I have a fairly simple project set up to demonstrate what I want here. Here's the data:
Group
ID Name
1 Group 1
2 Group 2
3 Group 3
Person
ID GroupID Age Name
1 1 18 John
2 1 21 Stephen
3 1 18 Kate
4 2 18 Mary
5 2 19 Joseph
6 2 19 Michael
7 3 21 David
8 3 22 Kevin
9 3 21 Julian
I have 1 measure in my cube called Person Count which is a Distinct count on Person ID
I have set up each non-ID column in the dimensions as attributes (Age, Person Name, Group).
When I process and browse the cube in Business Intelligence Development Studio, I get the following result set:
But what I actually want here are the rows for Age to aggregate up the count of the Person Count together, so here it should show 2 and only one row for 18.
Is this possible (and how)?
Turns out this was a problem with the way I set up the Age attribute for the dimension.
I had:
KeyColumns = Person.ID
ValueColumn = Person.Age.
I don't know why I did this, but the solution is to delete the content of ValueColumn and set the KeyColumns to Person.Age again.
I now get the following result:
Everything else is the same for the project; this was the only change and is exactly what I wanted. If I get any issues with it I will keep this post updated for anyone else who may run into this in the future.
Related
I wanted to create a new column (Group ID) on the basis of following conditions:
If the DOB and first three letters of Name are same, then it must fall is same Group ID.
Name
DOB
Group ID
Anny
18-01-1922
0
Anny Scott
01-01-1950
1
Annie
01-01-1950
1
David
14-02-1950
2
David Kern
15-02-1951
3
William Perry
15-02-1953
4
Kenneth Field
15-02-1953
5
This how I want to create the groups
I have used the following code, to create the group ID for name (If first three letters are matched)
df['Group ID Name']=df.groupby(df['name'].str[:3]).ngroup()
The following code is used to create the group ID for DOB (If two records have the same DOB)
df['Group ID DOB']=df.groupby('Date of Birth').ngroup()
I want to use both the condition to create the Group ID, please help me out for the same.
Add multiple columns in list and also for correct ordering sort=False:
df['Group ID Name'] = df.groupby(['DOB',df['Name'].str[:3]], sort=False).ngroup()
print (df)
Name DOB Group;ID Group ID Name
0 Anny 18-01-1922 0 0
1 Anny Scott 01-01-1950 1 1
2 Annie 01-01-1950 1 1
3 David 14-02-1950 2 2
4 David Kern 15-02-1951 3 3
5 William erry 15-02-1953 4 4
6 Kenneth Field 15-02-1953 5 5
I am trying to convert some calculated fields in Hyperion Studio to SQL. I got stuck trying to aggregate enrollment counts based on a shared course location/date/time. I have a flag created using LEAD to mark rows where the course location is identical to the row below. I need to roll up those consecutive rows, based on the flag, to get a total enrollment count for each location. The flag calculation includes exceptions (seen in example below, rows 2 and 3) where I specifically command it not to flag despite a shared location.
This is an example of base data that includes the flag (Roll Up is the field I'm trying to calculate):
SectionID Course Name Title Instructor Location Enrollment Flag Roll Up
1 EN.100.201 Title1 Prof. W Building 1 16
2 EN.550.365 Title2 Prof. X Building 2 5
3 EN.530.403 Title3 Prof. Y Building 2 30
4 EN.400.401 Title4 Prof. Z Building 3 25 Y
5 EN.400.601 Title4 Prof. Z Building 3 10
Here is the output I'm trying to achieve
SectionID Course Name Title Instructor Location Enrollment Flag Roll Up
1 EN.100.201 Title1 Prof. W Building 1 16 16
2 EN.550.365 Title2 Prof. X Building 2 5 5
3 EN.530.403 Title3 Prof. Y Building 2 30 30
5 EN.400.601 Title4 Prof. Z Building 3 10 35
Thanks in advance! Edit: made this easier to read; sorry, I'm new here.
Pardon the title gore. I'm having trouble finding a good way to express my question, which is endemic to the problem.
