The FLATTEN_PATHS
feature enables you to flatten the results of a query based on the provided paths. This feature can transform nested arrays within your data into separate rows in the output, providing a simple and efficient way to handle hierarchical data structures.
Syntax
The basic syntax to use FLATTEN_PATHS
in a transformation job is as follows:
Copy CREATE sync JOB job_name
FLATTEN_PATHS = (path1, path2, ...)
AS INSERT INTO target_table
SELECT *
FROM source_table;
The FLATTEN_PATHS
feature is currently only supported when writing to Upsolver tables.
Example: Flattening a Single Path
The following example demonstrates how to flatten the items
array.
SQL Code
Copy CREATE sync JOB flatten_single_path_example
FLATTEN_PATHS = (items)
AS INSERT INTO orders_database.flattened_orders
SELECT *
FROM orders_database.raw_orders;
Input Row
Copy {
"name" : "Order1" ,
"items" : [
{ "product" : "apple" , "quantity" : 3 , "categories" : [ "fruit" , "fresh" ]} ,
{ "product" : "sugar" , "quantity" : 2 , "categories" : [ "pantry" ]}
]
}
Output Rows
Copy {
"name" : "Order1" ,
"product" : "apple" ,
"quantity" : 3 ,
"categories" : [ "fruit" , "fresh" ]
}
Copy {
"name" : "Order1" ,
"product" : "sugar" ,
"quantity" : 2 ,
"categories" : [ "pantry" ]
}
Example: Flattening a Nested Array
SQL Code
Copy CREATE sync JOB flatten_nested_path_example
FLATTEN_PATHS = (items[].categories)
AS INSERT INTO orders_database.flattened_categories
SELECT *
FROM orders_database.raw_orders;
Input Row
Copy {
"name" : "Order1" ,
"items" : [
{ "product" : "apple" , "quantity" : 3 , "categories" : [ "fruit" , "fresh" ]} ,
{ "product" : "sugar" , "quantity" : 2 , "categories" : [ "pantry" ]}
]
}
Output Rows
Copy {
"name" : "Order1" ,
"product" : "apple" ,
"quantity" : 3 ,
"categories" : "fruit"
}
Copy {
"name" : "Order1" ,
"product" : "apple" ,
"quantity" : 3 ,
"categories" : "fresh"
}
Copy {
"name" : "Order1" ,
"product" : "sugar" ,
"quantity" : 2 ,
"categories" : "pantry"
}
Example: Flattening Multiple Paths Creating a Cartesian Product
In this example, we flatten both categories
and pricing
, resulting in a Cartesian product since two independent arrays are used in the flattening.
SQL Code
Copy CREATE sync JOB flatten_multiple_paths_example
FLATTEN_PATHS = (categories, pricing)
AS INSERT INTO products_database.flattened_products
SELECT *
FROM products_database.raw_products;
Input Row
Copy {
"name" : "Apple" ,
"categories" : [ "fruit" , "fresh" ] ,
"pricing" : [ { "members" : 2.99 } , { "general" : 3.99 }]
}
Output Rows
Here, flattening both categories
and pricing
creates a Cartesian product of the two arrays, leading to combinations of each category with each pricing option.
Copy {
"name" : "Apple" ,
"categories" : "fruit" ,
"pricing" : { "members" : 2.99 }
}
Copy {
"name" : "Apple" ,
"categories" : "fruit" ,
"pricing" : { "general" : 3.99 }
}
Copy {
"name" : "Apple" ,
"categories" : "fresh" ,
"pricing" : { "members" : 2.99 }
}
Copy {
"name" : "Apple" ,
"categories" : "fresh" ,
"pricing" : { "general" : 3.99 }
}
The FLATTEN_PATHS
feature provides an intuitive way to handle complex data structures, making it easier to work with nested arrays in your data processing tasks.
Last updated 3 months ago