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

    【Schema】
    【DB_ID】 public_review_platform
【Schema】
# Table: Days
[
(day_id:INTEGER, Primary Key, Examples: [1, 2, 3]),
(day_of_week:TEXT, Examples: [Sunday, Monday, Tuesday])
]
# Table: Users
[
(user_id:INTEGER, Primary Key, Examples: [1, 2, 3]),
(user_yelping_since_year:INTEGER, Examples: [2012, 2010, 2009]),
(user_average_stars:TEXT, Examples: [4.0, 2.5, 4.5]),
(user_votes_funny:TEXT, Examples: [Low, None, Uber]),
(user_votes_useful:TEXT, Examples: [Low, Medium, Uber]),
(user_votes_cool:TEXT, Examples: [Low, Uber, None]),
(user_review_count:TEXT, Examples: [Medium, High, Low]),
(user_fans:TEXT, Examples: [Low, None, Medium])
]
# Table: Elite
[
(user_id:INTEGER, Primary Key, Examples: [3, 19, 33]),
(year_id:INTEGER, Primary Key, Examples: [2010, 2011, 2012])
]
# Table: Business_Attributes
[
(attribute_id:INTEGER, Primary Key, Examples: [1, 2, 3]),
(business_id:INTEGER, Primary Key, Examples: [2, 3, 13]),
(attribute_value:TEXT, Examples: [none, full_bar, beer_and_wine])
]
# Table: Compliments
[
(compliment_id:INTEGER, Primary Key, Examples: [1, 2, 3]),
(compliment_type:TEXT, Examples: [photos, cool, hot])
]
# Table: Business
[
(business_id:INTEGER, Primary Key, Examples: [1, 2, 3]),
(active:TEXT, Examples: [true, false]),
(city:TEXT, Examples: [Phoenix, Scottsdale, Glendale]),
(state:TEXT, Examples: [AZ, SC, CA]),
(stars:REAL, Examples: [3.0, 4.5, 4.0]),
(review_count:TEXT, Examples: [Low, Medium, High])
]
# Table: Business_Categories
[
(business_id:INTEGER, Primary Key, Examples: [1, 2, 3]),
(category_id:INTEGER, Primary Key, Examples: [8, 143, 18])
]
# Table: Reviews
[
(business_id:INTEGER, Primary Key, Examples: [1, 2, 3]),
(user_id:INTEGER, Primary Key, Examples: [36129, 40299, 59125]),
(review_stars:INTEGER, Examples: [2, 1, 5]),
(review_votes_funny:TEXT, Examples: [None, Low, Medium]),
(review_votes_useful:TEXT, Examples: [None, Low, Medium]),
(review_votes_cool:TEXT, Examples: [None, Low, Medium]),
(review_length:TEXT, Examples: [Medium, Short, Long])
]
# Table: Business_Hours
[
(business_id:INTEGER, Primary Key, Examples: [2, 3, 4]),
(day_id:INTEGER, Primary Key, Examples: [2, 3, 4]),
(opening_time:TEXT, Examples: [11AM, 12PM, 10AM]),
(closing_time:TEXT, Examples: [8PM, 9PM, 6PM])
]
# Table: Years
[
(year_id:INTEGER, Primary Key, Examples: [2005, 2006, 2007]),
(actual_year:INTEGER, Examples: [2005, 2006, 2007])
]
# Table: Attributes
[
(attribute_id:INTEGER, Primary Key, Examples: [1, 2, 3]),
(attribute_name:TEXT, Examples: [Alcohol, Waiter Service, Delivery])
]
# Table: Users_Compliments
[
(compliment_id:INTEGER, Primary Key, Examples: [1, 2, 3]),
(user_id:INTEGER, Primary Key, Examples: [3, 19, 45]),
(number_of_compliments:TEXT, Examples: [Medium, Low, High])
]
# Table: Checkins
[
(business_id:INTEGER, Primary Key, Examples: [1, 2, 3]),
(day_id:INTEGER, Primary Key, Examples: [1, 2, 3]),
(label_time_0:TEXT, Examples: [None, Low, Medium]),