The Tables
season
id name
---- ------
1 Season 1
2 Season 2
3 Season 3
episode
id season_id number title
---- ----------- -------- ---------------------------------------
1 1 1 Pilot
2 1 2 1x02 - We Got Picked Up
3 1 3 1x03 - This is the Third Episode
4 2 1 2x01 - We didn't get cancelled.
5 2 2 2x02 - We're running out of ideas!
6 3 1 3x01 - We're still here.
7 3 2 3x02 - Okay, this game show is dying.
8 3 3 3x03 - Untitled
score
id episode_id score contestant_id (table not given)
---- ------------ ------- ---------------------------------
1 1 35 1
2 1 -12 2
3 1 8 3
4 1 5 4
5 2 13 1
6 2 -2 5
7 2 3 3
8 2 -14 6
9 3 -14.5 1
10 3 -3 2
11 3 1.5 7
12 3 9.5 5
13 4 22.8 1
14 4 -3 8
15 5 2 1
16 5 13.5 9
17 5 7 3
18 6 13 1
19 6 -84 10
20 6 12 11
21 7 3 1
22 7 10 2
23 8 29 1
24 8 1 5
As you can see, you have multiple episodes per season, and multiple scores per episode (one score per contestant). Contestants can reappear in later episodes (irrelevant), scores are floating point values, and there can be an arbitrary number of scores per episode.
So what am I looking for?
I'd like to get the average total episode score per season, where the total episode score is the sum of all the scores in an episode. Mathematically, this comes out to be the sum of all scores in a season divided by the number of episodes. Easy enough to comprehend, but I have had trouble doing it in a single query and getting the correct result. I'd like an output like the following:
name average_total_episode_score
---------- -----------------------------
Season 1 9.83
Season 2 21.15
Season 3 -5.33
The top-level query needs to be on the season table as it will be combined with other, similar queries on the same table. It's easy enough to do this with an aggregate in a subquery, but an aggregation executes the subquery, failing my single-query requirement. Can this be done in a single query?
Hope this should work
Select s.id, avg(score)
FROM Season S,
Episode e,
Score sc
WHERE s.id = e.season_id
AND e.id = sc.episode_id
Group by s.id
Okay, just figured it out. As usual, I had to write and post a whole book before the simple solution descended upon me.
The problem in my query (which I didn't give in the question) was the lack of a DISTINCT count. Here is a working query:
SELECT
"season"."id",
"season"."name",
(SUM("score"."score") / COUNT(DISTINCT "episode"."id")) AS "average_total_episode_score"
FROM "season"
LEFT OUTER JOIN "episode"
ON ("season"."id" = "episode"."season_id")
LEFT OUTER JOIN "score"
ON ("episode"."id" = "score"."episode_id")
GROUP BY "season"."id"
select Se.id AS Season_Id, sum(score) As season_score, avg(score) from score S join episode E ON S.episode_id = E.id
join Season se ON se.id = e.season_id group by se.id
My company sends folks to training. Based on projected new hires/transfers, I was asked to generate a report that estimates the number of seats we need in each course broken out by quarter.
Question: My question is two-fold:
What is the best way to represent a sequence of courses (i.e. prerequisites) in a relational DB?
How do I create the query(-ies) necessary to produce the following desired output:
Desired Output:
ID PersonnelID CourseID ProjectedStartDate ProjectedEndDate
1 1 1 1/14/2017 1/14/2017
2 2 1 2/17/2017 2/17/2017
3 2 2 2/18/2017 2/19/2017
4 2 3 2/20/2017 2/20/2017
5 3 49 1/18/2017 2/03/2017
6 …
Background Info: The courses are taken in-sequence: the first few courses are orientation courses for the company, and later courses are more specific to the employee's workrole. There are over 50 different courses, 40 different workroles and we're projecting ~1k new hires/transfers. Each work role must take a sequence of courses in a prescribed order, but I'm having trouble representing this ordering and subsequently writing the necessary query.
Existing Tables:
I have several tables that I've used to store the data: Personnel, LnkPersonnelToWorkroles,Workroles, LnkWorkrolesToCourses, and Courses (there's many others as well, but I omit them for the sake of scoping this question down). Here's some notional data from these tables:
Personnel (These are the projected new hires and their estimated arrival date.)
