ohlc(开放，高，低和关闭)记录在两个日期范围内不同时间内(1，5，15，60,120)分钟，1天甚至没有记录

Question

我有什么

1.我的领域"User_Order"

CREATE TABLE `user_order` (
  `id` bigint(20) NOT NULL AUTO_INCREMENT,
  `created_date` datetime DEFAULT NULL,
  `fees` decimal(19,2) NOT NULL,
  `instrument` varchar(255) NOT NULL,
  `is_limit_order` bit(1) NOT NULL,
  `market_id` bigint(20) NOT NULL,
  `order_id` varchar(255) NOT NULL,
  `order_status` varchar(255) NOT NULL,
  `order_type` varchar(255) NOT NULL,
  `price` decimal(20,8) NOT NULL,
  `quantity` decimal(20,8) NOT NULL,
  `remaining_quantity` decimal(20,8) NOT NULL,
  `updated_date` datetime DEFAULT NULL,
  `user_id` bigint(20) NOT NULL,
  PRIMARY KEY (`id`),
  UNIQUE KEY `UK_t5ah1x4wm9314qclf90dy0lyu` (`order_id`)
) ENGINE=InnoDB DEFAULT CHARSET=utf8;

2.我们在表中有下面的记录.

| id | created_date        | fees   | instrument | is_limit_order | market_id | order_id         | order_status | order_type | price       | quantity   | remaining_quantity | updated_date        | user_id |
+----+---------------------+--------+------------+----------------+-----------+------------------+--------------+------------+-------------+------------+--------------------+---------------------+---------+
|  1 | 2017-09-15 05:08:57 | 0.0100 | INBTCINR   |               |         1 | 12:05:52-0000001 | EXECUTED     | BUY        | 10.00000000 | 2.00000000 |         0.00000000 | 2017-09-15 05:08:57 |       3 |
|  2 | 2017-09-15 05:09:34 | 0.0100 | INBTCINR   |               |         1 | 12:25:43-0000001 | EXECUTED     | SELL       | 10.00000000 | 2.00000000 |         0.00000000 | 2017-09-15 05:09:34 |       4 |
|  3 | 2017-09-15 05:11:18 | 0.0100 | INBTCINR   |               |         1 | 12:05:52-0000002 | CANCELLED    | BUY        |  2.00000000 | 1.00000000 |         1.00000000 | 2017-09-15 05:11:18 |       3 |
|  4 | 2017-09-15 05:12:43 | 0.0100 | INBTCINR   |               |         1 | 12:05:52-0000003 | EXECUTED     | BUY        |  4.00000000 | 2.00000000 |         0.00000000 | 2017-09-15 05:12:43 |       3 |
|  5 | 2017-09-15 05:23:10 | 0.0100 | INBTCINR   |               |         1 | 12:25:43-0000002 | EXECUTED     | SELL       |  4.00000000 | 2.00000000 |         0.00000000 | 2017-09-15 05:23:10 |       4 |
|  6 | 2017-09-15 08:34:17 | 0.0100 | INBTCINR   |               |         1 | 12:25:43-0000003 | OPEN         | BUY        |  2.00000000 | 1.00000000 |         1.00000000 | 2017-09-15 08:34:17 |       4 |
|  7 | 2017-09-15 08:36:32 | 0.0100 | INBTCINR   |               |         1 | 12:05:52-0000004 | CANCELLED    | SELL       |  1.00000000 | 2.00000000 |         2.00000000 | 2017-09-15 08:36:32 |       3 |
|  8 | 2017-09-15 09:24:22 | 0.0100 | INBTCINR   |               |         1 | 12:25:43-0000004 | OPEN         | BUY        |  2.00000000 | 1.00000000 |         1.00000000 | 2017-09-15 09:24:22 |       4 |
|  9 | 2017-09-15 09:30:19 | 0.0100 | INBTCINR   |               |         1 | 12:25:43-0000005 | OPEN         | BUY        |  1.00000000 | 2.00000000 |         2.00000000 | 2017-09-15 09:30:19 |       4 |
| 10 | 2017-09-15 09:32:10 | 0.0100 | INBTCINR   |               |         1 | 12:05:52-0000005 | CANCELLED    | SELL       |  1.00000000 | 2.00000000 |         2.00000000 | 2017-09-15 09:32:10 |       3 |
| 11 | 2017-09-15 10:02:57 | 0.0100 | INBTCINR   |               |         1 | 12:05:52-0000006 | OPEN         | SELL       |  2.00000000 | 4.00000000 |         4.00000000 | 2017-09-15 10:02:57 |       3 |
| 12 | 2017-09-15 10:16:19 | 0.0100 | INBTCINR   |               |         1 | 12:25:43-0000006 | OPEN         | BUY        |  4.00000000 | 2.00000000 |         2.00000000 | 2017-09-15 10:16:19 |       4 |

