How do you display the latest data for a particular month?
For example I have data like this
date data
2003-04-18 | 12
2003-04-25 | 14
2003-05-16 | 51
2003-05-23 | 21
2003-05-30 | 22
2003-06-06 | 11
2003-06-27 | 14
I want to display data
date data
2003-04-25 | 14
2003-05-30 | 22
2003-06-27 | 14
What kind of example query is used?
i try this query, but showing all data
SELECT tgl_hargaemas, harga FROM tbl_hargaemas
WHERE tgl_hargaemas >= '2003-01-03' - INTERVAL DAYOFMONTH('2018-01-03') MONTH
Use a simple GROUP BY sub query to find the max date for each year-month followed by an INNER JOIN:
SELECT t.*
FROM (
SELECT MAX(date) AS maxdate
FROM t
GROUP BY YEAR(date), MONTH(date)
) AS g
INNER JOIN t ON g.maxdate = t.date
Demo on DB<>Fiddle
Related
I have a table with the following data (merely an example, actual table has 600,000 rows) (aid = access id [primary key] and id = user id [foreign key]):
aid | id | date
332 | 1 | 2016-12-15
331 | 4 | 2016-12-15
330 | 3 | 2016-12-15
329 | 1 | 2016-12-14
328 | 1 | 2016-12-14
327 | 2 | 2016-12-14
326 | 3 | 2016-12-13
325 | 2 | 2016-12-13
324 | 1 | 2016-12-13
323 | 1 | 2016-12-12
322 | 3 | 2016-12-12
321 | 1 | 2016-12-12
Each id is a users primary key, and every time they access something in my system I log them in this table (with the date in the format as shown, and their id). A user can be logged multiple times a day.
I'm looking to: return the total number of times the thing has been accessed in a day and return the total number of NEW users who have accessed the thing in a day, for the last 8 days (something will always be logged each day, so using "LIMIT 8" is fine for getting only the last 8 days).
My SQL currently looks like:
SELECT COUNT(id), COUNT(distinct id), date
FROM table
GROUP BY date
ORDER BY date DESC
LIMIT 8;
That SQL does the first part correctly, but I can't figure out how to get it to return the number of users who have never accessed the thing until that day.
Desired results would be, the one "newuser" represents the user with id "4" as they have never accessed the thing before:
COUNT(id) | newusers | date
3 | 1 | 2016-12-15
3 | 0 | 2016-12-14
3 | 0 | 2016-12-13
3 | 0 | 2016-12-12
Sorry if I didn't explain this clear enough.
To get new users you want the first day an id appeared:
select id, min(date)
from t
group by id;
The rest is just a join and group by:
select d.date, cnt, count(dd.id) as newusers
from (select date, count(*) as cnt
from t
group by date
) d left join
(select id, min(date) as mindate
from t
group by id
) dd
on d.date = dd.mindate
group by d.date, d.cnt
limit 8;
To get the number of new users you need to compare them to a set of ids over the past 8 days
My MySQL is a bit rusty, so you might have to correct the syntax.
SELECT COUNT(id)
FROM table
WHERE id NOT IN (
SELECT DISTINCT id
FROM table
WHERE date BETWEEN DATE(DATE_SUB(NOW(), INTERVAL 8 DAY)) AND DATE(DATE_SUB(NOW(), INTERVAL 1 DAY))
)
I'll leave it as a task for you to combine it with your other query ;)
Hi if your date column in database is datetime/date or other date representing format you can do something like this:
for getting all users who accessed something in 8 days:
Select id, date from table
where date BETWEEN DATE_ADD(NOW(), INTERVAL -9 DAY) AND NOW()
I think, you can do whatever grouping you want on that.