(label_time_1:TEXT, Examples: [None, Low, Medium]),
(label_time_2:TEXT, Examples: [None, Low, Medium]),
(label_time_3:TEXT, Examples: [None, Low, Medium]),
(label_time_4:TEXT, Examples: [None, Low, Medium]),
(label_time_5:TEXT, Examples: [None, Low, Medium]),
(label_time_6:TEXT, Examples: [None, Low, Medium]),
(label_time_7:TEXT, Examples: [None, Low, Medium]),
(label_time_8:TEXT, Examples: [None, Low, Medium]),
(label_time_9:TEXT, Examples: [Low, None, Medium]),
(label_time_10:TEXT, Examples: [None, Low, Medium]),
(label_time_11:TEXT, Examples: [Low, None, Medium]),
(label_time_12:TEXT, Examples: [None, Low, Medium]),
(label_time_13:TEXT, Examples: [None, Low, Medium]),
(label_time_14:TEXT, Examples: [None, Low, Medium]),
(label_time_15:TEXT, Examples: [None, Low, Medium]),
(label_time_16:TEXT, Examples: [None, Low, Medium]),
(label_time_17:TEXT, Examples: [Low, None, Medium]),
(label_time_18:TEXT, Examples: [None, Low, Medium]),
(label_time_19:TEXT, Examples: [None, Low, Medium]),
(label_time_20:TEXT, Examples: [None, Low, Medium]),
(label_time_21:TEXT, Examples: [None, Low, Medium]),
(label_time_22:TEXT, Examples: [None, Low, Medium]),
(label_time_23:TEXT, Examples: [None, Low, Medium])
]
# Table: Tips
[
(business_id:INTEGER, Primary Key, Examples: [2, 3, 6]),
(user_id:INTEGER, Primary Key, Examples: [12490, 16328, 19191]),
(likes:INTEGER, Examples: [0, 1, 2]),
(tip_length:TEXT, Examples: [Medium, Short, Long])
]
# Table: Categories
[
(category_id:INTEGER, Primary Key, Examples: [1, 2, 3]),
(category_name:TEXT, Examples: [Active Life, Arts & Entertainment, Stadiums & Arenas])
]
【Foreign keys】
Elite.year_id=Years.year_id
Elite.user_id=Users.user_id
Business_Attributes.business_id=Business.business_id
Business_Attributes.attribute_id=Attributes.attribute_id
Business_Categories.category_id=Categories.category_id
Business_Categories.business_id=Business.business_id
Reviews.user_id=Users.user_id
Reviews.business_id=Business.business_id
Business_Hours.day_id=Days.day_id
Business_Hours.business_id=Business.business_id
Users_Compliments.user_id=Users.user_id
Users_Compliments.compliment_id=Compliments.compliment_id
Checkins.day_id=Days.day_id
Checkins.business_id=Business.business_id
Tips.user_id=Users.user_id
Tips.business_id=Business.business_id

    【Question】
    Among the elite users of 10 consecutive year from 2005 to 2014, list down the user ID and their number of compliment on photos. from 2005 to 2014 refers to year_id BETWEEN 2005 AND 2014; compliment_type = 'photos';

    【Evidence】
    from 2005 to 2014 refers to year_id BETWEEN 2005 AND 2014; compliment_type = 'photos';

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

SQL: SELECT T2.user_id, T2.number_of_compliments FROM Compliments AS T1 INNER JOIN Users_Compliments AS T2 ON T1.compliment_id = T2.compliment_id INNER JOIN Elite AS T3 ON T2.user_id = T3.user_id WHERE T3.year_id BETWEEN 2005 AND 2014 AND T1.compliment_type = 'photos'