Question

我试图按月计算上个月没有的唯一身份用户。因此，如果用户有1月份的记录，然后是2月份的另一份记录，那么我只计算该用户的1月份。

user_id    time
a1         1/2/17
a1         2/10/17
a2         2/18/17
a4         2/5/17
a5         3/25/17

我的结果应该是这样的

Month   User Count
January     1
February    2
March       1

Answer 1

我对BigQuery并不熟悉，但这是我如何使用TSQL解决问题。我想你可以在BigQuery中使用类似的逻辑。

1）。首先按user_id排序数据，然后按时间排序。在TSQL中，您可以使用以下内容完成此操作并将其存储在公用表表达式中，您将在此后的步骤中进行查询。

;WITH cte AS
(
select  ROW_NUMBER() OVER (PARTITION BY [user_id] ORDER BY [time]) AS rn,*
from    dbo.employees
)

2）。下一个查询仅针对rn = 1（特定用户的第一次出现）和按月分组的行。

select    DATENAME(month, [time]) AS [Month], count(*) AS user_count 
from      cte
where     rn = 1    
group by  DATENAME(month, [time])

这假设2017年是您唯一需要处理的年份。如果您处理的时间超过一年，您可能希望步骤＃2看起来像这样：

select    year([time]) as [year],  DATENAME(month, [time]) AS [month], 
          count(*) AS user_count 
from      cte
where     rn = 1    
group by  year([time]), DATENAME(month, [time])

Answer 2

首先按用户ID和月份汇总。然后使用lag()查看用户是否在上个月出现：

with du as (
      select date_trunc(time, month) as yyyymm, user_id
      from t
      group by date_trunc(time, month)
     )
select yyyymm, count(*)
from (select du.*,
             lag(yyyymm) over (partition by user_id order by yyyymm) as prev_yyyymm
      from du
     ) du
where prev_yyyymm is not null or
      prev_yyyymm < date_add(yyyymm, interval 1 month)
group by yyyymm;

注意：这使用date函数，但timestamp存在类似的函数。

Answer 3

我理解问题的方法是 - 仅在相同用户在上个月展示时，将用户排除在给定月份内。但是如果同一个用户在给出之前的几个月内出现，而不是之前的用户 - 用户应该被计算在内。

如果这是正确的 - 请尝试以下BigQuery Standard SQL

#standardSQL
SELECT Year, Month, COUNT(DISTINCT user_id) AS User_Count
FROM (
  SELECT *,
    DATE_DIFF(time, LAG(time) OVER(PARTITION BY user_id ORDER BY time), MONTH) AS flag
  FROM (
    SELECT 
      user_id,
      DATE_TRUNC(PARSE_DATE('%x', time), MONTH) AS time, 
      EXTRACT(YEAR FROM PARSE_DATE('%x', time)) AS Year, 
      FORMAT_DATE('%B', PARSE_DATE('%x', time)) AS Month
    FROM yourTable
    GROUP BY 1, 2, 3, 4
  )
)
WHERE IFNULL(flag, 0) <> 1
GROUP BY Year, Month, time
ORDER BY time

您可以使用以下示例使用您的问题

中的虚拟数据来测试/播放上面的内容

#standardSQL
WITH yourTable AS (
  SELECT 'a1' AS user_id, '1/2/17' AS time UNION ALL
  SELECT 'a1', '2/10/17' UNION ALL
  SELECT 'a2', '2/18/17' UNION ALL
  SELECT 'a4', '2/5/17' UNION ALL
  SELECT 'a5', '3/25/17' 
)
SELECT Year, Month, COUNT(DISTINCT user_id) AS User_Count
FROM (
  SELECT *,
    DATE_DIFF(time, LAG(time) OVER(PARTITION BY user_id ORDER BY time), MONTH) AS flag
  FROM (
    SELECT 
      user_id,
      DATE_TRUNC(PARSE_DATE('%x', time), MONTH) AS time, 
      EXTRACT(YEAR FROM PARSE_DATE('%x', time)) AS Year, 
      FORMAT_DATE('%B', PARSE_DATE('%x', time)) AS Month
    FROM yourTable
    GROUP BY 1, 2, 3, 4
  )
)
WHERE IFNULL(flag, 0) <> 1
GROUP BY Year, Month, time
ORDER BY time

输出

Year    Month       User_Count   
2017    January     1    
2017    February    2    
2017    March       1

Answer 4

尝试此查询：

    {
  "items": [
    {
      "id": "4",
      "order_id": "000000145",
      "creditmemo": {
        "items": [
          {
            "sku": "SWETA0582",
            "product_id": "2640",
            "item_id": "211",
            "qty": "1.0000",
            "reason": "Product didn’t meet your expectation."
          },
          {
            "sku": "SWETA0583",
            "product_id": "2642",
            "item_id": "212",
            "qty": "2.0000",
            "reason": "Product didn’t meet your expectation."
          }
        ],
        "do_offline": 1,
        "comment_text": "",
        "shipping_amount": "49.0000",
        "adjustment_positive": "",
        "adjustment_negative": "49.0000"
      },
      "additional_remark": "",
      "type": "1",
      "status": "3",
      "account": {
        "ifsc": "PYTM0123456",
        "account_no": "918981961927",
        "name": "Shruti Dhandhania"
      },
      "refund_status": "0",
      "totals_info": "",
      "refund_id": "0",
      "created_at": "2018-10-25 08:58:37",
      "update_at": "2018-10-25 08:58:37",
      "tracking_number": "",
      "method": "cashondelivery",
      "comment": null
    },
    {
      "id": "5",
      "order_id": "000000146",
      "creditmemo": {
        "items": [
          {
            "sku": "SWETA0584",
            "product_id": "2644",
            "item_id": "215",
            "qty": "3.0000",
            "reason": "Product didn’t meet your expectation."
          },
          {
            "sku": "SWETA0585",
            "product_id": "2646",
            "item_id": "216",
            "qty": "2.0000",
            "reason": "Product didn’t meet your expectation."
          }
        ],
        "do_offline": 1,
        "comment_text": "",
        "shipping_amount": "49.0000",
        "adjustment_positive": "",
        "adjustment_negative": "49.0000"
      },
      "additional_remark": "",
      "type": "1",
      "status": "3",
      "account": {
        "ifsc": "PYTM0123456",
        "account_no": "918981961927",
        "name": "Shruti Dhandhania"
      },
      "refund_status": "0",
      "totals_info": "",
      "refund_id": "0",
      "created_at": "2018-10-25 08:58:37",
      "update_at": "2018-10-25 08:58:37",
      "tracking_number": "",
      "method": "cashondelivery",
      "comment": null
    }
  ]
}

如何计算一个月内没有出现的用户？

4 个答案: