Schema migration for PostgreSQL

Spanner migration tool makes some assumptions while performing data type conversion from PostgreSQL to Spanner. There are also nuances to handling certain specific data types. These are captured below.

Table of contents

Data type mapping
NUMERIC
BIGSERIAL and SERIAL
TIMESTAMP
CHAR(n) and VARCHAR(n)
Storage Use
Arrays
Primary Keys
NOT NULL Constraints
Foreign Keys
Default Values
Secondary Indexes
Other PostgreSQL features

Data type mapping

The Spanner migration tool maps PostgreSQL types to Spanner types as follows:

PostgreSQL Type	Spanner Type	Notes
`BOOL`	`BOOL`
`BIGINT`	`INT64`
`BIGSERIAL`	`INT64`	dropped autoincrement functionality
`BYTEA`	`BYTES(MAX)`
`CHAR`	`STRING(1)`	CHAR defaults to length 1
`CHAR(N)`	`STRING(N)`	differences in treatment of fixed-length character types
`DATE`	`DATE`
`DOUBLE PRECISION`	`FLOAT64`
`INTEGER`	`INT64`	changes in storage size
`NUMERIC`	`NUMERIC`	potential changes of precision
`REAL`	`FLOAT32`
`SERIAL`	`INT64`	dropped autoincrement functionality , changes in storage size
`SMALLINT`	`INT64`	changes in storage size
`TEXT`	`STRING(MAX)`
`TIMESTAMP`	`TIMESTAMP`	differences in treatment of timezones
`TIMESTAMPTZ`	`TIMESTAMP`
`VARCHAR`	`STRING(MAX)`
`VARCHAR(N)`	`STRING(N)`	differences in treatment of fixed-length character types
`JSON`, `JSONB`	`JSON`
`ARRAY(`pgtype`)`	`ARRAY(`spannertype`)`	if scalar type pgtype maps to spannertype

All other types map to STRING(MAX).

NUMERIC

Spanner’s NUMERIC type can store up to 29 digits before the decimal point and up to 9 after the decimal point. PostgreSQL’s NUMERIC type can potentially support higher precision that this, so please verify that Spanner’s NUMERIC support meets your application needs.

BIGSERIAL and SERIAL

Spanner does not support autoincrementing types, so these both map to INT64 and the autoincrementing functionality is dropped.

TIMESTAMP

PosgreSQL has two timestamp types: TIMESTAMP and TIMESTAMPTZ. Both have an 8 byte data representation and provide microsecond resolution, but neither actually stores a timezone with the data. The key difference between the two types is how string literals are converted to timestamps and queries return data. For TIMESTAMP, all timezone information is dropped, and data is returned without a timezone. For TIMESTAMPTZ, string literals are converted to UTC, using the literal’s timezone if it is specified, or the PostgreSQL’s timezone paramater if not. When data is printed stored data (in UTC) is converted to the timezone from the timezone parameter

Spanner has a single timestamp type. Data is stored as UTC (there is no separate timezone) Spanner client libraries convert timestamps to UTC before sending them to Spanner. Data is always returned as UTC. Spanner’s timestamp type is essentially the same as TIMESTAMPTZ, except that there is no analog of PostgreSQL’s timezone parameter.

In other words, mapping PostgreSQL TIMESTAMPTZ to TIMESTAMP is fairly straightforward, but care should be taken with PostgreSQL TIMESTAMP data because Spanner clients will not drop the timezone.

CHAR(n) and VARCHAR(n)

The semantics of fixed-length character types differ between PostgreSQL and Spanner. The CHAR(n) type in PostgreSQL is padded with spaces. If a string value smaller than the limit is stored, spaces will be added to pad it out to the specified length. If a string longer than the specified length is stored, and the extra characters are all spaces, then it will be silently truncated. Moreover, trailing spaces are ignored when comparing two values. In constrast, Spanner does not give special treatment to spaces, and the specified length simply represents the maximum length that can be stored. This is close to the semantics of PostgreSQL’s VARCHAR(n). However there are some minor differences. For example, even VARCHAR(n) has some special treatment of spaces: strings longer than the specified length are silently truncated if the extra characters are all spaces.

Storage Use

The tool maps several PostgreSQL types to Spanner types that use more storage. For example, SMALLINT is a two-byte integer, but it maps to Spanner’s INT64, an eight-byte integer. This additional storage could be significant for large arrays.

Arrays

Spanner does not support multi-dimensional arrays. So while TEXT[4] maps to ARRAY<STRING(MAX)> and REAL ARRAY maps to ARRAY<FLOAT32>, TEXT[][] maps to STRING(MAX).

Also note that PosgreSQL supports array limits, but the PostgreSQL implementation ignores them. Spanner does not support array size limits, but since they have no effect anyway, the tool just drops them.

Primary Keys

Spanner requires primary keys for all tables. PostgreSQL recommends the use of primary keys for all tables, but does not enforce this. When converting a table without a primary key, Spanner migration tool will create a new primary key of type INT64. By default, the name of the new column is synth_id. If there is already a column with that name, then a variation is used to avoid collisions.

NOT NULL Constraints

The tool preserves NOT NULL constraints. Note that Spanner does not require primary key columns to be NOT NULL. However, in PostgreSQL, a primary key is a combination of NOT NULL and UNIQUE, and so primary key columns from PostgreSQL will be mapped to Spanner columns that are both primary keys and NOT NULL.

Foreign Keys

The tool maps PostgreSQL foreign key constraints into Spanner foreign key constraints, and preserves constraint names where possible. Note that Spanner requires foreign key constraint names to be globally unique (within a database), but in postgres they only have to be unique for a table, so we add a uniqueness suffix to a name if needed. Spanner doesn’t support ON DELETE and ON UPDATE actions, so we drop these.

Default Values

While Spanner supports default values, Spanner migration tool currently does not support translating source DEFAULT constraints to Spanner DEFAULT constraints. We drop the DEFAULT MySQL constraint during conversion. It can be manually added to the DDL via an ALTER TABLE command.

Secondary Indexes

The tool maps PostgresSQL secondary indexes to Spanner secondary indexes, preserving constraint names where possible. The tool also maps PostgreSQL UNIQUE constraints to Spanner UNIQUE secondary indexes. Check here for more details.