We have a time series in an spark sql table which describes every time a user does an event.
However, users tend to do many events in a burst. I want to find the min time for everyone of these bursts.
Unfortunately this is historical data so I cant change how the table was created. So I essentially want a select min(time_), user from my_table group by user, but for each burst. Any help would be much appreciated!
EDIT:
Some example data would be:
user time_
0 10
0 11
2 12
0 12
2 13
2 15
0 83
0 84
0 85
so for example in the above data I would like to find (0, 10), (2, 12) and (0, 83). We can say that a burst occurs if it is within 1 hour (that would be 60 in the above example data).
If this is the only information you need:
select user
,time_
from (select user
,time_
,case when time_ - lag (time_,1,time_-60) over (partition by user order by time_) >= 60 then 'Y' else null end as burst
from my_table
) t
where burst = 'Y'
;
user time_
0 10
0 83
2 12
If you'll need to gather some additional information on each burst:
select user
,burst_seq
,min (time_) as min_time_
,max (time_) as max_time_
,count (*) as events_num
from (select user
,time_
,count(burst) over
(
partition by user
order by time_
rows unbounded preceding
) + 1 as burst_seq
from (select user
,time_
,case when time_ - lag (time_) over (partition by user order by time_) >= 60 then 'Y' else null end as burst
from my_table
) t
) t
group by user
,burst_seq
;
user burst_seq min_time_ max_time_ events_num
0 1 10 12 3
0 2 83 85 3
2 1 12 15 3
P.s.
There seems to be a bug with the CASE statement.
case when ... then 'Y' end yields FAILED: IndexOutOfBoundsException Index: 2, Size: 2 although it is a legal syntax.
Adding else null solved it.
Related
I have data in this format
ColA
Date
RSN
ID
DesiredColumn
70
0904
2
0904-2
1
71
0904
3
0904-3
1
100
0904
4
0904-4
1
70
0904
5
0904-5
2
I want to add the DesiredColumn that changes its values every time it sees RTI = 070 in ColA
Can someone please help?
You can use a cumulative sum, something like:
select t.*,
sum(case when colA = 70 then 1 else 0 end) over (partition by date order by rsn)
from t;
I am guessing that you want this per value of date and the ordering is based on rsn. If that is not true, remove the partition by clause.
Sql Fiddle: http://sqlfiddle.com/#!18/59e49/10
So my company has an application that has a certain "in-app currency". We record every transaction.
Recently, we found out there was a bug running for a couple of weeks that allowed users to spend currency in a certain place, even when they had none. When this happened, users wouldn't get charged at all: e.g. User had 4 m.u. and bought something that's worth 10 m.u. it's balance would remain at 4.
Now we need to find out who abused it and what's their available balance.
I want to get the column BUG_ABUSE and WISHFUL_CUMMULATIVE that reflect the illegitimate transactions and the amount that our users really see in their in-app wallets but I'm running out of ideas of how to get there.
I was wondering if I could do something like a sum(estrelas) if result over 0 else lag over (partition by user order by date) or something of the likes to get the wishful cummulative.
We're using oracle. Any help is highly appreciated
User_ID
EVENT_DATE
AMOUNT
DIRECTION
RK
CUM
WISHFUL_CUMMULATIVE
BUG_ABUSE
1
02/01/2021 13:37:19,009000
-5
0
1
-5
0
1
1
08/01/2021 01:55:40,000000
40
1
2
35
40
0
1
10/01/2021 10:45:41,000000
2
1
3
37
42
0
1
10/01/2021 10:45:58,000000
2
1
4
39
44
0
1
10/01/2021 13:47:37,456000
-5
0
5
34
39
0
2
13/01/2021 20:09:59,000000
2
1
1
2
2
0
2
16/01/2021 15:14:54,000000
-50
0
2
-48
2
1
2
19/01/2021 02:02:59,730000
-5
0
3
-53
2
1
2
23/01/2021 21:14:40,000000
3
1
4
-50
5
0
2
23/01/2021 21:14:50,000000
-5
0
5
-55
0
0
Here's something you can try. This uses recursive subquery factoring (recursive WITH clause), so it will only work in Oracle 11.2 and higher.
I use columns USER_ID, EVENT_DATE and AMOUNT from your inputs. I assume all three columns are constrained NOT NULL, two events can't have exactly the same timestamp for the same user, and AMOUNT is negative for purchases and other debits (fees, etc.) and positive for deposits or other credits.
