Transforms

​

The issue

Depending on how you choose to source your data, you might find that you run into 1 of 2 issues:

1. You only care about a few contracts
   Rather than fill up your database with a ton of extra data, you’d rather filter down your data to a smaller set.

2. The data is still a bit raw
   Maybe you’d rather track gwei rounded to the nearest whole number instead of wei. You’re looking to map data to a different format so you don’t have to run this calculation over and over again.

​

The SQL Solution

You can use SQL-based transforms to solve both of these challenges that normally would have you writing your own indexer or data pipeline. Instead, Goldsky can automatically run these for you using just 3 pieces of info:

• name: A shortname for this transform
  You can refer to this from sinks via from or treat it as a table in SQL from other transforms.
• sql: The actual SQL
  To filter your data, use a WHERE clause, e.g. WHERE liquidity > 1000.
  To map your data, use an AS clause combined with SELECT, e.g. SELECT wei / 1000000000 AS gwei.
• primary_key: A unique ID
  This should be unique, but you can also use this to intentionally de-duplicate data - the latest row with the same ID will replace all the others.

Combine them together into your config:

• v3
• v2 (deprecated)

transforms:
  negative_fpmm_scaled_liquidity_parameter:
    sql: SELECT id FROM polymarket.fixed_product_market_maker WHERE scaled_liquidity_parameter < 0
    primary_key: id

Voila! You can now filter and map data to exactly what you need.