![]() _sdc_source_key_ - This contains the top level record’s Primary Key.In addition to the attributes in the nested record - in this case, product ID, price, and quantity for line items - Stitch will add these columns to second level tables: This table contains the order record’s Primary Key, order_id. Let’s take a look at the schemas for each of the Shopify tables to get a better idea of how this works. When subtables are created, Stitch will append a few columns to be used as composite keys that enable you to connect subrecords back to their parent. orders_line_items_tax_lines - This table contains the tax line info: price, rate, and title.Ĭonnecting Subtables to Top Level Records.orders_line_items - This table contains the line item info: product ID, price, and quantity.orders - This table contains the core order data: order ID, created timestamp, and customer ID.From this one order record, three tables will be created: Stitch will denest the arrays from the top level record - in this case, the core order info - and create subtables. This record contains three levels of data due to the nested arrays. Objects begin with a left curly bracket ( ObjectsĪn object is an unordered set of name and value pairs each set is called a property. JSON records can contain structures called objects and arrays. When Stitch pulls data from an integration, it’s pulling a series of JSON records. How to connect subtables to top level records.How nested structures are deconstructed.Stitch is designed to deconstruct these nested structures into separate tables to easily query the data. MongoDB and many SaaS integrations use nested structures, which means each attribute (or column) in a table could have its own set of attributes. To understand how Stitch interprets the data it receives, you need to know a little bit about JSON. These data types will be stored as strings in your data warehouse, whether it’s Postgres, Panoply, or Redshift. ![]() Postgres ARRAY & JSON datatypes: The info in this article is NOT applicable to Postgres ARRAY and JSON data types. Because these rows are not denested, there is no additional impact on row counts when replicating these records. ![]() When Stitch encounters nested data from sources like MongoDB, that data is persisted into BigQuery with its structure intact. BigQuery destinations: This article is not applicable to BigQuery, as it natively supports nested structures. ![]()
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