Ingest data from Google Cloud SQL

This page shows you how to stream data from Google Cloud SQL for PostgreSQL to Materialize using thePostgreSQL source.

💡 Tip: For help getting started with your own data, you can schedule a free guided trial.

Before you begin

Make sure you are running PostgreSQL 11 or higher.
Make sure you have access to your PostgreSQL instance via psql, or your preferred SQL client.

A. Configure Google Cloud SQL

1. Enable logical replication

Materialize uses PostgreSQL’s logical replication protocol to track changes in your database and propagate them to Materialize.

To enable logical replication in Cloud SQL, see the Cloud SQL documentation.

2. Create a publication and a replication user

Once logical replication is enabled, the next step is to create a publication with the tables that you want to replicate to Materialize. You’ll also need a user for Materialize with sufficient privileges to manage replication.

For each table that you want to replicate to Materialize, set the replica identity to FULL:
```
ALTER TABLE <table1> REPLICA IDENTITY FULL;
```
```
ALTER TABLE <table2> REPLICA IDENTITY FULL;
```
REPLICA IDENTITY FULL ensures that the replication stream includes the previous data of changed rows, in the case of UPDATE and DELETE operations. This setting enables Materialize to ingest PostgreSQL data with minimal in-memory state. However, you should expect increased disk usage in your PostgreSQL database.
Create a publication with the tables you want to replicate:

For specific tables:
```
CREATE PUBLICATION mz_source FOR TABLE <table1>, <table2>;
```
For all tables in the database:
```
CREATE PUBLICATION mz_source FOR ALL TABLES;
```
The mz_source publication will contain the set of change events generated from the specified tables, and will later be used to ingest the replication stream.

Be sure to include only the tables you need. If the publication includes additional tables, Materialize will waste resources on ingesting and then immediately discarding the data.
Create a user for Materialize, if you don’t already have one:
```
CREATE USER materialize PASSWORD '<password>';
```
Grant the user permission to manage replication:
```
ALTER ROLE materialize WITH REPLICATION;
```
Grant the user the required permissions on the tables you want to replicate:
```
GRANT CONNECT ON DATABASE <dbname> TO materialize;
```
```
GRANT USAGE ON SCHEMA <schema> TO materialize;
```
```
GRANT SELECT ON <table1> TO materialize;
```
```
GRANT SELECT ON <table2> TO materialize;
```
Once connected to your database, Materialize will take an initial snapshot of the tables in your publication. SELECT privileges are required for this initial snapshot.

If you expect to add tables to your publication, you can grant SELECT on all tables in the schema instead of naming the specific tables:
```
GRANT SELECT ON ALL TABLES IN SCHEMA <schema> TO materialize;
```

B. (Optional) Configure network security

NOTE: If you are prototyping and your Google Cloud SQL instance is publicly accessible, you can skip this step. For production scenarios, we recommend configuring one of the network security options below.

There are various ways to configure your database’s network to allow Materialize to connect:

Allow Materialize IPs: If your database is publicly accessible, you can configure your database’s firewall to allow connections from a set of static Materialize IP addresses.
Use an SSH tunnel: If your database is running in a private network, you can use an SSH tunnel to connect Materialize to the database.

Select the option that works best for you.

In the Materialize console’s SQL Shell, or your preferred SQL client connected to Materialize, find the static egress IP addresses for the Materialize region you are running in:
```
SELECT * FROM mz_egress_ips;
```
Update your Google Cloud SQL firewall rules to allow traffic from each IP address from the previous step.

To create an SSH tunnel from Materialize to your database, you launch an instance to serve as an SSH bastion host, configure the bastion host to allow traffic only from Materialize, and then configure your database’s private network to allow traffic from the bastion host.

Launch a GCE instance to serve as your SSH bastion host.
- Make sure the instance is publicly accessible and in the same VPC as your database.
- Add a key pair and note the username. You’ll use this username when connecting Materialize to your bastion host.
- Make sure the VM has a static public IP address. You’ll use this IP address when connecting Materialize to your bastion host.
Configure the SSH bastion host to allow traffic only from Materialize.
1. In the Materialize console’s SQL Shell, or your preferred SQL client connected to Materialize, get the static egress IP addresses for the Materialize region you are running in:
```
SELECT * FROM mz_egress_ips;
```
2. Update your SSH bastion host’s firewall rules to allow traffic from each IP address from the previous step.
Update your Google Cloud SQL firewall rules to allow traffic from the SSH bastion host.

C. Ingest data in Materialize

1. (Optional) Create a cluster

NOTE: If you are prototyping and already have a cluster to host your PostgreSQL source (e.g. quickstart), you can skip this step. For production scenarios, we recommend separating your workloads into multiple clusters for resource isolation.

