I have below prices table and I want to obtain last_30_days price array and last_year_price from it. As shown below
CREATE TABLE prices
(
id integer NOT NULL,
"time" timestamp without time zone NOT NULL,
close double precision NOT NULL,
CONSTRAINT prices_pkey PRIMARY KEY (id, "time")
)
select id,time,first_value(close) over (partition by id order by time range between '1 year' preceding and CURRENT ROW) as prev_year_close,
array_agg(p.close) OVER (PARTITION BY id ORDER BY time ROWS BETWEEN 30 PRECEDING AND CURRENT ROW) as prices_30
from prices p
However I want to place a where clause on the prices table to get last_30_days price array and last_year_price for some specific rows. Eg. where time >= '1 week' interval (so I run this query only for last 1 week values as opposed to the entire table)
But a where clause pre-filtering the rows and then window partition only runs on that conditioned rows which results in wrong results. it is giving result like
time, id, last_30_days
-1day, X, [A,B,C,D,E, F,G]
-2day, X, [A,B,C,D,E,F]
-3day, X, [A,B,C,D,E]
-4day, X, [A,B,C,D]
-5day, X, [A,B,C]
-6day, X, [A,B]
-7day, X, [A]
How do I fix this so that partition over window always takes 30 values irrespective of where condition? Without having to run the query always on the entire table and then selecting a subset of rows with where clause. My prices table is huge and running it on entire table is very expensive.
EDIT
CREATE TABLE prices
(
id integer NOT NULL,
"time" timestamp without time zone NOT NULL,
close double precision NOT NULL,
prev_30 double precision[],
prev_year double precision,
CONSTRAINT prices_pkey PRIMARY KEY (id, "time")
)
Use a subquery:
SELECT *
FROM (select id, time,
first_value(close) over (partition by id order by time range between '1 year' preceding and CURRENT ROW) as prev_year_close,
array_agg(p.close) OVER (PARTITION BY id ORDER BY time ROWS BETWEEN 30 PRECEDING AND CURRENT ROW) as prices_30 I
from prices p
WHERE time >= current_timestamp - INTERVAL '1 year 1 week') AS q
WHERE time >= current_timestamp - INTERVAL '1 week' ;
Related
Sut:
create table meter.materialized_quarters
(
id int4 not null generated by default as identity,
tm timestamp without time zone
,constraint pk_materialized_quarters primary key (id)
--,constraint uq_materialized_quarters unique (tm)
);
Then setup data:
insert into meter.materialized_quarters (tm)
select GENERATE_SERIES ('1999-01-01', '2030-10-30', interval '15 minute');
And check data:
select count(*),tm
from meter.materialized_quarters
group by tm
having count(*)> 1
Some results:
count|tm |
-----+-----------------------+
2|1999-10-31 02:00:00.000|
2|1999-10-31 02:15:00.000|
2|1999-10-31 02:30:00.000|
2|1999-10-31 02:45:00.000|
2|2000-10-29 02:00:00.000|
2|2000-10-29 02:15:00.000|
2|2000-10-29 02:30:00.000|
2|2000-10-29 02:45:00.000|
2|2001-10-28 02:00:00.000|
2|2001-10-28 02:15:00.000|
2|2001-10-28 02:30:00.000|
....
Details:
select * from meter.materialized_quarters where tm = '1999-10-31 01:45:00';
Result:
id |tm |
-----+-----------------------+
29092|1999-10-31 01:45:00.000|
As I see, 29092 is maximum series of nonduplicated data generated by: GENERATE_SERIES with 15 minutes interval.
How to fill table (meter.materialized_quarters) from 1999 to 2030?
One solution is:
insert into meter.materialized_quarters (tm)
select GENERATE_SERIES ('1999-01-01', '1999-10-31 01:45:00', interval '15 minute');
then:
insert into meter.materialized_quarters (tm)
select GENERATE_SERIES ('1999-10-31 02:00:00.000', '2000-10-29 00:00:00.000', interval '15 minute');
and again, and again.
Or
with bad as (
select count(*),tm
from meter.materialized_quarters
group by tm
having count(*)> 1
)
, ids as (
select mq1.id, mq2.id as iddel
from meter.materialized_quarters mq1 inner join bad on bad.tm = mq1.tm inner join meter.materialized_quarters mq2 on bad.tm = mq2.tm
where mq1.id<mq2.id
)
delete from meter.materialized_quarters
where id in (select iddel from ids);
Is there more 'elegant' way?
EDIT.
I see the problem.
xxxx-10-29 02:00:00 - summer time become winter time.
select GENERATE_SERIES ('1999-10-31 01:45:00', '1999-10-31 02:00:00', interval '15 minute');
Your problem is the conversion from timestamp WITH time zone which is returned by generate_series() and your column which is defined as timestamp WITHOUT time zone.
1999-10-31 is the day where daylight savings time changes (at least in some countries)
If you change your column to timestamp WITH time zone your code works without any modification.