To get new users, you can either go with self join or with sub select
selfjoin:
select t.id, t.date from table as t
LEFT join table as t2
ON t.id = t2.id
AND t.date BETWEEN DATE_ADD(NOW(), INTERVAL -1 DAY) AND NOW()
AND t2.date NOT BETWEEN DATE_ADD(NOW(), INTERVAL -9 DAY) AND NOW()
WHERE t2.id IS NULL
i used left join to match all access from users and then in where excluded those rows. However self joins are slow, and even slower with LEFT join
subselect:
select id, date from table
where date BETWEEN DATE_ADD(NOW(), INTERVAL -1 DAY) AND NOW()
AND id NOT IN (
SELECT id FROM table
WHERE date BETWEEN DATE_ADD(NOW(), INTERVAL -2 DAY) AND DATE_ADD(NOW(), INTERVAL -1 DAY)
)
I know those betweens with date_adds are not exactly nice looking, but i hope it will help you more than grouping dates
I would suggest using date with time for more information, but its entirely up to meaning of yours data
I'm aware that there are several answers on SO about cumulative totals. I have experimented and have not found a solution to my problem.
Here is a sqlfiddle.
We have a contacts table with two fields, eid and create_time:
eid create_time
991772 April, 21 2016 11:34:21
989628 April, 17 2016 02:19:57
985557 April, 04 2016 09:56:39
981920 March, 30 2016 11:03:12
981111 March, 30 2016 09:36:48
I would like to select the number of new contacts in each month along with the size of our contacts database at the end of each month. New contacts by year and month is simple enough. For the size of the contacts table at the end of each month I did some research and found what looked to be a straight forwards method:
set #csum = 0;
select
year(c.create_time) as yr,
month(c.create_time) as mth,
count(c.eid) as new_contacts,
(#csum + count(c.eid)) as cumulative_contacts
from
contacts c
group by
yr,
mth
That runs but gives me unexpected results.
If I run:
select count(*) from contacts where date(create_time) < current_date
I get the total number of records in the table 146.
I therefore expected the final row in my query using #csum to have 146 for April 2016. It has only 3?
What my goal is for field cumulative_contacts:
For the record with e.g. January 2016.
select count(*) from contacts where date(create_time) < '2016-02-01';
And the record for February would have:
select count(*) from contacts where date(create_time) < '2016-03-01';
And so on
Try this, a bit of modification from your sql;)
CREATE TABLE IF NOT EXISTS `contacts` (
`eid` char(50) DEFAULT NULL,
`create_time` timestamp NULL DEFAULT NULL
) ENGINE=InnoDB DEFAULT CHARSET=utf8 ROW_FORMAT=COMPACT;
INSERT INTO `contacts` (`eid`, `create_time`) VALUES
('991772', '2016-04-21 11:34:21'),
('989628', '2016-04-17 02:19:57'),
('985557', '2016-04-04 09:56:39'),
('981920', '2016-03-30 11:03:12'),
('981111', '2016-03-30 09:36:48');
SET #csum = 0;
SELECT t.*, #csum:=(#csum + new_contacts) AS cumulative_contacts
FROM (
SELECT YEAR(c.create_time) AS yr, MONTH(c.create_time) AS mth, COUNT(c.eid) AS new_contacts
FROM contacts c
GROUP BY yr, mth) t
Output results is
| yr | mth | new_contacts | cumulative_contacts |
------ ----- -------------- ---------------------
| 2016 | 3 | 2 | 2 |
| 2016 | 4 | 3 | 5 |
This sql will get the cumulative sum and is pretty efficient. It numbers each row first and then uses that as the cumulative sum.
