Sql 按5、10、15分钟块分组时间戳记录

我的表中以类似的格式存储了每分钟的财务记录

         dt          |   open   |   high   |   low    |  close   |  vol  
---------------------+----------+----------+----------+----------+-------
 2018-05-04 15:30:00 | 171.0000 | 171.3000 | 170.9000 | 171.0000 | 42817
 2018-05-04 15:29:00 | 170.8000 | 171.0000 | 170.8000 | 170.9500 | 32801
 2018-05-04 15:28:00 | 170.8500 | 171.0000 | 170.8000 | 170.8000 | 22991
 2018-05-04 15:27:00 | 170.8500 | 170.8500 | 170.7500 | 170.8000 | 40283
 2018-05-04 15:26:00 | 170.9500 | 171.0000 | 170.8000 | 170.8500 | 46636

等等

我想把它们分为5分钟，10分钟，60分钟，就像烛台一样。使用

date\u trunc（'hour'，dt）

是不可能的，因为我想将它们分组为最后60分钟、最后15分钟等

---

我使用的是PostgreSQL。

您可以使用

generate_series（）

创建您想要的任何范围

---

然后检查您的记录是否在该范围内。

您应该使用

分组依据

和：

floor(extract('epoch' from dt) / 300)

以5分钟为间隔对数据进行分组。300是5分钟内的秒数。因此，如果你想要10分钟，你可以除以600。如果你想要1小时，3600

如果希望间隔时间从00 05 10开始，请使用

floor（）

。如果希望它们在00、05、10点结束，请使用

ceil（）

在
SELECT
子句中，您应该使用

不清楚您是否希望所有的“块”结果都在同一个查询中，如果您想要一个烛台图，我假设是。我还从逻辑上推导了每列的正确聚合函数（MIN、MAX、AVG、SUM），紧跟在它们的名称后面。你可能必须适应这个

我们开始：

 SELECT '5 minutes' as block,
        to_timestamp(floor((extract('epoch' from dt) / 300)) * 300)  as ts, 
        round(AVG(open),4) as avg_open,  
        round(MAX(high),4) as max_high, 
        round(MIN(low),4) as min_low, 
        round(AVG(close),4) as avg_close,  
        SUM(vol) as sum_vol  
 FROM mytable
 GROUP BY floor(extract('epoch' from dt) / 300)

 UNION ALL

  SELECT '10 minutes' as block,
        to_timestamp(floor((extract('epoch' from dt) / 600)) * 600)  as ts, 
        round(AVG(open),4) as avg_open,  
        round(MAX(high),4) as max_high, 
        round(MIN(low),4) as min_low, 
        round(AVG(close),4) as avg_close,  
        SUM(vol) as sum_vol  
 FROM mytable
 GROUP BY floor(extract('epoch' from dt) / 600)

  UNION ALL

  SELECT '1 hour' as block,
        to_timestamp(floor((extract('epoch' from dt) / 3600)) * 3600)  as ts, 
        round(AVG(open),4) as avg_open,  
        round(MAX(high),4) as max_high, 
        round(MIN(low),4) as min_low, 
        round(AVG(close),4) as avg_close,  
        SUM(vol) as sum_vol  
 FROM mytable
 GROUP BY floor(extract('epoch' from dt) / 3600)

结果:

    block       ts                  avg_open    max_high    min_low     avg_close   sum_vol
    5 minutes   04.05.2018 17:30:00 171         171,3       170,9       171         42817
    5 minutes   04.05.2018 17:25:00 170,8625    171         170,75      170,85      142711
    10 minutes  04.05.2018 17:20:00 170,8625    171         170,75      170,85      142711
    10 minutes  04.05.2018 17:30:00 171         171,3       170,9       171         42817
    1 hour      04.05.2018 17:00:00 170,89      171,3       170,75      170,88      185528

在
Show us db schema、示例数据、当前和预期输出上测试它。请阅读，这里是学习如何提高问题质量和获得更好答案的好地方。非常感谢，它成功了，我不得不做一些轻微的调整，现在它很完美选择“5分钟”作为块，将时区“UTC”处的时间戳（ceil（（从dt中提取（'epoch'））/300））*300）作为ts，（数组_agg（由dt ASC打开的订单））[1]o，最大（高）作为h，最小（低）作为l，（数组_agg（由dt DESC关闭的订单））[1]c，总和（vol）作为来自dt>=“2018-05-03”组中的数据（摘录（'epoch'from dt）/300）ts desc limit 20命令，``由于声誉原因，它不会记录我的投票，这里新增：D
 SELECT '5 minutes' as block,
        to_timestamp(floor((extract('epoch' from dt) / 300)) * 300)  as ts, 
        round(AVG(open),4) as avg_open,  
        round(MAX(high),4) as max_high, 
        round(MIN(low),4) as min_low, 
        round(AVG(close),4) as avg_close,  
        SUM(vol) as sum_vol  
 FROM mytable
 GROUP BY floor(extract('epoch' from dt) / 300)

 UNION ALL

  SELECT '10 minutes' as block,
        to_timestamp(floor((extract('epoch' from dt) / 600)) * 600)  as ts, 
        round(AVG(open),4) as avg_open,  
        round(MAX(high),4) as max_high, 
        round(MIN(low),4) as min_low, 
        round(AVG(close),4) as avg_close,  
        SUM(vol) as sum_vol  
 FROM mytable
 GROUP BY floor(extract('epoch' from dt) / 600)

  UNION ALL

  SELECT '1 hour' as block,
        to_timestamp(floor((extract('epoch' from dt) / 3600)) * 3600)  as ts, 
        round(AVG(open),4) as avg_open,  
        round(MAX(high),4) as max_high, 
        round(MIN(low),4) as min_low, 
        round(AVG(close),4) as avg_close,  
        SUM(vol) as sum_vol  
 FROM mytable
 GROUP BY floor(extract('epoch' from dt) / 3600)

    block       ts                  avg_open    max_high    min_low     avg_close   sum_vol
    5 minutes   04.05.2018 17:30:00 171         171,3       170,9       171         42817
    5 minutes   04.05.2018 17:25:00 170,8625    171         170,75      170,85      142711
    10 minutes  04.05.2018 17:20:00 170,8625    171         170,75      170,85      142711
    10 minutes  04.05.2018 17:30:00 171         171,3       170,9       171         42817
    1 hour      04.05.2018 17:00:00 170,89      171,3       170,75      170,88      185528