In a mysql databse, I have tblA.price and tblB.price. There is no relationship between them.
I want summarize all sales from tableA and tableB. It will be something like that sum(tblA.price)+sum(tblB.price) AS total.
how could I perform that query?
The union that #cjsfj shows would work, and here are a couple of other options:
Do two scalar subqueries and add them together.
select (select sum(price) from tblA) + (select sum(price) from tblB) as total;
Do two queries from your application, get the results of each, and add them together.
Quick and Dirty. Unions aren't great. But if you have a fixed number of tables, this will work. Performance might get tricky, and it's definitely not pretty, but answers your question.
select sum(price) as totalprice from
(select sum(a.price) as price
from a
union all
select sum(b.price) as price
from b) as ab
In order to complement the other answers, I had some issues when there is no result from one of the tables. It was returning null. For that reason I had to filter that result and turn it into 0. Just just did IFNULL(SUM(field),0).
Here is my final query:
SELECT
IFNULL(SUM(tblA.price),0) + (SELECT
IFNULL(SUM(fieldB),0)
FROM
tblB
WHERE
creation_date BETWEEN '$startDT' AND DATE_SUB(NOW(), INTERVAL 1 HOUR) AS amount
FROM
tableA tblA
WHERE
tblA.transaction_date BETWEEN 'startDT' AND DATE_SUB(NOW(),
INTERVAL 1 HOUR)
AND tblA.service_type <> 'service1'
AND tblA.service_type <> 'service2'
AND tblA.service_type <> 'service3';
Related
I have a table that has just two fields - a date field and customer_id. I am looking to count the number of customer ids from each date field to current date. My query below is timing out - seems very inefficient. Is there a better way to do this?
select
t.base_date,
( select
count(distinct customer_id)
from user_base as ub
where ub.base_date >= t.base_date
and ub.base_date <= current_date
) as cts
from user_base as t
Try if this gives you same results not tested but seems the way you extracted data was not the right way of doing:
select base_date, count(distinct customer_id) as cts
from user_base
where base_date between base_date AND current_date
I want to get all records which are not "older" than 20 days. If there are no records within 20 days, I want all records from the most recent day. I'm doing this:
SELECT COUNT(DISTINCT t.id) FROM t
WHERE
(DATEDIFF(NOW(), t.created) <= 20
OR
(date(t.created) >= (SELECT max(date(created)) FROM t)));
This works so far, but it is awful slow. created is a datetime, might be due tue the conversion to a date... Any ideas how to speed this up?
SELECT COUNT(*) FROM (
SELECT * FROM t WHERE datediff(now(),created) between 0 and 20
UNION
SELECT * FROM (SELECT * FROM t WHERE created<now() LIMIT 1) last1
) last20d
I used the between clause just in case there might be dates in the future in the table. These will be excluded. Also you can simplify the select, if you just need the count() to
SELECT COUNT(*) FROM (
SELECT id FROM t WHERE datediff(now(),created) between 0 and 20
UNION
SELECT id FROM (SELECT id FROM t WHERE created<now() LIMIT 1) last1
) last20d
otherwise, in the first select version you can leave out the outer select if you want all the data of the chosen records. The UNION will make sure that duplicates will be excluded (in other cases I always use UNION ALL since it is faster).
Note: I found this similar question but it does not address my issue, so I do not believe this is a duplicate.
I have two simple MySQL tables (created with the MyISAM engine), Table1 and Table2.
Both of the tables have 3 columns, a date-type column, an integer ID column, and a float value column. Both tables have about 3 million records and are very straightforward.
The contents of the tables looks like this (with Date and Id as primary keys):
Date Id Var1
2012-1-27 1 0.1
2012-1-27 2 0.5
2012-2-28 1 0.6
2012-2-28 2 0.7
(assume Var1 becomes Var2 for the second table).
