Suppose we have the following data in the table named My_Tabel:
╔═══════════╦═════════════╦════════════╗
║ ID ║ Person_Name ║ Partner_ID ║
╠═══════════╬═════════════╬════════════╬
║ 101 ║ John ║ 3 ║
║ 100 ║ Miller ║ 0 ║
║ 3 ║ Ruby ║ 101 ║
║ 180 ║ Jack ║ 0 ║
║ 199 ║ George ║ 65 ║
║ 23 ║ Joseph ║ 0 ║
║ 34 ║ Fredrick ║ 117 ║
║ 117 ║ Jinan ║ 34 ║
║ 122 ║ Verena ║ 0 ║
║ 65 ║ Mary ║ 199 ║
╚═══════════╩═════════════╩════════════╝
Where 0 values in Partner_ID Column indicates that he/she is single.
We need to display partnered persons without repeating or duplication, the desired result should look like:
╔═════════════╦══════════════╗
║ Person_Name ║ Partner_Name ║
╠═════════════╬══════════════╬
║ John ║ Ruby ║
║ George ║ Mary ║
║ Fredrick ║ Jinan ║
╚═════════════╩══════════════╝
what is the best SQL query that returns the above results?
I'm using this code:
SELECT
t1.Name, t2.Name
FROM My_Tabel t1
INNER JOIN My_Tabel t2 ON (t2.ID = t1.Partner_ID)
but it the returned result is:
╔═════════════╦══════════════╗
║ Person_Name ║ Partner_Name ║
╠═════════════╬══════════════╬
║ John ║ Ruby ║
║ Ruby ║ John ║
║ George ║ Mary ║
║ Mary ║ George ║
║ Fredrick ║ Jinan ║
║ Jinan ║ Fredrick ║
╚═════════════╩══════════════╝
how the SQL statement should be updated (or replaced with another) to get the desired results?
Just add a condition to get one side of each pair:
SELECT t1.Name, t2.Name
FROM My_Table t1 INNER JOIN
My_Table t2
ON (t2.ID = t1.Partner_ID)
WHERE t1.ID < t2.ID;
Related
I have a table with this structure:
╔══════╦════╦═════════╗
║ Comp ║ ID ║ Desc ║
╠══════╬════╬═════════╣
║ 1 ║ 1 ║ Comp1-1 ║
║ 1 ║ 2 ║ Comp1-2 ║
║ 3 ║ 2 ║ Comp3-2 ║
║ 1 ║ 3 ║ Comp1-3 ║
║ 1 ║ 4 ║ Comp1-4 ║
║ 3 ║ 5 ║ Comp3-5 ║
╚══════╩════╩═════════╝
The dataset I'm creating should have a unique ID.
If an ID exists in Comp1, use that Desc.
If it does not exist in Comp1, use Comp3.
End result should look like this instead:
╔══════╦════╦═════════╗
║ Comp ║ ID ║ Desc ║
╠══════╬════╬═════════╣
║ 1 ║ 1 ║ Comp1-1 ║
║ 1 ║ 2 ║ Comp1-2 ║
║ 1 ║ 3 ║ Comp1-3 ║
║ 1 ║ 4 ║ Comp1-4 ║
║ 3 ║ 5 ║ Comp3-5 ║
╚══════╩════╩═════════╝
I've tried using NOT EXISTS and joining with a subquery but I'm not sure what to Join on.
