I need find the number of days between status change in SQL Server 2014.
For example, please see the data below
+--------+--------+------------+-------------+
| status | Number | updated_on | opened_at |
+--------+--------+------------+-------------+
| Draft | 100 | 2017-11-03 | 2017-11-03 |
| Draft | 100 | 2017-12-12 | 2017-11-03 |
| WIP | 100 | 2017-12-12 | 2017-11-03 |
| Appr | 100 | 2018-01-05 | 2017-11-03 |
| Launch | 100 | 2018-01-10 | 2017-11-03 |
| Close | 100 | 2018-01-11 | 2017-11-03 |
+--------+--------+------------+-------------+
Based on the above input, I need to get
Draft --- 40 days,
WIP --- 23 days,
appro -- 5 days,
deploy/launch - 1 days,
closed --- 69 days
Please help me with SQL query to arrive this results.
Thanks.
I don't think your numbers are right. But this should do what you want, assuming that the statuses are unique:
select status,
datediff(day, updated_on, lead(updated_on) over (order by updated_on) ) as days
from t;
I don't understand the first and last numbers, though.
Try this
SELECT
tb.status,
DATEDIFF(dayofyear, tb.opened_at, tb.LastUpdate) AS DaysInDifference
FROM
(
SELECT
DISTINCT
status,
Max(updated_on) OVER(PARTITION BY [status] )LastUpdate,
opened_at
FROM Table1
)AS tb
Related
I have a table with columns as follows:
+-----------+--------------------+---------------+-------------+
| person_id | appointment_status | starting_date | ending_date |
+-----------+--------------------+---------------+-------------+
| 1 | P | 2011-11-23 | 2012-11-23 |
+-----------+--------------------+---------------+-------------+
| 2 | JO | 2011-11-23 | 2012-11-23 |
+-----------+--------------------+---------------+-------------+
Based on the table, I wanted to output the total number of the person registered in a certain year group by their status. Basically something like this:
+-----------+---------------+------+
| Status | No. of Person | Year |
+-----------+---------------+------+
| Permanent | 5 | 2011 |
+-----------+---------------+------+
| Job Order | 16 | 2011 |
+-----------+---------------+------+
| Permanent | 10 | 2012 |
+-----------+---------------+------+
| Job Order | 19 | 2012 |
+-----------+---------------+------+
Assuming that in the year 2011, there are about 5 registered persons(employees) who are permanent and 16 on job orders. Then following year 2012, there are 10 permanent and 19 job orders.
Try this:
SELECT CASE appointment_status
WHEN 'P' THEN 'Permanent '
WHEN 'JO' THEN 'Job Order'
END AS [Status]
,COUNT(person_id) AS [No. of Person]
,YEAR(starting_date) AS [Year]
FROM [my_table]
GROUP BY CASE appointment_status
WHEN 'P' THEN 'Permanent '
WHEN 'JO' THEN 'Job Order'
END
,YEAR(starting_date);
Let's say I have the following table (data is completely fiction):
ID | MonthDate | PersonID | Name | Status | MonthsAgoSinceLastCheck
1 | 2017-12 | 900 | Jack | Ill | -
2 | 2018-01 | 900 | Jack | Ill | 1
3 | 2018-02 | 900 | Jack | Ill | 2
4 | 2018-03 | 900 | Jack | Healthy | 1
5 | 2017-02 | 901 | Bill | Ill | -
6 | 2017-03 | 901 | Bill | Ill | 1
7 | 2017-05 | 901 | Bill | Healthy | 1
For each record, I would like to see the previous status that person had X months ago since last check (column MonthsAgoSinceLastCheck). Notice that MonthDate can skip months.
So in this case, the result would be
ID | MonthDate | PersonID | Name | Status | MonthsAgoSinceLastCheck | PreviousSatus
1 | 2017-12 | 900 | Jack | Ill | - | -
2 | 2018-01 | 900 | Jack | Ill | 1 | Ill
3 | 2018-02 | 900 | Jack | Ill | 2 | Ill
4 | 2018-03 | 900 | Jack | Healthy | 1 | Ill
5 | 2017-02 | 901 | Bill | Healthy | - | -
6 | 2017-03 | 901 | Bill | Healthy | 1 | Healthy
7 | 2017-05 | 901 | Bill | Ill | 2 | Healthy
Any sugestions/tips? I tried to do this with CTE's and self-joins but failed on both.
It's way easier to use full dates than year and months separately. The first thing you should do is generate a full date from your year + month. Then just self join with previous month, depending on the last check.
