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

    【Schema】
    【DB_ID】 shipping
【Schema】
# Table: driver
[
(driver_id:INTEGER, Primary Key, Examples: [20, 21, 22]),
(first_name:TEXT, Examples: [Sue, Andrea, Roger]),
(last_name:TEXT, Examples: [Newell, Simons, McHaney]),
(address:TEXT, Examples: [268 Richmond Ave, 3574 Oak Limb Cv, 1839 S Orleans St]),
(city:TEXT, Examples: [Memphis]),
(state:TEXT, Examples: [TN]),
(zip_code:INTEGER, Examples: [38106, 38135, 38118]),
(phone:TEXT, Examples: [(901) 774-6569, (901) 384-0984, (901) 948-1043])
]
# Table: customer
[
(cust_id:INTEGER, Primary Key, Examples: [193, 304, 314]),
(cust_name:TEXT, Examples: [Advanced Fabricators]),
(annual_revenue:INTEGER, Examples: [39588651, 17158109, 47403613]),
(cust_type:TEXT, Examples: [manufacturer, wholesaler, retailer]),
(address:TEXT, Examples: [5141 Summit Boulevard]),
(city:TEXT, Examples: [West Palm Beach, Salt Lake City, Council Bluffs]),
(state:TEXT, Examples: [FL, UT, IA]),
(zip:REAL, Examples: [33415.0, 84107.0, 51503.0]),
(phone:TEXT, Examples: [(561) 683-3535, (801) 262-4864, (712) 366-4929])
]
# Table: truck
[
(truck_id:INTEGER, Primary Key, Examples: [1, 2, 3]),
(make:TEXT, Examples: [Peterbilt, Mack, Kenworth]),
(model_year:INTEGER, Examples: [2005, 2006, 2007])
]
# Table: shipment
[
(ship_id:INTEGER, Primary Key, Examples: [1000, 1001, 1002]),
(cust_id:INTEGER, Examples: [3660, 2001, 1669]),
(weight:REAL, Examples: [3528.0, 11394.0, 8712.0]),
(truck_id:INTEGER, Examples: [1, 2, 3]),
(driver_id:INTEGER, Examples: [23, 27, 21]),
(city_id:INTEGER, Examples: [137, 186, 268]),
(ship_date:TEXT, Examples: [2016-01-08, 2016-01-18, 2016-01-19])
]
# Table: city
[
(city_id:INTEGER, Primary Key, Examples: [100, 101, 102]),
(city_name:TEXT, Examples: [Union City, Huntington Park, Passaic]),
(state:TEXT, Examples: [New Jersey, California, New York]),
(population:INTEGER, Examples: [67088, 61348, 67861]),
(area:REAL, Examples: [1.3, 3.0, 3.1])
]
【Foreign keys】
shipment.cust_id=customer.cust_id
shipment.city_id=city.city_id
shipment.driver_id=driver.driver_id
shipment.truck_id=truck.truck_id

    【Question】
    Among all shipments placed by Sunguard Window Tinting & Truck Accessories in 2017, identify the percentage of shipments whose weight exceeded 10,000 pounds. "Sunguard Window Tinting & Truck Accessories" is the cust_name; weight exceed 10,000 pounds refers to weight > = 10000; in 2017 refers to Cast(ship_date AS DATE) = 2017; percentage = Divide (Sum(weight > = 10000), Sum(weight)) * 100

    【Evidence】
    "Sunguard Window Tinting & Truck Accessories" is the cust_name; weight exceed 10,000 pounds refers to weight > = 10000; in 2017 refers to Cast(ship_date AS DATE) = 2017; percentage = Divide (Sum(weight > = 10000), Sum(weight)) * 100

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

SQL: SELECT CAST(SUM(CASE WHEN T1.weight >= 10000 THEN 1 ELSE 0 END) AS REAL) * 100 / COUNT(*) FROM shipment AS T1 INNER JOIN customer AS T2 ON T1.cust_id = T2.cust_id WHERE T2.cust_name = 'Sunguard Window Tinting & Truck Accessories' AND STRFTIME('%Y', T1.ship_date) = '2017'