suppose I have a table MyTable with a column some_date (date type of course) and I want to select the newest 3 months data (or x days).
What is the best way to achieve this?
Please notice that the date should not be measured from today but rather from the date range in the table (which might be older then today)
I need to find the maximum date and compare it to each row - if the difference is less than x days, return it.
All of this should be done with sqlalchemy and without loading the entire table.
What is the best way of doing it? must I have a subquery to find the maximum date? How do I select last X days?
Any help is appreciated.
EDIT:
The following query works in Oracle but seems inefficient (is max calculated for each row?) and I don't think that it'll work for all dialects:
select * from my_table where (select max(some_date) from my_table) - some_date < 10
You can do this in a single query and without resorting to creating datediff.
Here is an example I used for getting everything in the past day:
one_day = timedelta(hours=24)
one_day_ago = datetime.now() - one_day
Message.query.filter(Message.created > one_day_ago).all()
You can adapt the timedelta to whatever time range you are interested in.
UPDATE
Upon re-reading your question it looks like I failed to take into account the fact that you want to compare two dates which are in the database rather than today's day. I'm pretty sure that this sort of behavior is going to be database specific. In Postgres, you can use straightforward arithmetic.
Operations with DATEs
1. The difference between two DATES is always an INTEGER, representing the number of DAYS difference
DATE '1999-12-30' - DATE '1999-12-11' = INTEGER 19
You may add or subtract an INTEGER to a DATE to produce another DATE
DATE '1999-12-11' + INTEGER 19 = DATE '1999-12-30'
You're probably using timestamps if you are storing dates in postgres. Doing math with timestamps produces an interval object. Sqlalachemy works with timedeltas as a representation of intervals. So you could do something like:
one_day = timedelta(hours=24)
Model.query.join(ModelB, Model.created - ModelB.created < interval)
I haven't tested this exactly, but I've done things like this and they have worked.
I ended up doing two selects - one to get the max date and another to get the data
using the datediff recipe from this thread I added a datediff function and using the query q = session.query(MyTable).filter(datediff(max_date, some_date) < 10)
I still don't think this is the best way, but untill someone proves me wrong, it will have to do...
Related
I'd like some advices to know if what I need to do is achievable with timescale functions.
I've just found out I can use time_bucket_gapfill() to complete missing data, which is amazing! I need data each 5 minutes but I can receive 10 minutes, 30 minutes or 1 hour data. So the function helps me to complete the missing points in order to have only 5 minutes points. Also, I use locf() to set the gapfilled value with last value found.
My question is: can I set a max range when I set the last value found with locf() in order to never overpass 1 hour ?
Example: If the last value found is older than 1 hour ago I don't want to fill gaps, I need to leave it empty to say we have real missing values here.
I think I'm close to something with this but apparently I'm not allowed to use locf() in the same case.
ERROR: multiple interpolate/locf function calls per resultset column not supported
Somebody have an idea how I can resolve that?
How to reproduce:
Create table powers
CREATE table powers (
delivery_point_id BIGINT NOT NULL,
at timestamp NOT NULL,
value BIGINT NOT NULL
);
Create hypertable
SELECT create_hypertable('powers', 'at');
Create indexes
CREATE UNIQUE INDEX idx_dpid_at ON powers(delivery_point_id, at);
CREATE INDEX index_at ON powers(at);
Insert data for one day, one delivery point, point 10 minutes
INSERT INTO powers SELECT 1, at, round(random()*10000) FROM generate_series(TIMESTAMP '2021-01-01 00:00:00', TIMESTAMP '2022-01-02 00:00:00', INTERVAL '10 minutes') AS at;
Remove three hours of data from 4am to 7am
DELETE FROM powers WHERE delivery_point_id = 1 AND at < '2021-01-1 07:00:00' AND at > '2021-01-01 04:00:00';
The query that need to be fixed
SELECT
time_bucket_gapfill('5 minutes', at) AS point_five,
avg(value) AS avg,
CASE
WHEN (locf(at) - at) > interval '1 hour' THEN null
ELSE locf(avg(value))
END AS gapfilled
FROM powers
GROUP BY point_five, at
ORDER BY point_five;
Actual: ERROR: multiple interpolate/locf function calls per resultset column not supported
Expected: Gapfilled values each 5 minutes except between 4am and 7 am (real missing values).