The input data looks like this:
select user_id, event_date, amount
from sample_data
order by user_id, event_date
;
USER_ID EVENT_DATE AMOUNT
------- ----------------------------- ------
1 02/01/2021 13:37:19,009000000 -5
1 08/01/2021 01:55:40,000000000 40
1 10/01/2021 10:45:41,000000000 2
1 10/01/2021 10:45:58,000000000 2
1 10/01/2021 13:47:37,456000000 -5
2 13/01/2021 20:09:59,000000000 2
2 16/01/2021 15:14:54,000000000 -50
2 19/01/2021 02:02:59,730000000 -5
2 23/01/2021 21:14:40,000000000 3
2 23/01/2021 21:14:50,000000000 -5
Perhaps your input data has additional columns (like cumulative amount, which I left out because it plays no role in the problem or its solution). You show a RK column - I assume you computed it as a step in your attempt to solve the problem; I re-create it in my solution below.
Here is what you can do with a recursive query (recursive WITH clause):
with
p (user_id, event_date, amount, rk) as (
select user_id, event_date, amount,
row_number() over (partition by user_id order by event_date)
from sample_data
)
, r (user_id, event_date, amount, rk, bug_flag, balance) as (
select user_id, event_date, amount, rk,
case when amount < 0 then 'bug' end, greatest(amount, 0)
from p
where rk = 1
union all
select p.user_id, p.event_date, p.amount, p.rk,
case when p.amount + r.balance < 0 then 'bug' end,
r.balance + case when r.balance + p.amount >= 0
then p.amount else 0 end
from p join r on p.user_id = r.user_id and p.rk = r.rk + 1
)
select *
from r
order by user_id, event_date
;
Output:
USER_ID EVENT_DATE AMOUNT RK BUG BALANCE
------- ----------------------------- ------ -- --- -------
1 02/01/2021 13:37:19,009000000 -5 1 bug 0
1 08/01/2021 01:55:40,000000000 40 2 40
1 10/01/2021 10:45:41,000000000 2 3 42
1 10/01/2021 10:45:58,000000000 2 4 44
1 10/01/2021 13:47:37,456000000 -5 5 39
2 13/01/2021 20:09:59,000000000 2 1 2
2 16/01/2021 15:14:54,000000000 -50 2 bug 2
2 19/01/2021 02:02:59,730000000 -5 3 bug 2
2 23/01/2021 21:14:40,000000000 3 4 5
2 23/01/2021 21:14:50,000000000 -5 5 0
In order to produce the result you want you'll probably want to process the rows sequentially: once the first row is processed for a user you'll compute the second one, then the third one, and so on.
Assuming the column RK is already computed and sequential for each user you can do:
with
n (user_id, event_date, amount, direction, rk, cum, wishful, bug_abuse) as (
select t.*,
greatest(amount, 0),
case when amount < 0 then 1 else 0 end
from t where rk = 1
union all
select
t.user_id, t.event_date, t.amount, t.direction, t.rk, t.cum,
greatest(n.wishful + t.amount, 0),
case when n.wishful + t.amount < 0 then n.wishful
else n.wishful + t.amount
end
from n
join t on t.user_id = n.user_id and t.rk = n.rk + 1
)
select *
from n
order by user_id, rk;
I am using SQL Server 2014. When I was testing my code I noticed a problem.
Assume that max personal hour is 80 hours.
SELECT
lsm.EmployeeName,
pd.absenceDate,
pd.amountInDays * 8 AS [HoursReported],
pd.status,
(SUM(CASE WHEN pd.[status]='App' THEN (pd.amountInDays * 8)
ELSE 0 END) OVER (partition by lsm.[EmployeeName] order by pd.absenceDate)) AS [TotalUsedHours]
( #maxPSHours ) - (sum(
CASE WHEN pd.[status]='App' THEN (pd.amountInDays * 8)
ELSE 0 END)
over (
partition by lsm.[EmployeeName] order by pd.absenceDate)) AS [TotalRemainingHours]
FROM
[LocationStaffMembers] lsm
INNER JOIN
[PersonalDays] pd ON lsm.staffMemberId = pd.staffMemberId
This query returns these results:
EmployeeName AbsenceDate HoursReported Status TotalUsdHrs TotalRemingHrs
X 11/11/2015 4 approved 4 76
X 11/15/2015 8 approved 12 68
X 11/20/2015 2 decline 14 66
X 11/20/2015 2 approved 14 66
So, query works fine for different status. First 2 rows are fine. But when an employee does more than one action in a day (decline, approved etc.), my query only shows the total used and total remaining for the day.
