2

I have a design a table for attendance and here are the genral fileds

  1. AttendanceMachineLoginId
  2. EmpId
  3. AttendanceDateTime

Whenever user will come to office, he has to make his attendance.

The first attendance will consider login and the second will consider the logout. Each time a record will be added with the time. A user can make multiple entries (login logout in a single day. Like this

enter image description here

EmpId 81 has login and logout two times in same day.

Now, My aim is to generate per day employee report that how many minutes he has given to the company. I just came to know that TIMESTAMPDIFF() can provide the minutes but i am unable to understand that how can I apply it to my table. Additionally, I want to ask that, do the table Fields are right for the desired report or I need to change it?

One Another Strategy: I was also thinking that I should add minutes column in the table and whenever user logout I should calculate the minutes and add that minutes with logout entry.

Sample Data:

INSERT INTO `attendancemachinelogin` (`AttendanceMachineLoginId`, `EmpId`, `TimeTrackId`, `AttendanceDateTime`, `RecordAddDateTime`) VALUES
(0, 81, 315079, '2018-8-15 14:8:46', '2018-08-15 14:09:25'),
(0, 81, 315079, '2018-8-15 14:20:38', '2018-08-15 14:21:17'),
(0, 81, 315079, '2018-8-15 14:21:9', '2018-08-15 14:21:47'),
(0, 81, 315079, '2018-8-15 14:28:37', '2018-08-15 14:29:16'),
(0, 81, 315079, '2018-8-15 14:28:58', '2018-08-15 14:29:36'),
(0, 81, 315079, '2018-8-15 14:36:42', '2018-08-15 14:37:21'),
(0, 81, 315079, '2018-8-15 15:36:34', '2018-08-15 15:37:13'),
(0, 81, 315079, '2018-8-15 15:52:39', '2018-08-15 15:53:17'),
(0, 81, 315079, '2018-8-15 16:5:38', '2018-08-15 16:06:17'),
(0, 81, 315079, '2018-8-15 16:6:50', '2018-08-15 16:07:29'),
(0, 81, 315079, '2018-8-15 16:8:49', '2018-08-15 16:09:29'),
(0, 81, 315079, '2018-8-15 16:18:28', '2018-08-15 16:19:08'),
(0, 81, 315079, '2018-8-15 16:20:49', '2018-08-15 16:21:28'),
(0, 81, 315079, '2018-8-15 16:23:18', '2018-08-15 16:23:58'),
(0, 81, 315079, '2018-8-15 16:24:3', '2018-08-15 16:24:42'),
(0, 81, 315079, '2018-8-15 16:24:47', '2018-08-15 16:25:26'),
(0, 81, 315079, '2018-8-15 16:24:58', '2018-08-15 16:25:37'),
(0, 81, 315079, '2018-8-15 16:25:54', '2018-08-15 16:26:33'),
(0, 81, 315079, '2018-8-15 16:56:47', '2018-08-15 16:57:27'),
(0, 101, 417092, '2018-8-15 17:37:53', '2018-08-15 17:38:32'),
(0, 101, 417092, '2018-8-15 18:4:34', '2018-08-15 18:05:14'),
(0, 101, 417092, '2018-8-15 18:7:43', '2018-08-15 18:08:22'),
(0, 81, 315079, '2018-8-15 18:13:15', '2018-08-15 18:13:54'),
(0, 81, 315079, '2018-8-17 10:50:16', '2018-08-17 10:50:54'),
(0, 101, 417092, '2018-8-17 10:51:54', '2018-08-17 10:52:31'),
(0, 4, 413034, '2018-8-17 11:45:16', '2018-08-17 11:45:54'),
(0, 91, 916086, '2018-8-17 11:59:34', '2018-08-17 12:00:12'),
(0, 81, 315079, '2018-8-17 12:0:19', '2018-08-17 12:00:56'),
(0, 81, 315079, '2018-8-17 15:7:41', '2018-08-17 15:08:17'),
