BigQuery

BigQuery is a completely serverless and cost-effective enterprise data warehouse that works across clouds and scales with your data, with BI, machine learning and AI built in.

The BigQuery Wrapper allows you to read and write data from BigQuery within your Postgres database.

Supported Data Types#

Postgres Type	BigQuery Type
boolean	BOOL
bigint	INT64
double precision	FLOAT64
numeric	NUMERIC
text	STRING
varchar	STRING
date	DATE
timestamp	DATETIME
timestamp	TIMESTAMP

Preparation#

Before you get started, make sure the wrappers extension is installed on your database:

create extension if not exists wrappers;

and then create the foreign data wrapper:

create foreign data wrapper bigquery_wrapper
  handler big_query_fdw_handler
  validator big_query_fdw_validator;

Secure your credentials (optional)#

By default, Postgres stores FDW credentials inide pg_catalog.pg_foreign_server in plain text. Anyone with access to this table will be able to view these credentials. Wrappers is designed to work with Vault, which provides an additional level of security for storing credentials. We recommend using Vault to store your credentials.

-- Save your BigQuery service account json in Vault and retrieve the `key_id`
insert into vault.secrets (name, secret)
values (
  'bigquery',
  '
    {
      "type": "service_account",
      "project_id": "your_gcp_project_id",
      "private_key_id": "your_private_key_id",
      "private_key": "-----BEGIN PRIVATE KEY-----\n...\n-----END PRIVATE KEY-----\n",
      ...
    }
  '
)
returning key_id;

Connecting to BigQuery#

We need to provide Postgres with the credentials to connect to BigQuery, and any additional options. We can do this using the create server command:

create server bigquery_server
  foreign data wrapper bigquery_wrapper
  options (
    sa_key_id '<key_ID>', -- The Key ID from above.
    project_id 'your_gcp_project_id',
    dataset_id 'your_gcp_dataset_id'
  );

Creating Foreign Tables#

The BigQuery Wrapper supports data reads and writes from BigQuery.

Integration	Select	Insert	Update	Delete	Truncate
BigQuery	✅	✅	✅	✅	❌

For example:

create foreign table my_bigquery_table (
  id bigint,
  name text,
  ts timestamp
)
  server bigquery_server
  options (
    table 'people',
    location 'EU'
  );

Foreign table options#

The full list of foreign table options are below:

table - Source table or view name in BigQuery, required.

This can also be a subquery enclosed in parentheses, for example,

_10table '(select * except(props), to_json_string(props) as props from `my_project.my_dataset.my_table`)'

Note: When using subquery in this option, full qualitified table name must be used.
location - Source table location, optional. Default is 'US'.
timeout - Query request timeout in milliseconds, optional. Default is '30000' (30 seconds).
rowid_column - Primary key column name, optional for data scan, required for data modify

Examples#

Some examples on how to use BigQuery foreign tables.

Basic example#

This will create a "foreign table" inside your Postgres database called people:

-- Run below SQLs on BigQuery to create source table
create table your_project_id.your_dataset_id.people (
  id int64,
  name string,
  ts timestamp
);
-- Add some test data
insert into your_project_id.your_dataset_id.people values
  (1, 'Luke Skywalker', current_timestamp()), 
  (2, 'Leia Organa', current_timestamp()), 
  (3, 'Han Solo', current_timestamp());

Create foreign table on Postgres database:

create foreign table people (
  id bigint,
  name text,
  ts timestamp
)
  server bigquery_server
  options (
    table 'people',
    location 'EU'
  );
select * from people;

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