Schemas overview

This page discusses Spanner schema requirements, how to use the schema to create hierarchical relationships, and schema features. It also introduces interleaved tables, which can improve query performance when querying tables in a parent-child relationship.

A schema is a namespace that contains database objects, such as tables, views, indexes, and functions. You use schemas to organize objects, apply fine-grained access control privileges, and avoid naming collisions. You must define a schema for each database in Spanner.

You can also further segment and store rows in your database table across different geographic regions. For more information, see the Geo-partitioning overview.

Strongly typed data

Data in Spanner is strongly typed. Data types include scalar and complex types, which are described in Data types in GoogleSQL and PostgreSQL data types.

Choose a primary key

Spanner databases can contain one or more tables. Tables are structured as rows and columns. The table schema defines one or more table columns as the table's primary key which uniquely identifies each row. Primary keys are always indexed for quick row lookup. If you want to update or delete existing rows in a table, then the table must have a primary key. A table with no primary key columns can only have one row. Only GoogleSQL-dialect databases can have tables without a primary key.

Often your application already has a field that's a natural fit for use as the primary key. For example, for a Customers table, there might be an application-supplied CustomerId that serves well as the primary key. In other cases, you might need to generate a primary key when inserting the row. This would typically be a unique integer value with no business significance (a surrogate primary key).

In all cases, you should be careful not to create hotspots with the choice of your primary key. For example, if you insert records with a monotonically increasing integer as the key, you'll always insert at the end of your key space. This is undesirable because Spanner divides data among servers by key ranges, which means your inserts will be directed at a single server, creating a hotspot. There are techniques that can spread the load across multiple servers and avoid hotspots:

• Hash the key and store it in a column. Use the hash column (or the hash column and the unique key columns together) as the primary key.
• Swap the order of the columns in the primary key.
• Use a Universally Unique Identifier (UUID). Version 4 UUID is recommended, because it uses random values in the high-order bits. Don't use a UUID algorithm (such as version 1 UUID) that stores the timestamp in the high order bits.
• Bit-reverse sequential values.

Parent-child table relationships

There are two ways to define parent-child relationships in Spanner: table interleaving and foreign keys.

Spanner's table interleaving is a good choice for many parent-child relationships. With interleaving, Spanner physically colocates child rows with parent rows in storage. Co-location can significantly improve performance. For example, if you have a Customers table and an Invoices table, and your application frequently fetches all the invoices for a customer, you can define Invoices as an interleaved child table of Customers. In doing so, you're declaring a data locality relationship between two independent tables. You're telling Spanner to store one or more rows of Invoices with one Customers row. This parent-child relationship is enforced when interleaved with the INTERLEAVE IN PARENT clause. INTERLEAVE IN child tables share the same physical row interleaving characteristics, but Spanner doesn't enforce referential integrity between parent and child.

You associate a child table with a parent table by using DDL that declares the child table as interleaved in the parent, and by including the parent table primary key as the first part of the child table composite primary key.

For more information about interleaving, see Create interleaved tables.

Foreign keys are a more general parent-child solution and address additional use cases. They are not limited to primary key columns, and tables can have multiple foreign key relationships, both as a parent in some relationships and a child in others. However, a foreign key relationship does not imply co-location of the tables in the storage layer.

Google recommends that you choose to represent parent-child relationships either as interleaved tables or as foreign keys, but not both. For more information on foreign keys and their comparison to interleaved tables, see Foreign keys overview.

Primary keys in interleaved tables

For interleaving, every table must have a primary key. If you declare a table to be an interleaved child of another table, the table must have a composite primary key that includes all of the components of the parent's primary key, in the same order, and, typically, one or more additional child table columns.

Spanner stores rows in sorted order by primary key values, with child rows inserted between parent rows. See an illustration of interleaved rows in Create interleaved tables later in this page.

In summary, Spanner can physically colocate rows of related tables. The schema examples show what this physical layout looks like.