(0, 101, 417092, '2018-8-17 15:9:54', '2018-08-17 15:10:32'),
(0, 101, 417092, '2018-8-17 15:10:9', '2018-08-17 15:10:45'),
(0, 101, 417092, '2018-8-17 15:10:23', '2018-08-17 15:10:59'),
(0, 101, 417092, '2018-8-17 15:10:25', '2018-08-17 15:11:02'),
(0, 101, 417092, '2018-8-17 15:11:6', '2018-08-17 15:11:43'),
(0, 101, 417092, '2018-8-17 15:11:15', '2018-08-17 15:11:52'),
(0, 101, 417092, '2018-8-17 15:11:17', '2018-08-17 15:11:54'),
(0, 81, 315079, '2018-8-17 15:11:32', '2018-08-17 15:12:09'),
(0, 81, 315079, '2018-8-17 15:12:32', '2018-08-17 15:13:09'),
(0, 81, 315079, '2018-8-17 15:35:33', '2018-08-17 15:36:10'),
(0, 81, 315079, '2018-8-17 15:41:58', '2018-08-17 15:42:34'),
(0, 81, 315079, '2018-8-17 15:42:17', '2018-08-17 15:42:54'),
(0, 81, 315079, '2018-8-17 16:8:25', '2018-08-17 16:09:01'),
(0, 81, 315079, '2018-8-17 16:8:32', '2018-08-17 16:09:08'),
(0, 101, 417092, '2018-8-17 16:8:53', '2018-08-17 16:09:30'),
(0, 101, 417092, '2018-8-17 16:9:20', '2018-08-17 16:09:57'),
(0, 4, 413034, '2018-8-17 16:10:16', '2018-08-17 16:10:53'),
(0, 36, 413037, '2018-8-17 16:10:46', '2018-08-17 16:11:23'),
(0, 81, 315079, '2018-8-17 16:22:21', '2018-08-17 16:22:58'),
(0, 101, 417092, '2018-8-17 16:22:45', '2018-08-17 16:23:21'),
(0, 4, 413034, '2018-8-17 16:23:12', '2018-08-17 16:23:49'),
(0, 81, 315079, '2018-8-17 16:23:35', '2018-08-17 16:24:12'),
(0, 81, 315079, '2018-8-17 16:44:4', '2018-08-17 16:44:42'),
(0, 101, 417092, '2018-8-17 16:44:22', '2018-08-17 16:44:58'),
(0, 81, 315079, '2018-8-17 17:6:51', '2018-08-17 17:07:28'),
(0, 101, 417092, '2018-8-17 17:7:8', '2018-08-17 17:07:45'),
(0, 4, 413034, '2018-8-17 17:7:52', '2018-08-17 17:08:28'),
(0, 81, 315079, '2018-8-17 17:9:25', '2018-08-17 17:10:02'),
(0, 101, 417092, '2018-8-17 17:9:46', '2018-08-17 17:10:22'),
(0, 4, 413034, '2018-8-17 17:10:6', '2018-08-17 17:10:42'),
(0, 81, 315079, '2018-8-17 17:10:24', '2018-08-17 17:11:01'),
(0, 81, 315079, '2018-8-17 17:10:39', '2018-08-17 17:11:15'),
(0, 101, 417092, '2018-8-17 17:10:47', '2018-08-17 17:11:24'),
(0, 101, 417092, '2018-8-17 17:10:58', '2018-08-17 17:11:35'),
(0, 81, 315079, '2018-8-17 17:11:10', '2018-08-17 17:11:46'),
(0, 101, 417092, '2018-8-17 17:11:31', '2018-08-17 17:12:09'),
(0, 4, 413034, '2018-8-17 17:40:40', '2018-08-17 17:41:18'),
(0, 101, 417092, '2018-8-17 17:41:23', '2018-08-17 17:41:59'),
(0, 36, 413037, '2018-8-17 17:41:37', '2018-08-17 17:42:14'),
(0, 81, 315079, '2018-8-17 17:42:9', '2018-08-17 17:42:45'),
(0, 3, 213020, '2018-8-17 17:47:34', '2018-08-17 17:48:11'),
(0, 81, 315079, '2018-8-17 17:48:16', '2018-08-17 17:48:52'),
(0, 4, 413034, '2018-8-17 17:48:59', '2018-08-17 17:49:36'),
(0, 4, 413034, '2018-8-17 17:49:59', '2018-08-17 17:50:36'),
(0, 36, 413037, '2018-8-17 17:52:36', '2018-08-17 17:53:13'),
(0, 101, 417092, '2018-8-17 17:52:53', '2018-08-17 17:53:29'),
(0, 6, 213016, '2018-8-17 17:53:30', '2018-08-17 17:54:06'),
(0, 81, 315079, '2018-8-17 17:53:44', '2018-08-17 17:54:20'),
(0, 4, 413034, '2018-8-17 17:54:27', '2018-08-17 17:55:03'),
