I am querying an Oracle 11.2 instance to build a small data mart that includes extracting the date of birth and date of death of people.
Unfortunately the INSERT query (which takes its data from a SELECT) fails due to ORA-01847 (day of month must be between 1 and last day of month).
To find my bad dates I first did:
SELECT extract(day FROM SOME_DT_TM),
extract(month FROM SOME_DT_TM),
COUNT(*)
FROM PERSON
GROUP BY extract(day FROM SOME_DT_TM), extract(month FROM SOME_DT_TM)
ORDER BY COUNT(*) DESC;
It gave me 367 rows, one for each day of the year including NULL and February-29th (leap year). True for the other date column as well, so it looks like the data is fine from a SELECT perspective.
However if I set logging up on my insert
create table registry_new_dates
(some_dob date, some_death_date date);
exec dbms_errlog.create_error_log('SOME_NEW_DATES');
And then run my long insert query:
SELECT some_dob,some_death_date,ora_err_mesg$ FROM ERR$_SOME_NEW_DATES;
I get the following weird results (first 3 rows shown) which makes me think that zip codes have been somehow inserted instead of dates for the 2nd column.
31-DEC-25 35244 "ORA-01847: day of month must be between 1 and last day of month"
13-DEC-33 35244-3402 "ORA-01847: day of month must be between 1 and last day of month"
23-JUN-58 35235 "ORA-01847: day of month must be between 1 and last day of month"
My question is - how do I detect these bad rows (there are 11 apparentlyh) with an SQL statement so I can fix or remove them. Fixing them in the originating table is not an option (no write privileges). I tried using queries like this:
SELECT DECEASED_DT_TM
FROM WH_CLN_PERSON
WHERE DECEASED_DT_TM LIKE '35%'
AND rownum<3;
But it did not find the offending rows.
Not sure if you are still actively researching this (or if you got an answer already).
To find the rows with the bad data, can't you instead select the DOB and the date of death, and express the WHERE clause in terms of DOB - like so:
...WHERE some_dob = to_date('31-DEC-25')
? After you find those rows, you may want to do another query on just one or two of those rows, including a calculated column: dump(date of death). Then post that. We can learn a lot from the dump - the internal representation of the so-called "date" (which may very well be a ZIP code instead). With that in hand we may be able to figure out what's stored, and how to hunt for it.
Related
In my program, I have a data grid view. I make some amounts due for payment today. I made a display of the amounts that are due and have not been paid (late) I want a code that displays the dates less than the current date of the day I tried that following code but it only fetches the lower days and does not look For the month or year if it is greater or not than the current day's date
tbl = db.readData("SELECT * from Payments where date_batch < CONVERT(varchar(50),GetDate(), 103)", "");
DgvSearch.DataSource = tbl;
The problem with the previous code is that it doesn't fetch the date lower by day, month and year.
Fetches the date less than the current date in terms of day only I want in terms of day, month and year
Ok, so I'm going to assume date_batch is a VARCHAR(10) or similar and contains data like:
28/12/2021
29/11/2021
30/08/2021
31/12/2021
As you can see these "strings that look like dates to a human" are in order. They are not in date order, they are in alphabetical order. Big difference - SQLServer sorts strings alphabetically. When you ask for strings "less than x" it uses alphabetical sorting rules to determine "less than"-ness
Don't stores dates in a string. SQLServer has several date specific datatypes. Use them.
The following process will dig you out of the hole you've dug yourself into:
ALTER TABLE Payments ADD COLUMN BatchDate DATE;
UPDATE Payments SET BatchDate = TRY_CONVERT(Date, date_batch, 103);
Now go look at your table and sanity check it:
SELECT * FROM payments WHERE batchdate is null and date_batch is not null
This shows any dates that didn't convert. Correct their wonky bad data and run the update again.
