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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 TypeBigQuery Type
booleanBOOL
bigintINT64
double precisionFLOAT64
numericNUMERIC
textSTRING
varcharSTRING
dateDATE
timestampDATETIME
timestampTIMESTAMP

Preparation#

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


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create extension if not exists wrappers;

and then create the foreign data wrapper:


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create foreign data wrapper bigquery_wrapper
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handler big_query_fdw_handler
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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.


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


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

Creating Foreign Tables#

The BigQuery Wrapper supports data reads and writes from BigQuery.

IntegrationSelectInsertUpdateDeleteTruncate
BigQuery

For example:


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

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,


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    table '(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

Inserting Rows & the Streaming Buffer#

This foreign data wrapper uses BigQuery’s insertAll API method to create a streamingBuffer with an associated partition time. Within that partition time, the data cannot be updated, deleted, or fully exported. Only after the time has elapsed (up to 90 minutes according to BigQuery’s documentation); can you perform operations.

If you attempt an UPDATE or DELETE statement on rows while in the streamingBuffer, you will get an error of UPDATE or DELETE statement over table datasetName - note that tableName would affect rows in the streaming buffer, which is not supported.

Examples#

Some examples on how to use BigQuery foreign tables.

Let's prepare the source table in BigQuery first:


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

Basic example#

This example will create a "foreign table" inside your Postgres database called people and query its data:


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

Data modify example#

This example will modify data in a "foreign table" inside your Postgres database called people, note that rowid_column option is mandatory:


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create foreign table people (
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id bigint,
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name text,
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ts timestamp
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)
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server bigquery_server
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options (
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table 'people',
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location 'EU',
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rowid_column 'id'
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);
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-- insert new data
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insert into people(id, name, ts)
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values (4, 'Yoda', '2023-01-01 12:34:56');
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-- update existing data
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update people
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set name = 'Anakin Skywalker'
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where id = 1;
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-- delete data
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delete from people
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where id = 2;