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

Alternative variants #

Multiple variants of tap-bigquery are available. This document describes the default anelendata variant, which is recommended for new users.

Alternative variants are:

Getting Started #

Prerequisites #

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 : 

    meltano add extractor tap-bigquery
  2. Configure the settings below using meltano config .

Next steps #

Follow the remaining steps of the Getting Started guide:

  1. Select entities and attributes to extract
  2. Add a loader to send data to a destination
  3. Run a data integration (EL) pipeline
If you run into any issues, learn how to get help.

Capabilities #

Settings #

tap-bigquery requires the configuration of the following settings:

The settings for extractor tap-bigquery that are known to Meltano are documented below. To quickly find the setting you're looking for, use the Table of Contents at the top of the page.

Streams (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'".

How to use #

Manage this setting using meltano config or an environment variable: 

meltano config tap-bigquery set streams '[...]'

export TAP_BIGQUERY_STREAMS='[...]'

Credentials Path (credentials_path) #

  • Environment variable: TAP_BIGQUERY_CREDENTIALS_PATH
  • Default: $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 https://cloud.google.com/docs/authentication/production.

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

How to use #

Manage this setting using meltano config or an environment variable: 

meltano config tap-bigquery set credentials_path <credentials_path>

export TAP_BIGQUERY_CREDENTIALS_PATH=<credentials_path>

Start Datetime (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.

How to use #

Manage this setting using meltano config or an environment variable: 

meltano config tap-bigquery set start_datetime YYYY-MM-DDTHH:MM:SSZ

export TAP_BIGQUERY_START_DATETIME=YYYY-MM-DDTHH:MM:SSZ

End Datetime (end_datetime) #

Date up to when historical data will be extracted.

How to use #

Manage this setting using meltano config or an environment variable: 

meltano config tap-bigquery set end_datetime YYYY-MM-DDTHH:MM:SSZ

export TAP_BIGQUERY_END_DATETIME=YYYY-MM-DDTHH:MM:SSZ

Limit (limit) #

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

How to use #

Manage this setting using meltano config or an environment variable: 

meltano config tap-bigquery set limit 1234

export TAP_BIGQUERY_LIMIT=1234

Start Always Inclusive (start_always_inclusive) #

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.

How to use #

Manage this setting using meltano config or an environment variable: 

meltano config tap-bigquery set start_always_inclusive false

export TAP_BIGQUERY_START_ALWAYS_INCLUSIVE=false

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 #plugins-general channel.

Found an issue on this page? #

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