The tap-bigquery extractor pulls data from BigQuery that can then be sent to a destination using a loader.
Available Variants
- anelendata (default)
 - fixdauto
 
Getting Started
Prerequisites
If you haven't already, follow the initial steps of the Getting Started guide:
Additionally you should follow the steps in the "Activate the Google BigQuery API" section of the repository's README.
Installation and configuration
- 
                Add the tap-bigquery extractor to your project
                using
                
:meltano add - 
                Configure the tap-bigquery settings using
                
:meltano config - 
                  Test that extractor settings are valid using
                  
:meltano config 
meltano add extractor tap-bigquerymeltano config tap-bigquery set --interactivemeltano config tap-bigquery testNext steps
Follow the remaining steps of the Getting Started guide:
If you run into any issues, learn how to get help.
Capabilities
      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 If you find they are out of date, please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.
    
Settings
      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 inmeltano.ymlshould 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 ofWHEREclauses 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 https://cloud.google.com/docs/authentication/production.
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)
- 
          Environment variable:
          
TAP_BIGQUERY_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?
#plugins-general
    channel.
  Install
meltano add extractor tap-bigqueryMaintenance Status
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