My table structure is this:
ID,
country,
month,
year,
total amt in previous period,
total amt during period,
incr/decr in total amt in previous period,
incr/decr in total amt during (month, year)
The ID, month, year and total amt fields are available in table abc.
The incr/decr in total amt in previous period is the difference between total amt in previous period and total amt during period columns.
I wrote this query:
select m.id, m.month, m.year, m.total_amt
from abc m
order by year, month desc;
For the total amt in previous period I could not use Between Date( ) And DateAdd("M", -1, Date( )); as I have no date but just year and month.
How to compare the two columns with the columns year and month and how to have the last two derived columns using subqueries?
For comparing Month there is an specific function (that works for MS SQL and ORACLE). There's one function for days and years too. See links below:
YEAR
MONTH
DAY
Examples of this and getting derived columns from subqueries can be found in this topic already discussed in the forum:
Stackoverflow topic
Related
i am trying to work with this query to produce a list of all 11 years and 12 months within the years with the sales data for each month. Any suggestions? this is my query so far.
SELECT
distinct(extract(year from date)) as year
, sum(sale_dollars) as year_sales
from `project-1-349215.Dataset.sales`
group by date
it just creates a long list of over 2000 results when i am expecting 132 max one for each month in the years.
You should change your group by statement if you have more results than you expected.
You can try:
group by YEAR(date), MONTH(date)
or
group by EXTRACT(YEAR_MONTH FROM date)
A Grouping function is for takes a subsection of the date in your case year and moth and collect all rows that fit, and sum it up,
So a s´GROUp BY date makes no sense, what so ever as you don't want the sum of every day
So make this
SELECT
extract(year from date) as year
,extract(MONTH from date) as month
, sum(sale_dollars) as year_sales
from `project-1-349215.Dataset.sales`
group by 1,2
Or you can combine both year and month
SELECT
extract(YEAR_MONTH from date) as year
, sum(sale_dollars) as year_sales
from `project-1-349215.Dataset.sales`
group by 1
Table StructureWrite a query to display the total month wise sales amount received in the past 1 year . Display details like sales month, total sales amount. Give an alias_name as MONTH for retrieved sales month, TURN_OVER for sales amount. Sort the result by amount in descending order.
(Hint: Use table Sales_info. Use to_char for retrieving the month. Net amount for sales amount calculation. Use sysdate for calculation of past 1 year sales. DATA IS CASE-SENSITIVE.)
The code I have written is fetching me all years sales data.
select to_char(Sales_Date,'Month')"MONTH"
Net_Amount as Turn_Over
from Sales_Info
where Sales_Date= add_months(Sysdate,-12)
select to_char(Sales_Date,'MON')"MONTH",
Net_Amount as TURN_OVER
from Sales_Info
where Sales_Date > add_months(Sysdate,-12)
order by Net_Amount desc;
I'm not going to do your homework for you, but here is a list of things currently missing from your query:
a comma in the SELECT list
you need greater than, not equals because you want all dates "more than the moment it was a year ago"
you need to break your data into groups where each group has the same month, and you need to sum up all the data in that month, so your query needs to have the words GROUP BY and SUM in it..
The code I have written is fetching me all years sales data
No, the query as it stands will be giving you only the sales that happened at exactly the current date-time, one year ago, which is probably 0 records
You are pretty close. What you are missing is the GROUP BY and summary functions:
select to_char(Sales_Date, 'Month') as "MONTH"
SUM(Net_Amount) as Turn_Over
from Sales_Info
where Sales_Date= add_months(Sysdate, -12)
group by to_char(Sales_Date, 'Month');
Note that there are still some significant issues with the query. For instance, I really am not a fan of using month names for what you are doing. It leaves out the year. In fact, the above query is going to combine data from the current month and the same month last year.
I would instead go for complete months. And use trunc() instead:
select trunc(Sales_Date, 'MON') as "MONTH"
SUM(Net_Amount) as Turn_Over
from Sales_Info
where Sales_Date = add_months(trunc(Sysdate, 'MON'), -12) and
Sales_Date < trunc(sysdate, 'MON')
group by to_char(Sales_Date, 'Month')
order by "MONTH".