Here is the expected result.
EmployeeName AbsenceDate HoursReported Status TotalUsdHrs TotalRemingHrs
X 11/11/2015 4 approved 4 76
X 11/15/2015 8 approved 12 68
X 11/20/2015 2 decline 12 68
X 11/20/2015 2 approved 14 66
You are doing a cumulative sum that returns results based on the order of AbsenceDate (sum(...) over (partition by ... order by pd.absenceDate). But your last 2 records have the exact same date (11/20/2015) -- at least, according to what you are showing us. This creates an ambiguity.
So, it is absolutely conceivable, and legal, that SQL Server is processing the 2 approved hours row before the 2 declined hours row when calculating the cumulative sum --which would explain your current results--, despite the fact that rows themselves are returned to you in a different order (BTW, consider adding an order by clause to the query, otherwise, the order of the rows themselves are not guaranteed).
If the 2 rows do in fact share the exact same date, you'll have to find a 2nd column to remove the ambiguity and add that to the order by clause in the cumulative sum window function. Maybe you could add a timestamp field that you can order by.
Or maybe you always want the declined status to be considered ahead of the approved status when the AbsenceDate is the same. Here is an example of a query that would do exactly that (notice the changes in the order by clauses):
SELECT
lsm.EmployeeName,
pd.absenceDate,
pd.amountInDays * 8 AS [HoursReported],
pd.status,
(SUM(CASE WHEN pd.[status]='App' THEN (pd.amountInDays * 8)
ELSE 0 END) OVER (partition by lsm.[EmployeeName] order by pd.absenceDate,
case when pd.[status] = 'App' then 1 else 0 end)) AS [TotalUsedHours]
( #maxPSHours ) - (sum(
CASE WHEN pd.[status]='App' THEN (pd.amountInDays * 8)
ELSE 0 END)
over (
partition by lsm.[EmployeeName] order by pd.absenceDate,
case when pd.[status] = 'App' then 1 else 0 end)) AS [TotalRemainingHours]
FROM
[LocationStaffMembers] lsm
INNER JOIN
[PersonalDays] pd ON lsm.staffMemberId = pd.staffMemberId
ORDER BY lsm.[EmployeeName],
pd.absenceDate,
case when pd.[status] = 'App' then 1 else 0 end
How can one reference a calculated value from the previous row in a SQL query? In my case each row is an event that somehow manipulates the same value from the previous row.
The raw data looks like this:
Eventno Eventtype Totalcharge
3 ACQ 32
2 OUT NULL
1 OUT NULL
Lets say each Eventtype=OUT should half the previous row totalcharge in a column called Remaincharge:
Eventno Eventtype Totalcharge Remaincharge
3 ACQ 32 32
2 OUT NULL 16
1 OUT NULL 8
I've already tried the LAG analytic function but that does not allow me to get a calculated value from the previous row. Tried something like this:
LAG(remaincharge, 1, totalcharge) OVER (PARTITION BY ...) as remaincharge
But this didn't work because remaingcharge could not be found.
Any ideas how to achieve this? Would need a analytics function that can give me the the cumulative sum but given a function instead with access to the previous value.
Thank you in advance!
Update problem description
I'm afraid my example problem was to general, here is a better problem description:
What remains of totalcharge is decided by the ratio of outqty/(previous remainqty).
Eventno Eventtype Totalcharge Remainqty Outqty
4 ACQ 32 100 0
3 OTHER NULL 100 0
2 OUT NULL 60 40
1 OUT NULL 0 60
Eventno Eventtype Totalcharge Remainqty Outqty Remaincharge
4 ACQ 32 100 0 32
3 OTHER NULL 100 0 32 - (0/100 * 32) = 32
2 OUT NULL 60 40 32 - (40/100 * 32) = 12.8
1 OUT NULL 0 60 12.8 - (60/60 * 12.8) = 0
In your case you could work out the first value using the FIRST_VALUE() analytic function and the power of 2 that you have to divide by with RANK() in a sub-query and then use that. It's very specific to your example but should give you the general idea:
select eventno, eventtype, totalcharge
, case when eventtype <> 'OUT' then firstcharge
else firstcharge / power(2, "rank" - 1)
end as remaincharge
from ( select a.*
, first_value(totalcharge) over
( partition by 1 order by eventno desc ) as firstcharge
, rank() over ( partition by 1 order by eventno desc ) as "rank"
from the_table a
)
Here's a SQL Fiddle to demonstrate. I haven't partitioned by anything because you've got nothing in your raw data to partition by...