Using not exists, it looks like:
select t.*
from t
where t.descr like 'Comp1-%' or
not exists (select 1
from t t2
where t2.id = t.id and t2.descr like 'Comp1-%'
);
I'm trying to write a query that returns a table with columns name and numberOfClasses. This table includes the name of all students and the amount of classes the student follows. I use the following database tables:
╔══════════════╦═══════════╦══════════╗
║ TakesClasses ║ ║ ║
╠══════════════╬═══════════╬══════════╣
║ id ║ person_id ║ class_id ║
║ 99 ║ 1 ║ 40 ║
║ 98 ║ 1 ║ 41 ║
║ 97 ║ 1 ║ 42 ║
║ 96 ║ 1 ║ 43 ║
║ 95 ║ 2 ║ 44 ║
║ 94 ║ 2 ║ 45 ║
║ 93 ║ 2 ║ 46 ║
╚══════════════╩═══════════╩══════════╝
╔═════════╦═══════╦══╗
║ Persons ║ ║ ║
╠═════════╬═══════╬══╣
║ id ║ name ║ ║
║ 1 ║ Bart ║ ║
║ 2 ║ David ║ ║
║ 3 ║ Dani ║ ║
║ 4 ║ Erik ║ ║
╚═════════╩═══════╩══╝
I used the following query:
SELECT
name,
COUNT(T.person_id) AS numberOfClasses
FROM
Persons P
LEFT OUTER JOIN
TakesClasses T ON P.id = T.person_id
GROUP BY
P.id, P.name
And this is the output:
╔═══════╦═════════════════╗
║ name ║ numberOfClasses ║
╠═══════╬═════════════════╣
║ Bart ║ 4 ║
║ Dani ║ 3 ║
║ David ║ 0 ║
║ Erik ║ 0 ║
╚═══════╩═════════════════╝
How can I remove the entries with 0 from my the results table?
Thanks for the help in advance!
Just use JOIN instead of LEFT JOIN
select name, count(T.person_id) as amountOfClasses
from Persons P join
TakesClasses T
on P.id = T.person_id
group by P.id, P.name
If you want to filter on aggregated data like what comes out of GROUP BY you can use the HAVING clause
SELECT name,COUNT(T.person_id) as amountOfClasses
FROM Persons P LEFT OUTER JOIN TakesClasses T
on P.id = T.person_id
GROUP BY P.id, P.name
HAVING COUNT(T.person_id) > 0;
sqlFiddle: http://sqlfiddle.com/#!9/1108c5/8
I have three tables as below.
Table 1:
╔═════════════════════╗
║ Country_table ║
╠══════════════╦══════╣
║ Country_Name ║ Code ║
╠══════════════╬══════╣
║ India ║ 1 ║
╠══════════════╬══════╣
║ UK ║ 2 ║
╠══════════════╬══════╣
║ france ║ 3 ║
╠══════════════╬══════╣
║ germany ║ 4 ║
╚══════════════╩══════╝
Table 2 :
╔════════════════════════════════════════════════════════════════════════════════╗
║ Trade_Details ║
╠═════════╦═══════════╦═════════════╦═══════════╦══════════╦════════╦════════════╣
║ TradeID ║ ProductID ║ FromCountry ║ ToCountry ║ Curruncy ║ Amount ║ Date ║
╠═════════╬═══════════╬═════════════╬═══════════╬══════════╬════════╬════════════╣
║ T1 ║ P1 ║ 1 ║ 3 ║ INR ║ 10 ║ 01/01/2020 ║
╠═════════╬═══════════╬═════════════╬═══════════╬══════════╬════════╬════════════╣
║ T2 ║ P2 ║ 3 ║ 2 ║ USD ║ 11 ║ 10/01/2020 ║
╠═════════╬═══════════╬═════════════╬═══════════╬══════════╬════════╬════════════╣
║ T3 ║ P1 ║ 1 ║ 4 ║ GBP ║ 12 ║ 20/01/2020 ║
╠═════════╬═══════════╬═════════════╬═══════════╬══════════╬════════╬════════════╣
║ T4 ║ P2 ║ 2 ║ 3 ║ INR ║ 13 ║ 21/01/2020 ║
╠═════════╬═══════════╬═════════════╬═══════════╬══════════╬════════╬════════════╣
