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Schematizer

What is it?

The Schematizer is a schema store service that tracks and manages all the schemas used in the Data Pipeline and provides features like automatic documentation support. We use Apache Avro to represent our schemas.

Read More

How to download

git clone git@github.com:Yelp/schematizer.git

Tests

Running unit tests

make -f Makefile-opensource test

Running unit integration tests

make -f Makefile-opensource itest

Setup and Configuration

  1. Create a mysql database for Schematizer Service::
CREATE DATABASE <db_name> DEFAULT CHARACTER SET utf8;
  1. Create MySQL tables in <db_name> database for Schematizer Service::
cat schema/tables/*.sql | mysql <db_name>
  1. Create a topology.yaml file
topology:
-   cluster: <schematizer_cluster_name>
    replica: master
    entries:
        - charset: utf8
          use_unicode: true
          host: <db_ip>
          db: <db_name>
          user: <db_user>
          passwd: <db_password>
          port: <db_port>
  1. In config.yaml assign values to the following configs::
schematizer_cluster: <schematizer_cluster_name>

topology_path: /path/to/topology.yaml

Usage

Use serviceinitd/schematizer.py to start the Schematizer service.

Interactive directly with Schematizer Service.

Registering a schema::

curl -X POST --header 'Content-Type: application/json' --header 'Accept: text/plain' -d '{
  "namespace": "test_namespace",
  "source_owner_email": "test@test.com",
  "source": "test_source",
  "contains_pii": false,
  "schema": "{\"type\":\"record\",\"namespace\":\"test_namespace\",\"source\":\"test_source\",\"name\":\"test_name\",\"doc\":\"test_doc\",\"fields\":[{\"type\":\"string\",\"doc\":\"test_doc1\",\"name\":\"key1\"},{\"type\":\"string\",\"doc\":\"test_doc2\",\"name\":\"key2\"}]}"
}' 'http://127.0.0.1:8888/v1/schemas/avro'

Getting Schema By ID::

curl -X GET --header 'Accept: text/plain' 'http://127.0.0.1:8888/v1/schemas/<schema_id>'

Interactive with Schematizer Service using Schematizer Client Lib.

Registering a schema::

from data_pipeline.schematizer_clientlib.schematizer import get_schematizer
test_avro_schema_json = {
    "type": "record",
    "namespace": "test_namespace",
    "source": "test_source",
    "name": "test_name",
    "doc": "test_doc",
    "fields": [
        {"type": "string", "doc": "test_doc1", "name": "key1"},
        {"type": "string", "doc": "test_doc2", "name": "key2"}
    ]
}
schema_info = get_schematizer().register_schema_from_schema_json(
    namespace="test_namespace",
    source="test_source",
    schema_json=test_avro_schema_json,
    source_owner_email="test@test.com",
    contains_pii=False
)

Getting Schema By ID::

from data_pipeline.schematizer_clientlib.schematizer import get_schematizer

schema_info = get_schematizer().get_schema_by_id(
    schema_id=schema_info.schema_id
)

Disclaimer

We're still in the process of setting up this service as a stand-alone. There may be additional work required to run a Schematizer instance and integrate with other applications.

License

Schematizer is licensed under the Apache License, Version 2.0: http://www.apache.org/licenses/LICENSE-2.0

Contributing

Everyone is encouraged to contribute to Schematizer by forking the Github repository and making a pull request or opening an issue.

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A schema store service that tracks and manages all the schemas used in the Data Pipeline

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