DoubleClick Campaign Manager Transfers

The BigQuery Data Transfer Service for DoubleClick allows you to automatically schedule and manage recurring load jobs for DoubleClick reporting data.

Supported Reports

The BigQuery Data Transfer Service for DoubleClick Campaign Manager currently supports the following reporting options:

Reporting option Support
Supported API version June 26, 2017
Schedule

Every 8 hours, based on the creation time.

Not configurable

Refresh window

Last 2 days

Not configurable

Maximum backfill duration

Last 60 days

DoubleClick Campaign Manager retains Data Transfer files for up to 60 days. Files older than 60 days are deleted by DoubleClick Campaign Manager.

Before you begin

Before you create a DoubleClick Campaign Manager transfer:

  • Verify that you have completed all actions required to enable the BigQuery Data Transfer Service.
  • Create a BigQuery dataset to store the DoubleClick data.
  • Ensure that your organization has access to DoubleClick Campaign Manager Data Transfer v2 (DCM DTv2) files. These files are delivered by the DoubleClick team to a Google Cloud Storage bucket. To gain access to DCM DTv2 files, your next step depends on if you have a direct contract with DoubleClick Campaign Manager. In both cases, additional fees might apply.

    If you have a contract with DoubleClick Campaign Manager, contact DoubleClick Campaign Manager support to setup DCM DTv2 files.

    If you do not have a contract with DoubleClick Campaign Manager, your agency or DoubleClick reseller may have access to DCM DTv2 files. Contact your agency or reseller for access to these files.

    After completing this step, you will receive a Google Cloud Storage bucket similar to the following:

    dcdt_-dcm_account1234

    The Google Cloud team does NOT have the ability to generate or grant access to DCM DTv2 files on your behalf. Contact DoubleClick Campaign Manager support, your agency, or your DoubleClick reseller for access to DCM DTv2 files.

  • Ensure that you have the following required permissions:
    • DoubleClick Campaign Manager: Read access to the DCM DTv2 files stored in Google Cloud Storage. Access is managed by the entity from which you received the Google Cloud Storage bucket.
    • Google Cloud Platform: bigquery.transfers.update permission. The bigquery.admin predefined IAM role includes bigquery.transfers.update permissions. For more information on IAM roles in BigQuery, see Access Control.

Setting up a DoubleClick Campaign Manager transfer

Setting up a DoubleClick Campaign Manager transfer requires a:

  • GCS Bucket: The Google Cloud Storage bucket URI for your DCM DTv2 files as described in Before you Begin. The bucket name should look like the following:

      dcdt_-dcm_account1234
    
  • DoubleClick ID: Your DoubleClick Network, Advertiser, or Floodlight ID. Network ID is the parent in the hierarchy.

To retrieve your DoubleClick ID, you can use the Google Cloud Storage web UI to examine the files in your DoubleClick Data Transfer Cloud Storage bucket. The DoubleClick ID is used to match files in the provided Cloud Storage bucket. The ID is embedded in the file name, not the Cloud Storage bucket name.

For example:

  • In a file named dcm_account1234_activity_*, the ID is 1234.
  • In a file named dcm_floodlight7890_activity_*, the ID is 7890.
  • In a file named dcm_advertiser567_activity_*, the ID is 567.

To create a BigQuery data transfer for DoubleClick Campaign Manager:

Web UI

  1. Go to the BigQuery web UI.

    Go to the BigQuery web UI

  2. Click Transfers.

  3. Click Add Transfer.

  4. On the New Transfer page:

    • For Source, choose DCM Data Transfer.
    • For Destination, choose the appropriate dataset.
    • For Display Name, enter a name for the transfer such as My Transfer. The transfer name can be any value that allows you to easily identify the transfer if you need to modify it later.
    • For GCS Bucket, enter the name of the Cloud Storage bucket that stores your Data Transfer V2.0 files. When you enter the bucket name, do not include gs://.
    • For DoubleClick ID, enter the appropriate ID.

      Channel transfer

  5. Click Add.

  6. When prompted, click Allow to give the BigQuery Data Transfer Service permission to manage your DoubleClick campaigns. You must allow pop-ups from bigquery.cloud.google.com to view the permissions window.

