tap-bigquery from anelendata

BigQuery data warehouse extractor

The tap-bigquery extractor pulls data from BigQuery that can then be sent to a destination using a loader.

Available Variants

Getting Started


If you haven't already, follow the initial steps of the Getting Started guide:

  1. Install Meltano
  2. Create your Meltano project

Additionally you should follow the steps in the "Activate the Google BigQuery API" section of the repository's README.

Installation and configuration

  1. Add the tap-bigquery extractor to your project using
    meltano add
  2. meltano add extractor tap-bigquery
  3. Configure the tap-bigquery settings using
    meltano config
  4. meltano config tap-bigquery set --interactive
  5. Test that extractor settings are valid using
    meltano config
  6. meltano config tap-bigquery test

Next steps

If you run into any issues, learn how to get help.


The current capabilities for tap-bigquery may have been automatically set when originally added to the Hub. Please review the capabilities when using this extractor. If you find they are out of date, please consider updating them by making a pull request to the YAML file that defines the capabilities for this extractor.

This plugin has the following capabilities:

  • catalog
  • discover
  • state

You can override these capabilities or specify additional ones in your meltano.yml by adding the capabilities key.


The tap-bigquery settings that are known to Meltano are documented below. To quickly find the setting you're looking for, click on any setting name from the list:

You can override these settings or specify additional ones in your meltano.yml by adding the settings key.

Please consider adding any settings you have defined locally to this definition on MeltanoHub by making a pull request to the YAML file that defines the settings for this plugin.

Streams (streams)

  • Environment variable: TAP_BIGQUERY_STREAMS

Array of objects with name, table, columns, datetime_key, and filters keys:

  • name: The entity name, used by most loaders as the name of the table to be created.
  • table: Fully qualified table name in BigQuery, with format `<project>.<dataset>.<table>`. Since backticks have special meaning in YAML, values in meltano.yml should be wrapped in double quotes.
  • columns: Array of column names to select. Using ["*"] is not recommended as it can become very expensive for a table with a large number of columns.
  • datetime_key: Name of datetime column to use as replication key.
  • filters: Optional array of WHERE clauses to filter extracted data, e.g. "column='value'".

Credentials Path (credentials_path)

  • Environment variable: TAP_BIGQUERY_CREDENTIALS_PATH
  • Default Value: $MELTANO_PROJECT_ROOT/client_secrets.json

Fully qualified path to client_secrets.json for your service account.

See the "Activate the Google BigQuery API" section of the repository's README and

By default, this file is expected to be at the root of your project directory.

Start Datetime (start_datetime)

  • Environment variable: TAP_BIGQUERY_START_DATETIME

Determines how much historical data will be extracted. Please be aware that the larger the time period and amount of data, the longer the initial extraction can be expected to take.

End Datetime (end_datetime)

  • Environment variable: TAP_BIGQUERY_END_DATETIME

Date up to when historical data will be extracted.

Limit (limit)

  • Environment variable: TAP_BIGQUERY_LIMIT

Limits the number of records returned in each stream, applied as a limit in the query.

Start Always Inclusive (start_always_inclusive)

  • Default Value: true

When replicating incrementally, disable to only select records whose datetime_key is greater than the maximum value replicated in the last run, by excluding records whose timestamps match exactly. This could cause records to be missed that were created after the last run finished, but during the same second and with the same timestamp.

Something missing?

This page is generated from a YAML file that you can contribute changes to.

Edit it on GitHub!

Looking for help?

If you're having trouble getting the tap-bigquery extractor to work, look for an existing issue in its repository, file a new issue, or join the Meltano Slack community and ask for help in the


meltano add extractor tap-bigquery

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