A variation on Ben's answer to use a windowing clause, which seems to take care of your updated requirements:
select eventno, eventtype, totalcharge, remainingqty, outqty,
initial_charge - case when running_outqty = 0 then 0
else (running_outqty / 100) * initial_charge end as remainingcharge
from (
select eventno, eventtype, totalcharge, remainingqty, outqty,
first_value(totalcharge) over (partition by null
order by eventno desc) as initial_charge,
sum(outqty) over (partition by null
order by eventno desc
rows between unbounded preceding and current row)
as running_outqty
from t42
);
Except it gives 19.2 instead of 12.8 for the third row, but that's what your formula suggests it should be:
EVENTNO EVENT TOTALCHARGE REMAININGQTY OUTQTY REMAININGCHARGE
---------- ----- ----------- ------------ ---------- ---------------
4 ACQ 32 100 0 32
3 OTHER 100 0 32
2 OUT 60 40 19.2
1 OUT 0 60 0
If I add another split so it goes from 60 to zero in two steps, with another non-OUT record in the mix too:
EVENTNO EVENT TOTALCHARGE REMAININGQTY OUTQTY REMAININGCHARGE
---------- ----- ----------- ------------ ---------- ---------------
6 ACQ 32 100 0 32
5 OTHER 100 0 32
4 OUT 60 40 19.2
3 OUT 30 30 9.6
2 OTHER 30 0 9.6
1 OUT 0 30 0
There's an assumption that the remaining quantity is consistent and you can effectively track a running total of what has gone before, but from the data you've shown that looks plausible. The inner query calculates that running total for each row, and the outer query does the calculation; that could be condensed but is hopefully clearer like this...
Ben's answer is the better one (will probably perform better) but you can also do it like this:
select t.*, (connect_by_root Totalcharge) / power (2,level-1) Remaincharge
from the_table t
start with EVENTTYPE = 'ACQ'
connect by prior eventno = eventno + 1;
I think it's easier to read
Here is a demo
I have a table called crewWork as follows :
CREATE TABLE crewWork(
FloorNumber int, AptNumber int, WorkType int, simTime int )
After the table was populated, I need to know how many times a change in apt occurred and how many times a change in floor occurred. Usually I expect to find 10 rows on each apt and 40-50 on each floor.
I could just write a scalar function for that, but I was wondering if there's any way to do that in t-SQL without having to write scalar functions.
Thanks
The data will look like this:
FloorNumber AptNumber WorkType simTime
1 1 12 10
1 1 12 25
1 1 13 35
1 1 13 47
1 2 12 52
1 2 12 59
1 2 13 68
1 1 14 75
1 4 12 79
1 4 12 89
1 4 13 92
1 4 14 105
1 3 12 115
1 3 13 129
1 3 14 138
2 1 12 142
2 1 12 150
2 1 14 168
2 1 14 171
2 3 12 180
2 3 13 190
2 3 13 200
2 3 14 205
3 3 14 216
3 4 12 228
3 4 12 231
3 4 14 249
3 4 13 260
3 1 12 280
3 1 13 295
2 1 14 315
2 2 12 328
2 2 14 346
I need the information for a report, I don't need to store it anywhere.
If you use the accepted answer as written now (1/6/2023), you get correct results with the OP dataset, but I think you can get wrong results with other data.
CONFIRMED: ACCEPTED ANSWER HAS A MISTAKE (as of 1/6/2023)
I explain the potential for wrong results in my comments on the accepted answer.
In this db<>fiddle, I demonstrate the wrong results. I use a slightly modified form of accepted answer (my syntax works in SQL Server and PostgreSQL). I use a slightly modified form of the OP's data (I change two rows). I demonstrate how the accepted answer can be changed slightly, to produce correct results.
The accepted answer is clever but needs a small change to produce correct results (as demonstrated in the above db<>fiddle and described here:
Instead of doing this as seen in the accepted answer COUNT(DISTINCT AptGroup)...