ID DisplayName RequiredCompletionDate
1 Kristel Bump 10/1/2016
2 Shelton Franke 3/11/2017
3 Shaunda Launer 4/16/2017
4 Clarinda Kestler 3/13/2017
5 My Wimsatt 6/6/2017
6 Gillian Bramer 10/25/2016
7 ...
Workroles (These are the positions in the company)
ID Workrole
1 Manager
2 Secretary
3 Admin Asst.
4 ...
LnkPersonnelToWorkroles (Links projected new hires to their projected workrole)
ID PersonnelID WorkroleID
1 1 1
2 2 1
3 3 1
4 4 1
5 5 1
6 6 1
7 ...
Courses (All courses available)
ID CourseName LengthInDays
1 Orientation 1
2 Email Etiquette 2
3 Workplace Safety 1
4 ...
LnkWorkrolesToCourses
(Links workroles to their required courses in a Many-to-Many relationship)
ID WorkroleID CourseID
1 1 1
2 2 1
3 2 2
4 2 3
5 3 49
6 ...
Thoughts: My approach is to first develop a person-by-person schedule based upon the new hire's target completion date and workrole. Then for each class, I could sum the number of new hires starting in that quarter.
I've considered trying to represent the courses in the most general way I could think of (i.e. using a directed acyclic graph), but since most of the courses have only a single prerequisite course, I think it's much easier to represent the prerequisites using the Prerequisites table below; however, I don't know how I would use this in a query.
Prerequisites (Is this a good idea?)
ID CourseID PrereqCourseID
1 2 1
2 3 1
3 4 1
4 5 4
5 ...
Note: I am not currently concerned with whether or not the courses are actually offered on those days; we will figure out the course schedules once we know approximately how many we need each quarter. Right now, we're trying to estimate the demand for each course.
Edit 1: To clarify the Desired Output table: if the person begins course 1 on day D, then they can't start course 2 until after they finish course 1, i.e. until the next day. For courses with a length L >1 days, the start date for a subsequent courses is delayed L days. Notice this effect playing out for workrole ID 2 in the Desired Output table: He is expected to arrive on 2/17, start and complete course 1 the same day, begin course 2 the next day (on 2/18), and finish course 2 the day after that (on 2/19).
I'm posting this answer because it gives me an approximate solution; other answers are still welcome.
I avoided a prerequisite table altogether and opted for a simpler approach: a partial ordering of the courses.
First, I drew the course prerequisite tree; it looked similar to this image:
I defined a partial ordering of the courses based on their depth in the prerequisite tree. In the picture above, CHM124 and High School Chem w/ Lab are priority 1, CHM152 is priority 2, CHM 153 is priority 3, CHM260 and CHM 270 are priority 4, and so on... This partial ordering was stored in the CoursePriority table:
CoursePriority:
ID CourseID Priority
1 1 1
2 2 2
3 3 3
4 4 3
5 5 4
6 6 3
7 ...
So that no two courses would every be taken at the same time, I perturbed each course's priority by a small random number using the following Update query:
UPDATE CoursePriority SET CoursePriority.Priority = [Priority]+Rnd([ID])/1000;
(I used [ID] as input to the Rnd method to ensure each course was perturbed by a different random number.) I ended up with this:
ID CourseID Priority
1 1 1.000005623
2 2 2.000094955
3 3 3.000036401
4 4 3.000052486
5 5 4.000076711
6 6 3.00000535
7 ...
The approach above answers my first question "What is the best [sensible] way to represent a sequence of courses (i.e. prerequisites) in a relational DB?" Now as for generating the course schedule...
First, I created a query qryLnkCoursesPriorities to link Courses to the CoursePriority table:
SELECT Courses.ID AS CourseID, Courses.DurationInDays, CoursePriority.Priority
FROM Courses INNER JOIN CoursePriority ON Courses.ID = CoursePriority.CourseID;
Result:
CourseID DurationInDays Priority
1 35 1.000076177
2 21 2.000148297
3 28 3.000094352
4 14 3.000081442
5...
