For example have such table (named purchase_invoice_items)
Id
NameOfItem
PurchaseQuantity
PurchaseDate
SoldQuantity
1
x
2
2022-04-01
2
y
11
2022-04-01
3
z
8
2022-05-19
4
x
23
2022-08-19
5
x
15
2022-05-19
And i know that sum of sold quantity for NameOfItem x is 20. Sold 20 units of item x. I want to distribute the sold items between PurchaseQuantity using first-in-first-out method. Want to see table like this
Id
NameOfItem
PurchaseQuantity
PurchaseDate
SoldQuantity
1
x
2
2022-04-01
2
2
y
11
2022-04-01
3
z
8
2022-05-19
4
x
23
2022-08-19
3
5
x
15
2022-05-19
15
Using mysql two queries and php, i can do it in following way.
At first i select necessary data from mysql:
$sql_select_purchase_data = 'SELECT `IdPii`, `PurchasedQuantity`
FROM `purchase_invoice_items` WHERE `NameOfItem` = "x"
ORDER BY `PurchaseDate` ASC;';
Then create sql to update.
$sql_update_sold_quantity = 'INSERT INTO `purchase_invoice_items` (`IdPii`, `SoldQuantity`) VALUES ';
php code to continue creating sql
if( isset($arr_select_purchase_data) ){
$sum_of_sold_quantity = 20;
foreach( $arr_select_purchase_data as $one_arr_select_purchase_data ){
if( $sum_of_sold_quantity > 0 ){
$sql_update_sold_quantity .= '(?,?), ';
$data_update_sold_quantity[] = $one_arr_select_purchase_data['IdPii'];//For 'IdPii'
$data_update_sold_quantity[] = min( $one_arr_select_purchase_data['PurchasedQuantity'], $sum_of_sold_quantity);//For 'SoldQuantity'
$sum_of_sold_quantity = $sum_of_sold_quantity - min( $one_arr_select_purchase_data['PurchasedQuantity'], $sum_of_sold_quantity);
}//if( $sum_of_sold_quantity > 0 ){
else{ break; }
}//foreach(
$sql_update_sold_quantity = rtrim(trim($sql_update_sold_quantity), ','). ' ON DUPLICATE KEY UPDATE `SoldQuantity`= VALUES(`SoldQuantity`);';
But this is waste of resources (if i need to select-update many rows)? Two mysql queries and additionally php code.
Any ideas how can i get the same using only mysql (one mysql query; without php)?
Having a table with this values:
name | executing | failed |
-------------------------------
task1 0 1
task2 1 0
task3 1 0
task4 0 0
With a query i want to get:
The total amount of executing task (2 in the example, task2 and task3)
The total amount of failed task (1 in the example, task1)
The total amount of pending task (those that are executing=0 and failed=0, 1 in the example, task4)
I can get the first two by uysing the following query:
SELECT IFNULL(SUM(executing), 0) Executing, IFNULL(SUM(failed), 0) Failed FROM mytable;
How can I expand my query so I can get another column with the sum of pending tasks?
Thanks in advance
Expected output:
executing | failed | pending
----------------------------
2 1 1
You don't specify how you want the results. I would do this as:
select (case when executing = 1 and failed = 0 then 'Executing'
when failed = 1 then 'Failed'
when executing = 0 and failed = 0 then 'Pending'
else 'Unknown'
end) as status, count(*) as cnt
from t
group by status;
You can also easily pivot the data using conditional aggregation:
select sum(executing = 1 and failed = 0) as Executing,
sum(failed = 1) as Failed,
sum(executing = 0 and failed = 0) as Pending
from t;
This uses a MySQL shorthand that treats boolean expressions as numbers -- with "1" for true and "0" for false.
SELECT SUM(executing) AS Executing
, SUM(failed) as Failed
, SUM(CASE
WHEN executing = 0 AND failed = 0 THEN 1
ELSE 0 END
) AS Pending
FROM mytable;
This is follow-up/revision to a question I had earlier as I believe I was over-thinking.
I have a table set up as the following:
ItemNumber
StartTime
EndTime
Price
MonStartTime
MonEndTime
MonPrice
TueStartTime
TueEndTime
TuePrice
... and so on for the rest of the week.
Table would look like this
ItemNumber StartTime EndTime Price MonStartTime MonEndTime MonPrice .....
1234 1600 1800 2.99 1300 1500 1.89
2345 0900 1100 3.99 1400 2200 2.50
I need a script that uses the datepart function to find the day of the week and moves that days Start and End Times and Price to StartTime EndTime Price columns.
In the example above, if Today was Monday, the script would COPY/UPDATE for Item 1234 the MonStartTime of 1300 to the StartTime, the MonEndTime of 1500 to the EndTime and the MonPrice of 1.89 to the Price field.
