I currently have quite a messy query, which joins data from multiple tables involving two subqueries. I now have a requirement to group this data by DAY(), WEEK(), MONTH(), and QUARTER().
I have three tables: days, qos and employees. An employee is self-explanatory, a day is a summary of an employee's performance on a given day, and qos is a random quality inspection, which can be performed many times a day.
At the moment, I am selecting all employees, and LEFT JOINing day and qos, which works well. However, now, I need to group the data in order to breakdown a team or individual's performance over a date range.
Taking this data:
Employee
id | name
------------------
1 | Bob Smith
Day
id | employee_id | day_date | calls_taken
---------------------------------------------
1 | 1 | 2011-03-01 | 41
2 | 1 | 2011-03-02 | 24
3 | 1 | 2011-04-01 | 35
Qos
id | employee_id | qos_date | score
----------------------------------------
1 | 1 | 2011-03-03 | 85
2 | 1 | 2011-03-03 | 95
3 | 1 | 2011-04-01 | 91
If I were to start by grouping by DAY(), I would need to see the following results:
Day__date | Day__Employee__id | Day__calls | Day__qos_score
------------------------------------------------------------
2011-03-01 | 1 | 41 | NULL
2011-03-02 | 1 | 24 | NULL
2011-03-03 | 1 | NULL | 90
2011-04-01 | 1 | 35 | 91
As you see, Day__calls should be SUM(calls_taken) and Day__qos_score is AVG(score). I've tried using a similar method as above, but as the date isn't known until one of the tables has been joined, its only displaying a record where there's a day saved.
Is there any way of doing this, or am I going about things the wrong way?
Edit: As requested, here's what I've come up with so far. However, it only shows dates where there's a day.
SELECT COALESCE(`day`.day_date, qos.qos_date) AS Day__date,
employee.id AS Day__Employee__id,
`day`.calls_taken AS Day__Day__calls,
qos.score AS Day__Qos__score
FROM faults_employees `employee`
LEFT JOIN (SELECT `day`.employee_id AS employee_id,
SUM(`day`.calls_taken) AS `calls_in`,
FROM faults_days AS `day`
WHERE employee.id = 7
GROUP BY (`day`.day_date)
) AS `day`
ON `day`.employee_id = `employee`.id
LEFT JOIN (SELECT `qos`.employee_id AS employee_id,
AVG(qos.score) AS `score`
FROM faults_qos qos
WHERE employee.id = 7
GROUP BY (qos.qos_date)
) AS `qos`
ON `qos`.employee_id = `employee`.id AND `qos`.qos_date = `day`.day_date
WHERE employee.id = 7
GROUP BY Day__date
ORDER BY `day`.day_date ASC
The solution I'm comming up with looks like:
SELECT
`date`,
`employee_id`,
SUM(`union`.`calls_taken`) AS `calls_taken`,
AVG(`union`.`score`) AS `score`
FROM ( -- select from union table
(SELECT -- first select all calls taken, leaving qos_score null
`day`.`day_date` AS `date`,
`day`.`employee_id`,
`day`.`calls_taken`,
NULL AS `score`
FROM `employee`
LEFT JOIN
`day`
ON `day`.`employee_id` = `employee`.`id`
)
UNION -- union both tables
(
SELECT -- now select qos score, leaving calls taken null
`qos`.`qos_date` AS `date`,
`qos`.`employee_id`,
NULL AS `calls_taken`,
`qos`.`score`
FROM `employee`
LEFT JOIN
`qos`
ON `qos`.`employee_id` = `employee`.`id`
)
) `union`
GROUP BY `union`.`date` -- group union table by date
For the UNION to work, we have to set the qos_score field in the day table and the calls_taken field in the qos table to null. If we don't, both calls_taken and score would be selected into the same column by the UNION statement.
After this, I selected the required fields with the aggregation functions SUM() and AVG() from the union'd table, grouping by the date field in the union table.
Related
Trying to select last row each day.
This is my (simplified, more records in actual table) table:
+-----+-----------------------+------+
| id | datetime | temp |
+-----+-----------------------+------+
| 9 | 2017-06-05 23:55:00 | 9.5 |
| 8 | 2017-06-05 23:50:00 | 9.6 |
| 7 | 2017-06-05 23:45:00 | 9.3 |
| 6 | 2017-06-04 23:55:00 | 9.4 |
| 5 | 2017-06-04 23:50:00 | 9.2 |
| 4 | 2017-06-05 23:45:00 | 9.1 |
| 3 | 2017-06-03 23:55:00 | 9.8 |
| 2 | 2017-06-03 23:50:00 | 9.7 |
| 1 | 2017-06-03 23:45:00 | 9.6 |
+-----+-----------------------+------+
I want to select row with id = 9, id = 6 and id = 3.
