用户打车记录表tb_get_car_record id uid city event_time end_time order_id 1 101 北京 2021-10-01 07:00:00 2021-10-01 07:02:00 NULL 2 102 北京 2021-10-01 09:00:30 2021-10-01 09:01:00 9001 3 101 北京 2021-10-01 08:28:10 2021-10-01 08:30:00 9002 4 103 北京 2021-10-02 07:59:00 2021-10-02 08:01:00 9003 5 104 北京 2021-10-03 07:59:20 2021-10-03 08:01:00 9004 6 105 北京 2021-10-01 08:00:00 2021-10-01 08:02:10 9005 7 106 北京 2021-10-01 17:58:00 2021-10-01 18:01:00 9006 8 107 北京 2021-10-02 11:00:00 2021-10-02 11:01:00 9007 9 108 北京 2021-10-02 21:00:00 2021-10-02 21:01:00 9008 10 109 北京 2021-10-08 18:00:00 2021-10-08 18:01:00 9009 (uid-用户ID, city-城市, event_time-打车时间, end_time-打车结束时间, order_id-订单号) 打车订单表tb_get_car_order id order_id uid driver_id order_time start_time finish_time mileage fare grade 1 9002 101 202 2021-10-01 08:30:00 NULL 2021-10-01 08:31:00 NULL NULL NULL 2 9001 102 202 2021-10-01 09:01:00 2021-10-01 09:06:00 2021-10-01 09:31:00 10 41.5 5 3 9003 103 202 2021-10-02 08:01:00 2021-10-02 08:15:00 2021-10-02 08:31:00 11 41.5 4 4 9004 104 202 2021-10-03 08:01:00 2021-10-03 08:13:00 2021-10-03 08:31:00 7.5 22 4 5 9005 105 203 2021-10-01 08:02:10 NULL 2021-10-01 08:31:00 NULL NULL NULL 6 9006 106 203 2021-10-01 18:01:00 2021-10-01 18:09:00 2021-10-01 18:31:00 8 25.5 5 7 9007 107 203 2021-10-02 11:01:00 2021-10-02 11:07:00 2021-10-02 11:31:00 9.9 30 5 8 9008 108 203 2021-10-02 21:01:00 2021-10-02 21:10:00 2021-10-02 21:31:00 13.2 38 4 9 9009 109 203 2021-10-08 18:01:00 2021-10-08 18:11:50 2021-10-08 18:51:00 13 40 5 (order_id-订单号, uid-用户ID, driver_id-司机ID, order_time-接单时间, start_time-开始计费的上车时间, finish_time-订单完成时间, mileage-行驶里程数, fare-费用, grade-评分) 场景逻辑说明: 用户提交打车请求后,在用户打车记录表生成一条打车记录,order_id-订单号设为null; 当有司机接单时,在打车订单表生成一条订单,填充order_time-接单时间及其左边的字段,start_time-开始计费的上车时间及其右边的字段全部为null,并把order_id-订单号和order_time-接单时间(end_time-打车结束时间)写入打车记录表;若一直无司机接单,超时或中途用户主动取消打车,则记录end_time-打车结束时间。 若乘客上车前,乘客或司机点击取消订单,会将打车订单表对应订单的finish_time-订单完成时间填充为取消时间,其余字段设为null。 当司机接上乘客时,填充订单表中该start_time-开始计费的上车时间。 当订单完成时填充订单完成时间、里程数、费用;评分设为null,在用户给司机打1~5星评价后填充。 问题:请统计每个城市中评分最高的司机平均评分、日均接单量和日均行驶里程数。 注:有多个司机评分并列最高时,都输出。 平均评分和日均接单量保留1位小数, 日均行驶里程数保留3位小数,按日均接单数升序排序。 2285068 示例数据的输出结果如下 city driver_id avg_grade avg_order_num avg_mileage 北京 203 4.8 1.7 14.700 解释: 示例数据中,在北京市,共有2个司机接单,202的平均评分为4.3,203的平均评分为4.8,因此北京的最高评分的司机为203;203的共在3天里接单过,一共接单5次(包含1次接单后未完成),因此日均接单数为1.7;总行驶里程数为44.1,因此日均行驶里程数为14.700
示例1