║ T5 ║ P1 ║ 1 ║ 4 ║ USD ║ 14 ║ 22/01/2020 ║
╠═════════╬═══════════╬═════════════╬═══════════╬══════════╬════════╬════════════╣
║ T6 ║ P2 ║ 4 ║ 2 ║ GBP ║ 15 ║ 23/01/2020 ║
╠═════════╬═══════════╬═════════════╬═══════════╬══════════╬════════╬════════════╣
║ T7 ║ P1 ║ 3 ║ 1 ║ INR ║ 16 ║ 24/01/2020 ║
╠═════════╬═══════════╬═════════════╬═══════════╬══════════╬════════╬════════════╣
║ T8 ║ P2 ║ 3 ║ 1 ║ USD ║ 17 ║ 25/01/2020 ║
╠═════════╬═══════════╬═════════════╬═══════════╬══════════╬════════╬════════════╣
║ T9 ║ P1 ║ 2 ║ 3 ║ GBP ║ 18 ║ 26/01/2020 ║
╠═════════╬═══════════╬═════════════╬═══════════╬══════════╬════════╬════════════╣
║ T10 ║ P2 ║ 1 ║ 4 ║ INR ║ 19 ║ 27/01/2020 ║
╠═════════╬═══════════╬═════════════╬═══════════╬══════════╬════════╬════════════╣
║ T11 ║ P1 ║ 3 ║ 1 ║ USD ║ 20 ║ 28/01/2020 ║
╠═════════╬═══════════╬═════════════╬═══════════╬══════════╬════════╬════════════╣
║ T12 ║ P2 ║ 1 ║ 1 ║ GBP ║ 21 ║ 29/01/2020 ║
╠═════════╬═══════════╬═════════════╬═══════════╬══════════╬════════╬════════════╣
║ T13 ║ P1 ║ 2 ║ 2 ║ INR ║ 22 ║ 30/01/2020 ║
╚═════════╩═══════════╩═════════════╩═══════════╩══════════╩════════╩════════════╝
Table 3:
╔═══════════════════════════════════════════════════════╗
║ TradeStatus_Table ║
╠═════════╦════════════╦═══════════════════╦════════════╣
║ TradeID ║ StatusCode ║ StatusDescription ║ Date ║
╠═════════╬════════════╬═══════════════════╬════════════╣
║ T1 ║ inProcess ║ Reached HUB1 ║ 01/01/2020 ║
╠═════════╬════════════╬═══════════════════╬════════════╣
║ T1 ║ inProcess ║ Reached HUB2 ║ 01/01/2020 ║
╠═════════╬════════════╬═══════════════════╬════════════╣
║ T1 ║ inProcess ║ Reached HUB3 ║ 01/01/2020 ║
╠═════════╬════════════╬═══════════════════╬════════════╣
║ T1 ║ delivered ║ delivered ║ 01/01/2020 ║
╠═════════╬════════════╬═══════════════════╬════════════╣
║ T2 ║ inProcess ║ Reached HUB1 ║ 10/01/2020 ║
╠═════════╬════════════╬═══════════════════╬════════════╣
║ T2 ║ inProcess ║ Reached HUB2 ║ 10/01/2020 ║
╠═════════╬════════════╬═══════════════════╬════════════╣
║ T2 ║ inProcess ║ Reached HUB3 ║ 10/01/2020 ║
╠═════════╬════════════╬═══════════════════╬════════════╣
║ T2 ║ Returned ║ returned to home ║ 10/01/2020 ║
╠═════════╬════════════╬═══════════════════╬════════════╣
║ T3 ║ inProcess ║ Reached HUB1 ║ 20/01/2020 ║
╠═════════╬════════════╬═══════════════════╬════════════╣
║ T3 ║ inProcess ║ Reached HUB2 ║ 20/01/2020 ║
╠═════════╬════════════╬═══════════════════╬════════════╣
║ T3 ║ inProcess ║ Reached HUB3 ║ 20/01/2020 ║
╠═════════╬════════════╬═══════════════════╬════════════╣
║ T3 ║ inProcess ║ Reached HUB4 ║ 20/01/2020 ║
╠═════════╬════════════╬═══════════════════╬════════════╣
║ T3 ║ inProcess ║ Reached HUB5 ║ 20/01/2020 ║
╚═════════╩════════════╩═══════════════════╩════════════╝
Output tables :
Delivered : This column represents the total number of transactions final status as either delivered or returned.
