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pgx_json_schema

A JSON Schema validator for Postgres implemented in Rust

This repo is a lightweight connection between the following excellent packages:

Supported drafts:

  • Draft 7 (except optional idn-hostname)
  • Draft 6
  • Draft 4 (except optional bignum)

Partially supported drafts (some keywords are not implemented):

  • Draft 2019-09
  • Draft 2020-12

Bonus support added for:

Installation:

# Install Rust
# https://www.rust-lang.org/tools/install
curl --proto '=https' --tlsv1.2 -sSf https://sh.rustup.rs | sh

# Install PGX
cargo install cargo-pgx
cargo pgx init

# Download this repo
curl -L 'https://github.com/jefbarn/pgx_json_schema/archive/refs/tags/0.1.0.tar.gz' \
   | tar -xz --strip-components=1
   
# Build and install the extension package
cargo pgx package

# Enable the extension in your database
create extension pgx_json_schema;

How to use:

JSON Schema

select * from json_schema_is_valid('{"maxLength": 5}'::jsonb, '"foobar"'::jsonb);

json_schema_is_valid
----------------------
f

select * from json_schema_get_errors('{"maxLength": 5}'::jsonb, '"foobar"'::jsonb);

error_value |             description              |        details         | instance_path | schema_path
------------+--------------------------------------+------------------------+---------------+-------------
"foobar"    | "foobar" is longer than 5 characters | MaxLength { limit: 5 } |               | /maxLength

Warning A warning about performance.

Because the jsonschema crate must complile the schema before use, and Postgres uses separate heap per thread, this extension must compile the schema every time the function is invoked. This leads to pretty terrible performance for validating any large amount of data.

To fix this we'd need to get the jsonschema crate to implement Copy/Clone on the JSONSchema struct and then move the compiled schema into shared memory where it could be reused. Will explore this in the future.

JSON Type Definition

NOTE: The jtd library only reports the position of the validation errors, not a description.

select jtd_is_valid('{
    "properties": {
        "name": { "type": "string" },
        "age": { "type": "uint32" },
        "phones": {
            "elements": {
                "type": "string"
            }
        }
    }
}'::jsonb, '{
    "age": "43",
    "phones": ["+44 1234567", 442345678]
}'::jsonb);

 jtd_is_valid 
--------------
 f

select instance_path, schema_path from jtd_get_errors('{
    "properties": {
        "name": { "type": "string" },
        "age": { "type": "uint32" },
        "phones": {
            "elements": {
                "type": "string"
            }
        }
    }
}', '{
    "age": "43",
    "phones": ["+44 1234567", 442345678]
}'::jsonb);

 instance_path |           schema_path            
---------------+----------------------------------
 /age          | /properties/age/type
               | /properties/name
 /phones/1     | /properties/phones/elements/type

Apache Avro

NOTE: The avro library only does complete validation, there is no way to list the errors.

select avro_is_valid('{
    "type": "record",
    "name": "test",
    "fields": [
        {"name": "a", "type": "long", "default": 42},
        {"name": "b", "type": "string"}
    ]
}'::jsonb, '{
    "a": 27,
    "b": "foo"
}'::jsonb);

 avro_is_valid 
---------------
 t

Things left to do:

  • Use shared memory to store compiled validator (potential performance gain)
  • More testing
  • Benchmarking
  • Add more schema types like JTD and Avro
  • Support newer JSON Schema drafts
  • Add Dockerfile with installation example

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JSON Schema validation for Postgres

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