Do another select, of all the data, and eyeball it; does it look sensible? Do you have any dates that have been put in as 02/03/2021 when they should have been 03/02/2021 etc
Now your table is full of nice dates, get rid of the strings;
ALTER TABLE Payments DROP COLUMN date_batch;
Maybe rename the column, but in SQLServer and c# WeCallThingsNamesLikeThis, we_dont_call_them_names_like_this
sp_rename 'Payments.BatchDate', 'date-batch', 'COLUMN';
Now you can do:
SELECT * FROM payments WHERE batchDate < GetDate()
And never again store dates in a string
Let me start by saying that I am somewhat new to SQL/Snowflake and have been putting together queries for roughly 2 months. Some of my query language may not be ideal and I fully understand if there's a better, more efficient way to execute this query. Any and all input is appreciated. Also, this particular query is being developed in Snowflake.
My current query is pulling customer volumes by department and date based on a 45 day window with a 24 day lookback from current date and a 21 day look forward based on scheduled appointments. Each date is grouped based on where it falls within that 45 day window: current week (today through next 7 days), Week 1 (forward-looking days 8-14), and Week 2 (forward-looking days 15-21). I have been working to try and build out a comparison column that, for any date that lands within either the Week 1 or Week 2 group, will pull in prior period volumes from either 14 days prior (Week 1) or 21 days prior (Week 2) but am getting nowhere. Is there a best-practice for this type of column? Generic example of the current output is attached. Please note that the 'Prior Wk' column in the sample output was manually populated in an effort to illustrate the way this column should ideally work.
I have tried several different iterations of count(case...) similar to that listed below; however, the 'Prior Wk' column returns the count of encounters/scheduled encounters for the same day rather than those that occurred 14 or 21 days ago.
Count(Case When datediff(dd,SCHED_DTTM,getdate())
between -21 and -7 then 1 else null end
) as "Prior Wk"
I've tried to use an IFF statement as shown below, but no values return.
(IFF(ENCOUNTER_DATE > dateadd(dd,8,getdate()),
count(case when ENC_STATUS in (“Phone”,”InPerson”) AND
datediff(dd,ENCOUNTER_Date,getdate()) between 7 and 14 then 1
else null end), '0')
) as "Prior Wk"
Also have attempted creating and using a temporary table (example included) but have not managed to successfully pull information from the temp table that didn't completely disrupt my encounter/scheduled counts. Please note for this approach I've only focused on the 14 day group and have not begun to look at the 21 day/Week 2 group. My attempt to use the temp table to resolve the problem centered around the following clause (temp table alias: "Date1"):
CASE when AHS.GL_Number = "DATEVISIT1"."GL_NUMBER" AND
datevisit1.lookback14 = dateadd(dd,14,PE.CONTACT_Date)
then "DATEVISIT1"."ENC_Count"
else null end
as "Prior Wk"*
I am extremely appreciative of any insight on the current best practices around pulling prior period data into a column alongside current period data. Any misuse of terminology on my part is not deliberate.
I'm struggling to understand your requirement but it sounds like you need to use window functions https://docs.snowflake.com/en/sql-reference/functions-analytic.html, in this case likely a SUM window function. The LAG window function, https://docs.snowflake.com/en/sql-reference/functions/lag.html, might also be of some help
Long title, easy meaning:
How is it possible to extract from a date like "2014-04-04 10:47:30.000", which is stored in one column, it's components like year, month and day?
I'm not interested in the time.
For example, I have a table called "Incidents". Inside the table we got a column called "IncidentID" and a column called "ReportingDate", in which dates like the above-mentionend are stored. Let's say we have about 50k Incidents, therefore we have also 50k dates.
A year has 365 days. I want to query for the count of the Incidents, which were reported on different dates - for instance on the 5th of October 2013.
So: How can I get the components of the date and put them into another table while having own columns for the components and how can I query for the Incidents as well?
I guess at first I have to change the datatype of the date from DATETIME to DATE, but I'm not quite sure how to go further. May anyone help me while giving me a code and explains me what it does for a sql-noob? :-)
To achieve this
I want to query for the count of the Incidents, which were reported on
different dates - for instance on the 5th of October 2013.
you haven't do this:
I guess at first I have to change the datatype of the date from
DATETIME to DATE, but I'm not quite sure how to go further.