    Allow transfer

Command-line

Enter the bq mk command and supply the transfer creation flag — --transfer_config. The following flags are also required:

  • --data_source
  • --target_dataset
  • --display_name
  • --params

    bq mk --transfer_config --project_id=[PROJECT_ID] --target_dataset=[DATASET] --display_name=[NAME] --params='[PARAMETERS]' --data_source=[DATA_SOURCE]
    

Where:

  • --project_id is your project ID.
  • --target_dataset is the target dataset for the transfer configuration.
  • --display_name is the display name for the transfer configuration. The transfer name can be any value that allows you to easily identify the transfer if you need to modify it later.
  • --params contains the parameters for the created transfer configuration in JSON format. For example: --params='{"param":"param_value"}'. For DoubleClick Camapaign Manager, you must supply the bucket and network_id, parameters. bucket is the Cloud Storage bucket that contains your DCM DTv2 files. network_id is your network, floodlight, or advertiser ID.
  • --data_source is the data source — dcm_dt (DoubleClick Campaign Manager).

You can also supply the --project_id flag to specify a particular project. If --project_id isn't specified, the default project is used.

For example, the following command creates a DoubleClick Campaign Manager transfer named My Transfer using DoubleClick ID 1234, Cloud Storage bucket dcdt_-dcm_account1234, and target dataset mydataset. The transfer is created in the default project:

bq mk --transfer_config --target_dataset=mydataset --display_name='My Transfer' --params='{"bucket": "dcdt_-dcm_account1234","network_id": "1234"}' --data_source=dcm_dt

After running the command, you receive a message like the following:

[URL omitted] Please copy and paste the above URL into your web browser and follow the instructions to retrieve an authentication code.

Follow the instructions and paste the authentication code on the command line.

API

Use the projects.locations.transferConfigs.create method and supply an instance of the TransferConfig resource.

When your data is transferred to BigQuery, the data is written to date-partitioned tables. For more information, see Partitioned Tables.

If you change the schema of a report, all files on that day must have the same schema, or the transfer for the entire day will fail.

Troubleshooting DoubleClick Campaign Manager transfer setup

If you are having issues setting up your transfer, see DoubleClick Campaign Manager transfer issues in Troubleshooting BigQuery Data Transfer Service Transfer Setup.

DoubleClick sample queries

You can use the following DoubleClick Campaign Manager sample queries to analyze your transferred data. You can also use the queries in a visualization tool such as Google Cloud Datalab or Google Data Studio 360. These queries are provided to help you get started on querying your DoubleClick Campaign Manager data with BigQuery. For additional questions on what you can do with these reports, contact your DoubleClick Campaign Manager technical representative.

These samples use BigQuery’s support for standard SQL. Use the #standardSQL tag to let BigQuery know you want to use standard SQL. For more information about the #standardSQL prefix, see Setting a query prefix.

In each of the following queries, replace [DATASET] with your dataset name. Replace [DOUBLECLICK_ID] with your DoubleClick ID.

Latest campaigns

The following sample query retrieves the latest campaigns.

Web UI

#standardSQL
SELECT Campaign, Campaign_ID FROM `[DATASET].match_table_campaigns_[DOUBLECLICK_ID]`
WHERE _DATA_DATE = _LATEST_DATE

Command-line

bq query --use_legacy_sql=false '
SELECT Campaign, Campaign_ID FROM `[DATASET].match_table_campaigns_[DOUBLECLICK_ID]`
WHERE _DATA_DATE = _LATEST_DATE'

Impressions and distinct users by campaign

The following sample query analyzes the number of impressions and distinct users by campaign over the past 30 days.

Web UI

#standardSQL
# START_DATE = DATE_ADD(CURRENT_DATE(), INTERVAL -31 DAY)
# END_DATE = DATE_ADD(CURRENT_DATE(), INTERVAL -1 DAY)
SELECT Campaign_ID, DATA_DATE AS Date, count(*) AS count, count(distinct User_ID) AS du
FROM `[DATASET].impression[DOUBLECLICK_ID]` WHERE
  _DATA_DATE BETWEEN [START_DATE] AND [END_DATE]
GROUP BY Campaign_ID, Date

Command-line

# START_DATE = DATE_ADD(CURRENT_DATE(), INTERVAL -31 DAY)
# END_DATE = DATE_ADD(CURRENT_DATE(), INTERVAL -1 DAY)
bq query --use_legacy_sql=false '
SELECT Campaign_ID, _DATA_DATE AS Date, count(*) AS count, count(distinct User_ID) AS du
FROM `[DATASET].impression_[DOUBLECLICK_ID]` WHERE
  _DATA_DATE BETWEEN [START_DATE] AND [END_DATE]
GROUP BY Campaign_ID, Date'

Latest campaigns ordered by campaign and date

The following sample query analyzes the latest campaigns in the past 30 days, ordered by campaign and date.