Example
If you want to stick with timestamp WITHOUT timestamp you need to convert the value returned by generate_series()
insert into materialized_quarters (tm)
select g.tm at time zone 'UTC' --<< change to the time zone you need
from GENERATE_SERIES ('1999-01-01', '2030-10-30', interval '15 minute') as g(tm)
Example
I have the dataset:
The problem is that the records are added only if an event happened, e.g. for the row with id 13897, the record was updated on 4/18/2020 and then on 5/1/2020 - the status was changed. What I need is the status of each record at the end of every month.
I was thinking about the below logic:
generate the series of dates from the min(date) till now - T1
get distinct id from the dataset - T2
do cross join between two above tables so that we get a new row for every row in the second table - T3
extract the dataset with all required fields - T4
merge T3 and T4 by concatenate(date and id) - T5
sort T5 by id and d asc - T5
fill-down all the fields grouped by id - T5
generate the series of dates from min(date) till now with the interval of one month and get the last day of each month - T6
merge T5 and T6 by date - right join so that we get only rows with the date = end of month
I am on step 6.
SELECT *
FROM (SELECT d, Concat(dt, t2.id) AS cnct
FROM (SELECT d,d::date AS dt
FROM generate_series(
( SELECT min(created_at::date)
FROM new_table), CURRENT_DATE , interval '1 day') d) t1
CROSS JOIN
(SELECT DISTINCT id FROM new_table )) t2)t3
--in case if a record with the same id was updated several times throughout the day
LEFT JOIN (WITH cte AS
( SELECT id, status, created_at at time zone 'eat' at time zone 'utc' AS "created_at", updated_at::date AS date, updated_at::date, row_number() OVER (partition BY id, updated_at::date ORDER BY updated_at DESC) rnFROM new_table ))SELECT cte.*, Concat(updated_at::date, id) AS cnct
FROM cte
WHERE rn = 1) t4
ON t3.cnct = t4.cnct
I am stuck on step 7. I found fill column with last value from partition in postgresql but it is not what I need. I envision that I need to sort by a date block i.e. dates from min date to now for one id - 13894 are to be considered block 1, dates from min date to now for another id - 13897 are to be considered block 2. The next step I thought is to fill-down all fields per a block.
And another question, how do you deal with the event-based data to adapt it for the time-series?
Tried:
You can use Postgresql's DISTINCT ON feature to do this. We'll generate a series with the start of every month (you'll need to supply start and end dates here) and put the ID and the date into the DISTINCT ON so that we get only one row of new_table for each distinct ID and month pair. Then we simply filter and order to ensure that the row we're getting for each ID and month is the latest row for which the date is before the new month.
SELECT DISTINCT ON (new_table.id, month_start) *
FROM new_table, generate_series(start_date, end_date, interval '1 month') month_start
WHERE new_table.date < month_start
ORDER BY new_table.id, month_start ASC, new_table.date DESC;
(If you need your results to have the last day of the month and not the first day of the next month, you can just subtract 1 day from month_start in your select clause.)
EDIT: Running on the data you supplied, I get this:
SELECT DISTINCT ON (new_table.id, month_start) new_table.id, month_start - interval '1 day' as month_end, new_table.status
FROM new_table, generate_series('2020-05-01', '2020-06-01', interval '1 month') month_start
WHERE new_table.date < month_start
ORDER BY new_table.id, month_start ASC, new_table.date DESC;
id | month_end | status
-------+------------------------+--------
13894 | 2020-04-30 00:00:00-07 | 5
13894 | 2020-05-31 00:00:00-07 | 5
13897 | 2020-04-30 00:00:00-07 | 2
13897 | 2020-05-31 00:00:00-07 | 5
(4 rows)
I have two tables and I am trying to find data gaps in them where the dates do not overlap.
Item Table:
id unique start_date end_date data
1 a 2019-01-01 2019-01-31 X
2 a 2019-02-01 2019-02-28 Y
3 b 2019-01-01 2019-06-30 Y
Plan Table:
id item_unique start_date end_date
1 a 2019-01-01 2019-01-10
2 a 2019-01-15 'infinity'
I am trying to find a way to produce the following
Missing:
item_unique from to
a 2019-01-11 2019-01-14
b 2019-01-01 2019-06-30
step-by-step demo:db<>fiddle
WITH excepts AS (
SELECT
item,
generate_series(start_date, end_date, interval '1 day') gs
FROM items
EXCEPT
SELECT
item,
generate_series(start_date, CASE WHEN end_date = 'infinity' THEN ( SELECT MAX(end_date) as max_date FROM items) ELSE end_date END, interval '1 day')
FROM plan
)
SELECT
item,
MIN(gs::date) AS start_date,
MAX(gs::date) AS end_date
FROM (
SELECT
*,
SUM(same_day) OVER (PARTITION BY item ORDER BY gs)
FROM (
SELECT
item,
gs,
COALESCE((gs - LAG(gs) OVER (PARTITION BY item ORDER BY gs) >= interval '2 days')::int, 0) as same_day
FROM excepts
) s
) s
GROUP BY item, sum
ORDER BY 1,2
Finding the missing days is quite simple. This is done within the WITH clause:
Generating all days of the date range and subtract this result from the expanded list of the second table. All dates that not occur in the second table are keeping. The infinity end is a little bit tricky, so I replaced the infinity occurrence with the max date of the first table. This avoids expanding an infinite list of dates.