I have tried this query:
SELECT MAX(datetime) Stamp
, temp
FROM weatherdata
GROUP
BY YEAR(DateTime)
, MONTH(DateTime)
, DAY(DateTime)
order
by datetime desc
limit 10;
But datetime and temp does not match.
Kind Regards
Here's one way, which gets the MAX date per day and then uses it in the INNER query to get the other fields:
SELECT *
FROM test
WHERE `datetime` IN (
SELECT MAX(`datetime`)
FROM test
GROUP BY DATE(`datetime`)
);
Here's the SQL Fiddle.
If your rows are always inserted and never updated, and if id is an autoincrementing primary key, then
SELECT w.*
FROM weatherdata w
JOIN ( SELECT MAX(id) id
FROM weatherdata
GROUP BY DATE(datetime)
) last ON w.id = last.id
will get you what you want. Why? The inner query returns the largest (meaning most recent) id value for each date in weatherdata. This can be very fast indeed, especially if you put an index on the datetime column.
But it's possible the conditions for this to work don't hold. If your datetime column sometimes gets updated to change the date, it's possible that larger id values don't always imply larger datetime values.
In that case you need something like this.
SELECT w.*
FROM weatherdata w
JOIN ( SELECT MAX(datetime) datetime
FROM weatherdata
GROUP BY DATE(datetime)
) last ON w.datetime = last.datetime
Your query doesn't work because it misuses the nasty nonstandard extension to MySQL GROUP BY. Read this: https://dev.mysql.com/doc/refman/5.7/en/group-by-handling.html
It should, properly, use the ANY_VALUE() function to highlight the unpredictability of the results. It shoud read ....
SELECT MAX(datetime) Stamp, ANY_VALUE(temp) temp
which means you aren't guaranteed the right row's temp value. Rather, it can return the temp value from any row in each day's grouping.
With a table of dates, I'm trying to count different columns based on weeks.
I manage to do it with one column, and it works fine. But when I'm counting multiple columns I get either wrong or duplicated results. I think it's because of the join.
This works for one column as expected:
SELECT
DATE_FORMAT(thedate, '%u') as week
,COUNT(t.completed_date) as completed
FROM datetable
LEFT JOIN projects t ON t.completed_date = thedate
WHERE thedate BETWEEN YEAR(NOW()) AND NOW()
GROUP BY YEARWEEK(thedate,7)
By adding ,COUNT(t.sales_date) as sales to the select, I will get duplicated counts for completed and sales.
Based to this sample (projects)
| id | completed_date | sales_date |
| 1 | NULL | NULL |
| 2 | NULL | 2013-08-26 |
| 3 | NULL | 2013-08-28 |
| 4 | 2013-09-06 | NULL |
I'm looking for
| week | completed | sales |
| 34 | 0 | 0 |
| 35 | 0 | 2 |
| 36 | 1 | 0 |
I'm using a datetable because I need all dates with 0 when there's no dates.
I think I could solve it by subqueries, but there's 12 other date fields i need to count in this query as well (excluded from the sample).
Is there a better way of solving this than by using lots of subqueries? My SQL is a bit rusty.
One way is to use subqueries that group each value by week, then join them all together.
SELECT d.week, completed, sales
FROM (SELECT YEARWEEK(thedate) week
FROM datetable
WHERE thedate BETWEEN YEAR(NOW()) AND NOW()
GROUP BY week) d
LEFT JOIN (SELECT YEARWEEK(completed_date) week, COUNT(*) completed
FROM projects
WHERE completed_date BETWEEN YEAR(NOW()) AND NOW()
GROUP BY week) c
ON c.week = d.week
LEFT JOIN (SELECT YEARWEEK(sales_date) week, COUNT(*) sales
FROM projects
WHERE sales_date BETWEEN YEAR(NOW()) AND NOW()
GROUP BY week) s
ON s.week = d.week
This way is more easily extended to additional columns:
SELECT DATE_FORMAT(thedate, '%u') AS week,
IFNULL(SUM(completed_date = thedate), 0) AS completed,
IFNULL(SUM(sales_date = thedate), 0) AS sales
FROM datetable
LEFT JOIN projects
ON thedate IN (completed_date, sales_date)
WHERE thedate BETWEEN YEAR(NOW()) AND NOW()
GROUP BY week
I am struggling in to get result from mysql in the following way. I have 10 records in mysql db table having date and unit fields. I need to get used units on every date.