Web UI

#standardSQL
# START_DATE = DATE_ADD(CURRENT_DATE(), INTERVAL -31 DAY)
# END_DATE = DATE_ADD(CURRENT_DATE(), INTERVAL -1 DAY)
SELECT Campaign, Campaign_ID, Date FROM (
SELECT Campaign, Campaign_ID FROM `[DATASET].match_table_campaigns_[DOUBLECLICK_ID]`
  WHERE _DATA_DATE = _LATEST_DATE
), (
SELECT date AS Date
  FROM `bigquery-public-data.common_us.date_greg`
  WHERE Date BETWEEN [START_DATE] AND [END_DATE]
)
ORDER BY
  Campaign_ID, Date

Command-line

# START_DATE = DATE_ADD(CURRENT_DATE(), INTERVAL -31 DAY)
# END_DATE = DATE_ADD(CURRENT_DATE(), INTERVAL -1 DAY)
bq query --use_legacy_sql=false '
SELECT Campaign, Campaign_ID, Date FROM (
SELECT Campaign, Campaign_ID FROM `[DATASET].match_table_campaigns_[DOUBLECLICK_ID]`
  WHERE _DATA_DATE = _LATEST_DATE
), (
SELECT date AS Date
  FROM `bigquery-public-data.common_us.date_greg`
  WHERE Date BETWEEN [START_DATE] AND [END_DATE]
)
ORDER BY
  Campaign_ID, Date'

Impressions and distinct users by campaign within a date range

The following sample query analyzes the number of impressions and distinct users by campaign between [START_DATE] and [END_DATE].

Web UI

#standardSQL
# START_DATE = DATE_ADD(CURRENT_DATE(), INTERVAL -31 DAY)
# END_DATE = DATE_ADD(CURRENT_DATE(), INTERVAL -1 DAY)
SELECT
  base.*,
  imp.count AS imp_count,
  imp.du AS imp_du
FROM (
  SELECT
    *
  FROM (
    SELECT
      Campaign,
      Campaign_ID
    FROM
      `[DATASET].match_table_campaigns_[DOUBLECLICK_ID]`
    WHERE
      DATA_DATE = _LATEST_DATE ),
    (
    SELECT
      date AS Date
    FROM
      `bigquery-public-data.common_us.date_greg`
    WHERE
      Date BETWEEN [START_DATE]
      AND [END_DATE] ) ) AS base
LEFT JOIN (
  SELECT
    Campaign_ID,
    _DATA_DATE AS Date,
    COUNT() AS count,
    COUNT(DISTINCT User_ID) AS du
  FROM
    `[DATASET].impression[DOUBLECLICK_ID]`
  WHERE
    _DATA_DATE BETWEEN [START_DATE]
    AND [END_DATE]
  GROUP BY
    Campaign_ID,
    Date ) AS imp
ON
  base.Campaign_ID = imp.Campaign_ID
  AND base.Date = imp.Date
WHERE
  base.Campaign_ID = imp.Campaign_ID
  AND base.Date = imp.Date
ORDER BY
  base.Campaign_ID,
  base.Date

Command-line

# START_DATE = DATE_ADD(CURRENT_DATE(), INTERVAL -31 DAY)
# END_DATE = DATE_ADD(CURRENT_DATE(), INTERVAL -1 DAY)
bq query --use_legacy_sql=false '
SELECT
  base.*,
  imp.count AS imp_count,
  imp.du AS imp_du
FROM (
  SELECT
    *
  FROM (
    SELECT
      Campaign,
      Campaign_ID
    FROM
      `[DATASET].match_table_campaigns_[DOUBLECLICK_ID]`
    WHERE
      DATA_DATE = _LATEST_DATE ),
    (
    SELECT
      date AS Date
    FROM
      `bigquery-public-data.common_us.date_greg`
    WHERE
      Date BETWEEN [START_DATE]
      AND [END_DATE] ) ) AS base
LEFT JOIN (
  SELECT
    Campaign_ID,
    _DATA_DATE AS Date,
    COUNT() AS count,
    COUNT(DISTINCT User_ID) AS du
  FROM
    `[DATASET].impression[DOUBLECLICK_ID]`
  WHERE
    _DATA_DATE BETWEEN [START_DATE]
    AND [END_DATE]
  GROUP BY
    Campaign_ID,
    Date ) AS imp
ON
  base.Campaign_ID = imp.Campaign_ID
  AND base.Date = imp.Date
WHERE
  base.Campaign_ID = imp.Campaign_ID
  AND base.Date = imp.Date
ORDER BY
  base.Campaign_ID,
  base.Date'