Database splits

You can define hierarchies of interleaved parent-child relationships up to seven layers deep, which means that you can colocate rows of seven independent tables. If the size of the data in your tables is small, a single Spanner server can probably handle your database. But what happens when your related tables grow and start reaching the resource limits of an individual server? Spanner is a distributed database, which means that as your database grows, Spanner divides your data into chunks called "splits." Individual splits can move independently from each other and get assigned to different servers, which can be in different physical locations. A split holds a range of contiguous rows. The start and end keys of this range are called "split boundaries". Spanner automatically adds and removes split boundaries based on size and load, which changes the number of splits in the database.

Load-based splitting

As an example of how Spanner performs load-based splitting to mitigate read hotspots, suppose your database contains a table with 10 rows that are read more frequently than all of the other rows in the table. Spanner can add split boundaries between each of those 10 rows so that they're each handled by a different server, rather than allowing all the reads of those rows to consume the resources of a single server.

As a general rule, if you follow best practices for schema design, Spanner can mitigate hotspots such that the read throughput should improve every few minutes until you saturate the resources in your instance or run into cases where no new split boundaries can be added (because you have a split that covers just a single row with no interleaved children).

Named schemas

Named schemas help you organize similar data together. This helps you to quickly find objects in the Google Cloud console, apply privileges, and avoid naming collisions.

Named schemas, like other database objects, are managed using DDL.

Spanner named schemas permit you to use fully qualified names (FQNs) to query for data. FQNs let you combine the schema name and the object name to identify database objects. For example, you could create a schema called warehouse for the warehouse business unit. The tables that use this schema could include: product, order, and customer information. Or you could create a schema called fulfillment for the fulfillment business unit. This schema could also have tables called product, order, and customer information. In the first example, the FQN is warehouse.product and in the second example, the FQN is fulfillment.product. This prevents confusion in situations where multiple objects share the same name.

In the CREATE SCHEMA DDL, table objects are given both an FQN, for example, sales.customers, and a short name, for example, sales.

The following database objects support named schemas:

• TABLE
  • CREATE
  • INTERLEAVE IN [PARENT]
  • FOREIGN KEY
  • SYNONYM
• VIEW
• INDEX
• SEARCH INDEX
• FOREIGN KEY
• SEQUENCE

For more information about using named schemas, see Manage named schemas.

Use fine-grained access control with named schemas

Named schemas let you grant schema-level access to each object in the schema. This applies to schema objects that exist at the time that you grant access. You must grant access to objects that are added later.

Fine-grained access control limits access to entire groups of database objects, such as tables, columns, and rows in the table.

For more information, see Grant fine-grained access control privileges to named schemas.

Schema examples

The schema examples in this section show how to create parent and child tables with and without interleaving, and illustrate the corresponding physical layouts of data.

Create a parent table

Suppose you're creating a music application and you need a table that stores rows of singer data:

Note that the table contains one primary key column, SingerId, which appears to the left of the bolded line, and that tables are organized by rows and columns.

You can define the table with the following DDL:

CREATE TABLE Singers (
SingerId   INT64 NOT NULL PRIMARY KEY,
FirstName  STRING(1024),
LastName   STRING(1024),
SingerInfo BYTES(MAX),
);

CREATE TABLE singers (
singer_id   BIGINT PRIMARY KEY,
first_name  VARCHAR(1024),
last_name   VARCHAR(1024),
singer_info BYTEA
);

Note the following about the example schema:

• Singers is a table at the root of the database hierarchy (because it's not defined as an interleaved child of another table).
• For GoogleSQL-dialect databases, primary key columns are usually annotated with NOT NULL (though you can omit this annotation if you want to allow NULL values in key columns. For more information, see Key Columns).
• Columns that are not included in the primary key are called non-key columns, and they can have an optional NOT NULL annotation.
• Columns that use the STRING or BYTES type in GoogleSQL must be defined with a length, which represents the maximum number of Unicode characters that can be stored in the field. The length specification is optional for the PostgreSQL varchar and character varying types. For more information, see Scalar Data Types for GoogleSQL-dialect databases and PostgreSQL data types for PostgreSQL-dialect databases.