;WITH DataWithDates AS
(
SELECT
T.ID,
MonthDate = CONVERT(DATE, T.MonthDate + '-01'),
T.PersonID,
T.Name,
T.Status,
T.MonthsAgoSinceLastCheck
FROM
YourTable AS T
)
SELECT
D.ID,
D.MonthDate,
D.PersonID,
D.Name,
D.Status,
D.MonthsAgoSinceLastCheck,
PreviousStatus = N.Status
FROM
DataWithDates AS D
LEFT JOIN DataWithDates AS N ON
D.PersonID = N.PersonID AND
N.MonthDate = DATEADD(MONTH, -1 * D.MonthsAgoSinceLastCheck, D.MonthDate)
I'm assuming your MonthDate has values for all rows, otherwise the conversion will fail. I'm also assuming that your - values for MonthsAgoSinceLastCheck are actually NULL.
try this:
select *,LAG(Status) OVER(Partition by Name Order by MonthDate,Id) AS PreviousSatus
from tab1
order by id
SQl Fiddle:http://sqlfiddle.com/#!18/04407/4
The header of question might be confusing so I put my issue into words:
I have a table with master_ids, ids and years. A master_id can contain different ids. Each Id is associated with a year. I already partitioned by master_id and gave each year a rank (year_rank).
+-----------+----+------+-----------+
| master_id | id | year | year_rank |
+-----------+----+------+-----------+
| 100 | 1 | 2017 | 1 |
| 100 | 2 | 2016 | 2 |
| 100 | 3 | 2015 | 3 |
| 200 | 9 | 2001 | 1 |
| 300 | 5 | 2020 | 1 |
| 300 | 4 | 2010 | 2 |
| 400 | 7 | 1999 | 1 |
| 400 | 11 | 1996 | 2 |
| 500 | 20 | 1999 | 1 |
| 600 | 25 | 2005 | 1 |
| 600 | 29 | 2005 | 1 |
+-----------+----+------+-----------+
My goal is to pick only the clusters which have more than 1 record in order to compare it:
+-----------+----+------+-----------+
| master_id | id | year | year_rank |
+-----------+----+------+-----------+
| 100 | 1 | 2017 | 1 |
| 100 | 2 | 2016 | 2 |
| 100 | 3 | 2015 | 3 |
| 300 | 5 | 2020 | 1 |
| 300 | 4 | 2010 | 2 |
| 400 | 7 | 1999 | 1 |
| 400 | 11 | 1996 | 2 |
+-----------+----+------+-----------+
If I put where year_rank > 1 it eliminates the first rows in the clusters with multiple records which I don't want. How can I solve this? I thought about a group by but I don't know how to apply this.
Thank you very much!
Edit: Completely updated for new requirement. This will only show records for master_ids which have multiple years associated with them, however it will show all records associated for that master_id even if they are in the same year (see 600 vs 700).
SQLFiddle here
We will perform your year_rank in cte1 so we can aggregate it with the MAX() function in cte2 to filter out where max is greater than whatever variable you want to put there. We then query cte1 and join on cte2 to only show the records for master_ids that have multiple years associated with them.
WITH cte1 AS (
SELECT
master_id,
id,
year,
RANK() OVER (PARTITION BY master_id ORDER BY year DESC) AS year_rank
FROM tbl
),
cte2 AS (
SELECT
master_id
FROM cte1
GROUP BY master_id
HAVING MAX(year_rank) > 1
)
SELECT
cte1.master_id,
cte1.id,
cte1.year,
cte1.year_rank
FROM cte1
JOIN cte2 ON
cte1.master_id = cte2.master_id
I figured out to eliminate rows which don't have a discrepancy in years within their master_id:
select *,
case
when (master_id = (lead(master_id) over (order by master_id))) and
(year = (lead(service_year) over (order by master_id))) then 'no show'
when (master_id = (lag(master_id) over (order by master_id))) and
(year = (lag(service_year) over (order by master_id))) then 'no show'
else ''
end as note
from table
Now I can put all of that into a temp table and delete the records which have 'no show' in the note column.
What do you think of this? Is there an easier way?
I have a issues table where users can log worked hours and estimate hours that looks like this
id | assignee | task | timespent | original_estimate | date
--------------------------------------------------------------------------
1 | john | design | 2 | 3 | 2013-01-01
2 | john | mockup | 2 | 3 | 2013-01-02
3 | john | design | 2 | 3 | 2013-01-01
4 | rick | mockup | 5 | 4 | 2013-01-04
And I need to sum and group the worked and estimated hours by task and date to get this
assignee | task | total_spent | total_estimate | date
------------------------------------------------------------------
john | design | 4 | 6 | 2013-01-01
john | mockup | 2 | 3 | 2013-01-02
rick | design | 5 | 4 | 2013-01-04
Ok, this is easy, I've already got this:
SELECT assignee, task, SUM(timespent) as total_spent, SUM(original_estimate) AS total_estimate, date FROM issues GROUP BY assignee, task, date
My problem is I need to also show the assignees that did not logged hours on any task that day, I mean:
assignee | task | total_spent | total_estimate | date
------------------------------------------------------------------
john | design | 4 | 6 | 2013-01-01
john | mockup | 2 | 3 | 2013-01-02
rick | design | 5 | 4 | 2013-01-04
pete | design | 0 | 0 | 2013-01-01
pete | mockup | 0 | 0 | 2013-01-02
liz | design | 0 | 0 | 2013-01-04
liz | mockup | 0 | 0 | 2013-01-04
The goal is to draw a chart like this http://jsfiddle.net/uUjst/embedded/result/
You need the Assignees in their own separate table to join from.