Impressions, clicks, activities and distinct users by campaign

The following sample query analyzes the number of impressions, clicks, activities, and distinct users by campaign over the past 30 days.

Web UI

#standardSQL
# START_DATE = DATE_ADD(CURRENT_DATE(), INTERVAL -31 DAY)
# END_DATE = DATE_ADD(CURRENT_DATE(), INTERVAL -1 DAY)
SELECT
  base.*,
  imp.count AS imp_count,
  imp.du AS imp_du,
  click.count AS click_count,
  click.du AS click_du,
  activity.count AS activity_count,
  activity.du AS activity_du
FROM (
  SELECT
    *
  FROM (
    SELECT
      Campaign,
      Campaign_ID
    FROM
      `[DATASET].match_table_campaigns_[DOUBLECLICK_ID]`
    WHERE
      DATA_DATE = _LATEST_DATE ),
    (
    SELECT
      date AS Date
    FROM
      `bigquery-public-data.common_us.date_greg`
    WHERE
      Date BETWEEN DATE_ADD(CURRENT_DATE(), INTERVAL -31 DAY)
      AND DATE_ADD(CURRENT_DATE(), INTERVAL -1 DAY) ) ) AS base
LEFT JOIN (
  SELECT
    Campaign_ID,
    _DATA_DATE AS Date,
    COUNT() AS count,
    COUNT(DISTINCT User_ID) AS du
  FROM
    `[DATASET].impression[DOUBLECLICK_ID]`
  WHERE
    DATA_DATE BETWEEN DATE_ADD(CURRENT_DATE(), INTERVAL -31 DAY)
    AND DATE_ADD(CURRENT_DATE(), INTERVAL -1 DAY)
  GROUP BY
    Campaign_ID,
    Date ) AS imp
ON
  base.Campaign_ID = imp.Campaign_ID
  AND base.Date = imp.Date
LEFT JOIN (
  SELECT
    Campaign_ID,
    DATA_DATE AS Date,
    COUNT() AS count,
    COUNT(DISTINCT User_ID) AS du
  FROM
    `[DATASET].click[DOUBLECLICK_ID]`
  WHERE
    _DATA_DATE BETWEEN DATE_ADD(CURRENT_DATE(), INTERVAL -31 DAY)
    AND DATE_ADD(CURRENT_DATE(), INTERVAL -1 DAY)
  GROUP BY
    Campaign_ID,
    Date ) AS click
ON
  base.Campaign_ID = click.Campaign_ID
  AND base.Date = click.Date
LEFT JOIN (
  SELECT
    Campaign_ID,
    _DATA_DATE AS Date,
    COUNT() AS count,
    COUNT(DISTINCT User_ID) AS du
  FROM
    `[DATASET].activity[DOUBLECLICK_ID]`
  WHERE
    _DATA_DATE BETWEEN DATE_ADD(CURRENT_DATE(), INTERVAL -31 DAY)
    AND DATE_ADD(CURRENT_DATE(), INTERVAL -1 DAY)
  GROUP BY
    Campaign_ID,
    Date ) AS activity
ON
  base.Campaign_ID = activity.Campaign_ID
  AND base.Date = activity.Date
WHERE
  base.Campaign_ID IN [CAMPAIGN_LIST]
  AND (base.Date = imp.Date
    OR base.Date = click.Date
    OR base.Date = activity.Date)
ORDER BY
  base.Campaign_ID,
  base.Date

