pg_parquet

Copy from/to Parquet files in PostgreSQL!

pg_parquet is a PostgreSQL extension that allows you to read and write Parquet files, which are located in S3 or file system, from PostgreSQL via COPY TO/FROM commands. It depends on Apache Arrow project to read and write Parquet files and pgrx project to extend PostgreSQL's COPY command.

-- Copy a query result into Parquet in S3
COPY (SELECT * FROM table) TO 's3://mybucket/data.parquet' WITH (format 'parquet');

-- Load data from Parquet in S3
COPY table FROM 's3://mybucket/data.parquet' WITH (format 'parquet');

Quick Reference

• Installation From Source
• Usage
  • Copy FROM/TO Parquet files TO/FROM Postgres tables
  • Inspect Parquet schema
  • Inspect Parquet metadata
• Object Store Support
• Copy Options
• Configuration
• Supported Types
  • Nested Types
• Postgres Support Matrix

Installation From Source

After installing Postgres, you need to set up rustup, cargo-pgrx to build the extension.

# install rustup
> curl --proto '=https' --tlsv1.2 -sSf https://sh.rustup.rs | sh

# install cargo-pgrx
> cargo install cargo-pgrx

# configure pgrx
> cargo pgrx init --pg17 $(which pg_config)

# append the extension to shared_preload_libraries in ~/.pgrx/data-17/postgresql.conf 
> echo "shared_preload_libraries = 'pg_parquet'" >> ~/.pgrx/data-17/postgresql.conf

# run cargo-pgrx to build and install the extension
> cargo pgrx run

# create the extension in the database
psql> "CREATE EXTENSION pg_parquet;"

Usage

There are mainly 3 things that you can do with pg_parquet:

1. You can export Postgres tables/queries to Parquet files,
2. You can ingest data from Parquet files to Postgres tables,
3. You can inspect the schema and metadata of Parquet files.

COPY to/from Parquet files from/to Postgres tables

You can use PostgreSQL's COPY command to read and write Parquet files. Below is an example of how to write a PostgreSQL table, with complex types, into a Parquet file and then to read the Parquet file content back into the same table.

-- create composite types
CREATE TYPE product_item AS (id INT, name TEXT, price float4);
CREATE TYPE product AS (id INT, name TEXT, items product_item[]);

-- create a table with complex types
CREATE TABLE product_example (
    id int,
    product product,
    products product[],
    created_at TIMESTAMP,
    updated_at TIMESTAMPTZ
);

-- insert some rows into the table
insert into product_example values (
    1,
    ROW(1, 'product 1', ARRAY[ROW(1, 'item 1', 1.0), ROW(2, 'item 2', 2.0), NULL]::product_item[])::product,
    ARRAY[ROW(1, NULL, NULL)::product, NULL],
    now(),
    '2022-05-01 12:00:00-04'
);

-- copy the table to a parquet file
COPY product_example TO '/tmp/product_example.parquet' (format 'parquet', compression 'gzip');

-- show table
SELECT * FROM product_example;

-- copy the parquet file to the table
COPY product_example FROM '/tmp/product_example.parquet';

-- show table
SELECT * FROM product_example;

Inspect Parquet schema

You can call SELECT * FROM parquet.schema(<uri>) to discover the schema of the Parquet file at given uri.

Inspect Parquet metadata

You can call SELECT * FROM parquet.metadata(<uri>) to discover the detailed metadata of the Parquet file, such as column statistics, at given uri.

You can call SELECT * FROM parquet.file_metadata(<uri>) to discover file level metadata of the Parquet file, such as format version, at given uri.

You can call SELECT * FROM parquet.kv_metadata(<uri>) to query custom key-value metadata of the Parquet file at given uri.

Object Store Support

pg_parquet supports reading and writing Parquet files from/to S3 object store. Only the uris with s3:// scheme is supported.

The simplest way to configure object storage is by creating the standard ~/.aws/credentials and ~/.aws/config files:

$ cat ~/.aws/credentials
[default]
aws_access_key_id = AKIAIOSFODNN7EXAMPLE
aws_secret_access_key = wJalrXUtnFEMI/K7MDENG/bPxRfiCYEXAMPLEKEY

$ cat ~/.aws/config 
[default]
region = eu-central-1

Alternatively, you can use the following environment variables when starting postgres to configure the S3 client:

• AWS_ACCESS_KEY_ID: the access key ID of the AWS account
• AWS_SECRET_ACCESS_KEY: the secret access key of the AWS account
• AWS_REGION: the default region of the AWS account
• AWS_SHARED_CREDENTIALS_FILE: an alternative location for the credentials file
• AWS_CONFIG_FILE: an alternative location for the config file
• AWS_PROFILE: the name of the profile from the credentials and config file (default profile name is default)

Copy Options

pg_parquet supports the following options in the COPY TO command:

• format parquet: you need to specify this option to read or write Parquet files which does not end with .parquet[.<compression>] extension. (This is the only option that COPY FROM command supports.),
• row_group_size <int>: the number of rows in each row group while writing Parquet files. The default row group size is 122880,
• row_group_size_bytes <int>: the total byte size of rows in each row group while writing Parquet files. The default row group size bytes is row_group_size * 1024,
• compression <string>: the compression format to use while writing Parquet files. The supported compression formats are uncompressed, snappy, gzip, brotli, lz4, lz4raw and zstd. The default compression format is snappy. If not specified, the compression format is determined by the file extension.
• compression_level <int>: the compression level to use while writing Parquet files. The supported compression levels are only supported for gzip, zstd and brotli compression formats. The default compression level is 6 for gzip (0-10), 1 for zstd (1-22) and 1 for brotli (0-11).

Configuration

There is currently only one GUC parameter to enable/disable the pg_parquet:

• pg_parquet.enable_copy_hooks: you can set this parameter to on or off to enable or disable the pg_parquet extension. The default value is on.

Supported Types

pg_parquet has rich type support, including PostgreSQL's primitive, array, and composite types. Below is the table of the supported types in PostgreSQL and their corresponding Parquet types.

Nested Types

Postgres Support Matrix

pg_parquet is tested with the following PostgreSQL versions: