I have a database of bets. Each bet has a 'Win', 'Loss', or 'Pending' state. What I want to do is to have an SQL statement that will get the last, say, 20 bets a user has placed, find out their ROI (Total profit / Total staked * 100).
So I'm just wondering if there is a better way to do this. Do I basically have to get the users table, loop over every user, get their last 20 bets, find the ROI and then order it. If my User table gets huge then this process is going to take ages, right?
Is creating a 'View' going to save on this time?
Is there a way to do this in one statement that won't cost my life in processing time?
Here are the tables
Users
| ID | User |
| 1 | Test1 |
| 2 | Test2 |
| 3 | Test3 |
| 4 | Test4 |
Bets
| ID | User | Amount | Odds | Result |
| 1 | 1 | 10 | 1.35 | Win |
| 2 | 1 | 25 | 2.55 | Win |
| 3 | 3 | 15 | 1.65 | Loss |
| 4 | 2 | 11 | 2.12 | Pending |
Se essentially I would like a table that ranks them as ROI.
| User | AmountBet | AmountWon | ROI |
| 1 | 35 | 77 | 215 |
| 2 | 11 | 0 | 0 |
| 3 | 15 | 0 | 0 |
| 4 | 0 | 0 | 0 |
Assuming the ID of the bets table represents increasing time such that it can be used to identify "last 20", then
WITH b
AS
(
SELECT id,
user,
CASE WHEN result = 'Pending' THEN 0 ELSE amount END AS amount,
CASE WHEN result = 'Win' THEN amount * odds ELSE 0 END as winnings,
ROW_NUMBER() OVER (PARTITION BY user ORDER BY id DESC) AS rownum
FROM bets
)
SELECT user,
SUM(amount) AS amount_bet,
SUM(winnings) AS amount_won,
CASE
WHEN SUM(amount) > 0
THEN SUM(winnings) * 100 / SUM(amount)
ELSE 0
END AS roi
FROM b
WHERE rownum < 21
GROUP BY user;
dbfiddle.uk
Related
I have three tables.
The first one is Device table
+----------+------+
| DeviceId | Type |
+----------+------+
| 1 | 10 |
| 2 | 20 |
| 3 | 30 |
+----------+------+
The second one is History table - data received by different devices.
+----------+-------------+--------------------+
| DeviceId | Temperature | TimeStamp |
+----------+-------------+--------------------+
| 1 | 31 | 15.08.2020 1:42:00 |
| 2 | 100 | 15.08.2020 1:42:01 |
| 2 | 40 | 15.08.2020 1:43:00 |
| 1 | 32 | 15.08.2020 1:44:00 |
| 1 | 34 | 15.08.2020 1:45:00 |
| 3 | 20 | 15.08.2020 1:46:00 |
| 2 | 45 | 15.08.2020 1:47:00 |
+----------+-------------+--------------------+
The third one is DeviceStatusHistory table
+----------+---------+--------------------+
| DeviceId | State | TimeStamp |
+----------+---------+--------------------+
| 1 | 1(OK) | 15.08.2020 1:42:00 |
| 2 | 1(OK) | 15.08.2020 1:43:00 |
| 1 | 1(OK) | 15.08.2020 1:44:00 |
| 1 | 0(FAIL) | 15.08.2020 1:44:30 |
| 1 | 0(FAIL) | 15.08.2020 1:46:00 |
| 2 | 0(FAIL) | 15.08.2020 1:46:10 |
+----------+---------+--------------------+
I want to select the last temperature of devices, but take into account only those history records that occurs until the first device failure.
Since device1 starts failing from 15.08.2020 1:44:30, I don't want its records that go after that timestamp.
The same for the device2.
So as a final result, I want to have only data of all devices until they get first FAIL status:
+----------+-------------+--------------------+
| DeviceId | Temperature | TimeStamp |
+----------+-------------+--------------------+
| 2 | 40 | 15.08.2020 1:43:00 |
| 1 | 32 | 15.08.2020 1:44:00 |
| 3 | 20 | 15.08.2020 1:46:00 |
+----------+-------------+--------------------+
I can select an appropriate history only if device failed at least once:
SELECT * FROM Device D
CROSS APPLY
(SELECT TOP 1 * FROM History H
WHERE D.Id = H.DeviceId
and H.DeviceTimeStamp <
(select MIN(UpdatedOn) from DeviceStatusHistory Y where [State]=0 and DeviceId=D.Id)
ORDER BY H.DeviceTimeStamp desc) X
ORDER BY D.Id;
The problems is, if a device never fails, I don't get its history at all.
