i have another query to select return min, max, start and end price.
It is for a specific month and works perfect for metal_id = 1 but when changed to 2, it returns no data.
please see:
The query below does its job to select the min, max, start and last price per day in a given month.
I would like to select the same but for the whole month, as in show the overall performance for the given month instead of on a daily basis.
Fiddle:
http://sqlfiddle.com/#!9/bee86/1
I just need the last 2 prices, first and last price on the months selected...
select
highp.metal_price_datetime_IST AS high_price_metal_price_datetime_IST
, highp.metal_price as highest_price
, lowp.report_term
, lowp.metal_price as lowest_price
, lowp.metal_price_datetime_IST AS low_price_metal_price_datetime_IST
from (select #report_term:=concat(monthname(metal_price_datetime_IST), ' ', year(metal_price_datetime_IST)) as report_term
, metal_price_datetime_IST
, metal_price
, metal_id
, case when #report_term=#old_report_term then #rn1:=#rn1+1 else #rn1:=1 end as rn
, #old_report_term:=#report_term
from metal_prices
cross join (select #rn1:=0, #old_report_term:='') inituservar1
where datediff(now(), metal_price_datetime_IST) between 0 and 180
and metal_id = 1
order by metal_id, report_term, metal_price asc) lowp
inner join (select #report_term2:=concat(monthname(metal_price_datetime_IST), ' ', year(metal_price_datetime_IST)) as report_term
, metal_price_datetime_IST
, metal_price
, metal_id
, case when #report_term2=#old_report_term2 then #rn2:=#rn2+1 else #rn2:=1 end as rn
, #old_report_term2:=#report_term2
from metal_prices
cross join (select #rn2:=0, #old_report_term2:='') inituservar1
where datediff(now(), metal_price_datetime_IST) between 0 and 180
and metal_id = 1
order by metal_id, report_term, metal_price desc) highp
on lowp.rn=highp.rn
and lowp.metal_id = highp.metal_id
and lowp.report_term = highp.report_term
and lowp.rn = 1
order by lowp.metal_price_datetime_IST DESC
Related
I have a table of prices, 2 types. metal 1 and metal 2.
I have succeeded in getting the max, min price for each metal groups by day.
How can i also select the start (first) and end (last) of every day too?
I am nearly there, but struggling on getting these two final prices...
My SQL fiddle with example data:
http://sqlfiddle.com/#!9/ca4867/1
My query so far:
select
highp.metal_price_datetime_IST AS high_price_metal_price_datetime_IST
, highp.metal_price as highest_price
, lowp.report_term
, lowp.metal_id
, lowp.metal_price as lowest_price
, lowp.metal_price_datetime_IST AS low_price_metal_price_datetime_IST
from (select #report_term:=concat(day(metal_price_datetime_IST), ' ', monthname(metal_price_datetime_IST), ' ', year(metal_price_datetime_IST)) as report_term
, metal_price_datetime_IST
, metal_price
, metal_id
, case when #report_term=#old_report_term then #rn1:=#rn1+1 else #rn1:=1 end as rn
, #old_report_term:=#report_term
from metal_prices
cross join (select #rn1:=0, #old_report_term:='') inituservar1
where metal_price_datetime_IST BETWEEN '2018-02-01' AND LAST_DAY('2018-02-01')
order by metal_id, report_term, metal_price asc) lowp
inner join (select #report_term2:=concat(day(metal_price_datetime_IST), ' ', monthname(metal_price_datetime_IST), ' ', year(metal_price_datetime_IST)) as report_term
, metal_price_datetime_IST
, metal_price
, metal_id
, case when #report_term2=#old_report_term2 then #rn2:=#rn2+1 else #rn2:=1 end as rn
, #old_report_term2:=#report_term2
from metal_prices
cross join (select #rn2:=0, #old_report_term2:='') inituservar1
where metal_price_datetime_IST BETWEEN '2018-02-01' AND LAST_DAY('2018-02-01')
order by metal_id, report_term, metal_price desc) highp
on lowp.rn=highp.rn
and lowp.metal_id = highp.metal_id
and lowp.report_term = highp.report_term
and lowp.rn = 1
and (lowp.metal_id = 1 or lowp.metal_id = 2)
order by lowp.metal_price_datetime_IST DESC
The query you have in your fiddle seems too complex for what needs to be done. I have refactored and rewritten the query. Basically, the query is split in two parts. First one maxminprice determines the max and min price for each day for each metal. Fairly straight forward. The second part firstlastprice is a bit more complex. It finds out the max and min time stamps for each metal for each day. Then joins back to the main table to get the values for those time stamps. The case statement there is to merge the results for max and min (first and last) time so we don't have to do the query twice.
SELECT maxminprice.metal_id,
maxminprice.metal_price_datetime,
maxminprice.max_price,
maxminprice.min_price,
firstlastprice.first_price,
firstlastprice.last_price
FROM (SELECT metal_id,
DATE(metal_price_datetime) metal_price_datetime,
MAX(metal_price) max_price,
MIN(metal_price) min_price
FROM metal_prices
GROUP BY metal_id,
DATE(metal_price_datetime)
ORDER BY metal_id,
DATE(metal_price_datetime)) maxminprice
INNER JOIN (SELECT mp.metal_id,
day_range.metal_price_datetimefl,
SUM(CASE
WHEN TIME(mp.metal_price_datetime) = first_time
THEN
mp.metal_price
ELSE NULL
END) first_price,
SUM(CASE
WHEN TIME(mp.metal_price_datetime) = last_time
THEN
mp.metal_price
ELSE NULL
END) last_price
FROM metal_prices mp
INNER JOIN (SELECT metal_id,
DATE(metal_price_datetime)
metal_price_datetimefl,
MAX(TIME(metal_price_datetime))
last_time,
MIN(TIME(metal_price_datetime))
first_time
FROM metal_prices
GROUP BY metal_id,
DATE(metal_price_datetime))
day_range
ON mp.metal_id = day_range.metal_id
AND DATE(mp.metal_price_datetime) =
day_range.metal_price_datetimefl
AND TIME(mp.metal_price_datetime) IN
( last_time, first_time )
GROUP BY mp.metal_id,
day_range.metal_price_datetimefl) firstlastprice
ON maxminprice.metal_id = firstlastprice.metal_id
AND maxminprice.metal_price_datetime =
firstlastprice.metal_price_datetimefl
I am looking for queries, using which I can analyze a general employee database. This is for Data Analysis.
Tried this for monthly employee trend
SELECT
dt.FullDateAlternateKey as 'Date'
, count(1) as ActiveCount
FROM DimDate dt
LEFT JOIN (SELECT 'Active' as 'EmpStatus', * FROM DimEmployee) emp
-- regular active employees
ON (dt.FullDateAlternateKey between emp.StartDate and ISNULL(emp.EndDate,'9999-12-31'))
WHERE
dt.FullDateAlternateKey = EOMONTH(dt.FullDateAlternateKey)
GROUP BY
dt.FullDateAlternateKey
ORDER BY
1;
also found CTE use for finding employee hierarchy
WITH DirectReports (ManagerID, EmployeeID, Title, DeptID, Level)
AS
(
-- Anchor member definition
SELECT e.ParentEmployeeKey, e.EmployeeKey, e.Title, e.DepartmentName,
0 AS Level
FROM DimEmployee AS e
WHERE e.ParentEmployeeKey IS NULL
UNION ALL
-- Recursive member definition
SELECT e.ParentEmployeeKey, e.EmployeeKey, e.Title, e.DepartmentName,
Level + 1
FROM DimEmployee AS e
INNER JOIN DirectReports AS d
ON e.ParentEmployeeKey = d.EmployeeID
)
-- Statement that executes the CTE
SELECT ManagerID, EmployeeID, Title, DeptID, Level
FROM DirectReports
WHERE DeptID = 'Information Services' OR Level = 0
also, some good queries to analyze the sales data
-- Show each sales average for Group, Country, and Region all in one query
SELECT DISTINCT
t.SalesTerritoryGroup
, t.SalesTerritoryCountry
, t.SalesTerritoryRegion
, AVG(s.SalesAmount) OVER(PARTITION BY t.SalesTerritoryGroup ) as 'GroupAvgSales'
, AVG(s.SalesAmount) OVER(PARTITION BY t.SalesTerritoryCountry ) as 'CountryAvgSales'
, AVG(s.SalesAmount) OVER(PARTITION BY t.SalesTerritoryRegion ) as 'RegionAvgSales'
FROM FactInternetSales s
JOIN DimSalesTerritory t ON
s.SalesTerritoryKey = t.SalesTerritoryKey
WHERE
YEAR(s.OrderDate) = 2013
ORDER BY
1,2,3
Use additional aggregations to understand more about product sales such as the distribution of sales etc..
SELECT
cat.EnglishProductCategoryName 'Category'
, sub.EnglishProductSubcategoryName 'SubCategory'
, count(1) 'Count' -- How many sales where there?
, sum(s.SalesAmount) 'Sales' -- How much sales did we have?
, avg(s.SalesAmount) 'Avg_SalesAmount' -- What was the Avg sale amount?
, min(s.SalesAmount) 'Min_SaleAmount' -- What was the Min sale amount?
, max(s.SalesAmount) 'Max_SaleAmount' -- What was the Max sale amount
FROM FactInternetSales s
LEFT JOIN DimProduct p ON s.ProductKey = p.ProductKey
LEFT JOIN DimProductSubcategory sub ON p.ProductSubcategoryKey = sub.ProductSubcategoryKey
LEFT JOIN DimProductCategory cat ON sub.ProductCategoryKey = cat.ProductCategoryKey
-- must use group by in order for aggregation to work properly
GROUP BY
cat.EnglishProductCategoryName -- column aliases aren't allowed
, sub.EnglishProductSubcategoryName
ORDER BY
cat.EnglishProductCategoryName
, sub.EnglishProductSubcategoryName
-- Calculate the customer acquisition funnel
SELECT
c.FirstName
, c.LastName
, c.DateFirstPurchase
, DATEDIFF(d,c.DateFirstPurchase,getdate()) as 'DaysSinceFirstPurchase' -- How long have they been a customer?
FROM DimCustomer c
ORDER BY 3 DESC
-- Calculate a Monthly average of customer tenure
SELECT
EOMONTH(c.DateFirstPurchase) as 'MonthOfFirstPurchase' -- What month did they become a customer?
, DATEDIFF(d,EOMONTH(c.DateFirstPurchase),getdate()) as 'DaysSinceFirstPurchase' -- How long have they been a customer?
, COUNT(1) as 'CustomerCount' -- How manY customers are there for this month?