InProcess : This column represents the total number of transactions doesn't contains final status as either delivered or returned.
╔═════════════════════════════════════════════════════════════════════╗
║ Report 1 (example) ║
╠═════════════╦═══════════╦═══════════╦═══════════╦═══════════════════╣
║ FromCountry ║ ToCountry ║ Delivered ║ inProcess ║ Description ║
╠═════════════╬═══════════╬═══════════╬═══════════╬═══════════════════╣
║ India ║ UK ║ 1 ║ 1 ║ total transactions║
╠═════════════╬═══════════╬═══════════╬═══════════╬═══════════════════╣
║ UK ║ India ║ 2 ║ 1 ║ total transactions║
╠═════════════╬═══════════╬═══════════╬═══════════╬═══════════════════╣
║ France ║ India ║ 2 ║ 1 ║ total transactions║
╚═════════════╩═══════════╩═══════════╩═══════════╩═══════════════════╝
No of Trades : This column contains Total number of transactions were made between from country and to country.
Total Trade Value :- This column contains Total sum of value of the transactions made between from country and to country based on currency type.
╔═══════════════════════════════════════════════════════════════════════╗
║ Report 2 (example) ║
╠═════════════╦═══════════╦══════════════╦══════════╦═══════════════════╣
║ FromCountry ║ ToCountry ║ No of Trades ║ Currency ║ Total Trade Value ║
╠═════════════╬═══════════╬══════════════╬══════════╬═══════════════════╣
║ India ║ UK ║ 2 ║ INR ║ 1000 ║
╠═════════════╬═══════════╬══════════════╬══════════╬═══════════════════╣
║ India ║ UK ║ 1 ║ USD ║ 10 ║
╠═════════════╬═══════════╬══════════════╬══════════╬═══════════════════╣
║ UK ║ India ║ 2 ║ GBP ║ 10 ║
╠═════════════╬═══════════╬══════════════╬══════════╬═══════════════════╣
║ France ║ India ║ 1 ║ INR ║ 20 ║
╚═════════════╩═══════════╩══════════════╩══════════╩═══════════════════╝
I have tried many combinations but not able to figure out the required output. Please help me on this.
first query, But not able to accommodate inprocess message count.
select source.Country_name, destination.country_name, count(*)
from Trade_Details, Country_table source, Country_table destination
where date > '2020/01/01 00:00:00'
and date <'2020/02/01/ 00:00:00'
and FromCountry = source.code
and ToCountry =destination.code
group by source.Country_name, destination.country_name
2nd query ,
select source.Country_name as source, destination.country_name as destination, count(*) as inprocessCount
from Trade_Details a1, Country_table source, Country_table destination
where date > '2020/01/01 00:00:00'
and date <'2020/02/01/ 00:00:00'
and FromCountry = source.code
and ToCountry =destination.code
and 0=(select count(*) from Trade_Details a2 where (a2.StatusCode='delivered' or a2.StatusCode='Returned') and a1.TradeID=a2.TradeID)
group by source.Country_name, destination.country_name
QUESTION :
Basically i would like merge both query outputs to get it in a single query. But failed to achive. If possible could you please help me on these two reports.
regards,
Ks
Report 1 Solution Here !!!