Note that for each (year, month, ID) triplet, there will only be a single entry. But the actual day of the month that appears is not necessarily the final day, nor is it the final weekday, nor is it the final business day, etc... It's just some day of the month. This day is important as an observation day in other tables, but the day-of-month itself doesn't matter between Table1 and Table2.
Because of this, I cannot rely on Date + INTERVAL 1 MONTH to produce the matching day-of-month for the date it should match to that is one month ahead.
I'm looking to join the two tables on Date and Id but where the values from the second table (Var2) come from 1-month ahead than Var1.
This sort of code will accomplish it, but I am noticing a significant performance degradation with this, explained below.
-- This is exceptionally slow for me
SELECT b.Date,
b.Id,
a.Var1,
b.Var2
FROM Table1 a
JOIN Table2 b
ON a.Id = b.Id
AND YEAR(a.Date + INTERVAL 1 MONTH) = YEAR(b.Date)
AND MONTH(a.Date + INTERVAL 1 MONTH) = MONTH(b.Date)
-- This returns quickly, but if I use it as a sub-query
-- then the parent query is very slow.
SELECT Date + INTERVAL 1 MONTH as FutureDate,
Id,
Var1
FROM Table1
-- That is, the above is fast, but this is super slow:
select b.Date,
b.Id,
a.Var1,
b.Var2
FROM (SELECT Date + INTERVAL 1 MONTH as FutureDate
Id,
Var1
FROM Table1) a
JOIN Table2 b
ON YEAR(a.FutureDate) = YEAR(b.Date)
AND MONTH(a.FutureDate) = MONTH(b.Date)
AND a.Id = b.Id
I've tried re-ordering the JOIN criteria, thinking maybe that matching on Id first in the code would change the query execution plan, but it seems to make no difference.
When I say "super slow", I mean that option #1 from the code above doesn't return the results for all 3 million records even if I wait for over an hour. Option #2 returns in less than 10 minutes, but then option number three takes longer than 1 hour again.
I don't understand why the introduction of the date lag makes it take so long.
How can I
profile the queries to understand why it takes a long time?
write a better query for joining tables based on a 1-month date lag (where day-of-month that results from the 1-month lag may cause mismatches).
Here is an alternative approach:
SELECT b.Date, b.Id, b.Var2
(select a.var1
from Table1 a
where a.id = b.id and a.date < b.date
order by a.date
limit 1
) as var1
b.Var2
FROM Table2 b;
Be sure the primary index is set up with id first and then date on Table1. Otherwise, create another index Table1(id, date).
Note that this assumes that the preceding date is for the preceding month.
Here's another alternative way to go about this:
SELECT thismonth.Date,
thismonth.Id,
thismonth.Var1 AS Var1_thismonth,
lastmonth.Var1 AS Var1_lastmonth
FROM Table2 AS thismonth
JOIN
(SELECT id, Var1,
DATE(DATE_FORMAT(Date,'%Y-%m-01')) as MonthStart
FROM Table2
) AS lastmonth
ON ( thismonth.id = lastmonth.id
AND thismonth.Date >= lastmonth.MonthStart + INTERVAL 1 MONTH
AND thismonth.Date < lastmonth.MonthStart + INTERVAL 2 MONTH
)
To get this to perform ideally, I think you're going to need a compound covering index on (id, Date, Var1).
It works by generating a derived table containing Id,MonthStart,Var1 and then joining the original table to it by a sequence of range scans. Hence the compound covering index.
The other answers gave very useful tips, but ultimately, without making significant modifications to the index structure of my data (which is not feasible at the moment), those methods would not work faster (in any meaningful sense) than what I had already tried in the question.
Ollie Jones gave me the idea to use date formatting, and coupling that with the TIMESTAMPDIFF function seems to make it passably fast, though I still welcome any comments explaining why the use of YEAR, MONTH, DATE_FORMAT, and TIMESTAMPDIFF have such wildly different performance properties.