Table structure as follows, adding today unit with past previous unit in every record:
Date Units
---------- ---------
10/10/2012 101
11/10/2012 111
12/10/2012 121
13/10/2012 140
14/10/2012 150
15/10/2012 155
16/10/2012 170
17/10/2012 180
18/10/2012 185
19/10/2012 200
Desired output will be :
Date Units
---------- ---------
10/10/2012 101
11/10/2012 10
12/10/2012 10
13/10/2012 19
14/10/2012 10
15/10/2012 5
16/10/2012 15
17/10/2012 10
18/10/2012 5
19/10/2012 15
Any help will be appreciated. Thanks
There's a couple of ways to get the resultset. If you can live with an extra column in the resultset, and the order of the columns, then something like this is a workable approach.
using user variables
SELECT d.Date
, IF(#prev_units IS NULL
,#diff := 0
,#diff := d.units - #prev_units
) AS `Units_used`
, #prev_units := d.units AS `Units`
FROM ( SELECT #prev_units := NULL ) i
JOIN (
SELECT t.Date, t.Units
FROM mytable t
ORDER BY t.Date, t.Units
) d
This returns the specified resultset, but it includes the Units column as well. It's possible to have that column filtered out, but it's more expensive, because of the way MySQL processes an inline view (MySQL calls it a "derived table")
To remove that extra column, you can wrap that in another query...
SELECT f.Date
, f.Units_used
FROM (
query from above goes here
) f
ORDER BY f.Date
but again, removing that column comes with the extra cost of materializing that result set a second time.
using a semi-join
If you are guaranteed to have a single row for each Date value, either stored as a DATE, or as a DATETIME with the timecomponent set to a constant, such as midnight, and no gaps in the Date value, and Date is defined as DATE or DATETIME datatype, then another query that will return the specifid result set:
SELECT t.Date
, t.Units - s.Units AS Units_Used
FROM mytable t
LEFT
JOIN mytable s
ON s.Date = t.Date + INTERVAL -1 DAY
ORDER BY t.Date
If there's a missing Date value (a gap) such that there is no matching previous row, then Units_used will have a NULL value.
using a correlated subquery
If you don't have a guarantee of no "missing dates", but you have a guarantee that there is no more than one row for a particular Date, then another approach (usually more expensive in terms of performance) is to use a correlated subquery:
SELECT t.Date
, ( t.Units - (SELECT s.Units
FROM mytable s
WHERE s.Date < t.Date
ORDER BY s.Date DESC
LIMIT 1)
) AS Units_used
FROM mytable t
ORDER BY t.Date, t.Units
spencer7593's solution will be faster, but you can also do something like this...
SELECT * FROM rolling;
+----+-------+
| id | units |
+----+-------+
| 1 | 101 |
| 2 | 111 |
| 3 | 121 |
| 4 | 140 |
| 5 | 150 |
| 6 | 155 |
| 7 | 170 |
| 8 | 180 |
| 9 | 185 |
| 10 | 200 |
+----+-------+
SELECT a.id,COALESCE(a.units - b.units,a.units) units
FROM
( SELECT x.*
, COUNT(*) rank
FROM rolling x
JOIN rolling y
ON y.id <= x.id
GROUP
BY x.id
) a
LEFT
JOIN
( SELECT x.*
, COUNT(*) rank
FROM rolling x
JOIN rolling y
ON y.id <= x.id
GROUP
BY x.id
) b
ON b.rank= a.rank -1;
+----+-------+
| id | units |
+----+-------+
| 1 | 101 |
| 2 | 10 |
| 3 | 10 |
| 4 | 19 |
| 5 | 10 |
| 6 | 5 |
| 7 | 15 |
| 8 | 10 |
| 9 | 5 |
| 10 | 15 |
+----+-------+
This should give the desired result. I don't know how your table is called so I named it "tbltest".
Naming a table date is generally a bad idea as it also refers to other things (functions, data types,...) so I renamed it "fdate". Using uppercase characters in field names or tablenames is also a bad idea as it makes your statements less database independent (some databases are case sensitive and some are not).
SELECT
A.fdate,
A.units - coalesce(B.units, 0) AS units
FROM
tbltest A left join tbltest B ON A.fdate = B.fdate + INTERVAL 1 DAY
All right, so here's a challenge for all you SQL pros:
I have a table with two columns of interest, group and birthdate. Only some rows have a group assigned to them.
I now want to print all rows sorted by birthdate, but I also want all rows with the same group to end up next to each other. The only semi-sensible way of doing this would be to use the groups' average birthdates for all the rows in the group when sorting. The question is, can this be done with pure SQL (MySQL in this instance), or will some scripting logic be required?