SELECT source.country_name AS FromCountry,
destination.country_name AS ToCountry,
Count(Trdsts1.statuscode) AS Delivered,
Count(Trdsts2.statuscode) AS inProcess,
'no of messages' AS Description
FROM trade_details Trddts,
tradestatus_table Trdsts1,
tradestatus_table Trdsts2,
country_table source,
country_table destination
WHERE Trddts.date > '2020/01/01 00:00:00'
AND Trddts.date < '2020/02/01/ 00:00:00'
AND Trdsts1.tradeid = Trddts.tradeid
AND Trdsts2.tradeid = Trddts.tradeid
AND Trdsts1.statuscode = "delivered"
AND Trdsts2.statuscode ="inprocess"
AND source.code = Trddts.fromcountry
AND destination.code = Trddts.tocountry
all
I've been trying to do, with data following the structure:
╔══════════════╦═══════════╦══╗
║ Alphabetical ║ Numerical ║ ║
╠══════════════╬═══════════╬══╣
║ A ║ 15 ║ ║
║ A ║ 30 ║ ║
║ E ║ 100 ║ ║
║ C ║ 45 ║ ║
║ F ║ 25 ║ ║
║ C ║ 65 ║ ║
║ B ║ 25 ║ ║
║ F ║ 35 ║ ║
║ C ║ 100 ║ ║
║ A ║ 10 ║ ║
║ C ║ 20 ║ ║
║ B ║ 5 ║ ║
║ E ║ 10 ║ ║
║ F ║ 85 ║ ║
║ D ║ 30 ║ ║
║ F ║ 1 ║ ║
╚══════════════╩═══════════╩══╝
To get the following:
╔══════════════╦══════╦═════════╗
║ Alphabetical ║ Rank ║ Numeric ║
╠══════════════╬══════╬═════════╣
║ A ║ 1 ║ 30 ║
║ A ║ 2 ║ 15 ║
║ A ║ 3 ║ 10 ║
║ B ║ 1 ║ 25 ║
║ B ║ 2 ║ 5 ║
║ C ║ 1 ║ 100 ║
║ C ║ 2 ║ 65 ║
║ C ║ 3 ║ 45 ║
║ C ║ 4 ║ 20 ║
║ D ║ 1 ║ 30 ║
║ E ║ 1 ║ 100 ║
║ E ║ 2 ║ 10 ║
║ F ║ 1 ║ 85 ║
║ F ║ 2 ║ 35 ║
║ F ║ 3 ║ 25 ║
║ F ║ 4 ║ 1 ║
╚══════════════╩══════╩═════════╝
Basically, to order the alphabetical field in ascending order, the numerical field in descending order and get the order or rank by using the order used for the numerical field, grouped by the alphabetical field.
I have only achieved it if I limit it to one specific value in the Alphabetical column, by using something like:
select ordered_src.*, ROWNUM Rank from (select src.* from Source src where alphabetical = 'A' order by Numeric desc) ordered_src;
But I have no idea how to get the result shown above. Any idea? Also, is there any alternative that will work also in mysql/mssql/etc?
Thanks!
Use row_number():
select s.*,
row_number() over (partition by alphabetical order by numerical desc) as rank
from source s
order by alphabetical, rank;
Hi i have postgres database and four tables
vehicles -> trips
vehicles -> component_values -> component_types
vehicles:
╔════╦══════════════════════════╦════════════════════════╦════════════════╦═════════╗
║ id ║ slug ║ name ║ manufacturer ║ model ║
╠════╬══════════════════════════╬════════════════════════╬════════════════╬═════════╣
║ 1 ║ manufacturer-x-model-3 ║ Manufacturer X Model 3 ║ Manufacturer X ║ Model 3 ║
║ 2 ║ manufacturer-x-model-1 ║ Manufacturer X Model 1 ║ Manufacturer X ║ Model 1 ║
║ 3 ║ manufacturer-x-model-1-1 ║ Manufacturer X Model 1 ║ Manufacturer X ║ Model 1 ║
╚════╩══════════════════════════╩════════════════════════╩════════════════╩═════════╝
trips:
╔═════╦════════════╦═════════════╦═════════════╦═════════════════╗
║ id ║ vehicle_id ║ name ║ mileage ║ recorded_at ║
╠═════╬════════════╬═════════════╬═════════════╬═════════════════╣