FROM DimCustomer c
GROUP BY EOMONTH(c.DateFirstPurchase)
ORDER BY 2 DESC
-- Show the top product Sub Categories for each year
SELECT
count(DISTINCT s.SalesOrderNumber) 'OrderCount' -- use 1 instead of a field for faster performance
, RANK() OVER (PARTITION BY YEAR(s.OrderDate) ORDER BY sum(s.SalesAmount) DESC) 'SalesRank'
, sum(s.SalesAmount) 'TotalSales'
, cat.EnglishProductCategoryName 'Category'
, sub.EnglishProductSubcategoryName 'SubCategory'
, YEAR(s.OrderDate) 'Year'
FROM FactInternetSales s
INNER JOIN DimProduct p ON s.ProductKey = p.ProductKey
INNER JOIN DimProductSubcategory sub ON p.ProductSubcategoryKey = sub.ProductSubcategoryKey
INNER JOIN DimProductCategory cat ON sub.ProductCategoryKey = cat.ProductCategoryKey
-- must use group by in order for aggregation to work properly
GROUP BY
cat.EnglishProductCategoryName -- column aliases aren't allowed
, sub.EnglishProductSubcategoryName
, YEAR(s.OrderDate)
ORDER BY YEAR(s.OrderDate), SUM(s.SalesAmount) DESC;
-- first, create weekly sales totals
SELECT SUM(s.SalesAmount) 'WeeklySales'
, DATEPART(ww, s.OrderDate) as 'WeekNum'
FROM FactInternetSales s
WHERE YEAR(s.OrderDate) = 2013
GROUP BY
DATEPART(ww, s.OrderDate)
ORDER BY
DATEPART(ww, s.OrderDate) ASC
-- use that subquery as our source and calculate the moving average
SELECT
AVG(WeeklySales) OVER (ORDER BY WeekNum ROWS BETWEEN 6 PRECEDING AND CURRENT ROW) as AvgSales
, WeeklySales as 'TotalSales'
, WeekNum
FROM (
SELECT SUM(s.SalesAmount) 'WeeklySales'
, DATEPART(ww, s.OrderDate) as 'WeekNum'
FROM FactInternetSales s
WHERE YEAR(s.OrderDate) = 2013
GROUP BY
DATEPART(ww, s.OrderDate)
) AS s
GROUP BY
WeekNum, WeeklySales
ORDER BY
WeekNum ASC
-- Running Total
SELECT
SUM(MonthlySales) OVER (PARTITION BY SalesYear ORDER BY SalesMonth ROWS UNBOUNDED PRECEDING) as YTDSales
, MonthlySales as 'MonthlySales'
, SalesYear
, SalesMonth
FROM (
SELECT SUM(s.SalesAmount) 'MonthlySales'
, MONTH(s.OrderDate) as 'SalesMonth'
, year(s.OrderDate) as 'SalesYear'
FROM FactInternetSales s
GROUP BY
MONTH(s.OrderDate)
, year(s.OrderDate)
) AS s
GROUP BY
SalesMonth, SalesYear, MonthlySales
ORDER BY
SalesYear, SalesMonth ASC
-- Get Prev Year Sales
WITH MonthlySales (YearNum, MonthNum, Sales)
AS
(
SELECT d.CalendarYear, d.MonthNumberOfYear, SUM(s.SalesAmount)
FROM DimDate d
JOIN FactInternetSales s ON d.DateKey = s.OrderDateKey
GROUP BY d.CalendarYear, d.MonthNumberOfYear
)
-- Get Current Year and join to CTE for previous year
SELECT
d.CalendarYear
, d.MonthNumberOfYear
, ms.Sales PrevSales
, SUM(s.SalesAmount) CurrentSales
FROM DimDate d
JOIN FactInternetSales s ON d.DateKey = s.OrderDateKey
JOIN MonthlySales ms ON
d.CalendarYear-1 = ms.YearNum AND
d.MonthNumberOfYear = ms.MonthNum
GROUP BY
d.CalendarYear
, d.MonthNumberOfYear
, ms.Sales
ORDER BY
1 DESC, 2 DESC
-- Now calculate the % change Year over Year
WITH MonthlySales (YearNum, MonthNum, Sales)
AS
(
SELECT d.CalendarYear, d.MonthNumberOfYear, SUM(s.SalesAmount)
FROM DimDate d
JOIN FactInternetSales s ON d.DateKey = s.OrderDateKey
GROUP BY d.CalendarYear, d.MonthNumberOfYear
)
-- Get Current Year and join to CTE for previous year
SELECT
d.CalendarYear
, d.MonthNumberOfYear
, ms.Sales PrevSales
, SUM(s.SalesAmount) CurrentSales
, (SUM(s.SalesAmount) - ms.Sales) / SUM(s.SalesAmount) 'PctGrowth'
FROM DimDate d
JOIN FactInternetSales s ON d.DateKey = s.OrderDateKey
JOIN MonthlySales ms ON
d.CalendarYear-1 = ms.YearNum AND
d.MonthNumberOfYear = ms.MonthNum
GROUP BY
d.CalendarYear
, d.MonthNumberOfYear
, ms.Sales
ORDER BY
1 DESC, 2 DESC
Im trying to calculate the amount of money won by all the offspring of a male race horse (Sire) over a time period. Listed by the Sire with the most amount of money won.