SELECT s1.yr, s1.mth, s1.new_contacts, s2.cummulative_contacts
FROM
(SELECT
YEAR(create_time) AS yr,
MONTH(create_time) AS mth,
COUNT(eid) AS new_contacts,
MAX(eid) AS max_eid
FROM
contacts
GROUP BY
yr,
mth
ORDER BY create_time) s1 INNER JOIN
(SELECT eid, (#sum:=#sum+1) AS cummulative_contacts
FROM
contacts INNER JOIN
(SELECT #sum := 0) r
ORDER BY create_time) s2 ON max_eid=s2.eid;
--Result sample--
| yr | mth | new_contacts | cumulative_contacts |
|------|-----|--------------|---------------------|
| 2016 | 1 | 4 | 132 |
| 2016 | 2 | 4 | 136 |
| 2016 | 3 | 7 | 143 |
| 2016 | 4 | 3 | 146 |
Try this: fiddele
Here you have a "greater than or equal" join, so each group "contains" all previous values. Times 12 part, converts the hole comparation to months. I did offer this solution as it is not MySql dependant. (can be implemented on many other DBs with minimun or no changes)
select dates.yr, dates.mth, dates.new_contacts, sum(NC.new_contacts) as cumulative_new_contacts
from (
select
year(c.create_time) as yr,
month(c.create_time) as mth,
count(c.eid) as new_contacts
from
contacts c
group by
year(c.create_time),
month(c.create_time)
) as dates
left join
(
select
year(c.create_time) as yr,
month(c.create_time) as mth,
count(c.eid) as new_contacts
from
contacts c
group by
year(c.create_time),
month(c.create_time)
) as NC
on dates.yr*12+dates.mth >= NC.yr*12+NC.mth
group by
dates.yr,
dates.mth,
dates.new_contacts -- not needed by MySql, present here for other DBs compatibility
order by 1,2
I have the following table
customerID | orderID | orderDate
----------------------------------
1 | 67 | 2015-12-15
1 | 66 | 2015-10-20
1 | 65 | 2015-1-7
2 | 64 | 2014-9-6
2 | 63 | 2014-7-8
3 | 62 | 2015-1-15
I need to identify all the customerIDs that have at least 3 distinct orderIDs within a 12 month period in 2014 and 2015
Hmmm. You could do something like this:
select distinct customerId
from t
where 3 <= (select count(*)
from t t2
where t2.customerId = t.customerId and
t2.date >= t.date and
t2.date < date_add(t.date, interval 12 month)
);
An index on (customerId, date) would help performance. And, you might need count(distinct OrderId) in the subquery, but that doesn't seem necessary given your sample data.
Try this:
SELECT customerID, order_count FROM (SELECT customerID, COUNT(DISTINCT orderID) AS
order_count WHERE YEAR(orderDate) = 2014 GROUP BY customerID) AS
table_orders WHERE order_count >= 3
You could change first WHERE clausule in order to change date range, i suggest you a approach counting in all 2014 year
This is my table named period.
id | year | month
222 | 2014 | 2
345 | 2013 | 5
33 | 2014 | 1
224 | 2014 | 2
I want get only id what have latest month (2014-02). Result should be 222, 224.
I wrote following query.
SELECT id, MAX(year*100 + month) FROM period
But it is returning following result.
222| 201402
How can i get my result
SELECT x.*
FROM period x
JOIN
( SELECT year
, month
FROM period
ORDER
BY year DESC
, month DESC
LIMIT 1
) y
ON y.year = x.year
AND y.month = x.month;
You should you the following query:---
SELECT id FROM period where year=(SELECT max(year) from period) and month=(SELECT max(month) from period);
I have 2 tables, SVISE and OVERW
Inside OVERW I have some scores with person ids and the date of that score.
E.g
p_id degrees mo_date
5 10.2 2013-10-09
5 9.85 2013-03-10
8 14.75 2013-04-25
8 11.00 2013-02-22
5 5.45 2013-08-11
5 6.2 2013-06-10
SVISE.ofh field must be updated with the sum of the last three records
(for a specific person, ordered by date descending), so for person with id 5, the sum would result from the rows
5 10.2 2013-10-09
5 5.45 2013-08-11
5 6.2 2013-06-10
sum=21.85.
Desired final result on SVISE, based on the values above:
HID OFH START
5 21.85 October, 16 2013 ##(10.2 + 5.45 + 6.2)
5 21.5 September, 07 2013 ##(5.45 + 6.2 + 9.85)
5 0 March, 05 2013 ##(no rows)
8 25.75 October, 14 2013 ##(14.75 + 11)
3 0 October, 14 2013 ##(no rows)
5 0 March, 05 2012 ##(no rows)
OFHwas 0 initially
I can get the total sum for a specific person, but I can't use limit to get the last 3 rows. It gets ignored.