To illustrate, with the given table:
id | group | birthdate
---+-------+-----------
1 | 1 | 1989-12-07
2 | NULL | 1990-03-14
3 | 1 | 1987-05-25
4 | NULL | 1985-09-29
5 | NULL | 1988-11-11
and let's say that the "average" of 1987-05-25 and 1989-12-07 is 1988-08-30 (this can be found by averaging the UNIX timestamp equivalents of the dates and then converting back to a date. This average doesn't have to be completely correct!).
The output should then be:
id | group | birthdate | [sort_by_birthdate]
---+-------+------------+--------------------
4 | NULL | 1985-09-29 | 1985-09-29
3 | 1 | 1987-05-25 | 1988-08-30
1 | 1 | 1989-12-07 | 1988-08-30
5 | NULL | 1988-11-11 | 1988-11-11
2 | NULL | 1990-03-14 | 1990-03-14
Any ideas?
Cheers,
Jon
I normally program in T-SQL, so please forgive me if I don't translate the date functions perfectly to MySQL:
SELECT
T.id,
T.group
FROM
Some_Table T
LEFT OUTER JOIN (
SELECT
group,
'1970-01-01' +
INTERVAL AVG(DATEDIFF('1970-01-01', birthdate)) DAY AS avg_birthdate
FROM
Some_Table T2
GROUP BY
group
) SQ ON SQ.group = T.group
ORDER BY
COALESCE(SQ.avg_birthdate, T.birthdate),
T.group
I have a database table which holds each user's checkins in cities. I need to know how many days a user has been in a city, and then, how many visits a user has made to a city (a visit consists of consecutive days spent in a city).
So, consider I have the following table (simplified, containing only the DATETIMEs - same user and city):
datetime
-------------------
2011-06-30 12:11:46
2011-07-01 13:16:34
2011-07-01 15:22:45
2011-07-01 22:35:00
2011-07-02 13:45:12
2011-08-01 00:11:45
2011-08-05 17:14:34
2011-08-05 18:11:46
2011-08-06 20:22:12
The number of days this user has been to this city would be 6 (30.06, 01.07, 02.07, 01.08, 05.08, 06.08).
I thought of doing this using SELECT COUNT(id) FROM table GROUP BY DATE(datetime)
Then, for the number of visits this user has made to this city, the query should return 3 (30.06-02.07, 01.08, 05.08-06.08).
The problem is that I have no idea how shall I build this query.
Any help would be highly appreciated!
You can find the first day of each visit by finding checkins where there was no checkin the day before.
select count(distinct date(start_of_visit.datetime))
from checkin start_of_visit
left join checkin previous_day
on start_of_visit.user = previous_day.user
and start_of_visit.city = previous_day.city
and date(start_of_visit.datetime) - interval 1 day = date(previous_day.datetime)
where previous_day.id is null
There are several important parts to this query.
First, each checkin is joined to any checkin from the previous day. But since it's an outer join, if there was no checkin the previous day the right side of the join will have NULL results. The WHERE filtering happens after the join, so it keeps only those checkins from the left side where there are none from the right side. LEFT OUTER JOIN/WHERE IS NULL is really handy for finding where things aren't.
Then it counts distinct checkin dates to make sure it doesn't double-count if the user checked in multiple times on the first day of the visit. (I actually added that part on edit, when I spotted the possible error.)
Edit: I just re-read your proposed query for the first question. Your query would get you the number of checkins on a given date, instead of a count of dates. I think you want something like this instead:
select count(distinct date(datetime))
from checkin
where user='some user' and city='some city'
Try to apply this code to your task -
CREATE TABLE visits(
user_id INT(11) NOT NULL,
dt DATETIME DEFAULT NULL
);
INSERT INTO visits VALUES
(1, '2011-06-30 12:11:46'),
(1, '2011-07-01 13:16:34'),
(1, '2011-07-01 15:22:45'),
(1, '2011-07-01 22:35:00'),
(1, '2011-07-02 13:45:12'),
(1, '2011-08-01 00:11:45'),
(1, '2011-08-05 17:14:34'),
(1, '2011-08-05 18:11:46'),
(1, '2011-08-06 20:22:12'),
(2, '2011-08-30 16:13:34'),
(2, '2011-08-31 16:13:41');
SET #i = 0;
SET #last_dt = NULL;
SET #last_user = NULL;
SELECT v.user_id,
COUNT(DISTINCT(DATE(dt))) number_of_days,
MAX(days) number_of_visits
FROM
(SELECT user_id, dt
#i := IF(#last_user IS NULL OR #last_user <> user_id, 1, IF(#last_dt IS NULL OR (DATE(dt) - INTERVAL 1 DAY) > DATE(#last_dt), #i + 1, #i)) AS days,
#last_dt := DATE(dt),
#last_user := user_id
FROM
visits
ORDER BY
user_id, dt
) v
GROUP BY
v.user_id;
----------------
Output:
+---------+----------------+------------------+
| user_id | number_of_days | number_of_visits |
+---------+----------------+------------------+
| 1 | 6 | 3 |
| 2 | 2 | 1 |
+---------+----------------+------------------+
Explanation:
To understand how it works let's check the subquery, here it is.