In a real-world environment, this would typically provided cleaner, more useful results. In addition, because the first column is actually the date, it is easy to sort by.
The ans will be :
Select to_char(Sales_Date , 'MON' ) as "MONTH" , sum(Net_Amount) as TURN_OVER
from Sales_Info
where Sales_Date > add_months(Sysdate , -12)
group by to_char(Sales_Date , 'MON')
order by TURN_OVER desc;
I'm curious as to find the daily average sales for the month of December 1998 not greater than 100 as a where clause. So what I imagine is that since the table consists of the date of sales (sth like 1 december 1998, consisting of different date, months and year), amount due....First I'm going to define a particular month.
DEFINE a = TO_DATE('1-Dec-1998', 'DD-Month-YYYY')
SELECT SUBSTR(Sales_Date, 4,6), (SUM(Amount_Due)/EXTRACT(DAY FROM LAST_DAY(Sales_Date))
FROM ......
WHERE SUM(AMOUNT_DUE)/EXTRACT(DAY FROM LAST_DAY(&a)) < 100
I'm stuck as to extract the sum of amount due in the month of december 1998 for the where clause....
How can I achieve the objective?
To me, it looks like this:
select to_char(sales_date, 'mm.yyyy') month,
avg(amount_due) avg_value
from your_table
where sales_date >= trunc(date '1998-12-01', 'mm')
and sales_date < add_months(trunc(date '1998-12-01', 'mm'), 1)
group by to_char(sales_date, 'mm.yyyy')
having avg(amount_due) < 100;
WHERE clause can be simplified; it shows how to fetch certain period:
trunc to mm returns first day in that month
add_months to the above value (first day in that month) will return first day of the next month
the bottom line: give me all rows whose sales_date is >= first day of this month and < first day of the next month; basically, the whole this month
Finally, the where clause you used should actually be the having clause.
As long as the amount_due column only contains numbers, you can use the sum function.
Below SQL query should be able to satisfy your requirement.
Select SUM(Amount_Due) from table Sales where Sales_Date between '1-12-1998' and '31-12-1998'
OR
Select SUM(Amount_Due) from table Sales where Sales_Date like '%-12-1998'
I want to know the trick to find the list of customers who are transacting for consecutive 3 months ,that could be any 3 consecutive months with any number of occurrence.
example: suppose there is customer who transact in January then keep transacting till march then he stopped transacting.I want the list of these customer from my database .
I am working on AWS Athena.
One method uses aggregation and window functions:
select customer_id, yyyymm_2
from (select date_trunc(month, transactdate) as yyyymm, customer_id,
lag(date_trunc(month, transactdate), 2) over (partition by customer_id order by date_trunc(month, transactdate)) as prev_yyyymm_2
from t
where transactdate >= '2017-01-01' and
transactadte < '2019-01-01'
)
where prev_dt_2 = yyyymm - interval '2' month;
This aggregates transactions by month and looks at the transaction date two rows earlier. The outer filter checks that that date is exactly 2 months earlier.
I have a table say testTable in Hive(with data for 3 years) with the following columns:
retailers, order_total, order_total_qty, order_date
I have to create a new table with these columns:
'source_name' as source, sum(retailers), sum(order_total), sum(order_total_qty)
for each week from the starting order_date.
I am stuck with this. How can I group following data in the way that it will sum up on weekly basis.
Use WEEKOFYEAR() function to calculate aggregation on weekly basis.
select
'source_name' source,
sum(retailers) sum_retailers,
sum(order_total) sum_order_total,
sum(order_total_qty) sum_order_total_qty,
WEEKOFYEAR(order_date) week,
year(order_date) year
from testTable
where order_date >= '2015-01-01' --start_date
group by WEEKOFYEAR(order_date), year(order_date)
order by year, week; --order if necessary