Update:
My idea is to use something like this
SELECT * FROM DeviceHardwarePart HP
CROSS APPLY
(SELECT TOP 1 * FROM History H
WHERE HP.Id = H.DeviceId
and H.DeviceTimeStamp <
(select ISNULL((select MIN(UpdatedOn) from DeviceMetadataPart where [State]=0 and DeviceId=HP.Id),
cast('12/31/9999 23:59:59.997' as datetime)))
ORDER BY H.DeviceTimeStamp desc) X
ORDER BY HP.Id;
I'm not sure whether it is a good solution
You can use COALESCE: coalesce(min(UpdateOn), cast('9999-12-31 23:59:59' as datetime)). This ensures you always have an upperbound for your select instead of NULL.
I will treat this as two parts problem
I will try to find the time at which device has failed and if it hasn't failed I will keep it as a large value like some timestamp in 2099
Once I have the above I can simply join with histories table and take the latest value before the failed timestamp.
In order to get one, I guess there can be several approaches. From top of my mind something like below should work
select device_id, coalesce(min(failed_timestamps), cast('01-01-2099 01:01:01' as timestamp)) as failed_at
(select device_id, case when state = 0 then timestamp else null end as failed_timestamps from History) as X
group by device_id
This gives us the minimum of failed timestamp for a particular device, and an arbitrary large value for the devices which have never failed.
I guess after this the solution is straight forward.
I have a source table that has a few different prices for each product (depending on the order quantity). Those prices are listed vertically, so each product could have more than one row to display its prices.
Example:
ID | Quantity | Price
--------------------------
001 | 5 | 100
001 | 15 | 90
001 | 50 | 80
002 | 10 | 20
002 | 20 | 15
002 | 30 | 10
002 | 40 | 5
The other table I have is the result table in which there is only one row for each product, but there are five columns that each could contain the quantity and price for each row of the source table.
Example:
ID | Quantity_1 | Price_1 | Quantity_2 | Price_2 | Quantity_3 | Price_3 | Quantity_4 | Price_4 | Quantity_5 | Price_5
---------------------------------------------------------------------------------------------------------------------------
001 | | | | | | | | | |
002 | | | | | | | | | |
Result:
ID | Quantity_1 | Price_1 | Quantity_2 | Price_2 | Quantity_3 | Price_3 | Quantity_4 | Price_4 | Quantity_5 | Price_5
---------------------------------------------------------------------------------------------------------------------------
001 | 5 | 100 | 15 | 90 | 50 | 80 | | | |
002 | 10 | 20 | 20 | 15 | 30 | 10 | 40 | 5 | |
Here is my Python/SQL solution for this (I'm fully aware that this could not work in any way, but this was the only way for me to show you my interpretation of a solution to this problem):
For Each result_ID In result_table.ID:
Subselect = (SELECT * FROM source_table WHERE source_table.ID = result_ID ORDER BY source_table.Quantity) # the Subselect should only contain rows where the IDs are the same
For n in Range(0, len(Subselect)): # n (index) should start from 0 to last row - 1
price_column_name = 'Price_' & (n + 1)
quantity_column_name = 'Quantity_' & (n + 1)
(UPDATE result_table
SET result_table.price_column_name = Subselect[n].Price, # this should be the price of the n-th row in Subselect
result_table.quantity_column_name = Subselect[n].Quantity # this should be the quantity of the n-th row in Subselect
WHERE result_table.ID = Subselect[n].ID)
I honestly have no idea how to do this with only SQL or VBA (those are the only languages I'd be able to use -> MS-Access).
This is a pain in MS Access. If you can enumerate the values, you can pivot them.
If we assume that price is unique (or quantity or both), then you can generate such a column:
select id,
max(iif(seqnum = 1, quantity, null)) as quantity_1,
max(iif(seqnum = 1, price, null)) as price_1,
. . .
from (select st.*,
(select count(*)
from source_table st2
where st2.id = st.id and st2.price >= st.price
) as seqnum
from source_table st
) st
group by id;
I should note that another solution would use data frames in Python. If you want to take that route, ask another question and tag it with the appropriate Python tags. This question is clearly a SQL question.