This is the query I use to retrieve the sum of all degrees per person for a given date:
UPDATE SVISE SV
SET
SV.ofh=(SELECT sum(degrees) FROM OVERW WHERE p_id =SV.hid
AND date(mo_date)<date(SV.start)
AND year(mo_date)=year(SV.start))
I cannot just use limit with sum:
UPDATE SVISE SV
SET
SV.ofh=(SELECT sum(degrees) FROM OVERW WHERE p_id =SV.hid
AND date(mo_date)<date(SV.start)
AND year(mo_date)=year(SV.start)
ORDER BY mo_date DESC
LIMIT 3)
This does not work.
I have tried with multi-table updates and with nested queries to achieve this.
Every scenario has known limitations that block me from accomplishing the desired result.
Nested queries cant see the parent table. Unknown column 'SV.hid'in 'where clause'
Multi-table update cant be use with limit. Incorrect usage of UPDATE and LIMIT
Any solution will do. There is no need to do it in a single query. If anyone wants to try even with an intermediate table.
An SQL fiddle is also available.
Thanks in advance for your help.
--Update--
Here is the solution from Akash: http://sqlfiddle.com/#!2/4cf1a/1
This should work,
UPDATED to have a join on svice
UPDATE
svice SV
JOIN (
SELECT
hid,
start,
sum(degrees) as degrees
FROM
(
SELECT
*,
IF(#prev_row <> unix_timestamp(start)+P_ID, #row_number:=0,NULL),
#prev_row:=unix_timestamp(start)+P_ID,
#row_number:=#row_number+1 as row_number
FROM
(
SELECT
mo_date,
p_id,
hid,
start,
degrees
FROM
OVERW
JOIN svice sv ON ( p_id = hid
AND date(mo_date)<date(SV.start)
AND year(mo_date)=year(SV.start) )
ORDER BY
hid,
start,
mo_date desc
) sub_query1
JOIN ( select #row_number:=0, #prev_row:=0 ) sub_query2
) sub_query
where
row_number <= 3
GROUP BY
hid,
start
) sub_query ON ( sub_query.hid = sv.hid AND sub_query.start = sv.start )
SET
SV.ofh = sub_query.degrees
Note: Check this with your updated data, the test data provided could not yield the results you expected due to the date conditions
Try
UPDATE svice SV
JOIN (SELECT SUM(degrees)sumdeg,p_id FROM(SELECT DISTINCT degrees,p_id FROM OVERW,svice WHERE OVERW.p_id IN (SELECT svice.hid FROM svice)
AND date(mo_date)<date(svice.start)
AND year(mo_date)=year(svice.start)ORDER BY mo_date DESC )deg group by p_id)bbc
ON bbc.p_id=SV.hid
SET
SV.ofh=bbc.sumdeg where p_id =SV.hid
http://sqlfiddle.com/#!2/95b42/42
Getting closer,now it "only" needs a limit in GROUP BY.
Two assumptions:
You can figure out how to turn this into an update, and
A PK exists on (id,mo_date)
Then you can do this -
SELECT p_id
, SUM(degrees) ttl
FROM
( SELECT x.*
FROM overw x
JOIN overw y
ON y.p_id = x.p_id
AND y.mo_date >= x.mo_date
GROUP
BY p_id
, mo_date HAVING COUNT(*) <= 3
) a
GROUP
BY p_id;
Maybe I'm slow, but let's ignore svice for now.
Can you show the correct result and the working for each row below...
+------+---------+------------+--------+
| p_id | degrees | mo_date | result |
+------+---------+------------+--------+
| 5 | 6.20 | 2013-06-10 | ? |
| 5 | 5.45 | 2013-08-11 | ? |
| 5 | 10.20 | 2013-10-09 | 21.85 | <- = 10.2+5.45+6.2 = 21.85
| 8 | 14.75 | 2013-04-25 | ? |
| 5 | 9.85 | 2013-03-10 | ? |
| 8 | 11.00 | 2013-02-22 | ? |
+------+---------+------------+--------+