In Materialize, a cluster is an isolated environment, similar to a virtual warehouse in Snowflake. When you create a cluster, you choose the size of its compute resource allocation based on the work you need the cluster to do, whether ingesting data from a source, computing always-up-to-date query results, serving results to clients, or a combination.

In this case, you’ll create a dedicated cluster for ingesting source data from your PostgreSQL database.

In the SQL Shell, or your preferred SQL client connected to Materialize, use the CREATE CLUSTER command to create the new cluster:
```
CREATE CLUSTER ingest_postgres (SIZE = '200cc');

SET CLUSTER = ingest_postgres;
```
A cluster of size 200cc should be enough to process the initial snapshot of the tables in your publication. For very large snapshots, consider using a larger size to speed up processing. Once the snapshot is finished, you can readjust the size of the cluster to fit the volume of changes being replicated from your upstream PostgeSQL database.

2. Start ingesting data

Now that you’ve configured your database network and created an ingestion cluster, you can connect Materialize to your PostgreSQL database and start ingesting data. The exact steps depend on your networking configuration, so start by selecting the relevant option.

In a SQL client connected to Materialize, use the CREATE SECRET command to securely store the password for the materialize PostgreSQL user you created earlier:
```
CREATE SECRET pgpass AS '<PASSWORD>';
```
Use the CREATE CONNECTION command to create a connection object with access and authentication details for Materialize to use:
```
CREATE CONNECTION pg_connection TO POSTGRES (
  HOST '<host>',
  PORT 5432,
  USER 'materialize',
  PASSWORD SECRET pgpass,
  SSL MODE 'require',
  DATABASE '<database>'
  );
```
- Replace <host> with your PostgreSQL endpoint.
- Replace <database> with the name of the database containing the tables you want to replicate to Materialize.
Use the CREATE SOURCE command to connect Materialize to your PostgreSQL instance and start ingesting data from the publication you created earlier:
```
CREATE SOURCE mz_source
  IN CLUSTER ingest_postgres
  FROM POSTGRES CONNECTION pg_connection (PUBLICATION 'mz_source')
  FOR ALL TABLES;
```
By default, the source will be created in the active cluster; to use a different cluster, use the IN CLUSTER clause. To ingest data from specific schemas or tables in your publication, use FOR SCHEMAS (<schema1>,<schema2>) or FOR TABLES (<table1>, <table2>) instead of FOR ALL TABLES.
After source creation, you can handle upstream schema changes for specific replicated tables using the ALTER SOURCE...ADD SUBSOURCE and DROP SOURCE syntax.

In the SQL client connected to Materialize, use the CREATE CONNECTION command to create an SSH tunnel connection:
```
CREATE CONNECTION ssh_connection TO SSH TUNNEL (
    HOST '<SSH_BASTION_HOST>',
    PORT <SSH_BASTION_PORT>,
    USER '<SSH_BASTION_USER>'
);
```
- Replace <SSH_BASTION_HOST> and <SSH_BASTION_PORT> with the public IP address and port of the SSH bastion host you created earlier.
- Replace <SSH_BASTION_USER> with the username for the key pair you created for your SSH bastion host.
Get Materialize’s public keys for the SSH tunnel connection:
```
SELECT * FROM mz_ssh_tunnel_connections;
```

# Command for Linux
echo "ssh-ed25519 AAAA...76RH materialize" >> ~/.ssh/authorized_keys
echo "ssh-ed25519 AAAA...hLYV materialize" >> ~/.ssh/authorized_keys

Back in the SQL client connected to Materialize, validate the SSH tunnel connection you created using the VALIDATE CONNECTION command:
```
VALIDATE CONNECTION ssh_connection;
```
If no validation error is returned, move to the next step.
Use the CREATE SECRET command to securely store the password for the materialize PostgreSQL user you created earlier:
```
CREATE SECRET pgpass AS '<PASSWORD>';
```
Use the CREATE CONNECTION command to create another connection object, this time with database access and authentication details for Materialize to use:
```
CREATE CONNECTION pg_connection TO POSTGRES (
  HOST '<host>',
  PORT 5432,
  USER 'materialize',
  PASSWORD SECRET pgpass,
  DATABASE '<database>',
  SSH TUNNEL ssh_connection
  );
```
- Replace <host> with your PostgreSQL endpoint.
- Replace <database> with the name of the database containing the tables you want to replicate to Materialize.
Use the CREATE SOURCE command to connect Materialize to your Azure instance and start ingesting data from the publication you created earlier:
```
CREATE SOURCE mz_source
  IN CLUSTER ingest_postgres
  FROM POSTGRES CONNECTION pg_connection (PUBLICATION 'mz_source')
  FOR ALL TABLES;
```
To ingest data from specific schemas or tables in your publication, use FOR SCHEMAS (<schema1>,<schema2>) or FOR TABLES (<table1>, <table2>) instead of FOR ALL TABLES.

