In my database, I have a user table and a workgroup table, and a many-to-many relationship. A user can belong to one or more workgroups. I am using entity framework for my ORM (EF 4.1 Code First).
User Table has users:
1,2,3,4,5,6,7,8,9,10
Workgroup table has workgroups:
A,B,C, D
WorkgroupUser table has entries
A1, A2, A3, A4, A5
B1, B3, B5, B7, B9
C2, C4, C6, C8, C10
D1, D2, D3, D9, D10
What I would like to do is:
Given user 4, it belongs to workgroups A,C
and has common users
1,2,3,4,5 (from workgroup A) and
2,4,6,8,10 from workgroup C
and the distinct set of users in common is 1,2,3,4,5,6,8,10
How do I write a LINQ statement (preferably in fluent API) for this?
Thank you,
Here's the general idea (since I don't know the properties of User and WorkGroup entity)
var result = context.users.Where(u => u.ID == 4)
.SelectMany(u => u.WorkGroups.SelectMany(wg => wg.Users))
.Distinct()
Related
I have 4 tables named A1, A2, B1, B2.
To fulfill a requirement, I have two ways to write SQL queries. The first one is:
(A1 UNION ALL A2) A JOIN (B1 UNION ALL B2) B ON A.id = B.a_id WHERE ...
And the second one is:
(A1 JOIN B1 on A1.id = B1.a_id WHERE ...) UNION ALL (A2 JOIN B2 on A2.id = B2.a_id WHERE ... )
I tried both approaches and realized they both give the same execution time and query plans in some specific cases. But I'm unsure whether they will always give the same performance or not.
So my question is when the first/second one is better in terms of performance?
In terms of coding, I prefer the first one because I can create two views on (A1 UNION ALL A2) as well as (B1 UNION ALL B2) and treat them like two tables.
The second one is better:
(A1 JOIN B1 on A1.id = B1.a_id WHERE ...) UNION ALL (A2 JOIN B2 on A2.id = B2.a_id WHERE ... )
It gives more information to Oracle CBO optimizer about how your tables are related to each other. CBO can calculate potentials plans' costs more precisely. It's all about cardinality, column statistics, etc.
Purely functionally, and without knowing what's in the tables,the first seems better - if data matches in a1 and b2, your 2nd query won't join it.
Lets say I have package A version 1 and package A version 2, Will call them A1 and A2 respectively.
If I have a pool of packages: A1, A2, B1, B2, C1, C2, D1, D2
A1 depends on B1, will represent as (A1, (B1)).
Plus A1 depends on any version of package C "C1 or C2 satisfy A1", will represent as (A1, (C1, C2))
combining A1 deps together, then A1 data-structure becomes: (A1, (B1), (C1, C2))
Also B1 depends on D1: (B1, (D1))
A1 structure becomes: (A1, ((B1, (D1))), (C1, C2))
similarly A2 structure is (A2, ((B2, (D2))), (C1, C2))
My question is: How can I select best candidate of package A, where I can select based on a condition (for example, the condition is the package does not conflict with current installed packages).
by combining A1 and A2: ((A1, ((B1, (D1))), (C1, C2)), (A2, ((B2, (D2))), (C1, C2)))
How can I traverse this data structure
So start with A1, if doesn't conflict check B1, if doesn't conflict check D1, if doesn't conflict check (C1, C2), and take one only either C1 or C2.
With this I end up selecting (A1, B1, D1, C1).
In case if A1 or any of its deps did not meet the condition, (for example if B1 conflicts with installed packages), then drop A1 entirely and move to check A2. then end up with (A2, B2, D2, C1).
What kind of traversal would that be?
I have been reading about in-order, pre-order, post-order traversal, and wondering if I need to do something similar here.
Assuming you are asking traversal on a more generic problem rather than working on this instance, I don't think there exists such a traversal.
Note that in-order is only applicable to BINARY trees. Any other kind of tree does not have in-order traversal. If your generic problem has B1, B2, B3, then apparently there wouldn't be a binary tree representation.
One property about traversal, is that the tree has all the information inclusively in the itself. When you traverse over a tree you never worry about "external information". In your case, your tree is not complete in information - you need to depend on external information to see if there is a conflict. e.g. B1 is installed - this information is never in the tree.
You can use adjacency list to represent the data:
Suppose the packages are A1, A2, B1, B2, C1, C2.
And A1 depends on B1 and C2, A2 depends on B1 and C1 and C2.
The above data can be represented as
[A1] -> [B1, C2]
[A2] -> [B1, C1, C2]
Use Topological Sorting to get the order of dependencies
Given a table:
T = {A1, A2, A3, A4}
How do you write a relational algebra statement that picks all tuples that have the same value for A3 as another tuple in the table?
You do a equijoin with T and itself on column A3.