输入

DROP TABLE IF EXISTS tb_get_car_record,tb_get_car_order;
CREATE TABLE tb_get_car_record (
    id INT PRIMARY KEY AUTO_INCREMENT COMMENT '自增ID',
    uid INT NOT NULL COMMENT '用户ID',
    city VARCHAR(10) NOT NULL COMMENT '城市',
    event_time datetime COMMENT '打车时间',
    end_time datetime COMMENT '打车结束时间',
    order_id INT COMMENT '订单号'
) CHARACTER SET utf8 COLLATE utf8_bin;

CREATE TABLE tb_get_car_order (
    id INT PRIMARY KEY AUTO_INCREMENT COMMENT '自增ID',
    order_id INT NOT NULL COMMENT '订单号',
    uid INT NOT NULL COMMENT '用户ID',
    driver_id INT NOT NULL COMMENT '司机ID',
    order_time datetime COMMENT '接单时间',
    start_time datetime COMMENT '开始计费的上车时间',
    finish_time datetime COMMENT '订单结束时间',
    mileage FLOAT COMMENT '行驶里程数',
    fare FLOAT COMMENT '费用',
    grade TINYINT COMMENT '评分'
) CHARACTER SET utf8 COLLATE utf8_bin;

INSERT INTO tb_get_car_record(uid, city, event_time, end_time, order_id) VALUES
 (101, '北京', '2021-10-01 07:00:00', '2021-10-01 07:02:00', null),
 (102, '北京', '2021-10-01 09:00:30', '2021-10-01 09:01:00', 9001),
 (101, '北京', '2021-10-01 08:28:10', '2021-10-01 08:30:00', 9002),
 (103, '北京', '2021-10-02 07:59:00', '2021-10-02 08:01:00', 9003),
 (104, '北京', '2021-10-03 07:59:20', '2021-10-03 08:01:00', 9004),
 (105, '北京', '2021-10-01 08:00:00', '2021-10-01 08:02:10', 9005),
 (106, '北京', '2021-10-01 17:58:00', '2021-10-01 18:01:00', 9006),
 (107, '北京', '2021-10-02 11:00:00', '2021-10-02 11:01:00', 9007),
 (108, '北京', '2021-10-02 21:00:00', '2021-10-02 21:01:00', 9008),
 (109, '北京', '2021-10-08 18:00:00', '2021-10-08 18:01:00', 9009);

INSERT INTO tb_get_car_order(order_id, uid, driver_id, order_time, start_time, finish_time, mileage, fare, grade) VALUES
 (9002, 101, 202, '2021-10-01 08:30:00', null, '2021-10-01 08:31:00', null, null, null),
 (9001, 102, 202, '2021-10-01 09:01:00', '2021-10-01 09:06:00', '2021-10-01 09:31:00', 10.0, 41.5, 5),
 (9003, 103, 202, '2021-10-02 08:01:00', '2021-10-02 08:15:00', '2021-10-02 08:31:00', 11.0, 41.5, 4),
 (9004, 104, 202, '2021-10-03 08:01:00', '2021-10-03 08:13:00', '2021-10-03 08:31:00', 7.5, 22, 4),
 (9005, 105, 203, '2021-10-01 08:02:10', null, '2021-10-01 08:31:00', null, null, null),
 (9006, 106, 203, '2021-10-01 18:01:00', '2021-10-01 18:09:00', '2021-10-01 18:31:00', 8.0, 25.5, 5),
 (9007, 107, 203, '2021-10-02 11:01:00', '2021-10-02 11:07:00', '2021-10-02 11:31:00', 9.9, 30, 5),
 (9008, 108, 203, '2021-10-02 21:01:00', '2021-10-02 21:10:00', '2021-10-02 21:31:00', 13.2, 38, 4),
 (9009, 109, 203, '2021-10-08 18:01:00', '2021-10-08 18:11:50', '2021-10-08 18:51:00', 13, 40, 5);

输出

北京|203|4.8|1.7|14.700
加载中...