Working with hierarchical tables

Introduction to Databases in Python

Jason Myers

Co-Author of Essential SQLAlchemy and Software Engineer

Hierarchical tables

Contain a relationship with themselves
Commonly found in:
- Organizational
- Geographic
- Network
- Graph

Hierarchical tables - example

Hierarchical tables - alias()

Requires a way to view the table via multiple names
Creates a unique reference that we can use

Querying hierarchical data

managers = employees.alias()

stmt = select(
        [managers.columns.name.label('manager'),
         employees.columns.name.label('employee')])

stmt = stmt.select_from(employees.join(
        managers, managers.columns.id ==     
        employees.columns.manager)

stmt = stmt.order_by(managers.columns.name)

print(connection.execute(stmt).fetchall())

[(u'FILLMORE', u'GRANT'),
 (u'FILLMORE', u'ADAMS'),
 (u'HARDING', u'TAFT'), ...

group_by and func

It's important to target group_by() at the right alias
Be careful with what you perform functions on
If you don't find yourself using both the alias and the table name for a query, don't create the alias at all

Querying hierarchical data

managers = employees.alias()

stmt = select([managers.columns.name,
        func.sum(employees.columns.sal)])

stmt = stmt.select_from(employees.join(
        managers, managers.columns.id ==     
        employees.columns.manager)

stmt = stmt.group_by(managers.columns.name)
print(connection.execute(stmt).fetchall())

[(u'FILLMORE', Decimal('96000.00')),
 (u'GARFIELD', Decimal('83500.00')),
 (u'HARDING', Decimal('52000.00')),
 (u'JACKSON', Decimal('197000.00'))]

Let's practice!

Introduction to Databases in Python