You are now a sqlite data analyst, and you are given a database schema as follows:

    【Schema】
    【DB_ID】 movie_3
【Schema】
# Table: country
[
(country_id:INTEGER, Primary Key, Examples: [1, 2, 3]),
(country:TEXT, Examples: [Afghanistan, Algeria, American Samoa]),
(last_update:DATETIME, Examples: [2006-02-15 04:44:00])
]
# Table: customer
[
(customer_id:INTEGER, Primary Key, Examples: [1, 2, 3]),
(store_id:INTEGER, Examples: [1, 2]),
(first_name:TEXT, Examples: [MARY, PATRICIA, LINDA]),
(last_name:TEXT, Examples: [SMITH, JOHNSON, WILLIAMS]),
(email:TEXT),
(address_id:INTEGER, Examples: [5, 6, 7]),
(active:INTEGER, Examples: [1, 0]),
(create_date:DATETIME, Examples: [2006-02-14 22:04:36]),
(last_update:DATETIME, Examples: [2006-02-15 04:57:20])
]
# Table: film_text
[
(film_id:INTEGER, Primary Key, Examples: [1, 2, 3]),
(title:TEXT, Examples: [ACADEMY DINOSAUR, ACE GOLDFINGER, ADAPTATION HOLES]),
(description:TEXT)
]
# Table: store
[
(store_id:INTEGER, Primary Key, Examples: [1, 2]),
(manager_staff_id:INTEGER, Examples: [1, 2]),
(address_id:INTEGER, Examples: [1, 2]),
(last_update:DATETIME, Examples: [2006-02-15 04:57:12])
]
# Table: film_category
[
(film_id:INTEGER, Primary Key, Examples: [1, 2, 3]),
(category_id:INTEGER, Primary Key, Examples: [6, 11, 8]),
(last_update:DATETIME, Examples: [2006-02-15 05:07:09])
]
# Table: payment
[
(payment_id:INTEGER, Primary Key, Examples: [1, 2, 3]),
(customer_id:INTEGER, Examples: [1, 2, 3]),
(staff_id:INTEGER, Examples: [1, 2]),
(rental_id:INTEGER, Examples: [76, 573, 1185]),
(amount:REAL, Examples: [2.99, 0.99, 5.99]),
(payment_date:DATETIME, Examples: [2005-05-25 11:30:37]),
(last_update:DATETIME, Examples: [2006-02-15 22:12:30])
]
# Table: actor
[
(actor_id:INTEGER, Primary Key, Examples: [1, 2, 3]),
(first_name:TEXT, Examples: [PENELOPE, NICK, ED]),
(last_name:TEXT, Examples: [GUINESS, WAHLBERG, CHASE]),
(last_update:DATETIME, Examples: [2006-02-15 04:34:33])
]
# Table: rental
[
(rental_id:INTEGER, Primary Key, Examples: [1, 2, 3]),
(rental_date:DATETIME, Examples: [2005-05-24 22:53:30]),
(inventory_id:INTEGER, Examples: [367, 1525, 1711]),
(customer_id:INTEGER, Examples: [130, 459, 408]),
(return_date:DATETIME, Examples: [2005-05-26 22:04:30]),
(staff_id:INTEGER, Examples: [1, 2]),
(last_update:DATETIME, Examples: [2006-02-15 21:30:53])
]
# Table: language
[
(language_id:INTEGER, Primary Key, Examples: [1, 2, 3]),
(name:TEXT, Examples: [English, Italian, Japanese]),
(last_update:DATETIME, Examples: [2006-02-15 05:02:19])
]
# Table: film
[
(film_id:INTEGER, Primary Key, Examples: [1, 2, 3]),
(title:TEXT, Examples: [ACADEMY DINOSAUR, ACE GOLDFINGER, ADAPTATION HOLES]),
(description:TEXT),
(release_year:TEXT, Examples: [2006]),
(language_id:INTEGER, Examples: [1]),
(original_language_id:INTEGER),
(rental_duration:INTEGER, Examples: [6, 3, 7]),
(rental_rate:REAL, Examples: [0.99, 4.99, 2.99]),
(length:INTEGER, Examples: [86, 48, 50]),
(replacement_cost:REAL, Examples: [20.99, 12.99, 18.99]),
(rating:TEXT, Examples: [PG, G, NC-17]),
(special_features:TEXT, Examples: [Deleted Scenes,Behind the Scenes]),
(last_update:DATETIME, Examples: [2006-02-15 05:03:42])
]
# Table: inventory
[
(inventory_id:INTEGER, Primary Key, Examples: [1, 2, 3]),
(film_id:INTEGER, Examples: [1, 2, 3]),
(store_id:INTEGER, Examples: [1, 2]),
(last_update:DATETIME, Examples: [2006-02-15 05:09:17])