(0, 3, 213020, '2018-8-17 17:54:49', '2018-08-17 17:55:27'),
(0, 4, 413034, '2018-8-17 17:55:23', '2018-08-17 17:56:00'),
(0, 36, 413037, '2018-8-17 17:58:33', '2018-08-17 17:59:10'),
(0, 101, 417092, '2018-8-17 17:58:47', '2018-08-17 17:59:24'),
(0, 102, 517094, '2018-8-17 17:59:4', '2018-08-17 17:59:40'),
(0, 81, 315079, '2018-8-17 17:59:33', '2018-08-17 18:00:09'),
(0, 4, 413034, '2018-8-17 18:0:16', '2018-08-17 18:00:52'),
(0, 3, 213020, '2018-8-17 18:0:40', '2018-08-17 18:01:17'),
(0, 6, 213016, '2018-8-17 18:1:30', '2018-08-17 18:02:06'),
(0, 36, 413037, '2018-8-17 18:26:24', '2018-08-17 18:27:01'),
(0, 101, 417092, '2018-8-17 18:26:38', '2018-08-17 18:27:14'),
(0, 6, 213016, '2018-8-17 18:27:9', '2018-08-17 18:27:45'),
(0, 81, 315079, '2018-8-17 18:27:24', '2018-08-17 18:28:00'),
(0, 102, 517094, '2018-8-17 18:27:38', '2018-08-17 18:28:14'),
(0, 4, 413034, '2018-8-17 18:28:13', '2018-08-17 18:28:49'),
(0, 81, 315079, '2018-8-17 19:36:49', '2018-08-17 19:37:26'),
(0, 101, 417092, '2018-8-17 19:37:17', '2018-08-17 19:37:54'),
(0, 102, 517094, '2018-8-17 19:37:30', '2018-08-17 19:38:07'),
(0, 36, 413037, '2018-8-17 19:38:13', '2018-08-17 19:38:50'),
(0, 4, 413034, '2018-8-17 19:38:54', '2018-08-17 19:39:32'),
(0, 3, 213020, '2018-8-17 19:39:58', '2018-08-17 19:40:35'),
(0, 101, 417092, '2018-8-18 10:21:26', '2018-08-18 10:22:03'),
(0, 81, 315079, '2018-8-18 10:30:23', '2018-08-18 10:31:09'),
(0, 4, 413034, '2018-8-18 10:31:46', '2018-08-18 10:32:27'),
(0, 102, 517094, '2018-8-18 10:32:15', '2018-08-18 10:32:53'),
(0, 6, 213016, '2018-8-18 10:32:44', '2018-08-18 10:33:22'),
(0, 3, 213020, '2018-8-18 10:33:23', '2018-08-18 10:34:03'),
(0, 81, 315079, '2018-8-18 10:42:49', '2018-08-18 10:43:27'),
(0, 101, 417092, '2018-8-18 10:43:25', '2018-08-18 10:44:03'),
(0, 81, 315079, '2018-8-18 10:48:51', '2018-08-18 10:49:30'),
(0, 102, 517094, '2018-8-18 10:49:9', '2018-08-18 10:49:49'),
(0, 81, 315079, '2018-8-18 10:56:46', '2018-08-18 10:57:25'),
(0, 1, 1211003, '2018-8-18 10:57:0', '2018-08-18 10:57:38'),
(0, 4, 413034, '2018-8-18 10:57:51', '2018-08-18 10:58:38'),
(0, 3, 213020, '2018-8-18 10:58:43', '2018-08-18 10:59:26');
2
  • Your structure seems incomplete, since it does not indicate whether an event is a login or logout, and assumptions of clean pairing and ordering, and sessions never spanning midnight... seem problematic. You don't need to store minutes, but updating the login row with a logout time or another strategy that captures a more thorough perspective of what is actually happening might be a distinct improvement. Solving this problem with the current schemata with pure declarative SQL (no procs, functions, temp tables, cursors, etc.) seems like it will not be straightforward. Commented Aug 18, 2018 at 23:20
  • Unrelated, but very important: The pairing of login to logout will fail some day. Someone will fail to logout. Or will login twice. Or the system will drop a record. Or...
    – Rick James
    Commented Aug 26, 2018 at 22:29

