Manage schemas using Iglu Server

To manage your schemas, you will need to have an Iglu Server installed (you will already have one if you followed the Snowplow Self-Hosted Quick Start).

Alternatively, you can host a static Iglu registry in Amazon S3 or Google Cloud Storage.

Create a schema

First, design the schema for your custom event (or entity). For example:

json

{
     "$schema": "http://iglucentral.com/schemas/com.snowplowanalytics.self-desc/schema/jsonschema/1-0-0#",
     "description": "Schema for a button click event",
     "self": {
         "vendor": "com.snowplowanalytics",
         "name": "button_click",
         "format": "jsonschema",
         "version": "1-0-0"
     },
     "type": "object",
     "properties": {
         "id": {
             "type": "string",
             "minLength": 1
         },
         "target": {
             "type": "string"
         },
         "content": {
             "type": "string"
         }
     },
     "required": ["id"],
     "additionalProperties": false
 }

Next, save this schema in the following folder structure, with a filename of 1-0-0 (without any extension):

schemas
└── com.snowplowanalytics
    └── button_click
        └── jsonschema
            └── 1-0-0

tip

If you update the vendor or the name in the example, you should update the above path too.

Finally, to upload your schema to your Iglu registry, you can use igluctl:

bash

igluctl static push --public <local path to schemas> <Iglu server endpoint> <iglu_super_api_key>

See the Igluctl reference page for more information on the static push command.

Versioning schemas

When evolving your schema and uploading it to your Iglu Server, you will need to choose how to increment its version.

There are two kinds of schema changes:

• Non-breaking - a non-breaking change is backward compatible with historical data and increments the patch number i.e. 1-0-0 -> 1-0-1, or the middle digit i.e. 1-0-0 -> 1-1-0.
• Breaking - a breaking change is not backwards compatible with historical data and increments the model number i.e. 1-0-0 -> 2-0-0.

Different data warehouses handle schema evolution slightly differently. Use the table below as a guide for incrementing the schema version appropriately.

	Redshift	Snowflake, BigQuery, Databricks
Add / remove / rename an optional field	Non-breaking	Non-breaking
Add / remove / rename a required field	Breaking	Breaking
Change a field from optional to required	Breaking	Breaking
Change a field from required to optional	Breaking	Non-breaking
Change the type of an existing field	Breaking	Breaking
Change the size of an existing field	Non-breaking	Non-breaking

Size changes

In Redshift and Databricks, changing size may also mean type change. For example, changing the maximum integer from 30000 to 100000. See our documentation on how schemas translate to database types.