You should do thisCOUNT(DISTINCT CONCAT(AptGroup, '_', AptNumber))...
DDL:
SELECT * INTO crewWork FROM (VALUES
-- data from question, with a couple changes to demonstrate problems with the accepted answer
-- https://stackoverflow.com/q/8666295/1175496
--FloorNumber AptNumber WorkType simTime
(1, 1, 12, 10 ),
-- (1, 1, 12, 25 ), -- original
(2, 1, 12, 25 ), -- new, changing FloorNumber 1->2->1
(1, 1, 13, 35 ),
(1, 1, 13, 47 ),
(1, 2, 12, 52 ),
(1, 2, 12, 59 ),
(1, 2, 13, 68 ),
(1, 1, 14, 75 ),
(1, 4, 12, 79 ),
-- (1, 4, 12, 89 ), -- original
(1, 1, 12, 89 ), -- new , changing AptNumber 4->1->4 ges)
(1, 4, 13, 92 ),
(1, 4, 14, 105 ),
(1, 3, 12, 115 ),
...
DML:
;
WITH groupedWithConcats as (SELECT
*,
CONCAT(AptGroup,'_', AptNumber) as AptCombo,
CONCAT(FloorGroup,'_',FloorNumber) as FloorCombo
-- SQL SERVER doesnt have TEMPORARY keyword; Postgres doesn't understand # for temp tables
-- INTO TEMPORARY groupedWithConcats
FROM
(
SELECT
-- the columns shown in Andriy's answer:
-- https://stackoverflow.com/a/8667477/1175496
ROW_NUMBER() OVER ( ORDER BY simTime) as RN,
-- AptNumber
AptNumber,
ROW_NUMBER() OVER (PARTITION BY AptNumber ORDER BY simTime) as RN_Apt,
ROW_NUMBER() OVER ( ORDER BY simTime)
- ROW_NUMBER() OVER (PARTITION BY AptNumber ORDER BY simTime) as AptGroup,
-- FloorNumber
FloorNumber,
ROW_NUMBER() OVER (PARTITION BY FloorNumber ORDER BY simTime) as RN_Floor,
ROW_NUMBER() OVER ( ORDER BY simTime)
- ROW_NUMBER() OVER (PARTITION BY FloorNumber ORDER BY simTime) as FloorGroup
FROM crewWork
) grouped
)
-- if you want to see how the groupings work:
-- SELECT * FROM groupedWithConcats
-- otherwise just run this query to see the counts of "changes":
SELECT
COUNT(DISTINCT AptCombo)-1 as CountAptChangesWithConcat_Correct,
COUNT(DISTINCT AptGroup)-1 as CountAptChangesWithoutConcat_Wrong,
COUNT(DISTINCT FloorCombo)-1 as CountFloorChangesWithConcat_Correct,
COUNT(DISTINCT FloorGroup)-1 as CountFloorChangesWithoutConcat_Wrong
FROM groupedWithConcats;
ALTERNATIVE ANSWER
The accepted-answer may eventually get updated to remove the mistake. If that happens I can remove my warning but I still want leave you with this alternative way to produce the answer.
My approach goes like this: "check the previous row, if the value is different in previous row vs current row, then there is a change". SQL doesn't have idea or row order functions per se (at least not like in Excel for example; )
Instead, SQL has window functions. With SQL's window functions, you can use the window function RANK plus a self-JOIN technique as seen here to combine current row values and previous row values so you can compare them. Here is a db<>fiddle showing my approach, which I pasted below.
The intermediate table, showing the columns which has a value 1 if there is a change, 0 otherwise (i.e. FloorChange, AptChange), is shown at the bottom of the post...
DDL:
...same as above...
DML:
;
WITH rowNumbered AS (
SELECT
*,
ROW_NUMBER() OVER ( ORDER BY simTime) as RN
FROM crewWork
)
,joinedOnItself AS (
SELECT
rowNumbered.*,
rowNumberedRowShift.FloorNumber as FloorShift,
rowNumberedRowShift.AptNumber as AptShift,
CASE WHEN rowNumbered.FloorNumber <> rowNumberedRowShift.FloorNumber THEN 1 ELSE 0 END as FloorChange,
CASE WHEN rowNumbered.AptNumber <> rowNumberedRowShift.AptNumber THEN 1 ELSE 0 END as AptChange
FROM rowNumbered
LEFT OUTER JOIN rowNumbered as rowNumberedRowShift
ON rowNumbered.RN = (rowNumberedRowShift.RN+1)
)
-- if you want to see:
-- SELECT * FROM joinedOnItself;
SELECT
SUM(FloorChange) as FloorChanges,
SUM(AptChange) as AptChanges
FROM joinedOnItself;
Below see the first few rows of the intermediate table (joinedOnItself). This shows how my approach works. Note the last two columns, which have a value of 1 when there is a change in FloorNumber compared to FloorShift (noted in FloorChange), or a change in AptNumber compared to AptShift (noted in AptChange).