Second, I created the qryWorkrolePriorityDelay query:
SELECT LnkWorkrolesToCourses.WorkroleID, qryLnkCoursePriorities.CourseID AS CourseID, qryLnkCoursePriorities.Priority, qryLnkCoursePriorities.DurationInDays, ([DurationInDays]+Nz(DSum("DurationInDays","qryLnkCoursePriorities","[Priority]>" & [Priority] & ""))) AS LeadTimeInDays
FROM LnkWorkrolesToCourses INNER JOIN qryLnkCoursePriorities ON LnkWorkrolesToCourses.CourseID = qryLnkCoursePriorities.CourseID
ORDER BY LnkWorkrolesToCourses.WorkroleID, qryLnkCoursePriorities.Priority;
Simply put: The qryWorkrolePriorityDelay query tells me how many days in advance each course should be taken to ensure the new hire can complete all subsequent courses prior to their required training completion deadline. It looks like this:
WorkroleID CourseID Priority DurationInDays LeadTimeInDays
1 7 1.000060646 7 147
1 1 1.000076177 35 140
1 2 2.000148297 21 105
1 4 3.000081442 14 84
1 6 3.000082824 14 70
1 3 3.000094352 28 56
1 5 4.000106905 28 28
2...
Finally, I was able to bring this all together to create the qryCourseSchedule query:
SELECT Personnel.ID AS PersonnelID, LnkWorkrolesToCourses.CourseID, [ProjectedHireDate]-[leadTimeInDays] AS ProjectedStartDate, [ProjectedHireDate]-[leadTimeInDays]+[Courses].[DurationInDays] AS ProjectedEndDate
FROM Personnel INNER JOIN (((LnkWorkrolesToCourses INNER JOIN (Courses INNER JOIN qryWorkrolePriorityDelay ON Courses.ID = qryWorkrolePriorityDelay.CourseID) ON (Courses.ID = LnkWorkrolesToCourses.CourseID) AND (LnkWorkrolesToCourses.WorkroleID = qryWorkrolePriorityDelay.WorkroleID)) INNER JOIN LnkPersonnelToWorkroles ON LnkWorkrolesToCourses.WorkroleID = LnkPersonnelToWorkroles.WorkroleID) INNER JOIN CoursePriority ON Courses.ID = CoursePriority.CourseID) ON Personnel.ID = LnkPersonnelToWorkroles.PersonnelID
ORDER BY Personnel.ID, [ProjectedHireDate]-[leadTimeInDays]+[Courses].[DurationInDays];
This query gives me the following output:
PersonnelID CourseID ProjectedStartDate ProjectedEndDate
1 7 5/7/2016 5/14/2016
1 1 5/14/2016 6/18/2016
1 2 6/18/2016 7/9/2016
1 4 7/9/2016 7/23/2016
1 6 7/23/2016 8/6/2016
1 3 8/6/2016 9/3/2016
1 5 9/3/2016 10/1/2016
2...
With this output, I created a pivot table, where course start dates were grouped by quarter and counted. This gave me exactly what I needed.
Given the following SQL tables:
Administrators:
id Name rating
1 Jeff 48
2 Albert 55
3 Ken 35
4 France 56
5 Samantha 52
6 Jeff 50
Meetings:
id originatorid Assitantid
1 3 5
2 6 3
3 1 2
4 6 4
I would like to generate a table from Ken's point of view (id=3) therefore his id could be possibly present in two different columns in the meetings' table. (The statement IN does not work since I introduce two different field columns).
Thus the ouput would be:
id originatorid Assitantid
1 3 5
2 6 3
If you really just need to see which column Ken's id is in, you only need an OR. The following will produce your example output exactly.
SELECT * FROM Meetings WHERE originatorid = 3 OR Assistantid = 3;
If you need to take the complex route and list names along with meetings, an OR in your join's ON clause should work here:
SELECT
Administrators.name,
Administrators.id,
Meetings.originatorid,
Meetings.Assistantid
FROM Administrators
JOIN Meetings
ON Administrators.id = Meetings.originatorid
OR Administrators.id = Meetings.Assistantid
Where Administrators.name = 'Ken'