dbt BigQuery
Table of Contents
The dbt-bigquery
transformer uses SQL to transform data stored in your warehouse.
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- Repository: https://github.com/dbt-labs/dbt-bigquery
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- Maintainer: dbt Labs
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Getting Started #
Prerequisites #
If you haven't already, follow the initial steps of the Getting Started guide:
Installation and configuration #
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Add the
dbt-bigquery
transformer to your project usingmeltano add
:meltano add transformer dbt-bigquery
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Configure the settings below using
meltano config
.
Next steps #
Follow the remaining steps of the Getting Started guide:
If you run into any issues, learn how to get help.Settings #
Settings for dbt itself can be configured through dbt_project.yml as usual, which can be found at transform/dbt_project.yml in your Meltano project. dbt also has adapter-specific documentation for BigQuery.
The settings for transformer dbt-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.
Project Directory (project_dir
)
#
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Environment variable:
DBT_BIGQUERY_PROJECT_DIR
- Default:
$MELTANO_PROJECT_ROOT/transform
How to use #
Manage this setting using
meltano config
or an
environment variable:
meltano config dbt-bigquery set project_dir <project_dir>
export DBT_BIGQUERY_PROJECT_DIR=<project_dir>
Profiles Directory (profiles_dir
)
#
-
Environment variable:
DBT_PROFILES_DIR
, alias:DBT_BIGQUERY_PROFILES_DIR
- Default:
$MELTANO_PROJECT_ROOT/transform/profiles/bigquery
How to use #
Manage this setting using
meltano config
or an
environment variable:
meltano config dbt-bigquery set profiles_dir <profiles_dir>
export DBT_PROFILES_DIR=<profiles_dir>
Authentication Method (auth_method
)
#
-
Environment variable:
DBT_BIGQUERY_AUTH_METHOD
The auth method to use. One of: “oauth”, “oauth-secrets”, or “service-account”
How to use #
Manage this setting using
meltano config
or an
environment variable:
meltano config dbt-bigquery set auth_method <auth_method>
export DBT_BIGQUERY_AUTH_METHOD=<auth_method>
Project (project
)
#
-
Environment variable:
DBT_BIGQUERY_PROJECT
The BigQuery project ID.
How to use #
Manage this setting using
meltano config
or an
environment variable:
meltano config dbt-bigquery set project <project>
export DBT_BIGQUERY_PROJECT=<project>
dataset
#
-
Environment variable:
DBT_BIGQUERY_DATASET
The dataset to use.
How to use #
Manage this setting using
meltano config
or an
environment variable:
meltano config dbt-bigquery set dataset <dataset>
export DBT_BIGQUERY_DATASET=<dataset>
Refresh Token (refresh_token
)
#
-
Environment variable:
DBT_BIGQUERY_REFRESH_TOKEN
The refresh token, if authenticating via oauth-secrets method.
How to use #
Manage this setting using
meltano config
or an
environment variable:
meltano config dbt-bigquery set refresh_token <refresh_token>
export DBT_BIGQUERY_REFRESH_TOKEN=<refresh_token>
Client ID (client_id
)
#
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Environment variable:
DBT_BIGQUERY_CLIENT_ID
The client id to use, if authenticating via oauth-secrets method.
How to use #
Manage this setting using
meltano config
or an
environment variable:
meltano config dbt-bigquery set client_id <client_id>
export DBT_BIGQUERY_CLIENT_ID=<client_id>
Client Secret (client_secret
)
#
-
Environment variable:
DBT_BIGQUERY_CLIENT_SECRET
The client secret to use, if authenticating via oauth-secrets method.
How to use #
Manage this setting using
meltano config
or an
environment variable:
meltano config dbt-bigquery set client_secret <client_secret>
export DBT_BIGQUERY_CLIENT_SECRET=<client_secret>
Token URI (token_uri
)
#
-
Environment variable:
DBT_BIGQUERY_TOKEN_URI
The token redirect URI
How to use #
Manage this setting using
meltano config
or an
environment variable:
meltano config dbt-bigquery set token_uri <token_uri>
export DBT_BIGQUERY_TOKEN_URI=<token_uri>
keyfile
#
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Environment variable:
DBT_BIGQUERY_KEYFILE
The path to the keyfile.json
` to use, if authenticating via service-account method.
How to use #
Manage this setting using
meltano config
or an
environment variable:
meltano config dbt-bigquery set keyfile <keyfile>
export DBT_BIGQUERY_KEYFILE=<keyfile>
Commands #
The dbt-bigquery
transformer supports the following commands that can be used with
meltano invoke
:
clean
#
- Equivalent to:
dbt clean
Delete all folders in the clean-targets list (usually the dbt_modules and target directories.)
How to use #
Run this command using
meltano invoke
:
meltano invoke dbt-bigquery:clean [additional arguments...]
compile
#
- Equivalent to:
dbt compile
Generates executable SQL from source model, test, and analysis files. Compiled SQL files are written to the target/ directory.
How to use #
Run this command using
meltano invoke
:
meltano invoke dbt-bigquery:compile [additional arguments...]
deps
#
- Equivalent to:
dbt deps
Pull the most recent version of the dependencies listed in packages.yml
How to use #
Run this command using
meltano invoke
:
meltano invoke dbt-bigquery:deps [additional arguments...]
run
#
- Equivalent to:
dbt run
Compile SQL and execute against the current target database.
How to use #
Run this command using
meltano invoke
:
meltano invoke dbt-bigquery:run [additional arguments...]
seed
#
- Equivalent to:
dbt seed
Load data from csv files into your data warehouse.
How to use #
Run this command using
meltano invoke
:
meltano invoke dbt-bigquery:seed [additional arguments...]
snapshot
#
- Equivalent to:
dbt snapshot
Execute snapshots defined in your project.
How to use #
Run this command using
meltano invoke
:
meltano invoke dbt-bigquery:snapshot [additional arguments...]
test
#
- Equivalent to:
dbt test
Runs tests on data in deployed models.
How to use #
Run this command using
meltano invoke
:
meltano invoke dbt-bigquery:test [additional arguments...]
freshness
#
- Equivalent to:
dbt source freshness
Check the freshness of your source data.
How to use #
Run this command using
meltano invoke
:
meltano invoke dbt-bigquery:freshness [additional arguments...]
build
#
- Equivalent to:
dbt build
Will run your models, tests, snapshots and seeds in DAG order.
How to use #
Run this command using
meltano invoke
:
meltano invoke dbt-bigquery:build [additional arguments...]
docs-generate
#
- Equivalent to:
dbt docs generate
Generate documentation for your project.
How to use #
Run this command using
meltano invoke
:
meltano invoke dbt-bigquery:docs-generate [additional arguments...]
docs-serve
#
- Equivalent to:
dbt docs serve
Serve documentation for your project. Make sure you ran docs-generate
first.
How to use #
Run this command using
meltano invoke
:
meltano invoke dbt-bigquery:docs-serve [additional arguments...]
debug
#
- Equivalent to:
dbt debug
Debug your DBT project and warehouse connection.
How to use #
Run this command using
meltano invoke
:
meltano invoke dbt-bigquery:debug [additional arguments...]
Looking for help? #
If you're having trouble getting the
dbt-bigquery
transformer 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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