floornumber
aptnumber
worktype
simtime
rn
floorshift
aptshift
floorchange
aptchange
1
1
12
10
1
0
0
2
1
12
25
2
1
1
1
0
1
1
13
35
3
2
1
1
0
1
1
13
47
4
1
1
0
0
1
2
12
52
5
1
1
0
1
1
2
12
59
6
1
2
0
0
1
2
13
68
7
1
2
0
0
Note instead of using the window function RANK and JOIN, you could use the window function LAG to compare values in the current row to the previous row directly (no need to JOIN). I don't have that solution here, but it is described in the Wikipedia article example:
Window functions allow access to data in the records right before and after the current record.
If I am not missing anything, you could use the following method to find the number of changes:
determine groups of sequential rows with identical values;
count those groups;
subtract 1.
Apply the method individually for AptNumber and for FloorNumber.
The groups could be determined like in this answer, only there's isn't a Seq column in your case. Instead, another ROW_NUMBER() expression could be used. Here's an approximate solution:
;
WITH marked AS (
SELECT
FloorGroup = ROW_NUMBER() OVER ( ORDER BY simTime)
- ROW_NUMBER() OVER (PARTITION BY FloorNumber ORDER BY simTime),
AptGroup = ROW_NUMBER() OVER ( ORDER BY simTime)
- ROW_NUMBER() OVER (PARTITION BY AptNumber ORDER BY simTime)
FROM crewWork
)
SELECT
FloorChanges = COUNT(DISTINCT FloorGroup) - 1,
AptChanges = COUNT(DISTINCT AptGroup) - 1
FROM marked
(I'm assuming here that the simTime column defines the timeline of changes.)
UPDATE
Below is a table that shows how the distinct groups are obtained for AptNumber.
AptNumber RN RN_Apt AptGroup (= RN - RN_Apt)
--------- -- ------ ---------
1 1 1 0
1 2 2 0
1 3 3 0
1 4 4 0
2 5 1 4
2 6 2 4
2 7 3 4
1 8 5 => 3
4 9 1 8
4 10 2 8
4 11 3 8
4 12 4 8
3 13 1 12
3 14 2 12
3 15 3 12
1 16 6 10
… … … …
Here RN is a pseudo-column that stands for ROW_NUMBER() OVER (ORDER BY simTime). You can see that this is just a sequence of rankings starting from 1.
Another pseudo-column, RN_Apt contains values produces by the other ROW_NUMBER, namely ROW_NUMBER() OVER (PARTITION BY AptNumber ORDER BY simTime). It contains rankings within individual groups of identical AptNumber values. You can see that, for a newly encountered value, the sequence starts over, and for a recurring one, it continues where it stopped last time.
You can also see from the table that if we subtract RN from RN_Apt (could be the other way round, doesn't matter in this situation), we get the value that uniquely identifies every distinct group of same AptNumber values. You might as well call that value a group ID.
So, now that we've got these IDs, it only remains for us to count them (count distinct values, of course). That will be the number of groups, and the number of changes is one less (assuming the first group is not counted as a change).
add an extra column changecount
CREATE TABLE crewWork(
FloorNumber int, AptNumber int, WorkType int, simTime int ,changecount int)
increment changecount value for each updation
if want to know count for each field then add columns corresponding to it for changecount
Assuming that each record represents a different change, you can find changes per floor by:
select FloorNumber, count(*)
from crewWork
group by FloorNumber
And changes per apartment (assuming AptNumber uniquely identifies apartment) by:
select AptNumber, count(*)
from crewWork
group by AptNumber
Or (assuming AptNumber and FloorNumber together uniquely identifies apartment) by:
select FloorNumber, AptNumber, count(*)
from crewWork
group by FloorNumber, AptNumber