But while looking for the all vertices connected to a given vertex, the number of cartesian products of the table depends on the number of vertices in the graph (number of tuples at max) in the table, which is unknown.

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+25 votes

Suppose the adjacency relation of vertices in a graph is represented in a table Adj (X,Y). Which of the following queries cannot be expressed by a relational algebra expression of constant length?

- List all vertices adjacent to a given vertex
- List all vertices which have self loops
- List all vertices which belong to cycles of less than three vertices
- List all vertices reachable from a given vertex

+29 votes

Best answer

Answer is D.

**(A)** :-> This is simple select query query.

**(B)** :-> This is simple query we need to check X=Y in where clause.

**(C) **:-> Cycle $< 3$ . Means cycle of length $1$ & $2$. Cycle of length 1 is easy., same as self loop. Cycle of length $2$ is also not too hard to compute. Though it'll be little complex, will need to do like $(X,Y)$ & $(Y, X )$ both present & $X != Y$,. We can do this with constant RA query.

**(D)** :-> This is most hard part. Here we need to find closure of vertices. This willl need kind of loop. If the graph is like skewed tree, our query must loop for $O(N)$ times. We can't do with constant length query here.

Answer :-> D

+6

Cycle of length 2 can be found by cartesian product of Adj tables renamed as A and B and then applying the select condition -> A.x=B.y and A.y=B.x. We can simply find cycles of length n with given n in input. Here, the number of cartesian products is based on input n.

But while looking for the all vertices connected to a given vertex, the number of cartesian products of the table depends on the number of vertices in the graph (number of tuples at max) in the table, which is unknown.

But while looking for the all vertices connected to a given vertex, the number of cartesian products of the table depends on the number of vertices in the graph (number of tuples at max) in the table, which is unknown.

+1

Constant length means it has specific value and value cannot go upto infinite

Here we can think of adjacency matrix

(D) is telling in it's row, if A to B=1

B to C=1

C to D=1

D to E=1 etc etc ,

but , there can be many path like for path A to D

we can go A-B-D

or A-E-D

or, A-C-B-D

etc

So, cannot measure in constant length

Here we can think of adjacency matrix

(D) is telling in it's row, if A to B=1

B to C=1

C to D=1

D to E=1 etc etc ,

but , there can be many path like for path A to D

we can go A-B-D

or A-E-D

or, A-C-B-D

etc

So, cannot measure in constant length

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