People of Stack Overflow!
Thanks for taking the time to read this question. What I am trying to accomplish is to pivot some data all from just one table.
The original table has multiple datetime entries of specific events (e.g. when the customer was added add_time and when the customer was lost lost_time).
This is one part of two rows of the deals table:
id
add_time
last_mail_time
lost_time
5
2020-03-24 09:29:24
2020-04-03 13:20:29
NULL
310
2020-03-24 09:29:24
NULL
2020-04-03 13:20:29
I want to create a view of this table. A view that has one row for each distinct date and counts the number of events at this specific time.
This is the goal (times do not match with the example!):
I have working code, like this:
SELECT DISTINCT
change_datetime,
(SELECT COUNT(add_time) as add_time_count FROM deals WHERE add_time::date = change_datetime),
(SELECT COUNT(lost_time) as lost_time_count FROM deals WHERE lost_time::date = change_datetime)
FROM (
SELECT
add_time::date AS change_datetime
FROM
deals
UNION ALL
SELECT
lost_time::date AS change_datetime
FROM
deals
) AS foo
WHERE change_datetime IS NOT NULL
ORDER BY
change_datetime;
but this has some ugly O(n2) queries and takes a lot of time.
Is there a better, more performant way to achieve this?
Thanks!!
You can use a lateral join to unpivot and then aggregate:
select t::date,
count(*) filter (where which = 'add'),
count(*) filter (where which = 'mail'),
count(*) filter (where which = 'lost')
from deals d cross join lateral
(values (add_time, 'add'),
(last_mail_time, 'mail'),
(lost_time, 'lost')
) v(t, which)
group by t::date;
Related
I have two tables, apps and reviews (simplified for the sake of discussion):
apps table
id int
reviews table
id int
review_date date
app_id int (foreign key that points to apps)
2 questions:
1. How can I write a query / function to answer the following question?:
Given a series of dates from the earliest reviews.review_date to the latest reviews.review_date (incrementing by a day), for each date, D, which apps had the most reviews if the app's earliest review was on or later than D?
I think I know how to write a query if given an explicit date:
SELECT
apps.id,
count(reviews.*)
FROM
reviews
INNER JOIN apps ON apps.id = reviews.app_id
group by
1
having
min(reviews.review_date) >= '2020-01-01'
order by 2 desc
limit 10;
But I don't know how to query this dynamically given the desired date series and compile all this information in a single view.
2. What's the best way to model this data?
It would be nice to have the # of reviews at the time for each date as well as the app_id. As of now I'm thinking something that might look like:
... 2020-01-01_app_id | 2020-01-01_review_count | 2020-01-02_app_id | 2020-01-02_review_count ...
But I'm wondering if there's a better way to do this. Stitching the data together also seems like a challenge.
I think this is what you are looking for:
Postgres 13 or newer
WITH cte AS ( -- MATERIALIZED
SELECT app_id, min(review_date) AS earliest_review, count(*)::int AS total_ct
FROM reviews
GROUP BY 1
)
SELECT *
FROM (
SELECT generate_series(min(review_date)
, max(review_date)
, '1 day')::date
FROM reviews
) d(review_window_start)
LEFT JOIN LATERAL (
SELECT total_ct, array_agg(app_id) AS apps
FROM (
SELECT app_id, total_ct
FROM cte c
WHERE c.earliest_review >= d.review_window_start
ORDER BY total_ct DESC
FETCH FIRST 1 ROWS WITH TIES -- new & hot
) sub
GROUP BY 1
) a ON true;
WITH TIES makes it a bit cheaper. Added in Postgres 13 (currently beta). See:
Get top row(s) with highest value, with ties
Postgres 12 or older
WITH cte AS ( -- MATERIALIZED
SELECT app_id, min(review_date) AS earliest_review, count(*)::int AS total_ct
FROM reviews
GROUP BY 1
)
SELECT *
FROM (
SELECT generate_series(min(review_date)
, max(review_date)
, '1 day')::date
FROM reviews
) d(review_window_start)
LEFT JOIN LATERAL (
SELECT total_ct, array_agg(app_id) AS apps
FROM (
SELECT total_ct, app_id
, rank() OVER (ORDER BY total_ct DESC) AS rnk
FROM cte c
WHERE c.earliest_review >= d.review_window_start
) sub
WHERE rnk = 1
GROUP BY 1
) a ON true;
db<>fiddle here
Same as above, but without WITH TIES.
We don't need to involve the table apps at all. The table reviews has all information we need.
The CTE cte computes earliest review & current total count per app. The CTE avoids repeated computation. Should help quite a bit.