What does the physical layout of the rows in the Singers table look like? The following diagram shows rows of the Singers table stored by primary key ("Singers(1)", and then "Singers(2)", where the number in parentheses is the primary key value.

The preceding diagram illustrates an example split boundary between the rows keyed by Singers(3) and Singers(4), with the data from the resulting splits assigned to different servers. As this table grows, it's possible for rows of Singers data to be stored in different locations.

Create parent and child tables

Assume that you now want to add some basic data about each singer's albums to the music application.

Note that the primary key of Albums is composed of two columns: SingerId and AlbumId, to associate each album with its singer. The following example schema defines both the Albums and Singers tables at the root of the database hierarchy, which makes them sibling tables.

-- Schema hierarchy:
-- + Singers (sibling table of Albums)
-- + Albums (sibling table of Singers)

CREATE TABLE Singers (
 SingerId   INT64 NOT NULL PRIMARY KEY,
 FirstName  STRING(1024),
 LastName   STRING(1024),
 SingerInfo BYTES(MAX),
);

CREATE TABLE Albums (
SingerId     INT64 NOT NULL,
AlbumId      INT64 NOT NULL,
AlbumTitle   STRING(MAX),
) PRIMARY KEY (SingerId, AlbumId);

CREATE TABLE singers (
singer_id   BIGINT PRIMARY KEY,
first_name  VARCHAR(1024),
last_name   VARCHAR(1024),
singer_info BYTEA
);

CREATE TABLE albums (
singer_id     BIGINT,
album_id      BIGINT,
album_title   VARCHAR,
PRIMARY KEY (singer_id, album_id)
);

The physical layout of the rows of Singers and Albums looks like the following diagram, with rows of the Albums table stored by contiguous primary key, then rows of Singers stored by contiguous primary key:

One important note about the schema is that Spanner assumes no data locality relationships between the Singers and Albums tables, because they are top-level tables. As the database grows, Spanner can add split boundaries between any of the rows. This means the rows of the Albums table could end up in a different split from the rows of the Singers table, and the two splits could move independently from each other.

Depending on your application's needs, it might be fine to allow Albums data to be located on different splits from Singers data. However, this might incur a performance penalty due to the need to coordinate reads and updates across distinct resources. If your application frequently needs to retrieve information about all the albums for a particular singer, then you should create Albums as an interleaved child table of Singers, which colocates rows from the two tables along the primary key dimension. The next example explains this in more detail.

Create interleaved tables

An interleaved table is a table that you declare to be an interleaved child of another table because you want the rows of the child table to be physically stored with the associated parent row. As mentioned earlier, the parent table primary key must be the first part of the child table composite primary key.

After you interleave a table, it's permanent. You can't undo the interleaving. Instead, you need to create the table again and migrate data to it.

As you're designing your music application, suppose you realize that the app needs to frequently access rows from the Albums table when it accesses a Singers row. For example, when you access the row Singers(1), you also need to access the rows Albums(1, 1) and Albums(1, 2). In this case, Singers and Albums need to have a strong data locality relationship. You can declare this data locality relationship by creating Albums as an interleaved child table of Singers.

-- Schema hierarchy:
-- + Singers
--   + Albums (interleaved table, child table of Singers)

The bolded line in the following schema shows how to create Albums as an interleaved table of Singers.

CREATE TABLE Singers (
 SingerId   INT64 NOT NULL PRIMARY KEY,
 FirstName  STRING(1024),
 LastName   STRING(1024),
 SingerInfo BYTES(MAX),
 );

CREATE TABLE Albums (
 SingerId     INT64 NOT NULL,
 AlbumId      INT64 NOT NULL,
 AlbumTitle   STRING(MAX),
 ) PRIMARY KEY (SingerId, AlbumId),
INTERLEAVE IN PARENT Singers ON DELETE CASCADE;

CREATE TABLE singers (
 singer_id   BIGINT PRIMARY KEY,
 first_name  VARCHAR(1024),
 last_name   VARCHAR(1024),
 singer_info BYTEA
 );

CREATE TABLE