I run the query and get the result Im after with one problem, I cant display the sires name, only their ID.
SELECT `horses`.`SireID` AS `SireID` , `horses`.`HorseName` AS `Sire Name`,
COUNT( `runs`.`HorsesID` ) AS `Runs` ,
COUNT(
CASE WHEN `runs`.`Finish` =1
THEN 1
ELSE NULL
END ) AS `Wins` ,
CONCAT( FORMAT( (
COUNT(
CASE WHEN `runs`.`Finish` =1
THEN 1
ELSE NULL
END ) / COUNT
( `runs`.`TrainersID` ) ) *100, 0 ) , '%'
) AS `Percent` ,
FORMAT( SUM( `runs`.`StakeWon` ) , 0 ) AS `Stakes`
FROM runs
INNER JOIN horses ON runs.HorsesID = horses.HorsesID
INNER JOIN races ON runs.RacesID = races.RacesID
WHERE `races`.`RaceDate` >= STR_TO_DATE( '2012,07,01', '%Y,%m,%d' )
AND `races`.`RaceDate` < STR_TO_DATE( '2012,07,01', '%Y,%m,%d' ) + INTERVAL 1
MONTH
AND `horses`.`SireID` <> `horses`.`HorsesID`
GROUP BY `horses`.`SireID`, `horses`.`HorseName`
ORDER BY SUM( `runs`.`StakeWon` ) DESC
Take a record in the horse table for example, a horse has a horsesID and they also have a sireID (their father). The sireID has an equivalent horsesID in another record in the same table as it is also a horse
Basically I need to map the horseName to the sireID.
I thought a self join would work.
`AND `horses`.`SireID` <> `horses`.`HorsesID``
but it doesn't return the correct Sire name corresponding to the SireID.
You can do a JOIN on the table itself. Here's a simpler example:
SELECT Horses.HorseID, Horses.HorseName, Horses.SireID, b.HorseName as SireName
FROM Horses
LEFT JOIN Horses b ON (Horses.SireID = b.HorseID)
You can probably figure out how to add the conditions from here.
join horses sires on sires.HorsesID = horses.SireID
With below Query I able to see the count(no) of issues for all issueType in JIRA for a given date .
ie.
SELECT count(*), STEP.STEP_ID
FROM (SELECT STEP_ID, ENTRY_ID
FROM OS_CURRENTSTEP
WHERE OS_CURRENTSTEP.START_DATE < '<your date>'
UNION SELECT STEP_ID, ENTRY_ID
FROM OS_HISTORYSTEP
WHERE OS_HISTORYSTEP.START_DATE < '<your date>'
AND OS_HISTORYSTEP.FINISH_DATE > '<your date>' ) As STEP,
(SELECT changeitem.OLDVALUE AS VAL, changegroup.ISSUEID AS ISSID
FROM changegroup, changeitem
WHERE changeitem.FIELD = 'Workflow'
AND changeitem.GROUPID = changegroup.ID
UNION SELECT jiraissue.WORKFLOW_ID AS VAL, jiraissue.id as ISSID
FROM jiraissue) As VALID,
jiraissue as JI
WHERE STEP.ENTRY_ID = VALID.VAL
AND VALID.ISSID = JI.id
AND JI.project = <proj_id>
Group By STEP.STEP_ID;
the result is
Status Count
open 12
closed 13
..... ....
