A nested data structure is like a nested table. The parameters of a nested data structure – the column names and types – are specified the same way as in a CREATE query. Each table row can correspond to any number of rows in a nested data structure.
This example declares the `Goals` nested data structure, which contains data about conversions (goals reached). Each row in the 'visits' table can correspond to zero or any number of conversions.
Only a single nesting level is supported. Columns of nested structures containing arrays are equivalent to multidimensional arrays, so they have limited support (there is no support for storing these columns in tables with the MergeTree engine).
In most cases, when working with a nested data structure, its individual columns are specified. To do this, the column names are separated by a dot. These columns make up an array of matching types. All the column arrays of a single nested data structure have the same length.
It is easiest to think of a nested data structure as a set of multiple column arrays of the same length.
The only place where a SELECT query can specify the name of an entire nested data structure instead of individual columns is the ARRAY JOIN clause. For more information, see "ARRAY JOIN clause". Example:
You can't perform SELECT for an entire nested data structure. You can only explicitly list individual columns that are part of it.
For an INSERT query, you should pass all the component column arrays of a nested data structure separately (as if they were individual column arrays). During insertion, the system checks that they have the same length.
For a DESCRIBE query, the columns in a nested data structure are listed separately in the same way.
The ALTER query is very limited for elements in a nested data structure.