Table: Users
\n+----------------+---------+\n| Column Name | Type |\n+----------------+---------+\n| user_id | int |\n| join_date | date |\n| favorite_brand | varchar |\n+----------------+---------+\nuser_id is the primary key of this table.\nThis table has the info of the users of an online shopping website where users can sell and buy items.\n\n\n
\n\n
Table: Orders
\n+---------------+---------+\n| Column Name | Type |\n+---------------+---------+\n| order_id | int |\n| order_date | date |\n| item_id | int |\n| buyer_id | int |\n| seller_id | int |\n+---------------+---------+\norder_id is the primary key of this table.\nitem_id is a foreign key to the Items table.\nbuyer_id and seller_id are foreign keys to the Users table.\n\n\n
\n\n
Table: Items
\n+---------------+---------+\n| Column Name | Type |\n+---------------+---------+\n| item_id | int |\n| item_brand | varchar |\n+---------------+---------+\nitem_id is the primary key of this table.\n\n\n
\n\n
Write an SQL query to find for each user, the join date and the number of orders they made as a buyer in 2019.
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: \nUsers table:\n+---------+------------+----------------+\n| user_id | join_date | favorite_brand |\n+---------+------------+----------------+\n| 1 | 2018-01-01 | Lenovo |\n| 2 | 2018-02-09 | Samsung |\n| 3 | 2018-01-19 | LG |\n| 4 | 2018-05-21 | HP |\n+---------+------------+----------------+\nOrders table:\n+----------+------------+---------+----------+-----------+\n| order_id | order_date | item_id | buyer_id | seller_id |\n+----------+------------+---------+----------+-----------+\n| 1 | 2019-08-01 | 4 | 1 | 2 |\n| 2 | 2018-08-02 | 2 | 1 | 3 |\n| 3 | 2019-08-03 | 3 | 2 | 3 |\n| 4 | 2018-08-04 | 1 | 4 | 2 |\n| 5 | 2018-08-04 | 1 | 3 | 4 |\n| 6 | 2019-08-05 | 2 | 2 | 4 |\n+----------+------------+---------+----------+-----------+\nItems table:\n+---------+------------+\n| item_id | item_brand |\n+---------+------------+\n| 1 | Samsung |\n| 2 | Lenovo |\n| 3 | LG |\n| 4 | HP |\n+---------+------------+\nOutput: \n+-----------+------------+----------------+\n| buyer_id | join_date | orders_in_2019 |\n+-----------+------------+----------------+\n| 1 | 2018-01-01 | 1 |\n| 2 | 2018-02-09 | 2 |\n| 3 | 2018-01-19 | 0 |\n| 4 | 2018-05-21 | 0 |\n+-----------+------------+----------------+\n\n", "translatedTitle": "市场分析 I", "translatedContent": "
Table: Users
\n+----------------+---------+\n| Column Name | Type |\n+----------------+---------+\n| user_id | int |\n| join_date | date |\n| favorite_brand | varchar |\n+----------------+---------+\n此表主键是 user_id。\n表中描述了购物网站的用户信息，用户可以在此网站上进行商品买卖。\n\n\n
\n\n
Table: Orders
\n+---------------+---------+\n| Column Name | Type |\n+---------------+---------+\n| order_id | int |\n| order_date | date |\n| item_id | int |\n| buyer_id | int |\n| seller_id | int |\n+---------------+---------+\n此表主键是 order_id。\n外键是 item_id 和（buyer_id，seller_id）。\n\n\n
\n\n
Table: Items
\n+---------------+---------+\n| Column Name | Type |\n+---------------+---------+\n| item_id | int |\n| item_brand | varchar |\n+---------------+---------+\n此表主键是 item_id。\n\n\n
\n\n
请写出一条SQL语句以查询每个用户的注册日期和在 2019 年作为买家的订单总数。
以 任意顺序 返回结果表。
\n\n查询结果格式如下。
\n\n\n\n
示例 1:
\n\n\n输入：\nUsers 表:\n+---------+------------+----------------+\n| user_id | join_date | favorite_brand |\n+---------+------------+----------------+\n| 1 | 2018-01-01 | Lenovo |\n| 2 | 2018-02-09 | Samsung |\n| 3 | 2018-01-19 | LG |\n| 4 | 2018-05-21 | HP |\n+---------+------------+----------------+\nOrders 表:\n+----------+------------+---------+----------+-----------+\n| order_id | order_date | item_id | buyer_id | seller_id |\n+----------+------------+---------+----------+-----------+\n| 1 | 2019-08-01 | 4 | 1 | 2 |\n| 2 | 2018-08-02 | 2 | 1 | 3 |\n| 3 | 2019-08-03 | 3 | 2 | 3 |\n| 4 | 2018-08-04 | 1 | 4 | 2 |\n| 5 | 2018-08-04 | 1 | 3 | 4 |\n| 6 | 2019-08-05 | 2 | 2 | 4 |\n+----------+------------+---------+----------+-----------+\nItems 表:\n+---------+------------+\n| item_id | item_brand |\n+---------+------------+\n| 1 | Samsung |\n| 2 | Lenovo |\n| 3 | LG |\n| 4 | HP |\n+---------+------------+\n输出：\n+-----------+------------+----------------+\n| buyer_id | join_date | orders_in_2019 |\n+-----------+------------+----------------+\n| 1 | 2018-01-01 | 1 |\n| 2 | 2018-02-09 | 2 |\n| 3 | 2018-01-19 | 0 |\n| 4 | 2018-05-21 | 0 |\n+-----------+------------+----------------+\n", "isPaidOnly": false, "difficulty": "Medium", "likes": 36, "dislikes": 0, "isLiked": null, "similarQuestions": "[]", "contributors": [], "langToValidPlayground": "{\"cpp\": false, \"java\": false, \"python\": false, \"python3\": false, \"mysql\": false, \"mssql\": false, \"oraclesql\": false, \"c\": false, \"csharp\": false, \"javascript\": false, \"ruby\": false, \"bash\": false, \"swift\": false, \"golang\": false, \"scala\": false, \"html\": false, \"pythonml\": false, \"kotlin\": false, \"rust\": false, \"php\": false, \"typescript\": false, \"racket\": false, \"erlang\": false, \"elixir\": false}", "topicTags": [ { "name": "Database", "slug": "database", "translatedName": "数据库", "__typename": "TopicTagNode" } ], "companyTagStats": null, "codeSnippets": [ { "lang": "MySQL", 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