Thank you for your feedback!
This works!
CREATE procedure p_Calculation_PLUSchedule_Wed
#Store int
, #vYYYYMMDD varchar(8)
, #iCard smallint
AS
/* PLU Schedule Wednesday */
SET NOCOUNT ON
DECLARE #Client smallint
SET #Client = 1
IF datepart(dw,getdate()) = '4'
BEGIN
Update DatabaseName.dbo.plusschedule
Set price = wedprice, StartTime = WedStartTime, EndTime = WedEndTime
From DatabaseName.dbo.plusschedule psched
Where psched.Wednesday = '1'
And EXISTS (Select *
From DatabaseName.dbo.PlusSchedule D
Where D.Wednesday = '1')
End
GO
I make a cohort analysis processor. Input parameters: time range and step, condition (initial event) to exctract cohorts, additional condition (retention event) to check after each N hours/days/months. Output parameters: cohort analysis grid, like this:
0h | 16h | 32h | 48h | 64h | 80h | 96h |
cohort #00 15 | 6 | 4 | 1 | 1 | 2 | 2 |
cohort #01 1 | 35 | 8 | 0 | 2 | 0 | 1 |
cohort #02 0 | 3 | 31 | 11 | 5 | 3 | 0 |
cohort #03 0 | 0 | 4 | 27 | 7 | 6 | 2 |
cohort #04 0 | 1 | 1 | 4 | 29 | 4 | 3 |
Basically:
fetch cohorts: unique users who did something 1 in every period from time_begin every time_step.
find how many of them (in each cohort) did something 2 after N seconds, N*2 seconds, N*3, and so on until now.
In short - I have 2 solutions. One works too slow and includes a heavy select with joins for each data step: 1 day, 2 day, 3 day, etc. I want to optimize it by joining result for every data step to cohorts - and it's the second solution. It looks like it works but I'm not sure it's the best way and that it will give the same result even if cohorts will intersect. Please check it out.
Here's the whole story.
I have a table of > 100,000 events, something like this:
#user-id, timestamp, event_name
events_view (uid varchar(64), tm int(11), e varchar(64))
example input row:
"user_sampleid1", 1423836540, "level_end:001:win"
To make a cohort analisys first I extract cohorts: for example, users, who send special event '1st_launch' in 10 hour periods starting from 2015-02-13 and ending with 2015-02-16. All code in this post is simplified and shortened to see the idea.
DROP TABLE IF EXISTS tmp_c;
create temporary table tmp_c (uid varchar(64), tm int(11), c int(11) );
set beg = UNIX_TIMESTAMP('2015-02-13 00:00:00');
set en = UNIX_TIMESTAMP('2015-02-16 00:00:00');
select min(tm) into t_start from events_view ;
select max(tm) into t_end from events_view ;
if beg < t_start then
set beg = t_start;
end if;
if en > t_end then
set en = t_end;
end if;
set period = 3600 * 10;
set cnt_c = ceil((en - beg) / period) ;
/*works quick enough*/
WHILE i < cnt_c DO
insert into tmp_c (
select uid, min(tm), i from events_view where
locate("1st_launch", e) > 0 and tm > (beg + period * i)
AND tm <= (beg + period * (i+1)) group by uid );
SET i = i+1;
END WHILE;
Cohorts may consist the same user ids, though usually one user is exist only in one cohort. And in each cohort users are unique.
Now I have temp table like this:
user_id | 1st timestamp | cohort_no
uid1 1423836540 0
uid2 1423839540 0
uid3 1423841160 1
uid4 1423841460 2
...
uidN 1423843080 M
Then I need to again divide time range on periods and calculate for each period how many users from each cohort have sent event "level_end:001:win".
For each small period I select all unique users who have sent "level_end:001:win" event and left join them to tmp_c cohorts table. So I have something like this:
user_id | 1st timestamp | cohort_no | user_id | other fields...
uid1 1423836540 0 uid1
uid2 1423839540 0 null
uid3 1423841160 1 null
uid4 1423841460 2 uid4
...
uidN 1423843080 M null
This way I see how many users from my cohorts are in those who have sent "level_end:001:win", exclude not found by where clause: where t2.uid is not null.
Finally I perform grouping and have counts of users in each cohort, who have sent "level_end:001:win" in this particluar period.