What I'd like to achieve is something like this actually ..where the total count for status open and closed for each day .
Date COUNT(Open) COUNT(Closed)
12-1-2012 12 1
13-1-2012 14 5
The general strategy would be this:
Select from a table of all the days in a month
LEFT OUTER JOIN your table that gets counts for each day
(left outer join being necessary in case there were no entries for that day, you'd want it to show a zero value).
So I think this is roughly what you need (not complete and date-function syntax is probably wrong for your db, but it will get you closer):
SELECT aDate
, COALESCE(SUM(CASE WHEN IssueStatus = 'whateverMeansOpen' THEN 1 END,0)) OpenCount
, COALESCE(SUM(CASE WHEN IssueStatus = 'whateverMeansClosed' THEN 1 END,0)) ClosedCount
FROM
(
SELECT DATEADD(DAY, I, #START_DATE) aDate
FROM
(
SELECT number AS I FROM [SomeTableWithAtLeast31Rows]
where number between 1 and 31
) Numbers
WHERE DATEADD(DAY, I, #START_DATE) < #END_DATE
) DateTimesInInterval
LEFT OUTER JOIN
(
Put your query here. It needs to output two columns, DateTimeOfIssue and IssueStatus
) yourHugeQuery ON yourHugeQuery.DateTimeOfIssue BETWEEN aDate and DATEADD(DAY, 1, aDate)
GROUP BY aDate
ORDER BY aDate
I have a table orders like this:
customer_id order_date
10 2012-01-01
11 2012-01-02
10 2012-01-02
12 2012-01-03
11 2012-01-04
12 2012-02-01
11 2012-02-04
13 2012-02-05
14 2012-02-06
How can I get a cumulative average over time (per month) like this:
order date count orders count customers (customer_id)
2012-01 1 1 (12)
2012-01 2 2 (10,11)
2012-02 1 2 (13,14)
2012-02 2 2 (10,12
2012-02 3 2 (11)
showing how the number of customers vs. number of orders per customer develops over time.
The following query gives me the wanted information - but not over time. How can I iterate the query over time?
SELECT number_of_orders, count(*) as amount FROM (
SELECT o.customer_id, count(*) as number_of_orders
FROM orders o
GROUP BY o.customer_id) as t1
GROUP BY number_of_orders
Update:
have now build the following PHP code to generate what I need, wonder if that could be done using cumulative counts like on http://www.freeopenbook.com/mysqlcookbook/mysqlckbk-chp-12-sect-14.html
$year = 2011;
for ($cnt_months = 1; $cnt_months <= 12; $cnt_months++) {
$cnt_months_str = ($cnt_months < 10) ? '0'.$cnt_months : $cnt_months;
$raw_query = "SELECT number_of_orders, count(*) as amount
FROM (
SELECT
o.customer_id,
count(*) as number_of_orders
FROM orders o
where Date_Format( o.order_date, '%Y%m' ) >= " . $year . "01 and Date_Format( o.order_date, '%Y%m' ) <= " . $year . $cnt_months_str . "
GROUP BY o.customer_id) as t1
GROUP BY number_of_orders";
$query = db_query($raw_query);
while ($row = db_fetch_array($query)) {
$data[$cnt_months_str][$row['number_of_orders']] = array($row['number_of_orders'], (int)$row['amount']);
}
}
A good starting point is
SELECT
order_date,
COUNT(*) AS distinctOrders,
COUNT(DISTINCT customer_id) AS distinctCustomers,
GROUP_CONCAT(DISTINCT customer_id ASC) AS customerIDs
FROM orders
GROUP BY order_date ASC
This will give you the order_date, the number of orders on that date, the number of customers on that date, and the list of customer ids on that date.
