Table: customer_transactions
\n+------------------+---------+\n| Column Name | Type | \n+------------------+---------+\n| transaction_id | int |\n| customer_id | int |\n| transaction_date | date |\n| amount | decimal |\n| transaction_type | varchar |\n+------------------+---------+\ntransaction_id is the unique identifier for this table.\ntransaction_type can be either 'purchase' or 'refund'.\n\n\n
Write a solution to find loyal customers. A customer is considered loyal if they meet ALL the following criteria:
\n\n3 purchase transactions.30 days.20% .Return the result table ordered by customer_id in ascending order.
The result format is in the following example.
\n\n\n
Example:
\n\nInput:
\n\ncustomer_transactions table:
\n\n\n+----------------+-------------+------------------+--------+------------------+\n| transaction_id | customer_id | transaction_date | amount | transaction_type |\n+----------------+-------------+------------------+--------+------------------+\n| 1 | 101 | 2024-01-05 | 150.00 | purchase |\n| 2 | 101 | 2024-01-15 | 200.00 | purchase |\n| 3 | 101 | 2024-02-10 | 180.00 | purchase |\n| 4 | 101 | 2024-02-20 | 250.00 | purchase |\n| 5 | 102 | 2024-01-10 | 100.00 | purchase |\n| 6 | 102 | 2024-01-12 | 120.00 | purchase |\n| 7 | 102 | 2024-01-15 | 80.00 | refund |\n| 8 | 102 | 2024-01-18 | 90.00 | refund |\n| 9 | 102 | 2024-02-15 | 130.00 | purchase |\n| 10 | 103 | 2024-01-01 | 500.00 | purchase |\n| 11 | 103 | 2024-01-02 | 450.00 | purchase |\n| 12 | 103 | 2024-01-03 | 400.00 | purchase |\n| 13 | 104 | 2024-01-01 | 200.00 | purchase |\n| 14 | 104 | 2024-02-01 | 250.00 | purchase |\n| 15 | 104 | 2024-02-15 | 300.00 | purchase |\n| 16 | 104 | 2024-03-01 | 350.00 | purchase |\n| 17 | 104 | 2024-03-10 | 280.00 | purchase |\n| 18 | 104 | 2024-03-15 | 100.00 | refund |\n+----------------+-------------+------------------+--------+------------------+\n\n\n
Output:
\n\n\n+-------------+\n| customer_id |\n+-------------+\n| 101 |\n| 104 |\n+-------------+\n\n\n
Explanation:
\n\nThe result table is ordered by customer_id in ascending order.
\n表：customer_transactions
\n+------------------+---------+\n| Column Name | Type | \n+------------------+---------+\n| transaction_id | int |\n| customer_id | int |\n| transaction_date | date |\n| amount | decimal |\n| transaction_type | varchar |\n+------------------+---------+\ntransaction_id 是这张表的唯一主键。\ntransaction_type 可以是 “purchase” 或 “refund”。\n\n\n
编写一个解决方案来查找 忠实客户。如果满足下述所有条件，可以认为该客户是 忠实 客户：
\n\n3 次购买交易。30 天。20%。返回结果表以 customer_id 升序 排序。
结果格式如下所示。
\n\n\n\n
示例：
\n\n输入：
\n\ncustomer_transactions 表：
\n\n\n+----------------+-------------+------------------+--------+------------------+\n| transaction_id | customer_id | transaction_date | amount | transaction_type |\n+----------------+-------------+------------------+--------+------------------+\n| 1 | 101 | 2024-01-05 | 150.00 | purchase |\n| 2 | 101 | 2024-01-15 | 200.00 | purchase |\n| 3 | 101 | 2024-02-10 | 180.00 | purchase |\n| 4 | 101 | 2024-02-20 | 250.00 | purchase |\n| 5 | 102 | 2024-01-10 | 100.00 | purchase |\n| 6 | 102 | 2024-01-12 | 120.00 | purchase |\n| 7 | 102 | 2024-01-15 | 80.00 | refund |\n| 8 | 102 | 2024-01-18 | 90.00 | refund |\n| 9 | 102 | 2024-02-15 | 130.00 | purchase |\n| 10 | 103 | 2024-01-01 | 500.00 | purchase |\n| 11 | 103 | 2024-01-02 | 450.00 | purchase |\n| 12 | 103 | 2024-01-03 | 400.00 | purchase |\n| 13 | 104 | 2024-01-01 | 200.00 | purchase |\n| 14 | 104 | 2024-02-01 | 250.00 | purchase |\n| 15 | 104 | 2024-02-15 | 300.00 | purchase |\n| 16 | 104 | 2024-03-01 | 350.00 | purchase |\n| 17 | 104 | 2024-03-10 | 280.00 | purchase |\n| 18 | 104 | 2024-03-15 | 100.00 | refund |\n+----------------+-------------+------------------+--------+------------------+\n\n\n
输出：
\n\n\n+-------------+\n| customer_id |\n+-------------+\n| 101 |\n| 104 |\n+-------------+\n\n\n
解释：
\n\n结果表以 customer_id 升序排序。
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"exampleTestcases": "{\"headers\":{\"customer_transactions\":[\"transaction_id\",\"customer_id\",\"transaction_date\",\"amount\",\"transaction_type\"]},\"rows\":{\"customer_transactions\":[[1,101,\"2024-01-05\",150.00,\"purchase\"],[2,101,\"2024-01-15\",200.00,\"purchase\"],[3,101,\"2024-02-10\",180.00,\"purchase\"],[4,101,\"2024-02-20\",250.00,\"purchase\"],[5,102,\"2024-01-10\",100.00,\"purchase\"],[6,102,\"2024-01-12\",120.00,\"purchase\"],[7,102,\"2024-01-15\",80.00,\"refund\"],[8,102,\"2024-01-18\",90.00,\"refund\"],[9,102,\"2024-02-15\",130.00,\"purchase\"],[10,103,\"2024-01-01\",500.00,\"purchase\"],[11,103,\"2024-01-02\",450.00,\"purchase\"],[12,103,\"2024-01-03\",400.00,\"purchase\"],[13,104,\"2024-01-01\",200.00,\"purchase\"],[14,104,\"2024-02-01\",250.00,\"purchase\"],[15,104,\"2024-02-15\",300.00,\"purchase\"],[16,104,\"2024-03-01\",350.00,\"purchase\"],[17,104,\"2024-03-10\",280.00,\"purchase\"],[18,104,\"2024-03-15\",100.00,\"refund\"]]}}",
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