T2←T,T⋈T.A3=T2.A3 T2
Now any tuple from T will be connected with all tuples that have the same value for A3. You can further select for a specific value of A3 from T and project to the attributes from T2.
I have an intermediate pig structure like
(A, B, (n. no Cs))
example:
(a1,b1, (c11,c12))
(a2,b2, (c21))
(a3,b3, (c31,c32, c33))
Now, I want the data in format
(a1, b1, c11)
(a1, b2, c12)
(a2, b2, c21) etc.
How do I go about doing it?
Essentially I want the size of the tuples, and then use this size for running a nested for loop.
Can you try the below approach?
input
a1 b1 (c11,c12)
a2 b2 (c21)
a3 b3 (c31,c32,c33)
PigScript:
A = LOAD 'input' AS(f1,f2,T:(f3:chararray));
B = FOREACH A GENERATE f1,f2,FLATTEN(T);
C = FOREACH B GENERATE f1,f2,FLATTEN(TOKENIZE(T::f3));
DUMP C;
Output:
(a1,b1,c11)
(a1,b1,c12)
(a2,b2,c21)
(a3,b3,c31)
(a3,b3,c32)
(a3,b3,c33)
I wish to create a program in Java which will ask the user a number of questions and report some results. It is pretty much like a survey. In order to explain the problem better consider the following example:
Let’s say that there are currently 4 questions available eg Qa, Qb, Qc and Qd. Each question has a number of possible options:
=> Question A has 4 possible options a1, a2, a3 and a4.
=> Question B has 3 possible options b1, b2 and b3
=> Question C has 5 possible options c1, c2, c3, c4 and c5
=> Question D has 2 possible options d1 and d2
Moreover there are some results available which will be reported based on the user’s answers in the above questions. Let’s assume that there are 5 such results called R1, R2, R3, R4 and R5. Each result has a number of characteristics. These characteristics are really answers to the above questions. More precisely:
=> The characteristics of R1 is the set of {Qa = a4, Qb = b2, Qc = c2, Qd = d1}
This says that R1 is related with Qa via the a1 option, with Qb via the b2 option and so on
=> R2: {Qa = a3, Qb = b3, Qc = c3, Qd = d2}
=> R3: {Qa = a4, Qb = b1, Qc = c1, Qd = d2}
=> R4: {Qa = a2, Qb = b2, Qc = c5, Qd = d1}
=> R5: {Qa = a1, Qb = b3, Qc = c4, Qd = d2}
Let’s say that a user U provides the following answers to the questions
{Qa = a4, Qb = b1, Qc = c1, Qd = d1}
The purpose of the program is to report the result which is closer to the user answers along with a percentage of how close it is. For instance since there is no any result which matches 100% the user answers the program should report the results which match as more answers as possible (above a certain threshold eg 50%). In that specific case the program should report the follow results:
=> R3 with 75% (since there are 3 matches on the 4 questions)
=> R1 with 50% (since there are 2 matches on the 4 questions)
Notice that R4 has one match (so 25%) whereas R2 and R5 have no matches at all (so 0%).
The main issue on implementing the above program is that there are a lot of questions (approximately 30) with a number of answers each (3-4 answers each). I am not aware of an efficient algorithm which can retrieve the results which are closer to the user answers. Notice that the way that these results are stored is not important at all. You can assume that the results are stored in a relational database and that SQL query is used to retrieve them.
The only solution I can think of is to perform an exhaustive search but this not efficient at all. In other words I am thinking to do the following:
=> First try to retrieve results which match exactly the user answers:
{Qa = a4, Qb = b1, Qc = c1, Qd = d1}
=> If no results exist then change the option of a question (eg Qa) and try again. For example try:
{Qa = a1, Qb = b1, Qc = c1, Qd = d1}
=> If there is still nothing then try the rest possible options for Qa eg a2, a3
=> If there is still nothing then give Qa the initial user answer (that is a4) and move to Qb to do something similar. For example try something like: {Qa = a4, Qb = b2, Qc = c1, Qd = d1}
=> If after trying all the possible options for all questions one by one there are any results then try changing the options of COMBINATIONS of questions. For example try change the options of two questions at the same time (eg Qa and Qb): {Qa = a1, Qb = b2, Qc = c1, Qd = d1}
=> Then try combinations of three questions and so on...
Clearly the above algorithm would be extremely slow on a large number of questions. Is there any known algorithm or heuristic which is more efficient than the above algorithm?
Thanks in advance
"Only" 30 Questions?
Then the following "stupid" algorithm will probably be faster than any highly "intelligent" and complicated algorithm.
iterate over characteristics
score = 0
iterate over questions
if questions's answer is right in current characteristic
score++
Then add a variable which keeps track of the maximum value and matching characteristic and you are set.
Runtime is size of characteristics * size of questions, whereas the algorithm you are describing can have exponential runtime, and on top of that is much more complicated both for programming and for executing (due to effects as branch misprediction)