It is always materialized before Postgres 12, and should be materialized automatically in Postgres 12 since it is used many times in the main query. Else you could add the keyword MATERIALIZED in Postgres 12 or later to force it. See:
How to force evaluation of subquery before joining / pushing down to foreign server
The optimized generate_series() call produces the series of days from earliest to latest review. See:
Generating time series between two dates in PostgreSQL
Join a count query on generate_series() and retrieve Null values as '0'
Finally, the LEFT JOIN LATERAL you already discovered. But since multiple apps can tie for the most reviews, retrieve all winners, which can be 0 - n apps. The query aggregates all daily winners into an array, so we get a single result row per review_window_start. Alternatively, define tiebreaker(s) to get at most one winner. See:
What is the difference between LATERAL JOIN and a subquery in PostgreSQL?
If you are looking for hints, then here are a few:
Are you aware of generate_series() and how to use it to compose a table of dates given a start and end date? If not, then there are plenty of examples on this site.
To answer this question for any given date, you need to have only two measures for each app, and only one of these is used to compare an app against other apps. Your query in part 1 shows that you know what these two measures are.
Hints 1 and 2 should be enough to get this done. The only thing I can add is for you not to worry about making the database do "too much work." That is what it is there to do. If it does not do it quickly enough, then you can think about optimizations, but before you get to that step, concentrate on getting the answer that you want.
Please comment if you need further clarification on this.
The missing piece for me was lateral join.
I can accomplish just about what I want using the following:
select
review_windows.review_window_start,
id,
review_total,
earliest_review
from
(
select
date_trunc('day', review_windows.review_windows) :: date as review_window_start
from
generate_series(
(
SELECT
min(reviews.review_date)
FROM
reviews
),
(
SELECT
max(reviews.review_date)
FROM
reviews
),
'1 year'
) review_windows
order by
1 desc
) review_windows
left join lateral (
SELECT
apps.id,
count(reviews.*) as review_total,
min(reviews.review_date) as earliest_review
FROM
reviews
INNER JOIN apps ON apps.id = reviews.app_id
where
reviews.review_date >= review_windows.review_window_start
group by
1
having
min(reviews.review_date) >= review_windows.review_window_start
order by
2 desc,
3 desc
limit
2
) apps_most_reviews on true;
I have two datasets hosted in Snowflake with social media follower counts by day. The main table we will be using going forward (follower_counts) shows follower counts by day:
This table is live as of 4/4/2020 and will be updated daily. Unfortunately, I am unable to get historical data in this format. Instead, I have a table with historical data (follower_gains) that shows net follower gains by day for several accounts:
Ideally - I want to take the follower_count value from the minimum date in the current table (follower_counts) and subtract the sum of gains (organic + paid gains) for each day, until the minimum date of the follower_gains table, to fill in the follower_count historically. In addition, there are several accounts with data in these tables, so it would need to be grouped by account. It should look like this:
I've only gotten as far as unioning these two tables together, but don't even know where to start with looping through these rows:
WITH a AS (
SELECT
account_id,
date,
organizational_entity,
organizational_entity_type,
vanity_name,
localized_name,
localized_website,
organization_type,
total_followers_count,
null AS paid_follower_gain,
null AS organic_follower_gain,
account_name,
last_update
FROM follower_counts
UNION ALL
SELECT
account_id,
date,
organizational_entity,
organizational_entity_type,
vanity_name,
localized_name,
localized_website,
organization_type,
null AS total_followers_count,
organic_follower_gain,
paid_follower_gain,
account_name,
last_update
FROM follower_gains)
SELECT
a.account_id,
a.date,
a.organizational_entity,
a.organizational_entity_type,
a.vanity_name,
a.localized_name,
a.localized_website,
a.organization_type,
a.total_followers_count,
a.organic_follower_gain,
a.paid_follower_gain,
a.account_name,
a.last_update
FROM a
ORDER BY date desc LIMIT 100
UPDATE: Changed union to union all and added not exists to remove duplicates. Made changes per the comments.
NOTE: Please make sure you don't post images of the tables. It's difficult to recreate your scenario to write a correct query. Test this solution and update so that I can make modifications if necessary.
You don't loop through in SQL because its not a procedural language. The operation you define in the query is performed for all the rows in a table.