Command-line

# START_DATE = DATE_ADD(CURRENT_DATE(), INTERVAL -31 DAY)
# END_DATE = DATE_ADD(CURRENT_DATE(), INTERVAL -1 DAY)
bq query --use_legacy_sql=false '
SELECT
  base.*,
  imp.count AS imp_count,
  imp.du AS imp_du,
  click.count AS click_count,
  click.du AS click_du,
  activity.count AS activity_count,
  activity.du AS activity_du
FROM (
  SELECT
    *
  FROM (
    SELECT
      Campaign,
      Campaign_ID
    FROM
      `[DATASET].match_table_campaigns_[DOUBLECLICK_ID]`
    WHERE
      DATA_DATE = _LATEST_DATE ),
    (
    SELECT
      date AS Date
    FROM
      `bigquery-public-data.common_us.date_greg`
    WHERE
      Date BETWEEN DATE_ADD(CURRENT_DATE(), INTERVAL -31 DAY)
      AND DATE_ADD(CURRENT_DATE(), INTERVAL -1 DAY) ) ) AS base
LEFT JOIN (
  SELECT
    Campaign_ID,
    _DATA_DATE AS Date,
    COUNT() AS count,
    COUNT(DISTINCT User_ID) AS du
  FROM
    `[DATASET].impression[DOUBLECLICK_ID]`
  WHERE
    DATA_DATE BETWEEN DATE_ADD(CURRENT_DATE(), INTERVAL -31 DAY)
    AND DATE_ADD(CURRENT_DATE(), INTERVAL -1 DAY)
  GROUP BY
    Campaign_ID,
    Date ) AS imp
ON
  base.Campaign_ID = imp.Campaign_ID
  AND base.Date = imp.Date
LEFT JOIN (
  SELECT
    Campaign_ID,
    DATA_DATE AS Date,
    COUNT() AS count,
    COUNT(DISTINCT User_ID) AS du
  FROM
    `[DATASET].click[DOUBLECLICK_ID]`
  WHERE
    _DATA_DATE BETWEEN DATE_ADD(CURRENT_DATE(), INTERVAL -31 DAY)
    AND DATE_ADD(CURRENT_DATE(), INTERVAL -1 DAY)
  GROUP BY
    Campaign_ID,
    Date ) AS click
ON
  base.Campaign_ID = click.Campaign_ID
  AND base.Date = click.Date
LEFT JOIN (
  SELECT
    Campaign_ID,
    _DATA_DATE AS Date,
    COUNT() AS count,
    COUNT(DISTINCT User_ID) AS du
  FROM
    `[DATASET].activity[DOUBLECLICK_ID]`
  WHERE
    _DATA_DATE BETWEEN DATE_ADD(CURRENT_DATE(), INTERVAL -31 DAY)
    AND DATE_ADD(CURRENT_DATE(), INTERVAL -1 DAY)
  GROUP BY
    Campaign_ID,
    Date ) AS activity
ON
  base.Campaign_ID = activity.Campaign_ID
  AND base.Date = activity.Date
WHERE
  base.Campaign_ID IN [CAMPAIGN_LIST]
  AND (base.Date = imp.Date
    OR base.Date = click.Date
    OR base.Date = activity.Date)
ORDER BY
  base.Campaign_ID,
  base.Date'

Campaign activity

The following sample query analyzes campaign activity over the past 30 days. In this query, replace [CAMPAIGN_LIST] with a comma separated list of all the DoubleClick campaigns of interest within the scope of the query.