Table name: Copies
+------------------------------------------------------------------------------------+
| group_id | my_id | previous | in_this | higher_value | most_recent |
+----------------------------------------------------------------------------------------------------------------
| 900 | 1 | null | Y | 7 | May16 |
| 900 | 2 | null | Y | 3 | Oct 16 |
| 900 | 3 | null | N | 9 | Oct 16 |
| 901 | 4 | 378 | Y | 3 | Oct 16 |
| 901 | 5 | null | N | 2 | Oct 16 |
| 902 | 6 | null | N | 5 | May16 |
| 902 | 7 | null | N | 9 | Oct 16 |
| 903 | 8 | null | Y | 3 | Oct 16 |
| 903 | 9 | null | Y | 3 | May16 |
| 904 | 10 | null | N | 0 | May 16 |
| 904 | 11 | null | N | 0 | May16
--------------------------------------------------------------------------------------
Output table
+---------------------------------------------------------------------------------------------------+
| group_id | my_id | previous | in_this | higher_value |most_recent|
+----------------------------------------------------------------------------------------------------
| 900 | 1 | null | Y | 7 | May16 |
| 902 | 7 | null | N | 9 | Oct 16 |
| 903 | 8 | null | Y | 3 | Oct 16 |
---------------------------------------------------------------------------------------------------------
Hi all, I need help with a query that returns one record within a group based on the importance of the field. The importance is ranked as follows:
previous- if one record within the group_id is not null, then neither record within a group_id is returned (because according to our rules, all records within a group should have the same previous value)
in_this- If one record is Y, and the other is N within a group_id, then we keep the Y; If all records are Y or all are N, then we move to the next attribute
Higher_value- If all records in the ‘in_this’ field are equal, then we need to select the record with the greater value from this field. If both records have an equal value, we move to the next attribute
Most_recent- If all records were of equal value in the ‘higher_value’ field, then we consider the newest record. If these are equal, then nothing is returned.
This is a simplified version of the table I am looking at, but I just would like to get the gist of how something like this would work. Basically, my table has multiple copies of records that have been grouped through some algorithm. I have been tasked with selecting which of these records within a group is the ‘good’ one, and we are basing this on these fields.
I’d like the output to actually show all fields, because I will likely attempt to refine the query to include other fields (there are over 40 to consider), but the most important is the group_id and my_id fields. It would be neat if we could also somehow flag why each record got picked, but that isn’t necessary.
It seems like something like this should be easy, but I have a hard time wrapping my head around how to pick from within a group_id. Thanks for your help.
You can use analytic functions for this. The trick is establishing the right variables for each condition:
select t.*
from (select t.*,
max(in_this) over (partition by group_id) as max_in_this,
min(higher_value) over (partition by group_id) as min_higher_value,
max(higher_value) over (partition by group_id) as max_higher_value,
row_number() over (partition by group_id, higher_value order by my_id) as seqnum_ghv,
min(most_recent) over (partition by group_id) as min_most_recent,
max(most_recent) over (partition by group_id) as max_most_recent,
row_number() over (partition by group_id order by most_recent) as seqnum_mr
from t
) t
where max_in_this is not null and
( (min_higher_value <> max_higher_value and seqnum_ghv = 1) or
(min_higher_value = max_higher_value and min_most_recent <> max_most_recent and seqnum_mr = 1
)
);
The third condition as stated makes no sense, but you should get the idea for how to implement this.
I'm trying to do an overall count function on a set of data with multiple conditions but am having trouble with it. I'm a beginner and tried using a simple count function but am having no luck. I looked into using case when but am having trouble with it. Does anyone know how I should go about this code?
Here is an example of my table:
Name | Date | Status | Candy | Soda | Water
Nancy | 10/19/16 | active | 2 | 0 | 1
Lindsy| 10/20/15 | active | 0 | 1 | 0
Erica | 10/20/13 | active | 0 | 2 | 3
Lane | 10/19/14 | active | 0 | 0 | 4
Alexa | 10/19/16 | notactive | 0 | 5 | 1
Jenn | 10/19/16 | active | 0 | 0 | 0
I'm looking to do an overall count of the names under the conditions that: either candy, soda, or water are anything other than zero(doesn't matter what column or how many, just if one of those three are not zero), the account is active and also when the date falls within the last two years, 10/2014 - 10/2016.
I would want the query to tell me that the count total was 3 and also show me:
Name | Date | Status | Candy | Soda | Water
Nancy | 10/19/16 | active | 2 | 0 | 1
Lindsy| 10/20/15 | active | 0 | 1 | 0
Lane | 10/19/14 | active | 0 | 0 | 4
These are two different questions. The basic idea to get the rows is:
select t.*
from t
where greatest(candy, soda, water) > 0 and
status = 'active' and
date >= curdate() - interval 2 year;
(In Oracle, you would could use sysdate rather than curdate().)