SET #i = 0;
SET #last_dt = NULL;
SET #last_user = NULL;
SELECT user_id, dt,
#i := IF(#last_user IS NULL OR #last_user <> user_id, 1, IF(#last_dt IS NULL OR (DATE(dt) - INTERVAL 1 DAY) > DATE(#last_dt), #i + 1, #i)) AS
days,
#last_dt := DATE(dt) lt,
#last_user := user_id lu
FROM
visits
ORDER BY
user_id, dt;
As you see the query returns all rows and performs ranking for the number of visits. This is known ranking method based on variables, note that rows are ordered by user and date fields. This query calculates user visits, and outputs next data set where days column provides rank for the number of visits -
+---------+---------------------+------+------------+----+
| user_id | dt | days | lt | lu |
+---------+---------------------+------+------------+----+
| 1 | 2011-06-30 12:11:46 | 1 | 2011-06-30 | 1 |
| 1 | 2011-07-01 13:16:34 | 1 | 2011-07-01 | 1 |
| 1 | 2011-07-01 15:22:45 | 1 | 2011-07-01 | 1 |
| 1 | 2011-07-01 22:35:00 | 1 | 2011-07-01 | 1 |
| 1 | 2011-07-02 13:45:12 | 1 | 2011-07-02 | 1 |
| 1 | 2011-08-01 00:11:45 | 2 | 2011-08-01 | 1 |
| 1 | 2011-08-05 17:14:34 | 3 | 2011-08-05 | 1 |
| 1 | 2011-08-05 18:11:46 | 3 | 2011-08-05 | 1 |
| 1 | 2011-08-06 20:22:12 | 3 | 2011-08-06 | 1 |
| 2 | 2011-08-30 16:13:34 | 1 | 2011-08-30 | 2 |
| 2 | 2011-08-31 16:13:41 | 1 | 2011-08-31 | 2 |
+---------+---------------------+------+------------+----+
Then we group this data set by user and use aggregate functions:
'COUNT(DISTINCT(DATE(dt)))' - counts the number of days
'MAX(days)' - the number of visits, it is a maximum value for the days field from our subquery.
That is all;)
As data sample provided by Devart, the inner "PreQuery" works with sql variables. By defaulting the #LUser to a -1 (probable non-existent user ID), the IF() test checks for any difference between last user and current. As soon as a new user, it gets a value of 1... Additionally, if the last date is more than 1 day from the new date of check-in, it gets a value of 1. Then, the subsequent columns reset the #LUser and #LDate to the value of the incoming record just tested against for the next cycle. Then, the outer query just sums them up and counts them for the final correct results per the Devart data set of
User ID Distinct Visits Total Days
1 3 9
2 1 2
select PreQuery.User_ID,
sum( PreQuery.NextVisit ) as DistinctVisits,
count(*) as TotalDays
from
( select v.user_id,
if( #LUser <> v.User_ID OR #LDate < ( date( v.dt ) - Interval 1 day ), 1, 0 ) as NextVisit,
#LUser := v.user_id,
#LDate := date( v.dt )
from
Visits v,
( select #LUser := -1, #LDate := date(now()) ) AtVars
order by
v.user_id,
v.dt ) PreQuery
group by
PreQuery.User_ID
for a first sub-task:
select count(*)
from (
select TO_DAYS(p.d)
from p
group by TO_DAYS(p.d)
) t
I think you should consider changing database structure. You could add table visits and visit_id into your checkins table. Each time you want to register new checkin you check if there is any checkin a day back. If yes then you add a new checkin with visit_id from yesterday's checkin. If not then you add new visit to visits and new checkin with new visit_id.
Then you could get you data in one query with something like that:
SELECT COUNT(id) AS number_of_days, COUNT(DISTINCT visit_id) number_of_visits FROM checkin GROUP BY user, city
It's not very optimal but still better than doing anything with current structure and it will work. Also if results can be separate queries it will work very fast.
But of course drawbacks are you will need to change database structure, do some more scripting and convert current data to new structure (i.e. you will need to add visit_id to current data).