Just query
SELECT
IncidentID
FROM incidents
WHERE ReportingDate >= '20131005'
AND ReportingDate < '20131006'
I am wondering if it's possible (without actually parsing the given string) to get the actual range (in terms of days, minutes or seconds) that is specified when you have an SQL statement like
[select 'x'
from dual
where date between to_date('20111113152049')
and to_date('20120113152049')]
I am working on a query where I'm given a string in the form of
"between to_date(A) and to_date(B)"
and would like to get that value in days to compare to a policy we let the user set so they don't enter a date range longer than say a week.
Assuming you're looking for a theoretical answer (that is: don't take this into production) this could work:
Prerequistes:
have three tables: days_seq(day_seq), month_seq(mth_seq) and year_seq(yr_seq)
days has the numbers 1...31, month 1..12, years 2011....?
Use te following query (I used access because I don't have proper RDBMS available here, keep in mind that MS-ACCESS/JET is forgiving in the use of the Dateserial function, that is, it doesn't break when you ask the dateserial for february, 30th, 2012)
SELECT Max(DateSerial(
[year_seq]![yr_seq]
,[month_seq]![mth_seq]
, [days_seq]![day_seq]))
-
Min(DateSerial(
[year_seq]![yr_seq]
,[month_seq]![mth_seq]
,[days_seq]![day_seq])) AS days
FROM days_seq, month_seq, year_seq
WHERE DateSerial(
[year_seq]![yr_seq]
,[month_seq]![mth_seq]
,[days_seq]![day_seq])
BETWEEN #2012-02-1# AND #2012-02-28#
The query basically produces a carthesian product of three tables which generates all possible days in months, months in a year for as many years as you have in the years table.
Bonus:
You could off-course generate a permanent Calendar table as X-Zero suggests.
table calendar([date])
INSERT INTO calendar
SELECT DISTINCT DateSerial(
[year_seq]![yr_seq]
,[month_seq]![mth_seq]
, [days_seq]![day_seq]))
FROM days_seq, month_seq, year_seq
You still have to pick your start year and your end year wisely. According to the Maya's an enddate of december 21st, 2012 will do.
I have an SQLite database with the following fields for example:
date (yyyymmdd fomrat)
total (0.00 format)
There is typically 2 months of records in the database. Does anyone know a SQL query to find a weekly average?
I could easily just execute:
SELECT COUNT(1) as total_records, SUM(total) as total FROM stats_adsense
Then just divide total by 7 but unless there is exactly x days that are divisible by 7 in the db I don't think it will be very accurate, especially if there is less than 7 days of records.
To get a daily summary it's obviously just total / total_records.
Can anyone help me out with this?
You could try something like this:
SELECT strftime('%W', thedate) theweek, avg(total) theaverage
FROM table GROUP BY strftime('%W', thedate)
I'm not sure how the syntax would work in SQLite, but one way would be to parse out the date parts of each [date] field, and then specifying which WEEK and DAY boundaries in your WHERE clause and then GROUP by the week. This will give you a true average regardless of whether there are rows or not.
Something like this (using T-SQL):
SELECT DATEPART(w, theDate), Avg(theAmount) as Average
FROM Table
GROUP BY DATEPART(w, theDate)
This will return a row for every week. You could filter it in your WHERE clause to restrict it to a given date range.
Hope this helps.
Your weekly average is
daily * 7
Obviously this doesn't take in to account specific weeks, but you can get that by narrowing the result set in a date range.
You'll have to omit those records in the addition which don't belong to a full week. So, prior to summing up, you'll have to find the min and max of the dates, manipulate them such that they form "whole" weeks, and then run your original query with a WHERE that limits the date values according to the new range. Maybe you can even put all this into one query. I'll leave that up to you. ;-)
Those values which are "truncated" are not used then, obviously. If there's not enough values for a week at all, there's no result at all. But there's no solution to that, apparently.