3. Monitor the ingestion status

Before it starts consuming the replication stream, Materialize takes a snapshot of the relevant tables in your publication. Until this snapshot is complete, Materialize won’t have the same view of your data as your PostgreSQL database.

In this step, you’ll first verify that the source is running and then check the status of the snapshotting process.

Back in the SQL client connected to Materialize, use the mz_source_statuses table to check the overall status of your source:

WITH
  source_ids AS
  (SELECT id FROM mz_sources WHERE name = 'mz_source')
SELECT *
FROM
  mz_internal.mz_source_statuses
    JOIN
      (
        SELECT referenced_object_id
        FROM mz_internal.mz_object_dependencies
        WHERE
          object_id IN (SELECT id FROM source_ids)
        UNION SELECT id FROM source_ids
      )
      AS sources
    ON mz_source_statuses.id = sources.referenced_object_id;

For each subsource, make sure the status is running. If you see stalled or failed, there’s likely a configuration issue for you to fix. Check the error field for details and fix the issue before moving on. Also, if the status of any subsource is starting for more than a few minutes, contact our team.

Once the source is running, use the mz_source_statistics table to check the status of the initial snapshot:

WITH
  source_ids AS
  (SELECT id FROM mz_sources WHERE name = 'mz_source')
SELECT sources.referenced_object_id AS id, mz_sources.name, snapshot_committed
FROM
  mz_internal.mz_source_statistics
    JOIN
      (
        SELECT object_id, referenced_object_id
        FROM mz_internal.mz_object_dependencies
        WHERE
          object_id IN (SELECT id FROM source_ids)
        UNION SELECT id, id FROM source_ids
      )
      AS sources
    ON mz_source_statistics.id = sources.referenced_object_id
    JOIN mz_sources ON mz_sources.id = sources.referenced_object_id;

object_id | snapshot_committed
----------|------------------
 u144     | t
(1 row)

Once snapshot_commited is t, move on to the next step. Snapshotting can take between a few minutes to several hours, depending on the size of your dataset and the size of the cluster the source is running in.

4. Right-size the cluster

After the snapshotting phase, Materialize starts ingesting change events from the PostgreSQL replication stream. For this work, Materialize generally performs well with an 100cc replica, so you can resize the cluster accordingly.

Still in a SQL client connected to Materialize, use the ALTER CLUSTER command to downsize the cluster to 100cc:
```
ALTER CLUSTER ingest_postgres SET (SIZE '100cc');
```
Behind the scenes, this command adds a new 100cc replica and removes the 200cc replica.

Use the SHOW CLUSTER REPLICAS command to check the status of the new replica:

SHOW CLUSTER REPLICAS WHERE cluster = 'ingest_postgres';

     cluster     | replica |  size  | ready
-----------------+---------+--------+-------
 ingest_postgres | r1      | 100cc  | t
(1 row)

Going forward, you can verify that your new cluster size is sufficient as follows:
1. In Materialize, get the replication slot name associated with your PostgreSQL source from the mz_internal.mz_postgres_sources table:
```
SELECT
    d.name AS database_name,
    n.name AS schema_name,
    s.name AS source_name,
    pgs.replication_slot
FROM
    mz_sources AS s
    JOIN mz_internal.mz_postgres_sources AS pgs ON s.id = pgs.id
    JOIN mz_schemas AS n ON n.id = s.schema_id
    JOIN mz_databases AS d ON d.id = n.database_id;
```
2. In PostgreSQL, check the replication slot lag, using the replication slot name from the previous step:
```
SELECT
    pg_size_pretty(pg_current_wal_lsn() - confirmed_flush_lsn)
    AS replication_lag_bytes
FROM pg_replication_slots
WHERE slot_name = '<slot_name>';
```
  The result of this query is the amount of data your PostgreSQL cluster must retain in its replication log because of this replication slot. Typically, this means Materialize has not yet communicated back to PostgreSQL that it has committed this data. A high value can indicate that the source has fallen behind and that you might need to scale up your ingestion cluster.

Next steps

With Materialize ingesting your PostgreSQL data into durable storage, you can start exploring the data, computing real-time results that stay up-to-date as new data arrives, and serving results efficiently.

Explore your data with SHOW SOURCES and SELECT.
Compute real-time results in memory with CREATE VIEW and CREATE INDEX or in durable storage with CREATE MATERIALIZED VIEW.
Serve results to a PostgreSQL-compatible SQL client or driver with SELECT or SUBSCRIBE or to an external message broker with CREATE SINK.
Check out the tools and integrations supported by Materialize.