Learn more about Google Cloud Storage Export Integration.

The Data Connector for Google Cloud Storage enables import of the contents of .tsv and .csv files stored in your GCS bucket.

For sample workflows importing data from GCS, view the Treasure Boxes.


  • Basic knowledge of Treasure Data

  • An existing Google Service Account

You also need to generate and obtain a JSON key file from Google Developers Console. See Generating a service account credential.

Use TD Console

Create a New Connection

When you configure a data connection, you provide authentication to access the integration. In Treasure Data, you configure the authentication and then specify the source information.

  1. Open TD Console.

  2. Navigate to Integrations Hub >  Catalog

  3. Search and select Google Cloud Storage.

  4. The following dialog opens.

  5. Create a New Google Cloud Storage Connector

  6. Set the following parameters:



Authentication mode

Select a JSON keyfile. This method uses the JSON keyfile generated from the Google Developers Console.

JSON Keyfile

Copy and paste the contents of the JSON keyfile generated from the Google Developers Console in this field

Application Name

Treasure Data GCS Output is the default value. As this is an arbitrary client name associated with API requests, you can leave the default value (Treasure Data GCS Output).

Name Your Connection

  1. Type a name for your connection.

  2. Select Done.

Transfer Your Google Cloud Storage Account Data to Treasure Data

After creating the authenticated connection, you are automatically taken to Authentications.

  1. Search for the connection you created. 

  2. Select New Source.


  1. Type a name for your Source in the Data Transfer field.

  2. Click Next

Source Table

  1. Select Next.

  2. The Source Table dialog opens. Edit the following parameters




Google Cloud Storage bucket name (Ex. your_bucket_name)

Path Prefix

Prefix of target keys. (Ex. logs/data_)

Path Regex

regexp to match file paths. If a file path doesn’t match with this pattern, the file is skipped. (Ex. .csv$ # in this case, a file is skipped if its path doesn’t match with this pattern)

Start after path

Inserts last_path parameter so that the first execution skips files before the path. (Ex. logs/data_20170101.csv)


Enables incremental loading. If incremental loading is enabled, config diff for the next execution will include last_path parameter so that next execution skips files before the path. Otherwise, last_path will not be included.

Example: CloudFront

Amazon CloudFront is a web service that speeds up the distribution of your static and dynamic web content. You can configure CloudFront to create log files that contain detailed information about every user request that CloudFront receives. If you enable logging, you can save CloudFront logfiles, shown as follows:

[your_bucket] - [logging] - [E231A697YXWD39.2017-04-23-15.a103fd5a.gz]
[your_bucket] - [logging] - [E231A697YXWD39.2017-04-23-15.b2aede4a.gz]
[your_bucket] - [logging] - [E231A697YXWD39.2017-04-23-16.594fa8e6.gz]
[your_bucket] - [logging] - [E231A697YXWD39.2017-04-23-16.d12f42f9.gz]

In this case, the Source Table setting should be as shown:

  • Bucket: your_bucket

  • Path Prefix: logging/

  • Path Regex: .gz$ (Not Required)

  • Start after path: logging/E231A697YXWD39.2017-04-23-15.b2aede4a.gz (Assuming that you want to import the logfiles from 2017-04-23-16.)

  • Incremental: true (if you want to schedule this job.)

Data Settings

  1. Select Next.
    The Data Settings page opens.

  2. Optionally, edit the data settings or skip this page of the dialog.





Parses a value as a specified type. And then, it stores after converting to Treasure Data schema.

  • boolean

  • long

  • timestamp: will be imported as String type at Treasure Data (Ex. 2017-04-01 00:00:00.000)

  • double

  • string

  • json

Default timezone

Changes time zone of timestamp columns if the value itself doesn’t include time zone.

Total file count limit

Maximum number of files to read. (optional)

Schema Settings

You can name the columns and set the data type.

Data Preview 

You can see a preview of your data before running the import by selecting Generate Preview.

Data shown in the data preview is approximated from your source. It is not the actual data that is imported.

  1. Select Next.
    Data preview is optional and you can safely skip to the next page of the dialog if you want.

  2. To preview your data, select Generate Preview. Optionally, select Next

  3. Verify that the data looks approximately like you expect it to.

  4. Select Next.

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 the query:

      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.

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