Guide: Handle upstream schema changes with zero downtime

Materialize allows you to handle certain types of upstream table schema changes seamlessly, specifically:

• Adding a column in the upstream database.
• Dropping a column in the upstream database.

This guide walks you through how to handle these changes without any downtime in Materialize.

Prerequisites

Some familiarity with Materialize. If you’ve never used Materialize before, start with our guide to getting started to learn how to connect a database to Materialize.

Set up a SQL Server database

For this guide, setup a SQL Server 2016+ database. In your SQL Server, create a table t1 and populate:

CREATE TABLE t1 (
    a INT
);

INSERT INTO t1 (a) VALUES
    (10);
GO -- The GO terminator may be unsupported or unnecessary for your client.

Configure your SQL Server Database

Configure your SQL Server database using the configuration instructions for self hosted SQL Server.

Connect your source database to Materialize

Create a connection to your SQL Server database using the CREATE CONNECTION syntax.

Create a source using the new syntax

In Materialize, create a source using the CREATE SOURCE syntax.

CREATE SOURCE my_source
  FROM SQL SERVER CONNECTION sqlserver_connection;

Create a table from the source

To start ingesting specific tables from your source database, you can create a table in Materialize. We’ll add it into the v1 schema in Materialize.

CREATE SCHEMA v1;

CREATE TABLE v1.t1
    FROM SOURCE my_source(REFERENCE dbo.t1);

Once you’ve created a table from source, the initial snapshot of table v1.t1 will begin.

Create a view on top of the table.

For this guide, add a materialized view matview (also in schema v1) that sums column a from table t1.

CREATE MATERIALIZED VIEW v1.matview AS
    SELECT SUM(a) from v1.t1;

Handle upstream column addition

A. Add a column in your upstream SQL Server database

In your upstream SQL Server database, add a new column b to the table t1:

ALTER TABLE t1
    ADD b BIT NULL;

INSERT INTO t1 (a,b) VALUES
    (20, 1);
GO -- The GO terminator may be unsupported or unnecessary for your client.

This operation does not impact the SQL Server CDC output; the SQL Server continues to publish CDC changes only for column a. As such, the addition of a new column has no immediate effect in Materialize. In Materialize:

• The table v1.t1 will continue to ingest only column a.
• The materialized view v1.matview will continue to have access to column a only.

B. Enable CDC for your table under a new capture instance in your upstream SQL Server database

In order for Materialize to begin receiving data for this new column, you must create a new capture instance for your table, explicitly specifing a new @capture_instance name.

EXEC sys.sp_cdc_enable_table
  @source_schema = 'dbo',
  @source_name = 't1',
  @role_name = 'materialize_role',
  @capture_instance = 'dbo_t1_v2', -- MUST BE SPECIFIED
  @supports_net_changes = 0;
GO -- The GO terminator may be unsupported or unnecessary for your client.

The newly created capture instance will include CDC data for column b. Now, when you create a new table t1 from your source in Materialize (see next step), Materialize will select the most recently created capture instance (i.e., the capture instance with the newly added column b).

See also:

• Capture instance selection
• Enable Change-Data-Capture for the tables

C. Create a new table from the source in Materialize

To incorporate the new column into Materialize, create a new v2 schema and recreate the table in the new schema. When creating the table, Materialize uses the most recently created capture instance (i.e., the capture instance with the newly added column b):

CREATE SCHEMA v2;

CREATE TABLE v2.t1
    FROM SOURCE my_source(REFERENCE dbo.t1);

The snapshotting of table v2.t1 will begin. v2.t1 will include columns a and b.

When the new v2.t1 table has finished snapshotting, create a new materialized view matview in the new schema. Since the new v2.matview is referencing the new v2.t1, it can reference column b:

CREATE MATERIALIZED VIEW v2.matview AS
    SELECT SUM(a)
    FROM v2.t1
    WHERE b = true;

Handle upstream column drop

A. Exclude the column in Materialize

To drop a column safely, in Materialize, first, create a new v3 schema, and recreate table t1 in the new schema but exclude the column to drop. In this example, we’ll drop the column b.

CREATE SCHEMA v3;
CREATE TABLE v3.t1
    FROM SOURCE my_source(REFERENCE dbo.t1) WITH (EXCLUDE COLUMNS (b));

B. Drop a column in your upstream SQL Server database

In your upstream SQL Server database, drop the column b from the table t1:

ALTER TABLE t1 DROP COLUMN b;
GO -- The GO terminator may be unsupported or unnecessary for your client.

Dropping the column b in SQL Server will not affect v3.t1 (or on v1.t1) in Materialize. However, the drop affects v2.t1 and v2.matview from our earlier examples. When the user attempts to read from either, Materialize will report an error that the source table schema has been altered.

Optional

Disable unused capture instance

SQL Server only allows a maximum of 2 capture instances per table.

To find the capture instance(s) for a table:

SELECT capture_instance
FROM cdc.change_tables
WHERE source_schema = '<schema>'
  AND source_table = '<table>';

After you have fully cut over to the new source version for the table, and you previously created a new capture instance for your upstream table, you may wish to disable the old capture instance if it is no longer in use.

To disable a capture instance for a table:

EXEC sys.sp_cdc_disable_table
    @source_schema = '<schema>',
    @source_name = '<source_table_name>',
    @capture_instance = '<old_capture_instance_name>';