This is a great question! I'm going to provide a workaround for how to do this with the current stuff, but I think it'd be great if you'd open a Github issue as well, because there might be a way to add an option for this that doesn't require a workaround like this.
I also think your attempt was a good approach and just requires a few tweaks to get it right!
The error that you're seeing is that we can't have multiple locf calls in a single column, this is a limitation that's pretty easy to work around as we can just shift both of them into a subquery, but that's not enough. The other thing that we need to change is that locf only works on aggregates, right now, you’re trying to use it on a column (at) that isn’t aggregated, which isn’t going to work, because it wouldn’t know which of the values of at in a time_bucket to “pull forward” for the gapfill.
Now you said you want to fill data as long as the previous point wasn’t more than one hour ago, so, we can take the last value of at in the bucket by using last(at, at) this is also the max(at) so either of those aggregates would work. So we put that into a CTE (common table expression or WITH query) and then we do the case statement outside like so:
WITH filled as (SELECT
time_bucket_gapfill('5 minutes', at) AS point_five,
avg(value) AS avg,
locf(last(at, at)) as filled_from,
locf(avg(value)) as filled_avg
FROM powers
WHERE at BETWEEN '2021-01-01 01:30:00' AND '2021-01-01 08:30:00'
AND delivery_point_id = 1
GROUP BY point_five
ORDER BY point_five)
SELECT point_five,
avg,
filled_from,
CASE WHEN point_five - filled_from > '1 hour'::interval THEN NULL
ELSE filled_avg
END as gapfilled
FROM filled;
Note that I’ve tried to name my CTE expressively so that it’s a little easier to read!
Also, I wanted to point out a couple other hyperfunctions that you might think about using:
heartbeat_agg is a new/experimental one that will help you determine periods when your system is up or down, so if you're expecting points at least every hour, you can use it to find the periods where the delivery point was down or the like.
When you have more irregular sampling or want to deal with different data frequencies from different delivery points, I’d take a look a the time_weight family of functions. They can be more efficient than using something like gapfill to upsample, by instead letting you treat all the different sample rates similarly, without having to create more points and more work to do so. Even if you want to, for instance, compare sums of values, you’d use something like integral to get the time weighted sum over a period based on the locf interpolation.
Anyway, hope all that is helpful!
Let's assume that we have the following input parameters:
date [Date]
period [Integer]
The task is the following: build the table which has two columns: date and dayname.
So, if we have date = 2018-07-12 and period = 3 the table should look like this:
date |dayname
-------------------
2018-07-12|THURSDAY
2018-07-13|FRIDAY
2018-07-14|SATURDAY
My solution is the following:
select add_days(date, -1) into previousDay from "DUMMY";
for i in 1..:period do
select add_days(previousDay, i) into nextDay from "DUMMY";
:result.insert((nextDay, dayname(nextDay));
end for;
but I don't like the loop. I assume that it might be a problem in the performance if there are more complicated values that I want to put to result table.
What would be the better solution to achieve the target?
Running through a loop and inserting values one by one is most certainly the slowest possible option to accomplish the task.
Instead, you could use SAP HANA's time series feature.
With a statement like
SELECT to_date(GENERATED_PERIOD_START)
FROM SERIES_GENERATE_TIMESTAMP('INTERVAL 1 DAY', '01.01.0001', '31.12.9999')
you could generate a bounded range of valid dates with a given interval length.
In my tests using this approach brought the time to insert a set of dates from ca. 9 minutes down to 7 seconds...
I've written about that some time ago here and here if you want some more examples for that.
In those examples, I even included the use of series tables that allow for efficient compression of timestamp column values.
