How to use row to JSON in PostgreSQL?
This means you can compose json operations to construct rows, you don’t always have to create hugely complex PostgreSQL composite types then call row_to_json on the output. My suggestion for maintainability over the long term is to use a VIEW to build the coarse version of your query, and then use a function as below:
How does column without precision work in PostgreSQL?
without any precision or scale creates a column in which numeric values of any precision and scale can be stored, up to the implementation limit on precision. A column of this kind will not coerce input values to any particular scale, whereas numeric columns with a declared scale will coerce input values to that scale.
How to declare column of type Numeric in PostgreSQL?
To declare a column of type numeric use the syntax: The precision must be positive, the scale zero or positive. Alternatively: selects a scale of 0. Specifying: without any precision or scale creates a column in which numeric values of any precision and scale can be stored, up to the implementation limit on precision.
How are primitive types mapped to PostgreSQL types?
When converting textual JSON input into jsonb, the primitive types described by RFC 7159 are effectively mapped onto native PostgreSQL types, as shown in Table 8-23.
How to represent joined rows as nested objects?
I’m having trouble figuring out the best way to represent joined rows as nested objects (1:1 relations) Here’s what I’ve tried (setup code: tables, sample data, followed by query):
Why is the type casting necessary in PostgreSQL?
Here are the two queries I ran: db=> select person->’dogs’->>0->’breed’ from people where id = 77; ERROR: operator does not exist: text -> unknown LINE 1: select person->’dogs’->>0->’bree… ^ HINT: No operator matches the given name and argument type (s). You might need to add explicit type casts. Why is the type casting necessary?
Can you use column aliases in PostgreSQL?
… but PostgreSQL’s ROW constructor doesn’t accept AS column aliases. Sadly. Thankfully, they optimize out the same. Compare the plans: Because CTEs are optimisation fences, rephrasing the nested subquery version to use chained CTEs ( WITH expressions) may not perform as well, and won’t result in the same plan.