I have a query below which fetches me the data for last day of a month. In this query, ME_DT is defined as date time type. So when I do the max on ME_DT then it gives me the data for last day of a month. I think I need to convert the date time type to integer YYYYMM in a teradata filter condition, so that it gives me the data for the entire month not just for the last day of a month. How should I modify my existing query to get my desired result?
PADW.PL_CURR_DEFN_LOSS_FRCST_ME.ME_DT =
(select max (PADW.PL_CURR_DEFN_LOSS_FRCST_ME.ME_DT) from PADW.PL_CURR_DEFN_LOSS_FRCST_ME)
You should try to avoid calculations on a column in the WHERE-condition to get better estimates and possible index/partition-access:
with cte (dt) as
(
select max (PADW.PL_CURR_DEFN_LOSS_FRCST_ME.ME_DT)
from PADW.PL_CURR_DEFN_LOSS_FRCST_ME
)
select ....
where PADW.PL_CURR_DEFN_LOSS_FRCST_ME.ME_DT
between TRUNC(dt, 'mon')
and last_day(dt)
I have to use filer on the table because it has millions of records...
i did this ...but still verifying if I have got what i want...
(PADW.PL_CURR_DEFN_LOSS_FRCST_ME.ME_DT =
(select max (cast(PADW.PL_CURR_DEFN_LOSS_FRCST_ME.ME_DT as date format 'YYYYMM')) from PADW.PL_CURR_DEFN_LOSS_FRCST_ME))
Related
Table A
Year(String), Month(String), and Day(String) are partition columns.
I want to get the count for the previous day.
Note - here no Date formate like 2022-06-01 in any columns
I tried the below query.
Select count(*) FROM Table A where Day='03' and Month='06' and Year='2022' GROUP BY city;
But I don't want to hard-coded value.
I think I got the solution -
select count(*) from Table A where cast(concat_ws('-',year,month,day) as date)=date_sub(current_date, 1);
this is giving me the correct results.
Consider a time-series table that contains three fields time of type timestamptz, balance of type numeric, and is_spent_column of type text.
The following query generates a valid result for the last day of the given interval.
SELECT
MAX(DATE_TRUNC('DAY', (time))) as last_day,
SUM(balance) FILTER ( WHERE is_spent_column is NULL ) AS value_at_last_day
FROM tbl
2010-07-12 18681.800775017498741407984000
However, I am in need of an equivalent query based on window functions to report the total value of the column named balance for all the days up to and including the given date .
Here is what I've tried so far, but without any valid result:
SELECT
DATE_TRUNC('DAY', (time)) AS daily,
SUM(sum(balance) FILTER ( WHERE is_spent_column is NULL ) ) OVER ( ORDER BY DATE_TRUNC('DAY', (time)) ) AS total_value_per_day
FROM tbl
group by 1
order by 1 desc
2010-07-12 16050.496339044977568391974000
2010-07-11 13103.159119670350269890284000
2010-07-10 12594.525752964512456914454000
2010-07-09 12380.159588711091681327014000
2010-07-08 12178.119542536668113577014000
2010-07-07 11995.943973804127033140014000
EDIT:
Here is a sample dataset:
LINK REMOVED
The running total can be computed by applying the first query above on the entire dataset up to and including the desired day. For example, for day 2009-01-31, the result is 97.13522530000000000000, or for day 2009-01-15 when we filter time as time < '2009-01-16 00:00:00' it returns 24.446144000000000000.
What I need is an alternative query that computes the running total for each day in a single query.
EDIT 2:
Thank you all so very much for your participation and support.
The reason for differences in result sets of the queries was on the preceding ETL pipelines. Sorry for my ignorance!
Below I've provided a sample schema to test the queries.
https://www.db-fiddle.com/f/veUiRauLs23s3WUfXQu3WE/2
Now both queries given above and the query given in the answer below return the same result.
Consider calculating running total via window function after aggregating data to day level. And since you aggregate with a single condition, FILTER condition can be converted to basic WHERE:
SELECT daily,
SUM(total_balance) OVER (ORDER BY daily) AS total_value_per_day
FROM (
SELECT
DATE_TRUNC('DAY', (time)) AS daily,
SUM(balance) AS total_balance
FROM tbl
WHERE is_spent_column IS NULL
GROUP BY 1
) AS daily_agg
ORDER BY daily
I'm trying to answer questions like, how many POs per month do we have? Or, how many lines are there in every PO by month, etc. The original PO dates are all formatted #1/1/2013#. So my first step was to Format each PO record date into 'mmyy' so I could group and COUNT them.
