Create sql selects to:

• get records person + phones + address
• get top 10 most younger person
• get top 10 most old person
• get most younger person per city
• get mean age per city

In the postgreSQL
Create user role with password to connect to the database;
Create data base with owner the created user;

Use the database user create in the new data base tables to store data about:

• persons (Name, SecondName, born date, city born)
• person phone (number, type (mobile, work etc.)) many to one to person
• person address (Address, city, type (home, work, summerhouse)) many to one to person

Create new column in the address table city_type.
Apply the categories of the cities by people lives in : 10 and more percentages of all is megalopolis, less than 5 percentages - village, other way city.

Update the collection in the mongo to synchronize it with new data in the PostgreSQL.

Create select from the mongo:

• Get the biggest megalopolis.
• Get the list of persons living in the smallest village.

Update the age of the persons so, the younger man living in the village should be 20 years old, and the oldest man in the megalopolis should be 60 years. ( change only year)

Synchronize the values with mongo db, only for updated values.

Load data from Mongo to PostgreSQL

MongoDB.
Generate random (possible to use py Faker) list of persons with list of the phones and address.
Push it to the mongoDB (use docker image or other solution), use database name traindb and collection name persons. Each person should have at least one address home.

links:
py Faker
MOngo doc
Docker mongo