with cte as (SELECT a.account_id,
a.date,
a.organizational_entity,
a.organizational_entity_type,
a.vanity_name,
a.localized_name,
a.localized_website,
a.organization_type,
(a.follower_count - (b.organic_gain+b.paid_gain)) AS follower_count,
a.account_name,
a.last_update,
b.organic_gain,
b.paid_gain
FROM follower_counts a
JOIN follower_gains b ON a.account_id = b.account_id
AND b.date < (select min(date) from
follower_counts c where a.account.id = c.account_id)
)
SELECT b.account_id,
b.date,
b.organizational_entity,
b.organizational_entity_type,
b.vanity_name,
b.localized_name,
b.localized_website,
b.organization_type,
b.follower_count,
b.account_name,
b.last_update,
b.organic_gain,
b.paid_gain
FROM cte b
UNION ALL
SELECT a.account_id,
a.date,
a.organizational_entity,
a.organizational_entity_type,
a.vanity_name,
a.localized_name,
a.localized_website,
a.organization_type,
a.follower_count,
a.account_name,
a.last_update,
NULL as organic_gain,
NULL as paid_gain
FROM follower_counts a where not exists (select 1 from
follower_gains c where a.account_id = c.account_id AND a.date = c.date)
You could do something like this, instead of using the variable you can just wrap it another bracket and write at end ) AS FollowerGrowth
DECLARE #FollowerGrowth INT =
( SELECT total_followers_count
FROM follower_gains
WHERE AccountID = xx )
-
( SELECT TOP 1 follower_count
FROM follower_counts
WHERE AccountID = xx
ORDER BY date ASCENDING )
I got help with a function yesterday to correctly get the count of multiple items in a column based on multiple criteria/columns. However, if there is a way to get the DISTINCT count of all the entries in the table based on aggregated GROUP BY statement.
SELECT TIME = ap.day,
acms.tenantId,
acms.CallingService,
policyList = ltrim(sp.value),
policyInstanceList = ltrim(dp.value),
COUNT(*) AS DISTINCTCount
FROM dbo.acms_data acms
CROSS APPLY string_split(acms.policyList, ',') sp
CROSS APPLY string_split(acms.policyInstanceList, ',') dp
CROSS APPLY (select day = convert(date, acms.[Time])) ap
GROUP BY ap.day, acms.tenantId, sp.value, dp.value, acms.CallingService
I would just like to know if there would be a way to see if there is a workaround for using DISTINCT and Count(*) together and whether or not it would affect my results to make this algorithm potentially invulnerable to duplicate entries.
The reason why I have to use COUNT(*) is because I am aggregating based on every column in the table not just a specific column or multiple.
We can use DISTINCT with COUNT together like this example.
USE AdventureWorks2012
GO
-- This query shows 290 JobTitle
SELECT COUNT(JobTitle) Total_JobTitle
FROM [HumanResources].[Employee]
GO
-- This query shows only 67 JobTitle
SELECT COUNT( DISTINCT JobTitle) Total_Distinct_JobTitle
FROM [HumanResources].[Employee]
GO
I need to update the following query so that it only returns one child record (remittance) per parent (claim).
Table Remit_To_Activate contains exactly one date/timestamp per claim, which is what I wanted.
But when I join the full Remittance table to it, since some claims have multiple remittances with the same date/timestamps, the outermost query returns more than 1 row per claim for those claim IDs.
SELECT * FROM REMITTANCE
WHERE BILLED_AMOUNT>0 AND ACTIVE=0
AND REMITTANCE_UUID IN (
SELECT REMITTANCE_UUID FROM Claims_Group2 G2
INNER JOIN Remit_To_Activate t ON (
(t.ClaimID = G2.CLAIM_ID) AND
(t.DATE_OF_LATEST_REGULAR_REMIT = G2.CREATE_DATETIME)
)
where ACTIVE=0 and BILLED_AMOUNT>0
)
I believe the problem would be resolved if I included REMITTANCE_UUID as a column in Remit_To_Activate. That's the REAL issue. This is how I created the Remit_To_Activate table (trying to get the most recent remittance for a claim):
SELECT MAX(create_datetime) as DATE_OF_LATEST_REMIT,
MAX(claim_id) AS ClaimID,
INTO Latest_Remit_To_Activate
FROM Claims_Group2
WHERE BILLED_AMOUNT>0
GROUP BY Claim_ID
ORDER BY Claim_ID
Claims_Group2 contains these fields:
REMITTANCE_UUID,
CLAIM_ID,
BILLED_AMOUNT,
CREATE_DATETIME
Here are the 2 rows that are currently giving me the problem--they're both remitts for the SAME CLAIM, with the SAME TIMESTAMP. I only want one of them in the Remits_To_Activate table, so only ONE remittance will be "activated" per Claim:
enter image description here
You can change your query like this:
SELECT
p.*, latest_remit.DATE_OF_LATEST_REMIT
FROM
Remittance AS p inner join
(SELECT MAX(create_datetime) as DATE_OF_LATEST_REMIT,
claim_id,
FROM Claims_Group2
WHERE BILLED_AMOUNT>0
GROUP BY Claim_ID
ORDER BY Claim_ID) as latest_remit
on latest_remit.claim_id = p.claim_id;
This will give you only one row. Untested (so please run and make changes).
Without having more information on the structure of your database -- especially the structure of Claims_Group2 and REMITTANCE, and the relationship between them, it's not really possible to advise you on how to introduce a remittance UUID into DATE_OF_LATEST_REMIT.