Series Data functions include SERIES_GENERATE_DATE which returns a set of values in date data format. So you don't have to bother to convert returned data into desired date format.
Here is a sample code
declare d int := 5;
declare dstart date := '01.01.2018';
SELECT generated_period_start FROM SERIES_GENERATE_DATE('INTERVAL 1 DAY', :dstart, add_days(:dstart, :d));
I'm looking to calculate how many days have passed since a specific date, retrieved from a table in my database. Based on the info I've found on W3Schools (Here), I have attempted using DATEDIFF, but am coming up against a couple of different errors I can't seem to work around.
I have included my code below, and based on this, what I want to happen is this: Select the "DD" from the "Wave_Data" table, and, based on "sysdate", work out how many days have lapsed since then.
SELECT DATEDIFF(WEEKDAY,:P1_DD,SYSDATE)
FROM WAVE_DATA
WHERE WAVE_NUMBER = :P1_WAVE;
The final calculation would then be inputted into a text field within my ApEx database.
Thank you in advance for any help you may be able to provide,
Dominic
In Oracle you can just subtract one Date from another to get the difference (in days) between them:
SELECT SYSDATE - :p1_dd
FROM Wave_Data
WHERE Wave_Number = :p1_wave;
If you want to know the difference between the dates without any time parts then you can do:
SELECT TRUNC( SYSDATE ) - TRUNC( :p1_dd )
FROM Wave_Data
WHERE Wave_Number = :p1_wave;
or
SELECT FLOOR( SYSDATE - :p1_dd )
FROM Wave_Data
WHERE Wave_Number = :p1_wave;
I have a date of birth DATE column in a customer table with ~13 million rows. I would like to query this table to find all customers who were born on a certain month and day of that month, but any year.
Can I do this by casting the date into a char and doing a subscript query on the cast, or should I create an aditional char column, update it to hold just the month and day, or create three new integer columns to hold month, day and year, respectively?
This will be a very frequently used query criteria...
EDIT:... and the table has ~13 million rows.
Can you please provide an example of your best solution?
If it will be frequently used, consider a 'functional index'. Searching on that term at the Informix 11.70 InfoCentre produces a number of relevant hits.
You can use:
WHERE MONTH(date_col) = 12 AND DAY(date_col) = 25;
You can also play games such as:
WHERE MONTH(date_col) * 100 + DAY(date_col) = 1225;
This might be more suitable for a functional index, but isn't as clear for everyday use. You could easily write a stored procedure too:
Note that in the absence of a functional index, invoking functions on a column in the criterion means that an index is unlikely to be used.
CREATE FUNCTION mmdd(date_val DATE DEFAULT TODAY) RETURNING SMALLINT AS mmdd;
RETURN MONTH(date_val) * 100 + DAY(date_val);
END FUNCTION;
And use it as:
WHERE mmdd(date_col) = 1225;
Depending on how frequently you do this and how fast it needs to run you might think about splitting the date column into day, month and year columns. This would make search faster but cause all sorts of other problems when you want to retrieve a whole date (and also problems in validating that it is a date) - not a great idea.
Assuming speed isn't a probem I would do something like:
select *
FROM Table
WHERE Month(*DateOfBirthColumn*) = *SomeMonth* AND DAY(*DateOfBirthColumn*) = *SomeDay*
I don't have informix in front of me at the moment but I think the syntax is right.
Could somebody recommend the query to retrieve records up to today or certain dates?
I'm required to produce an Oracle report where user needs to enter a date and records up to that date will be shown.
I tried
select * from the_table where the_date <= sysdate
However it seems to produce an inaccurate result. What is the better query for this. For now I'm just playing around with sysdate. Later I will need to use a certain date keyed in by the user and all the records up to that date needs to be shown.
Any suggestions?
Sometimes you get inaccurate records because of little differences like minutes and seconds when two dates have the same day/month/year. Try the following
select * from the_table where TRUNC(the_date) <= sysdate
The TRUNC removes the minute and the seconds. Sometimes you get inaccurate records without using that