Here's the code:
DROP TABLE IF EXISTS tmp_res;
create temporary table tmp_res (uid varchar(64) CHARACTER SET cp1251 NOT NULL, c int(11), cnt int(11) );
set i = 0;
set cnt_c = ceil((t_end - beg) / period) ;
WHILE i < cnt_c DO
insert into tmp_res
select concat(beg + period * i, "_", beg + period * (i+1)), c, count(distinct(uid)) from
(select t1.uid, t1.c from tmp_c t1 left join
(select uid, min(tm) from events_view where
locate("level_end:001:win", e) > 0 and
tm > (beg + period * i) AND tm <= (beg + period * (i+1)) group by uid ) t2
on t1.uid = t2.uid where t2.uid is not null) t3
group by c;
SET i = i+1;
END WHILE;
/*getting result of the first method: tooo slooooow!*/
select * from tmp_res;
The result I've got (it's ok that some cohorts are not appear on some periods):
"1423832400_1423890000","1","35"
"1423832400_1423890000","2","3"
"1423832400_1423890000","3","1"
"1423832400_1423890000","4","1"
"1423890000_1423947600","1","21"
"1423890000_1423947600","2","50"
"1423890000_1423947600","3","2"
"1423947600_1424005200","1","9"
"1423947600_1424005200","2","24"
"1423947600_1424005200","3","70"
"1423947600_1424005200","4","6"
"1424005200_1424062800","1","7"
"1424005200_1424062800","2","15"
"1424005200_1424062800","3","21"
"1424005200_1424062800","4","32"
"1424062800_1424120400","1","7"
"1424062800_1424120400","2","13"
"1424062800_1424120400","3","24"
"1424062800_1424120400","4","18"
"1424120400_1424178000","1","10"
"1424120400_1424178000","2","12"
"1424120400_1424178000","3","18"
"1424120400_1424178000","4","14"
"1424178000_1424235600","1","6"
"1424178000_1424235600","2","7"
"1424178000_1424235600","3","9"
"1424178000_1424235600","4","12"
"1424235600_1424293200","1","6"
"1424235600_1424293200","2","8"
"1424235600_1424293200","3","9"
"1424235600_1424293200","4","5"
"1424293200_1424350800","1","5"
"1424293200_1424350800","2","3"
"1424293200_1424350800","3","11"
"1424293200_1424350800","4","10"
"1424350800_1424408400","1","8"
"1424350800_1424408400","2","5"
"1424350800_1424408400","3","7"
"1424350800_1424408400","4","7"
"1424408400_1424466000","2","6"
"1424408400_1424466000","3","7"
"1424408400_1424466000","4","3"
"1424466000_1424523600","1","3"
"1424466000_1424523600","2","4"
"1424466000_1424523600","3","8"
"1424466000_1424523600","4","2"
"1424523600_1424581200","2","3"
"1424523600_1424581200","3","3"
It works but it takes too much time to process because there are many queries here instead of one, so I need to rewrite it.
I think it can be rewritten with joins, but I'm still not sure how.
I decided to make a temporary table and write period boundaries in it:
DROP TABLE IF EXISTS tmp_times;
create temporary table tmp_times (tm_start int(11), tm_end int(11));
set cnt_c = ceil((t_end - beg) / period) ;
set i = 0;
WHILE i < cnt_c DO
insert into tmp_times values( beg + period * i, beg + period * (i+1));
SET i = i+1;
END WHILE;
Then I get periods-to-events mapping (user_id + timestamp represent particular event) to temp table and left join it to cohorts table and group the result:
SELECT Concat(tm_start, "_", tm_end) per,
t1.c coh,
Count(DISTINCT( t2.uid ))
FROM tmp_c t1
LEFT JOIN (SELECT *
FROM tmp_times t3
LEFT JOIN (SELECT uid,
tm
FROM events_view
WHERE Locate("level_end:101:win", e) > 0)
t4
ON ( t4.tm > t3.tm_start
AND t4.tm <= t3.tm_end )
WHERE t4.uid IS NOT NULL
ORDER BY t3.tm_start) t2
ON t1.uid = t2.uid
WHERE t2.uid IS NOT NULL
GROUP BY per,
coh
ORDER BY per,
coh;
In my tests this returns the same result as method #1. I can't check the result manually, but I understand how method #1 work more and as far I can see it gives what I want. Method #2 is faster, but I'm not sure it's the best way and it will give the same result even if cohorts will intersect.
Maybe there are well-known common methods to perform a cohort analysis in SQL? Is method #1 I use more reliable than method #2? I work with joins not that often, that's why still do not fully understand joins magic yet.
Method #2 looks like pure magic, and I used to not believe in what I don't understand :)
Thanks for answers!
I'm working with a timecard database and trying to determine how much time for each punch falls into each one of three distinct shift periods.
For example
shift 1 = 7AM - 3pm
shift 2 = 3pm - 11pm
shift 3 = 11pm - 7am
Joe clocks in at 6:45AM and out at 1:45PM
15 minutes of this would need to be calculated as time on shift 3, but I'm not sure how to go about slicing out that bit of time in MySQL. All I have are a time in and time out field.