To get the count, you would use count(*) rather than * in the select. SQL queries only return one result set . . . so you either get all the rows or a single count.
SELECT *
FROM yourTable
WHERE (Candy > 0 OR Soda > 0 OR Water > 0) AND
Status = 'active' AND
Date BETWEEN '2014-10-01' AND SYSDATE
Assume I have this schema (tested on postgresql) where the 'Scorelines' relation contains results of sport matches. (kickoff is a TIMESTAMP but replaced by INT for readability)
SQLFiddle here: http://sqlfiddle.com/#!12/52475/3
CREATE TABLE Scorelines (
team TEXT,
kickoff INT,
scored INT,
conceded INT
);
Now I want to produce another column 'three_matches_scored' that contains the sum of the points scored
over the 3 preceding game (determined by kickoff) of the same team. I have this:
SELECT team, kickoff, scored, conceded, SUM(scored) OVER three_matches AS three_matches_scored
FROM Scorelines
WINDOW three_matches AS
(PARTITION BY team ORDER BY kickoff
ROWS BETWEEN 3 PRECEDING AND 1 PRECEDING)
ORDER BY kickoff;
This works beautifully so far, except that I get values starting from the second game. Example:
| TEAM | KICKOFF | SCORED | CONCEDED | THREE_MATCHES_SCORED |
|------|---------|--------|----------|----------------------|
| A | 1 | 1 | 0 | (null) |
| B | 2 | 1 | 1 | (null) |
| A | 3 | 1 | 1 | 1 |
| A | 4 | 3 | 0 | 2 |
| B | 4 | 1 | 4 | 1 |
| A | 6 | 0 | 2 | 5 |
| B | 6 | 4 | 2 | 2 |
| B | 8 | 1 | 2 | 6 |
| B | 10 | 1 | 1 | 6 |
| A | 11 | 2 | 1 | 4 |
I want the column 'three_matches_scored' to be (null) for the first 3 games because there are no 3 results to sum up. How can I achieve this?
I'd prefer simple understandable solutions, performance is not critical for this particular case.
My only idea right now, is to define a stored function SUM3, that results in (null) with less than 3 values to add up. But I never defined a function in SQL and can't seem to figure it out.
You can use a case statement to null the rows where there are less than 3 games:
SELECT team, kickoff, scored, conceded,
CASE WHEN COUNT(scored) OVER three_matches = 3
THEN SUM(scored) OVER three_matches
ELSE NULL
END AS three_matches_scored
FROM Scorelines
WINDOW three_matches AS
(PARTITION BY team ORDER BY kickoff
ROWS BETWEEN 3 PRECEDING AND 1 PRECEDING)
ORDER BY kickoff;
Output:
team | kickoff | scored | conceded | three_matches_scored
------+---------+--------+----------+----------------------
A | 1 | 1 | 0 |
B | 2 | 1 | 1 |
A | 3 | 1 | 1 |
A | 4 | 3 | 0 |
B | 4 | 1 | 4 |
A | 6 | 0 | 2 | 5
B | 6 | 4 | 2 |
B | 8 | 1 | 2 | 6
B | 10 | 1 | 1 | 6
A | 11 | 2 | 1 | 4
(10 rows)
See harmics answer above.
(my first solution, just for reference)
Solution with user defined aggregate:
CREATE TYPE intermediate_sum AS (
sum INT,
count INT
);
CREATE FUNCTION sum_sfunc(intermediate_sum, INTEGER) RETURNS intermediate_sum AS
$$ SELECT $2 + $1.sum AS sum, $1.count - 1 AS count $$ LANGUAGE SQL;
CREATE FUNCTION sum_ffunc(intermediate_sum) RETURNS INTEGER AS
$$ SELECT (CASE WHEN $1.count > 1 THEN null
WHEN $1.count = 0 THEN $1.sum
END)
$$ LANGUAGE SQL;
CREATE AGGREGATE sum3(INTEGER) (
sfunc = sum_sfunc,
finalfunc = sum_ffunc,
stype = intermediate_sum,
initcond = '(0,3)'
);
The aggregate SUM3 wants at least 3 values, otherwise it returns (null). One can define other aggreates like SUM4 by changing the initcond, for example to '(0,4)'.