3.我在下面为每5分钟(每秒300分钟)的间隔记录编写查询。

开始日期= '2017-09-11 : 00:00:00‘结束日期= '2017-09-15 23:59:59’

select  FROM_UNIXTIME(floor(min(UNIX_TIMESTAMP(created_date))/300)*300)
                 as timestampDate,
        sum(quantity) as volume,sum(price*quantity)/sum(quantity) as wavg_price,
        substring_index(min(concat('created_date','_',price)),
                '_',-1) as open,
        max(price) as high,
        min(price) as low,
        substring_index(max(concat ('created_date','_',price)),
                '_',-1) as 'close'
    from  user_order
    where  created_date between '2017-09-11 00:00:00' AND '2017-09-15 23:59:59'
    group by  floor(unix_timestamp(created_date)/300)
    order by  created_date;

上述查询的结果：-

 timestampDate       | volume     | wavg_price              | open        | high        | low         | close       |
+---------------------+------------+-------------------------+-------------+-------------+-------------+-------------+
| 2017-09-15 05:05:00 | 4.00000000 | 10.00000000000000000000 | 10.00000000 | 10.00000000 | 10.00000000 | 10.00000000 |
| 2017-09-15 05:10:00 | 3.00000000 |  3.33333333333333333333 | 2.00000000  |  4.00000000 |  2.00000000 | 4.00000000  |
| 2017-09-15 05:20:00 | 2.00000000 |  4.00000000000000000000 | 4.00000000  |  4.00000000 |  4.00000000 | 4.00000000  |
| 2017-09-15 08:30:00 | 1.00000000 |  2.00000000000000000000 | 2.00000000  |  2.00000000 |  2.00000000 | 2.00000000  |
| 2017-09-15 08:35:00 | 2.00000000 |  1.00000000000000000000 | 1.00000000  |  1.00000000 |  1.00000000 | 1.00000000  |
| 2017-09-15 09:20:00 | 1.00000000 |  2.00000000000000000000 | 2.00000000  |  2.00000000 |  2.00000000 | 2.00000000  |
| 2017-09-15 09:30:00 | 4.00000000 |  1.00000000000000000000 | 1.00000000  |  1.00000000 |  1.00000000 | 1.00000000  |
| 2017-09-15 10:00:00 | 4.00000000 |  2.00000000000000000000 | 2.00000000  |  2.00000000 |  2.00000000 | 2.00000000  |
| 2017-09-15 10:15:00 | 2.00000000 |  4.00000000000000000000 | 4.00000000  |  4.00000000 |  4.00000000 | 4.00000000  |
+---------------------+------------+-------------------------+-------------+-------------+-------------+-------------+

4.上面的结果只给出表永久记录，即使我需要对每个间隔的所有记录都有默认值或透水记录值(打开、关闭、高、低和它们的时间戳)。

预期产出:-

range= '2017-09-11 :00:00:00和'2017-09-15 23:59:59‘

 timestampDate       | volume     | wavg_price              | open        | high        | low         | close       |
+---------------------+------------+-------------------------+-------------+-------------+-------------+-------------+
| 2017-09-11 00:05:00 | 4.00000000 | 10.00000000000000000000 | 10.00000000 | 10.00000000 | 10.00000000 | 10.00000000 |
| 2017-09-11 00:10:00 | 3.00000000 |  3.33333333333333333333 | 2.00000000  |  4.00000000 |  2.00000000 | 4.00000000  |
| 2017-09-11 00:15:00 | 2.00000000 |  4.00000000000000000000 | 4.00000000  |  4.00000000 |  4.00000000 | 4.00000000  |
................................................
.................................................
.................................................
| 2017-09-15 23:05:00 | 1.00000000 |  2.00000000000000000000 | 2.00000000  |  2.00000000 |  2.00000000 | 2.00000000  |
| 2017-09-15 23:10:00 | 1.00000000 |  2.00000000000000000000 | 2.00000000  |  2.00000000 |  2.00000000 | 2.00000000  |
..........................................................
..........................................................
..........................................................

| 2017-09-15 23:50:00 | 1.00000000 |  2.00000000000000000000 | 2.00000000  |  2.00000000 |  2.00000000 | 2.00000000  |
| 2017-09-15 23:55:00 | 1.00000000 |  2.00000000000000000000 | 2.00000000  |  2.00000000 |  2.00000000 | 2.00000000  |

我想要什么

1. 输出只给表持久记录，即使我需要所有的记录，包括默认值或遍历记录值(打开、关闭、高、低和它们的时间戳)。 案例a) 这里没有“2017-09-11:05:00”的记录。在这种情况下，打开、关闭、高、低值将设置为0(零)。 案例b) 这里没有“2017-09-15 :05:25:00”、“2017-09-15 05:30:00”和“额外”的记录，但这是介于“2017-09-15 05:20:00”和“2017-09-15 8:30:00”两项记录之间的。在这种情况下，ohlc值‘2017-09-1505:25:00’应该是之前的日期时间(‘2017-09-1505:15:00’) ohlc值设定。

谢谢

Answer 1

要找到丢失的记录，你需要

1. 创建一个包含所有所需值的额外表
2. 从额外表到您已经拥有的查询的LEFT JOIN
3. 对输出中显示的NULLs做一些处理。

如果您使用的是MariaDB，那么就有一个方便的“序列”生成器。对于步骤1.在MySQL中，我建议您预先构建一个从0到100万的数字表，然后使用+ INTERVAL ... SECOND创建5分钟的日期时间。