There are three shift periods:
Shift TimeStart TimeEnd
1 07:00 15:00
2 15:00 23:00
3 23:00 07:00
Sample Data
ID TimeIn TimeOut Hours
100 2014-07-31 06:45 2014-07-31 13:45 7
Desired Result
ID Shift TimeWorked
100 1 06:45
100 2 00:00
100 3 00:15
SQL Fiddle
I was able to come up with a solution for this using PHP.
What I did was loop through each punch, minute by minute, and determine what shift each one minute time span applies to. Within the loop, I increment one of 4 variable for shifts 1, 2, 3 or 0(no shift pay), and at the end, dump those variables to the database for the record being analyzed.
$query = "SELECT * FROM source_filtered_timecard";
$result_set = mysqli_query($connection, $query);
while($record = mysqli_fetch_assoc($result_set)) {
$checkCount++;
$shift1_hours = 0; $shift2_hours = 0;
$shift3_hours = 0; $shift0_hours = 0;
$time = strtotime($record['in_time']);
$time_out = strtotime('-1 Minute',strtotime($record['out_time']));
while($time <= $time_out) {
$mysql_time = date('G:i:s',$time);
//SELECT SHIFT CODE THAT APPLIES TO CURRENT PIT//
$query = "SELECT shift FROM shift_rules WHERE STR_TO_DATE('{$mysql_time}','%H:%i:%S') BETWEEN start_time_24 AND end_time_24 LIMIT 1";
$current_shift_set = mysqli_query($connection, $query);
if(mysqli_num_rows($current_shift_set) == 1) {
$current_shift = mysqli_fetch_assoc($current_shift_set);
if($current_shift['shift'] == '1'){$shift1_hours++;}
elseif($current_shift['shift'] == '2'){$shift2_hours++;}
elseif($current_shift['shift'] == '3'){$shift3_hours++;}
else{$shift0_hours++;}
} else {
$shift0_hours++;
}
//INCRIMENT TIME BY 1 MINUTE//
$time = strtotime("+1 minute",$time);
}
$shift1_hours = $shift1_hours/60;
$shift2_hours = $shift2_hours/60;
$shift3_hours = $shift3_hours/60;
$shift0_hours = $shift0_hours/60;
//UPDATE TIMECARD ROWS WITH SHIFT HOURS//
$query = "UPDATE source_filtered_timecard
SET shift1_time = {$shift1_hours},
shift2_time = {$shift2_hours},
shift3_time = {$shift3_hours},
shift0_time = {$shift0_hours}
WHERE id = '{$record['id']}'";
$update = mysqli_query($connection, $query);
}
I'd do this in PHP. Looking at Joe's example, it is initially tempting to try to work out how his data maps onto the shift rules. However, I think it would be a neater solution to do it the other way around i.e. map the rules onto his data, until there is no data to classify.
The algorithm might go a bit like this:
Joe's remaining time is 6:45 - 13:45
Let's map the first rule onto it (i.e. how much of this rule contributes to that range?):
shift 1 = 7:00 - 15:00 (6:45 hours)
Now Joe's remaining time is:
6:45 - 7:00
Do the next rule:
shift 2 = 15:00 - 23:00 (0 hours)
Joe's remaining time is therefore unchanged. And finally the last rule:
shift 3 = 23:00 - 1d7:00 (0:15 hours)
There are a few things to note:
The amount of worked time could be stored in an array (a "worked time set"). It starts off as a simple start and end, but if a rule removes a chunk of time from the middle, it may split into two starts and two ends
When applying a rule, convert them to actual timestamps (i.e. a date and a time) so the wrapping to the next day works correctly
Write a function that takes a worked time set, plus a rule start and end timestamp, modifies a worked time set, and returns a number of hours for the rule
First you need to add day column for differentiate time from 23:59:59 to next day time.
id| shift_name | time_start | time_end | day
1 | Day Shift | '07:00:00' | '18:59:59' | 1
2 | Night Shift | '19:00:00' | '06:59:59' | 2
Procedure :
DELIMITER $$ CREATE PROCEDURE sp_check_shift(IN intime time) PROC: begin IF(intime>='00:00:01' AND intime<='23:59:59') THEN IF ( SELECT 1 FROM tbl_shift WHERE time_start<=intime AND time_end>=intime AND day=1) THEN SELECT shift_name FROM tbl_shift WHERE time_start<=intime AND time_end>=intime AND day=1;ELSEIF ( SELECT 1 FROM tbl_shift WHERE time_start<=intime AND day=2) THEN SELECT shift_name FROM tbl_shift WHERE time_start<=intime AND day=2;ELSEIF ( SELECT 1 FROM tbl_shift WHERE time_end>=intime AND day=2) THEN SELECT shift_name FROM tbl_shift WHERE time_end>=intime AND day=2;END IF;ELSE SELECT 'Invalid Time' shift_name;END IF;END$$ delimiter ;