The more interesting part is to reaggregate this list again, which is the part outside the WITH clause:
The lag() window function take the previous date. If the previous date in the list is the last day then give out true (here a time changing issue occurred: This is why I am not asking for a one day difference, but a 2-day-difference. Between 2019-03-31 and 2019-04-01 there are only 23 hours because of daylight saving time)
These 0 and 1 values are aggregated cumulatively. If there is one gap greater than one day, it is a new interval (the days between are covered)
This results in a groupable column which can be used to aggregate and find the max and min date of each interval
Tried something with date ranges which seems to be a better way, especially for avoiding to expand long date lists. But didn't come up with a proper solution. Maybe someone else?
I am trying to figure out a way to report how many people are in a location at the same time, down to the second.
I have a table with the id for the person, the date they entered, the time they entered, the date they left and the time they left.
example:
select unique_id, start_date, start_time, end_date, end_time
from My_Table
where start_date between '09/01/2019' and '09/02/2019'
limit 3
"unique_id" "start_date" "start_time" "end_date" "end_time"
989179 "2019-09-01" "06:03:13" "2019-09-01" "06:03:55"
995203 "2019-09-01" "11:29:27" "2019-09-01" "11:30:13"
917637 "2019-09-01" "11:06:46" "2019-09-01" "11:06:59"
i've concatenated the start_date & start_time as well as end_date & end_time so they are 2 fields
select unique_id, ((start_date + start_time)::timestamp without time zone) as start_date,
((end_date + end_time)::timestamp without time zone) as end_date
result example:
"start_date"
"2019-09-01 09:28:54"
so i'm making that a CTE, then using a second CTE that uses generate_series between dates down to the second.
The goal being, the generate series will have a row for every second between the two dates. Then when i join my data sets, i can count how many records exist in my_table where the start_date(plus time) is equal or greater than the generate_series date_time field, and the end_date(plus time) is less than or equal to the generate_series date_time field.
i feel that was harder to explain than it needed to be.
in theory, if a person was in the room from 2019-09-01 00:01:01 and left at 2019-09-01 00:01:03, i would count that record in the generate_series rows 2019-09-01 00:01:01, 2019-09-01 00:01:02 & 2019-09-01 00:01:03.
When i look at the data i can see that i should be returning hundreds of people in the room at specific peak periods. but the query returns all 0's.
is this possibly a field formatting issue i need to adjust?
Here is the query:
with CTE as (
select unique_id, ((start_date+start_time)::timestamp without time zone) as start_date,
((end_date+end_time)::timestamp without time zone) as end_date
from My_table
where start_date between '09/01/2019' and '09/02/2019'
),
time_series as (
select generate_series( (date '2019-09-01')::timestamp, (date '2019-09-02')::timestamp, interval '1 second') as date_time
)
/*FINAL SELECT*/
select date_time, count(B.unique_id) as NumPpl
FROM (
select A.date_time
FROM time_series a
)x
left join CTE b on b.start_date >= x.date_time AND b.end_date <= x.date_time
GROUP BY 1
ORDER BY 1
(partial) result screenshot
Thank you in advance
i should also add i have read only access to this database so i'm not able to create functions.
Simple version: b.start_date >= x.date_time AND b.end_date <= x.date_time will never be true assuming end_date is always after start_date.
Longer version: You also do not need a CTE for the generate_series() and there is no reason for selecting all columns and all rows of this CTE as a subquery. I would also drop the CTE for your original data and just join it to the seconds (NOTE: this does somehow change the query, since you might now take those entries into account, where start_date is earlier than 2019-09-01. If you do not want this, you can add your condition again to the join condition. But I guess this is what you really wanted). I also removed some casts which were not needed. Try this:
SELECT gs.second, COUNT(my.unique_id)
FROM generate_series('2019-09-01'::timestamp, '2019-09-02'::timestamp, interval '1 second') gs (second)
LEFT JOIN my_table my ON (my.start_date + my.start_time) <= gs.second
AND (my.end_date + my.end_time) >= gs.second
GROUP BY 1
ORDER BY 1
Below is my table and i am inserting data from my windows .Net application at every 1 Second Interval. i want to write query to fetch data from the table at every nth interval for example at every 5 second.Below is the query i am using but not getting result as required. Please Help me
CREATE TABLE table_1
(
timestamp_col timestamp without time zone,
value_1 bigint,
value_2 bigint
)
This is my query which i am using
select timestamp_col,value_1,value_2
from (
select timestamp_col,value_1,value_2,
INTERVAL '5 Seconds' * (row_number() OVER(ORDER BY timestamp_col) - 1 )
+ timestamp_col as r
from table_1
) as dt
Where r = 1
Use date_part() function with modulo operator:
select timestamp_col, value_1, value_2
from table_1
where date_part('second', timestamp_col)::int % 5 = 0