2 Answers 2

0

Well, I've made an assumption that first event each day for each employee is the login.

For mysql 8.x having CTEs the query can be the next:

WITH cteB (EID, mins) AS 
(
  WITH cteA (EID, TS, cnt) AS 
  ( 
    SELECT w.EmpId
         , w.AttendanceDateTime
         , IF( @prevEID != @prevID := w.EmpID, @cnt := 1, @cnt := @cnt+1 ) AS cnt
      FROM table AS w
     ORDER BY w.EmpId ASC
            , w.AttendanceDateTime ASC
  )
  SELECT z.EID
       , TIMESTAMPDIFF(MINUTE, z.TS, q.TS) AS mins
    FROM cteA AS z
    JOIN cteA AS q  ON q.EID = z.EID
                   AND z.cnt = q.cnt+1
                   AND z.cnt % 2 = 1
)
SELECT x.EID AS EmpID
     , SUM(x.mins) AS Eminutes
  FROM cteB AS x
 GROUP BY x.EID
 ORDER BY x.EID ASC 
;

The same result can be achieved in the earlier versions of mysql with subqueries.

2
  • 1
    The OP states "EmpId 81 has login and logout two times in same day", so this does not answer the question
    – Philᵀᴹ
    Commented Aug 18, 2018 at 12:46
  • This is valueable but i am looking for solution with multiple entries Commented Aug 18, 2018 at 13:00
0

Old post, but here goes anyhow. Using 8+ we can solve this with window functions. I'll use two here, one to determine login (odd row_numbers), one to determine logout time (lead):

SELECT empid, SUM(TIMESTAMPDIFF(MINUTE, AttendanceDateTime, leaddt))
FROM (
    SELECT empid
         , ROW_NUMBER() OVER (PARTITION BY empid 
                              ORDER BY AttendanceDateTime) as rn
         , AttendanceDateTime
         , LEAD(AttendanceDateTime) OVER (PARTITION BY empid 
                                          ORDER BY AttendanceDateTime) as leaddt
    FROM attendancemachinelogin     
) as t 
WHERE MOD(rn,2)=1 -- filter logout/login rows
GROUP BY empid;

If you want to take into concideration logins that have not yet logged out, you can replace null with current timestamp at the outer level. Replace:

leadtdt

with:

COALESCE(leaddt, NOW())

Your Answer

By clicking “Post Your Answer”, you agree to our terms of service and acknowledge you have read our privacy policy.

Not the answer you're looking for? Browse other questions tagged or ask your own question.