Just looking at a way to tally up on a month by month basis. So taking this forward I've used a subquery to tally up as it goes
SELECT
ordersPerDate.*,
IF(
MONTH(ordersPerDate.order_date)=#thisMonth,
#runningTotal := #runningTotal+ordersPerDate.distinctOrders,
#runningTotal := 0
) AS ordersInThisMonth,
#thisMonth := MONTH(ordersPerDate.order_date)
FROM
(
SELECT
#thisMonth := 0,
#runningTotal := 0
) AS variableInit,
(
SELECT
order_date,
COUNT(*) AS distinctOrders,
COUNT(DISTINCT customer_id) AS distinctCustomers,
GROUP_CONCAT(DISTINCT customer_id ASC) AS customerIDs
FROM orders
GROUP BY order_date ASC
) AS ordersPerDate
And finally to clean it up, wrapped it in yet another subquery just to return the rows desired rather than the internal variables
Grouping on individual days
SELECT
collatedData.order_date,
collatedData.ordersInThisMonth AS count_orders,
collatedData.distinctCustomers AS count_customers,
collatedData.customerIDs AS customer_ids
FROM (
SELECT
ordersPerDate.*,
IF(
MONTH(ordersPerDate.order_date)=#thisMonth,
#runningTotal := #runningTotal+ordersPerDate.distinctOrders,
#runningTotal := 0
) AS ordersInThisMonth,
#thisMonth := MONTH(ordersPerDate.order_date)
FROM
(
SELECT
#thisMonth := 0,
#runningTotal := 0
) AS variableInit,
(
SELECT
order_date,
COUNT(*) AS distinctOrders,
COUNT(DISTINCT customer_id) AS distinctCustomers,
GROUP_CONCAT(DISTINCT customer_id) AS customerIDs
FROM orders
GROUP BY order_date ASC
) AS ordersPerDate
) AS collatedData
And now finally, following additional information from the OP, the end product
Grouping on calendar months
// Top level will sanitise the output
SELECT
collatedData.orderYear,
collatedData.orderMonth,
collatedData.distinctOrders,
collatedData.ordersInThisMonth AS count_orders,
collatedData.distinctCustomers AS count_customers,
collatedData.customerIDs AS customer_ids
FROM (
// This level up will iterate through calculating running totals
SELECT
ordersPerDate.*,
IF(
(ordersPerDate.orderYear,ordersPerDate.orderMonth) = (#thisYear,#thisMonth),
#runningTotal := #runningTotal+ordersPerDate.distinctOrders*ordersPerDate.distinctCustomers,
#runningTotal := 0
) AS ordersInThisMonth,
#thisMonth := ordersPerDate.orderMonth,
#thisYear := ordersPerDate.orderYear
FROM
(
SELECT
#thisMonth := 0,
#thisYear := 0,
#runningTotal := 0
) AS variableInit,
(
// Next level up will collate this to get per year, month, and per number of orders
SELECT
ordersPerDatePerUser.orderYear,
ordersPerDatePerUser.orderMonth,
ordersPerDatePerUser.distinctOrders,
COUNT(DISTINCT ordersPerDatePerUser.customer_id) AS distinctCustomers,
GROUP_CONCAT(ordersPerDatePerUser.customer_id) AS customerIDs
FROM (
// Inner query will get the number of orders for each year, month, and customer
SELECT
YEAR(order_date) AS orderYear,
MONTH(order_date) AS orderMonth,
customer_id,
COUNT(*) AS distinctOrders
FROM orders
GROUP BY orderYear ASC, orderMonth ASC, customer_id ASC
) AS ordersPerDatePerUser
GROUP BY
ordersPerDatePerUser.orderYear ASC,
ordersPerDatePerUser.orderMonth ASC,
ordersPerDatePerUser.distinctOrders DESC
) AS ordersPerDate
) AS collatedData
SELECT
substr(order_date,1,7) AS order_period,
count(*) AS number_of_orders,
count(DISTINCT orders.customer_id) AS number_of_customers,
GROUP_CONCAT(DISTINCT orders.customer_id) AS customers
FROM orders
GROUP BY substr(order_date,1,7)