Web UI

#standardSQL
# START_DATE = DATE_ADD(CURRENT_DATE(), INTERVAL -31 DAY)
# END_DATE = DATE_ADD(CURRENT_DATE(), INTERVAL -1 DAY)
SELECT
  base.*,
  activity.count AS activity_count,
  activity.du AS activity_du
FROM (
  SELECT
    *
  FROM (
    SELECT
      Campaign,
      Campaign_ID
    FROM
      `[DATASET].match_table_campaigns_[DOUBLECLICK_ID]`
    WHERE
      DATA_DATE = _LATEST_DATE ),
    (
    SELECT
      mt_at.Activity_Group,
      mt_ac.Activity,
      mt_ac.Activity_Type,
      mt_ac.Activity_Sub_Type,
      mt_ac.Activity_ID,
      mt_ac.Activity_Group_ID
    FROM
      `[DATASET].match_table_activity_cats[DOUBLECLICK_ID]` AS mt_ac
    JOIN (
      SELECT
        Activity_Group,
        Activity_Group_ID
      FROM
        `[DATASET].match_table_activity_types_[DOUBLECLICK_ID]`
      WHERE
        _DATA_DATE = _LATEST_DATE ) AS mt_at
    ON
      mt_at.Activity_Group_ID = mt_ac.Activity_Group_ID
    WHERE
      _DATA_DATE = _LATEST_DATE ),
    (
    SELECT
      date AS Date
    FROM
      `bigquery-public-data.common_us.date_greg`
    WHERE
      Date BETWEEN [START_DATE]
      AND [END_DATE] ) ) AS base
LEFT JOIN (
  SELECT
    Campaign_ID,
    Activity_ID,
    _DATA_DATE AS Date,
    COUNT() AS count,
    COUNT(DISTINCT User_ID) AS du
  FROM
    `[DATASET].activity_[DOUBLECLICK_ID]`
  WHERE
    _DATA_DATE BETWEEN DATE_ADD(CURRENT_DATE(), INTERVAL -31 DAY)
    AND DATE_ADD(CURRENT_DATE(), INTERVAL -1 DAY)
  GROUP BY
    Campaign_ID,
    Activity_ID,
    Date ) AS activity
ON
  base.Campaign_ID = activity.Campaign_ID
  AND base.Activity_ID = activity.Activity_ID
  AND base.Date = activity.Date
WHERE
  base.Campaign_ID IN [CAMPAIGN_LIST]
  AND base.Activity_ID = activity.Activity_ID
ORDER BY
  base.Campaign_ID,
  base.Activity_Group_ID,
  base.Activity_ID,
  base.Date

Command-line

# START_DATE = DATE_ADD(CURRENT_DATE(), INTERVAL -31 DAY)
# END_DATE = DATE_ADD(CURRENT_DATE(), INTERVAL -1 DAY)
bq query --use_legacy_sql=false '
SELECT
  base.*,
  activity.count AS activity_count,
  activity.du AS activity_du
FROM (
  SELECT
    *
  FROM (
    SELECT
      Campaign,
      Campaign_ID
    FROM
      `[DATASET].match_table_campaigns_[DOUBLECLICK_ID]`
    WHERE
      DATA_DATE = _LATEST_DATE ),
    (
    SELECT
      mt_at.Activity_Group,
      mt_ac.Activity,
      mt_ac.Activity_Type,
      mt_ac.Activity_Sub_Type,
      mt_ac.Activity_ID,
      mt_ac.Activity_Group_ID
    FROM
      `[DATASET].match_table_activity_cats[DOUBLECLICK_ID]` AS mt_ac
    JOIN (
      SELECT
        Activity_Group,
        Activity_Group_ID
      FROM
        `[DATASET].match_table_activity_types_[DOUBLECLICK_ID]`
      WHERE
        _DATA_DATE = _LATEST_DATE ) AS mt_at
    ON
      mt_at.Activity_Group_ID = mt_ac.Activity_Group_ID
    WHERE
      _DATA_DATE = _LATEST_DATE ),
    (
    SELECT
      date AS Date
    FROM
      `bigquery-public-data.common_us.date_greg`
    WHERE
      Date BETWEEN [START_DATE]
      AND [END_DATE] ) ) AS base
LEFT JOIN (
  SELECT
    Campaign_ID,
    Activity_ID,
    _DATA_DATE AS Date,
    COUNT() AS count,
    COUNT(DISTINCT User_ID) AS du
  FROM
    `[DATASET].activity_[DOUBLECLICK_ID]`
  WHERE
    _DATA_DATE BETWEEN DATE_ADD(CURRENT_DATE(), INTERVAL -31 DAY)
    AND DATE_ADD(CURRENT_DATE(), INTERVAL -1 DAY)
  GROUP BY
    Campaign_ID,
    Activity_ID,
    Date ) AS activity
ON
  base.Campaign_ID = activity.Campaign_ID
  AND base.Activity_ID = activity.Activity_ID
  AND base.Date = activity.Date
WHERE
  base.Campaign_ID IN [CAMPAIGN_LIST]
  AND base.Activity_ID = activity.Activity_ID
ORDER BY
  base.Campaign_ID,
  base.Activity_Group_ID,
  base.Activity_ID,
  base.Date'

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