Table: Product
\n+--------------+---------+\n| Column Name | Type |\n+--------------+---------+\n| product_id | int |\n| product_name | varchar |\n| unit_price | int |\n+--------------+---------+\nproduct_id is the primary key of this table.\nEach row of this table indicates the name and the price of each product.\n\n\n
Table: Sales
\n+-------------+---------+\n| Column Name | Type |\n+-------------+---------+\n| seller_id | int |\n| product_id | int |\n| buyer_id | int |\n| sale_date | date |\n| quantity | int |\n| price | int |\n+-------------+---------+\nThis table has no primary key, it can have repeated rows.\nproduct_id is a foreign key to the Product table.\nEach row of this table contains some information about one sale.\n\n\n
\n\n
Write an SQL query that reports the products that were only sold in the spring of 2019. That is, between 2019-01-01 and 2019-03-31 inclusive.
Return the result table in any order.
\n\nThe query result format is in the following example.
\n\n\n
Example 1:
\n\n\nInput: \nProduct table:\n+------------+--------------+------------+\n| product_id | product_name | unit_price |\n+------------+--------------+------------+\n| 1 | S8 | 1000 |\n| 2 | G4 | 800 |\n| 3 | iPhone | 1400 |\n+------------+--------------+------------+\nSales table:\n+-----------+------------+----------+------------+----------+-------+\n| seller_id | product_id | buyer_id | sale_date | quantity | price |\n+-----------+------------+----------+------------+----------+-------+\n| 1 | 1 | 1 | 2019-01-21 | 2 | 2000 |\n| 1 | 2 | 2 | 2019-02-17 | 1 | 800 |\n| 2 | 2 | 3 | 2019-06-02 | 1 | 800 |\n| 3 | 3 | 4 | 2019-05-13 | 2 | 2800 |\n+-----------+------------+----------+------------+----------+-------+\nOutput: \n+-------------+--------------+\n| product_id | product_name |\n+-------------+--------------+\n| 1 | S8 |\n+-------------+--------------+\nExplanation: \nThe product with id 1 was only sold in the spring of 2019.\nThe product with id 2 was sold in the spring of 2019 but was also sold after the spring of 2019.\nThe product with id 3 was sold after spring 2019.\nWe return only product 1 as it is the product that was only sold in the spring of 2019.\n\n", "translatedTitle": null, "translatedContent": null, "isPaidOnly": false, "difficulty": "Easy", "likes": 158, "dislikes": 54, "isLiked": null, "similarQuestions": "[{\"title\": \"Sales Analysis II\", \"titleSlug\": \"sales-analysis-ii\", \"difficulty\": \"Easy\", \"translatedTitle\": null}]", "exampleTestcases": "{\"headers\":{\"Product\":[\"product_id\",\"product_name\",\"unit_price\"],\"Sales\":[\"seller_id\",\"product_id\",\"buyer_id\",\"sale_date\",\"quantity\",\"price\"]},\"rows\":{\"Product\":[[1,\"S8\",1000],[2,\"G4\",800],[3,\"iPhone\",1400]],\"Sales\":[[1,1,1,\"2019-01-21\",2,2000],[1,2,2,\"2019-02-17\",1,800],[2,2,3,\"2019-06-02\",1,800],[3,3,4,\"2019-05-13\",2,2800]]}}", "categoryTitle": "Database", "contributors": [], "topicTags": [ { "name": "Database", "slug": "database", "translatedName": 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MySQL 8.0.
mssql server 2019.
Oracle Sql 11.2.