Since you are using SQL Server, however, it is possible to use a window function to introduce a synthetic means to choose among remittances having the same timestamp. For example, it looks like you could approach the problem something like this:
select *
from (
select
r.*,
row_number() over (partition by cg2.claim_id order by cg2.create_datetime desc) as rn
from
remittance r
join claims_group2 cg2
on r.remittance_uuid = cg2.remittance_uuid
where
r.active = 0
and r.billed_amount > 0
and cg2.active = 0
and cg2.billed_amount > 0
) t
where t.rn = 1
Note that that that does not depend on your DATE_OF_LATEST_REMIT table at all, it having been subsumed into the inline view. Note also that this will introduce one extra column into your results, though you could avoid that by enumerating the columns of table remittance in the outer select clause.
It also seems odd to be filtering on two sets of active and billed_amount columns, but that appears to follow from what you were doing in your original queries. In that vein, I urge you to check the results carefully, as lifting the filter conditions on cg2 columns up to the level of the join to remittance yields a result that may return rows that the original query did not (but never more than one per claim_id).
A co-worker offered me this elegant demonstration of a solution. I'd never used "over" or "partition" before. Works great! Thank you John and Gaurasvsa for your input.
if OBJECT_ID('tempdb..#t') is not null
drop table #t
select *, ROW_NUMBER() over (partition by CLAIM_ID order by CLAIM_ID) as ROW_NUM
into #t
from
(
select '2018-08-15 13:07:50.933' as CREATE_DATE, 1 as CLAIM_ID, NEWID() as
REMIT_UUID
union select '2018-08-15 13:07:50.933', 1, NEWID()
union select '2017-12-31 10:00:00.000', 2, NEWID()
) x
select *
from #t
order by CLAIM_ID, ROW_NUM
select CREATE_DATE, MAX(CLAIM_ID), MAX(REMIT_UUID)
from #t
where ROW_NUM = 1
group by CREATE_DATE
Hi how can I get the percentage of each record over the total?
Lets imagine I have one table with the following
ID code Points
1 101 2
2 201 3
3 233 4
4 123 1
The percentage for ID 1 is 20% for 2 is 30% and so one
how do I get it?
There's a couple approaches to getting that result.
You essentially need the "total" points from the whole table (or whatever subset), and get that repeated on each row. Getting the percentage is a simple matter of arithmetic, the expression you use for that depends on the datatypes, and how you want that formatted.
Here's one way (out a couple possible ways) to get the specified result:
SELECT t.id
, t.code
, t.points
-- , s.tot_points
, ROUND(t.points * 100.0 / s.tot_points,1) AS percentage
FROM onetable t
CROSS
JOIN ( SELECT SUM(r.points) AS tot_points
FROM onetable r
) s
ORDER BY t.id
The view query s is run first, that gives a single row. The join operation matches that row with every row from t. And that gives us the values we need to calculate a percentage.
Another way to get this result, without using a join operation, is to use a subquery in the SELECT list to return the total.
Note that the join approach can be extended to get percentage for each "group" of records.
id type points %type
-- ---- ------ -----
1 sold 11 22%
2 sold 4 8%
3 sold 25 50%
4 bought 1 50%
5 bought 1 50%
6 sold 10 20%
To get that result, we can use the same query, but a a view query for s that returns total GROUP BY r.type, and then the join operation isn't a CROSS join, but a match based on type:
SELECT t.id
, t.type
, t.points
-- , s.tot_points_by_type
, ROUND(t.points * 100.0 / s.tot_points_by_type,1) AS `%type`
FROM onetable t
JOIN ( SELECT r.type
, SUM(r.points) AS tot_points
FROM onetable r
GROUP BY r.type
) s
ON s.type = t.type
ORDER BY t.id
To do that same result with the subquery, that's going to be a correlated subquery, and that subquery is likely to get executed for every row in t.
This is why it's more natural for me to use a join operation, rather than a subquery in the SELECT list... even when a subquery works the same. (The patterns we use for more complex queries, like assigning aliases to tables, qualifying all column references, and formatting the SQL... those patterns just work their way back into simple queries. The rationale for these patterns is kind of lost in simple queries.)
try like this
select id,code,points,(points * 100)/(select sum(points) from tabel1) from table1
To add to a good list of responses, this should be fast performance-wise, and rather easy to understand:
DECLARE #T TABLE (ID INT, code VARCHAR(256), Points INT)
INSERT INTO #T VALUES (1,'101',2), (2,'201',3),(3,'233',4), (4,'123',1)
;WITH CTE AS
(SELECT * FROM #T)
SELECT C.*, CAST(ROUND((C.Points/B.TOTAL)*100, 2) AS DEC(32,2)) [%_of_TOTAL]
FROM CTE C
JOIN (SELECT CAST(SUM(Points) AS DEC(32,2)) TOTAL FROM CTE) B ON 1=1
Just replace the table variable with your actual table inside the CTE.