SELECT tblAssignee.Name, task, SUM(timespent) as total_spent, SUM(original_estimate) AS total_estimate, date
FROM tblAssignee
LEFT JOIN issue ON issues.assignee = tblAssignee.Name
GROUP BY tblAssignee.Name, task, date
Assuming that you have a user table, but not a tasks or dates table... meaning that we have to derive these values from the values present in issues:
;WITH dates AS (
SELECT DISTINCT date
FROM issues
), tasks AS (
SELECT DISTINCT task
FROM issues
)
SELECT
u.user as assignee,
t.task,
SUM(i.timespent) as total_spent,
SUM(i.original_estimate) AS total_estimate,
d.date
FROM
users u CROSS JOIN
dates d CROSS JOIN
tasks t LEFT OUTER JOIN
issues i ON
i.assignee = u.user
AND i.task = t.task
AND i.date = d.date
GROUP BY u.user, t.task, d.date
SELECT
A.name,
task,
ISNULL(SUM(timespent), 0) as total_spent,
ISNULL(SUM(original_estimate), 0) AS total_estimate,
date
FROM Assignee A
LEFT JOIN issue
ON issues.assignee = A.Name
GROUP BY A.name, task, date
I have two tables:
A lookup table (tabOne):
KEY | Group | Name | Desc | Val_Key
----------------------------------------
1 | a | NameA | DescA | 10
2 | b | NameB | DescB | 20
3 | c | NameC | DescC | 30
4 | d | NameD | DescD | 40
5 | e | NameE | DescE | 50
6 | f | NameF | DescF | 60
A second table containing readings (tabTwo):
KEY | Date | Reading | Val_Key
----------------------------------------
1 | Date | Read | 10
2 | Date | Read | 20
3 | Date | Read | 40
4 | Date | Read | 40
5 | Date | Read | 30
6 | Date | Read | 20
7 | Date | Read | 40
8 | Date | Read | 20
9 | Date | Read | 10
10 | Date | Read | 20
11 | Date | Read | 50
12 | Date | Read | 60
What I need to do is join tabTwo with TabOne and create a column with the newest Reading and a column with the oldest reading for each item in the group column of TabOne.
At the end of the day I want a table that look as follow:
KEY | Group | Name | Desc | Val_Key | LastReading | FirstReading |
-------------------------------------------------------------------------
1 | a | NameA | DescA | 10 | | |
2 | b | NameB | DescB | 20 | | |
3 | c | NameC | DescC | 30 | | |
4 | d | NameD | DescD | 40 | | |
5 | e | NameE | DescE | 50 | | |
6 | f | NameF | DescF | 60 | | |
Thanks!
Freddie
If this is Sql Server 2005 or newer, outer apply will help:
select TabOne.*,
last.Reading LastReading,
first.Reading FirstReading
from TabOne
outer apply
(
select top 1
Reading
from TabTwo
where TabTwo.Val_Key = TabOne.val_Key
order by TabTwo.Date desc
) last
outer apply
(
select top 1
Reading
from TabTwo
where TabTwo.Val_Key = TabOne.val_Key
order by TabTwo.Date asc
) first
Live test is # Sql Fiddle.
#Nikola Markovinović's solution can be made more universally applicable if the subqueries are moved directly to the main query's SELECT clause, which is possible each of them retrieves only one value and is, therefore, valid as a scalar expression:
SELECT
t1.[KEY],
t1.[Group],
t1.Name,
t1.[Desc],
t1.Val_Key,
(
SELECT TOP 1 Reading
FROM TabTwo
WHERE Val_Key = t1.Val_Key
ORDER BY Date DESC
) AS LastReading,
(
SELECT TOP 1 Reading
FROM TabTwo
WHERE Val_Key = t1.Val_Key
ORDER BY Date ASC
) AS FirstReading
FROM TabOne t1
If you needed e.g. dates along the way, you would probably have to stick to Nikola's solution. There is an alternative to it, but it's more cumbersome (albeit more standard too): it would involve grouping TabTwo's data by Val_Key to get earliest/latest dates per Val_Key, then joining back to TabTwo to access entire rows corresponding to the found dates to finally pull the necessary columns, and ultimately joining both result sets to TabOne to get the final column set.