SELECT b.Date,
b.Id,
b.Var2,
a.Date,
a.Id,
a.Var1
FROM Table1 a
JOIN Table2 b
ON a.Id = b.Id
AND (TIMESTAMPDIFF(MONTH,
DATE_FORMAT(a.Date, '%Y-%m-01'),
DATE_FORMAT(b.Date, '%Y-%m-01')) = 1)
I've searched around SO and can't seem to find a question with an answer that works fine for me. I have a table with almost 2 million rows in, and each row has a MySQL Date formatted field.
I'd like to work out (in seconds) how often a row was inserted, so work out the average difference between the dates of all the rows with a SQL query.
Any ideas?
-- EDIT --
Here's what my table looks like
id, name, date (datetime), age, gender
If you want to know how often (on average) a row was inserted, I don't think you need to calculate all the differences. You only need to sum up the differences between adjacent rows (adjacent based on the timestamp) and divide the result by the number of the summands.
The formula
((T1-T0) + (T2-T1) + … + (TN-TN-1)) / N
can obviously be simplified to merely
(TN-T0) / N
So, the query would be something like this:
SELECT TIMESTAMPDIFF(SECOND, MIN(date), MAX(date)) / (COUNT(*) - 1)
FROM atable
Make sure the number of rows is more than 1, or you'll get the Division By Zero error. Still, if you like, you can prevent the error with a simple trick:
SELECT
IFNULL(TIMESTAMPDIFF(SECOND, MIN(date), MAX(date)) / NULLIF(COUNT(*) - 1, 0), 0)
FROM atable
Now you can safely run the query against a table with a single row.
Give this a shot:
select AVG(theDelay) from (
select TIMESTAMPDIFF(SECOND,a.date, b.date) as theDelay
from myTable a
join myTable b on b.date = (select MIN(x.date)
from myTable x
where x.date > a.date)
) p
The inner query joins each row with the next row (by date) and returns the number of seconds between them. That query is then encapsulated and is queried for the average number of seconds.
EDIT: If your ID column is auto-incrementing and they are in date order, you can speed it up a bit by joining to the next ID row rather than the MIN next date.
select AVG(theDelay) from (
select TIMESTAMPDIFF(SECOND,a.date, b.date) as theDelay
from myTable a
join myTable b on b.date = (select MIN(x.id)
from myTable x
where x.id > a.id)
) p
EDIT2: As brilliantly commented by Mikael Eriksson, you may be able to just do:
select (TIMESTAMPDIFF(SECOND,(MAX(date),MIN(date)) / COUNT(*)) from myTable
There's a lot you can do with this to eliminate off-peak hours or big spans without a new record, using the join syntax in my first example.
Try this:
select avg(diff) as AverageSecondsBetweenDates
from (
select TIMESTAMPDIFF(SECOND, t1.MyDate, min(t2.MyDate)) as diff
from MyTable t1
inner join MyTable t2 on t2.MyDate > t1.MyDate
group by t1.MyDate
) a
I am trying to write a query which will give me the last entry of each month in a table called transactions. I believe I am halfway there as I have the following query which groups all the entries by month then selects the highest id in each group which is the last entry for each month.
SELECT max(id),
EXTRACT(YEAR_MONTH FROM date) as yyyymm
FROM transactions
GROUP BY yyyymm
Gives the correct results
id yyyymm
100 201006
105 201007
111 201008
118 201009
120 201010
I don’t know how to then run a query on the same table but select the balance column where it matches the id from the first query to give results
id balance date
120 10000 2010-10-08
118 11000 2010-09-29
I've tried subqueries and looked at joins but i'm not sure how to go about using them.
You can make your first select an inline view, and then join to it. Something like this (not tested, but should give you the idea):
SELECT x.id
, t.balance
, t.date
FROM your_table t
/* here, we make your select an inline view, then we can join to it */
, (SELECT max(id) id,
EXTRACT(YEAR_MONTH FROM date) as yyyymm
FROM transactions
GROUP BY yyyymm) x
WHERE t.id = x.id