║ 1 ║ 1 ║ 10386735 ║ 386734.997 ║ 2/25/2014 13:56 ║
║ 2 ║ 1 ║ 11771530.14 ║ 771530.14 ║ 3/1/2014 19:41 ║
║ 3 ║ 1 ║ 121112028.4 ║ 1112028.39 ║ 3/5/2014 3:23 ║
║ 4 ║ 1 ║ 131406814.9 ║ 1406814.892 ║ 3/8/2014 20:56 ║
║ 5 ║ 1 ║ 141933528.7 ║ 1933528.711 ║ 3/13/2014 0:19 ║
║ 6 ║ 1 ║ 152256488.6 ║ 2256488.579 ║ 3/16/2014 21:15 ║
╚═════╩════════════╩═════════════╩═════════════╩═════════════════╝
component_values:
╔════╦═══════════════════╦═════════╦════════════╦════════════╦═════════════╦═════════════╗
║ id ║ component_type_id ║ trip_id ║ vehicle_id ║ mileage ║ damage ║ damage_eff ║
╠════╬═══════════════════╬═════════╬════════════╬════════════╬═════════════╬═════════════╣
║ 1 ║ 1 ║ 1 ║ 1 ║ 386734.997 ║ 0.002260565 ║ 0.002225831 ║
║ 2 ║ 2 ║ 1 ║ 1 ║ 386734.997 ║ 0.002260306 ║ 0.002238006 ║
║ 3 ║ 3 ║ 1 ║ 1 ║ 386734.997 ║ 0.002261288 ║ 0.002266295 ║
║ 4 ║ 4 ║ 1 ║ 1 ║ 386734.997 ║ 0.002054489 ║ 0.002060029 ║
║ 5 ║ 5 ║ 1 ║ 1 ║ 386734.997 ║ 0.002052669 ║ 0.002107272 ║
║ 6 ║ 6 ║ 1 ║ 1 ║ 386734.997 ║ NULL ║ NULL ║
║ 7 ║ 7 ║ 1 ║ 1 ║ 386734.997 ║ NULL ║ NULL ║
║ 8 ║ 1 ║ 2 ║ 1 ║ 771530.14 ║ 0.004792952 ║ 0.0048514 ║
║ 9 ║ 2 ║ 2 ║ 1 ║ 771530.14 ║ 0.004792404 ║ 0.004710451 ║
║ 10 ║ 3 ║ 2 ║ 1 ║ 771530.14 ║ 0.004794486 ║ 0.004805461 ║
╚════╩═══════════════════╩═════════╩════════════╩════════════╩═════════════╩═════════════╝
component_types:
╔════╦═════════════════════════════════════╦════════════════╦══════════════════════╗
║ id ║ slug ║ manufacturer ║ name ║
╠════╬═════════════════════════════════════╬════════════════╬══════════════════════╣
║ 6 ║ manufacturer-d-battery ║ Manufacturer D ║ Battery ║
║ 2 ║ manufacturer-b-differential-1 ║ Manufacturer B ║ Differential 1 ║
║ 3 ║ manufacturer-c-driveshaft-1 ║ Manufacturer C ║ Driveshaft 1 ║
║ 5 ║ manufacturer-c-gearbox-output-shaft ║ Manufacturer C ║ Gearbox output shaft ║
║ 1 ║ manufacturer-a-motor-1 ║ Manufacturer A ║ Motor 1 ║
║ 4 ║ manufacturer-c-gearbox-input-shaft ║ Manufacturer C ║ Gearbox input shaft ║
║ 7 ║ usage-profile ║ ║ Usage profile ║
╚════╩═════════════════════════════════════╩════════════════╩══════════════════════╝
and i'm trying to get the vehicles with the latest trip dates and mileage and also the heights and lowest damaged component for each vehicle
so the result will be like:
╔════════════╦══════════════════╦══════════════════════════╦═════════════════════════════════╦════════════════════════════════╦════════════════════════════════╦═══════════════════════════════╗
║ vehicle_id ║ latest_trip_date ║ latest_trip_date_mileage ║ heights_damaged_component_value ║ heights_damaged_component_name ║ lowest_damaged_component_value ║ lowest_damaged_component_name ║
╠════════════╬══════════════════╬══════════════════════════╬═════════════════════════════════╬════════════════════════════════╬════════════════════════════════╬═══════════════════════════════╣
║ 1 ║ 4/19/2014 3:27 ║ 4844305.912 ║ 0.029372972 ║ Gearbox input shaft ║ 0.002052669 ║ Gearbox output shaft ║
║ 2 ║ 5/19/2014 16:13 ║ 5567945.164 ║ 0.029405924 ║ Driveshaft 1 ║ 0.001864137 ║ Gearbox output shaft ║
