes available on the console, configure your import job.

1. Open TD Console.
2. Navigate to Integrations Hub > Authentications.
3. Locate your Amazon Ads authentication and select New Source.

Connection Details

Source Table

1. Select Next.

Data Preview

You can see a preview of your data before running the import by selecting Generate Preview. Data preview is optional and you can safely skip to the next page of the dialog if you choose to.

1. Select Next. The Data Preview page opens.
2. If you want to preview your data, select Generate Preview.
3. Verify the data.

Data Placement

For data placement, select the target database and table where you want your data placed and indicate how often the import should run.

1. Select Next. Under Storage, you will create a new or select an existing database and create a new or select an existing table for where you want to place the imported data.

2. Select a Database > Select an existing or Create New Database.

3. Optionally, type a database name.

4. Select a Table> Select an existing or Create New Table.

5. Optionally, type a table name.

6. Choose the method for importing the data.

   • Append (default)-Data import results are appended to the table. If the table does not exist, it will be created.
   • Always Replace-Replaces the entire content of an existing table with the result output of the query. If the table does not exist, a new table is created.
   • Replace on New Data-Only replace the entire content of an existing table with the result output when there is new data.

7. Select the Timestamp-based Partition Key column. If you want to set a different partition key seed than the default key, you can specify the long or timestamp column as the partitioning time. As a default time column, it uses upload_time with the add_time filter.

8. Select the Timezone for your data storage.

9. Under Schedule, you can choose when and how often you want to run this query.

Run once

1. Select Off.
2. Select Scheduling Timezone.
3. Select Create & Run Now.

Repeat Regularly

1. Select On.
2. Select the Schedule. The UI provides these four options: @hourly, @daily and @monthly or custom cron.
3. You can also select Delay Transfer and add a delay of execution time.
4. Select Scheduling Timezone.
5. Select Create & Run Now.

After your transfer has run, you can see the results of your transfer in Data Workbench > Databases.

Import from Amazon Ads reports via Workflow

You can import data from Amazon Ads reports via workflow using td_load>: src_id. If you have already created a source, you can run it; if you don't want to create a source, you can import it using a .yml file.

Using a Source or YML File

Using a Source

1. Select Integrations Hub > Sources.
2. On the Filters pane, select Amazon Ads from the Integration Type drop-down menu.
3. Select the ••• icon, and then select Copy Unique ID.

1. Define a workflow task using td_load>: sourceId

+load:
   td_load>: unique_id_of_your_source
   database: ${td.dest_db}
   table: ${td.dest_table}

2. Run a workflow.

Using a yml/yaml file

1. Identify your yml file.

   If you need to create the yml/yaml file, use the instructions found in Create Seed Config File (seed.yml) as a reference.

2. Define a workflow task using td_load>: <.yml file>

+load:  
   td_load>: config/daily_load.yml  
   database: ${td.dest_db}
   table: ${td.dest_table}

3. Run a workflow.

Sample Workflow Code

Visit Treasure Boxes for a sample workflow code.

Import from Amazon Ads via CLI (Toolbelt)

Before setting up the integration, install the latest version of the TD Toolbelt.

Create Seed Configuration File (seed.yml)

in:
  type: "amazon_ads"
  td_authentication_id: <td_authentication_id>
  data_type: "DSP_REPORT"  
  profile_marketplace: "US"  
  advertiser_ids: "advertiser_id_comma_separated_values"  
  report_type: "CAMPAIGN"  
  group_by: "campaign, ad, creative"  
  time_unit: "SUMMARY"  
  report_period: CUSTOM  
  start_date: "2024-05-05"  
  end_date: "2024-05-31"  
  base_metrics: true
out:
  mode: append

Parameters Reference

Generate load.yml

Use connector:guess to generate the load.yml file. This command automatically reads the source files and makes a best guess at the file format and its fields and columns.

$ td connector:guess seed.yml -o load.yml

You can open the load.yml to review the file format definitions including file formats, encodings, column names, and types.

Example load.yml

in:
  type: amazon_ads
  data_type: DSP_REPORT
  profile_marketplace: US
  advertiser_ids: '123123123123123'
  report_type: CAMPAIGN
  group_by: campaign, ad, creative
  time_unit: SUMMARY
  report_period: CUSTOM
  start_date: '2024-07-05'
  end_date: '2024-07-31'
  base_metrics: true
  td_authentication_id: <td_authentication_id>
out: {mode: append}
exec: {}filters:
- rules:
  - {rule: upper_to_lower}
  - pass_types:
    - a-z
    - 0-9
    pass_characters: _
    replace: _
    rule: character_types
 - pass_types:
   - a-z
   pass_characters: _
   prefix: _
   rule: first_character_types
 - {rule: unique_number_suffix, max_length: 128}
 type: rename
 - from_value: {mode: upload_time}
 to_column: {name: time}
 type: add_time

To preview the data, use the td connector:preview command.

td connector:preview

Execute the Load Job

It might take a couple of hours, depending on the size of the data. Be sure to specify the Treasure Data database and table where the data should be stored.  Treasure Data also recommends specifying the --time-column option because Treasure Data’s storage is partitioned by time (see data partitioning). If this option is not provided, the data connector chooses the first long or timestamp column as the partitioning time. The type of the column specified by --time-column must be either of long and timestamp type.

If your data doesn’t have a time column, you can add a time column by using the add_time filter option. For more details see the documentation for the add_time Filter Function.

$ td connector:issue load.yml --database td_sample_db --table td_sample_table \--time-column created_at

The connector:issue command assumes that you have already created a database(td_sample_db) and a table(td_sample_table). If the database or the table does not exist in TD, this command fails. Create the database and table manually or use --auto-create-table option with td connector:issue command to auto-create the database and table.

$ td connector:issue load.yml --database td_sample_db --table td_sample_table--time-column created_at --auto-create-table

The data connector does not sort records on the server side. To use time-based partitioning effectively, sort records in files beforehand.

If you have a field called time, you don’t have to specify the --time-column option.

$ td connector:issue load.yml --database td_sample_db --table td_sample_table

Import Modes

Specify the file import mode in the out: section of the load.yml file. The out: section controls how data is imported into a Treasure Data table. For example, you may choose to append data or replace data in an existing table.

See Also

For additional information about Amazon Ads Report V3, refer to the following Amazon documentation:

• Amazon Ads Report Types
• Amazon Ads API Reference Creating a Report Request