This worked well but, now I cannot view the data by date... For example, I cannot ask 'How many POs after December did we get?' I think this is because SQL does not recognize mm/yy as a comparable date.
Any ideas how I could restructure this?
There are 2 queries I wrote. This is the query to format the dates. This is also the query I was trying to add the date filter to (ex: >#3/14#)
SELECT qryALL_PO.POLN, Format([PO CREATE DATE],"mm/yy") AS [Date]
FROM qryALL_PO
GROUP BY qryALL_PO.POLN, Format([PO CREATE DATE],"mm/yy");
My group and counting query is:
SELECT qryALL_PO.POLN, Sum(qryALL_PO.[LINE QUANTITY]) AS SUM_QTY_PO
FROM qryALL_PO
GROUP BY qryALL_PO.POLN;
You can still count and group dates, as long as you have a way to determine the part of the date you are looking for.
In Access you can use year and month for example to get the year and month part of the date:
select year(mydate)
, month(mydate)
, count(*)
from tableX
group
by year(mydate)
, month(mydate)
You can format it 'YYYY-MM' , and then use '>' for 'after' clause
I have a table with a date column where date is stored in this format:
2012-08-01 16:39:17.601455+0530
How do I group or group_and_count on this column by month?
Your biggest problem is that SQLite won't directly recognize your dates as dates.
CREATE TABLE YOURTABLE (DateColumn date);
INSERT INTO "YOURTABLE" VALUES('2012-01-01');
INSERT INTO "YOURTABLE" VALUES('2012-08-01 16:39:17.601455+0530');
If you try to use strftime() to get the month . . .
sqlite> select strftime('%m', DateColumn) from yourtable;
01
. . . it picks up the month from the first row, but not from the second.
If you can reformat your existing data as valid timestamps (as far a SQLite is concerned), you can use this relatively simple query to group by year and month. (You almost certainly don't want to group by month alone.)
select strftime('%Y-%m', DateColumn) yr_mon, count(*) num_dates
from yourtable
group by yr_mon;
If you can't do that, you'll need to do some string parsing. Here's the simplest expression of this idea.
select substr(DateColumn, 1, 7) yr_mon, count(*) num_dates
from yourtable
group by yr_mon;
But that might not quite work for you. Since you have timezone information, it's sure to change the month for some values. To get a fully general solution, I think you'll need to correct for timezone, extract the year and month, and so on. The simpler approach would be to look hard at this data, declare "I'm not interested in accounting for those edge cases", and use the simpler query immediately above.
It took me a while to find the correct expression using Sequel. What I did was this:
Assuming a table like:
CREATE TABLE acct (date_time datetime, reward integer)
Then you can access the aggregated data as follows:
ds = DS[:acct]
ds.select_group(Sequel.function(:strftime, '%Y-%m', :date_time))
.select_append{sum(:reward)}.each do |row|
p row
end
I have data like this:
For example, today is on April 2012. Referring to data above, I want to get the data with M_PER = 03-2012 because this month is in the range 03-2012 TO 06-2012.
--EditedIn this case, I wanna get a rate for used currency code. Because today is still in April, and I want to know rate US Dollar (USD) to Indonesia Rupiah (IDR) I must get the data with M_PER = 03-2012 and CRR_CURRENCY_CODE = USD.
The question is what query can retrieve data like that?
Since you seem to be using quarterly values, I would use the TRUNC function with the 'Q' format model. This truncates a date to 1/1/YYYY, 1/4/YYYY, 1/7/YYYY and 1/10/YYYY, i.e. the first day of the quarter.
To fit your model which is the month at the end of the quarter, you would then have to add two months. This assumes that the MONTH_PERIOD column is a SQL date and not some other data type.
Included below is an example, using SYSDATE as the input date.
select *
from your_table
where add_months(trunc(sysdate, 'Q'),2) = month_period;
I use the rownum and order by to get the value.
SELECT * FROM tables WHERE m_per > '04-2012' AND ROWNUM = 1 ORDER BY month_period ASC