║ 3 ║ 4/28/2014 12:55 ║ 5286175.763 ║ 0.030745029 ║ Driveshaft 1 ║ 0.001957685 ║ Differential 1 ║
║ 4 ║ 2/25/2014 3:32 ║ 5398006.007 ║ 0.030495792 ║ Driveshaft 1 ║ 0.001814434 ║ Differential 1 ║
║ 5 ║ 4/25/2014 9:51 ║ 5179558.475 ║ 0.032060074 ║ Gearbox input shaft ║ 0.001936431 ║ Differential 1 ║
║ 6 ║ 5/9/2014 7:43 ║ 5234355.804 ║ 0.030576454 ║ Gearbox input shaft ║ 0.002254191 ║ Gearbox output shaft ║
║ 7 ║ 6/21/2014 18:09 ║ 5705722.416 ║ 0.029957374 ║ Driveshaft 1 ║ 0.001653441 ║ Gearbox output shaft ║
║ 8 ║ 4/23/2014 5:25 ║ 5590470.028 ║ 0.031900163 ║ Driveshaft 1 ║ 0.002083733 ║ Gearbox output shaft ║
║ 9 ║ 3/28/2014 20:37 ║ 5598159.883 ║ 0.031208918 ║ Driveshaft 1 ║ 0.00162805 ║ Differential 1 ║
║ 10 ║ 5/24/2014 19:27 ║ 5020795.001 ║ 0.02962505 ║ Gearbox input shaft ║ 0.001729646 ║ Differential 1 ║
╚════════════╩══════════════════╩══════════════════════════╩═════════════════════════════════╩════════════════════════════════╩════════════════════════════════╩═══════════════════════════════╝
i already tried this query
select
vehicles.id as vehicle_id,
latest_trips.recorded_at as latest_trip_date,
latest_trips.mileage as latest_trip_date_mileage,
heights_damaged_components.damage as heights_damaged_component_value,
heights_damaged_components.name as heights_damaged_component_name,
lowest_damaged_components.damage as lowest_damaged_component_value,
lowest_damaged_components.name as lowest_damaged_component_name
from vehicles
left join (
SELECT t.id, t.vehicle_id, t.mileage, t.recorded_at
FROM public.trips t
inner JOIN (SELECT vehicle_id, MAX(recorded_at) as latest_trip_date FROM public.trips GROUP BY vehicle_id)
tm ON t.vehicle_id = tm.vehicle_id AND t.recorded_at = tm.latest_trip_date
)
as latest_trips on latest_trips.vehicle_id = vehicles.id
left join (
select ct.name, hd.component_type_id, hd.vehicle_id, hd.damage
from public.component_values as hd
INNER JOIN (
SELECT vehicle_id,
MAX(damage) as heights_damaged_component
FROM public.component_values
GROUP BY vehicle_id
)
hdm ON hd.vehicle_id = hdm.vehicle_id AND hd.damage = hdm.heights_damaged_component
join public.component_types as ct on ct.id = hd.component_type_id
)
as heights_damaged_components on heights_damaged_components.vehicle_id = vehicles.id
left join (
select ct.name, ld.component_type_id, ld.vehicle_id, ld.damage
from public.component_values as ld
INNER JOIN (
SELECT vehicle_id, MIN(damage) as lowest_damaged_component
FROM public.component_values
GROUP BY vehicle_id
)
ldm ON ld.vehicle_id = ldm.vehicle_id AND ld.damage = ldm.lowest_damaged_component
join public.component_types as ct on ct.id = ld.component_type_id
) as lowest_damaged_components on lowest_damaged_components.vehicle_id = vehicles.id
but i have like 10000 vehicles and big trips and component_values and this query give me the result in like 3 to 6 seconds, is their a batter way to do this with better performance and time?
can i use GENERATED columns in my case and how ?
please any help and many many thanks in advance.