]
# Table: address
[
(address_id:INTEGER, Primary Key, Examples: [1, 2, 3]),
(address:TEXT, Examples: [47 MySakila Drive, 28 MySQL Boulevard, 23 Workhaven Lane]),
(address2:TEXT),
(district:TEXT, Examples: [Alberta, QLD, Nagasaki]),
(city_id:INTEGER, Examples: [300, 576, 463]),
(postal_code:TEXT, Examples: [35200, 17886, 83579]),
(phone:TEXT, Examples: [14033335568, 6172235589, 28303384290]),
(last_update:DATETIME, Examples: [2006-02-15 04:45:30])
]
# Table: film_actor
[
(actor_id:INTEGER, Primary Key, Examples: [1, 2, 3]),
(film_id:INTEGER, Primary Key, Examples: [1, 23, 25]),
(last_update:DATETIME, Examples: [2006-02-15 05:05:03])
]
# Table: category
[
(category_id:INTEGER, Primary Key, Examples: [1, 2, 3]),
(name:TEXT, Examples: [Action, Animation, Children]),
(last_update:DATETIME, Examples: [2006-02-15 04:46:27])
]
# Table: city
[
(city_id:INTEGER, Primary Key, Examples: [1, 2, 3]),
(city:TEXT, Examples: [A Corua (La Corua), Abha, Abu Dhabi]),
(country_id:INTEGER, Examples: [87, 82, 101]),
(last_update:DATETIME, Examples: [2006-02-15 04:45:25])
]
# Table: staff
[
(staff_id:INTEGER, Primary Key, Examples: [1, 2]),
(first_name:TEXT, Examples: [Mike, Jon]),
(last_name:TEXT, Examples: [Hillyer, Stephens]),
(address_id:INTEGER, Examples: [3, 4]),
(picture:BLOB),
(email:TEXT),
(store_id:INTEGER, Examples: [1, 2]),
(active:INTEGER, Examples: [1]),
(username:TEXT, Examples: [Mike, Jon]),
(password:TEXT, Examples: [8cb2237d0679ca88db6464eac60da96345513964]),
(last_update:DATETIME, Examples: [2006-02-15 04:57:16])
]
【Foreign keys】
customer.address_id=address.address_id
customer.store_id=store.store_id
store.address_id=address.address_id
store.manager_staff_id=staff.staff_id
film_category.category_id=category.category_id
film_category.film_id=film.film_id
payment.rental_id=rental.rental_id
payment.staff_id=staff.staff_id
payment.customer_id=customer.customer_id
rental.staff_id=staff.staff_id
rental.customer_id=customer.customer_id
rental.inventory_id=inventory.inventory_id
film.original_language_id=language.language_id
film.language_id=language.language_id
inventory.store_id=store.store_id
inventory.film_id=film.film_id
address.city_id=city.city_id
film_actor.film_id=film.film_id
film_actor.actor_id=actor.actor_id
city.country_id=country.country_id
staff.store_id=store.store_id
staff.address_id=address.address_id

    【Question】
    Who are the top 5 actors with the highest number of films? List their full names and calculate the average number of films for each of the actors. actors with highest number of films refers to actor_id with Max(Count(film_id)); full name refers to first_name, last_name; average number of film = Divide (Count(film_id), 5)

    【Evidence】
    actors with highest number of films refers to actor_id with Max(Count(film_id)); full name refers to first_name, last_name; average number of film = Divide (Count(film_id), 5)

    Please read and understand the database schema carefully, and generate an executable SQL based on the user's question and evidence. 

SQL: SELECT T.first_name, T.last_name, num FROM ( SELECT T1.first_name, T1.last_name, COUNT(T2.film_id) AS num FROM actor AS T1 INNER JOIN film_actor AS T2 ON T1.actor_id = T2.actor_id INNER JOIN film AS T3 ON T2.film_id = T3.film_id GROUP BY T1.first_name, T1.last_name ) AS T ORDER BY T.num DESC LIMIT 5