 | BigQuery
BigQuery data warehouse extractor |
The tap-bigquery Meltano extractor pulls data from BigQuery that can then be sent to a destination using a loader.
Other 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 test
meltano add extractor tap-bigquerymeltano config tap-bigquery set --interactivemeltano test tap-bigqueryNext 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 fortap-bigqueryThis 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-generalInstall
meltano add extractor tap-bigquery
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