Union of Disjoint Sets with at Most k Sets - Algorithm

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In summary, this conversation discusses an implementation of disjoint sets with union, using a hash table and ordered double hashing. The algorithm for merging two up trees with path compression and height reduction is presented, with a pointer function called Union. The conversation also mentions a case where a hash table is used and discusses the approach that should be taken in that scenario.
  • #1
evinda
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Hello! (Smirk)Consider an implementation of disjoint sets with union, where there can be at most $k$ disjoint sets.
The implementation uses a hash table $A[0.. \text{ max }-1]$ at which there are stored keys based on the method ordered double hashing.
Let $h1$ and $h2$ be the primary and the secondary hash function, respectively. $A$ contains the keys of the nodes of all of the above trees and also a pointer to the corresponding node for each of them.
I want to write an algorithm that takes as parameters the keys of two nodes and merges the upper trees to which the nodes belong (the nodes can belong to any upper trees, even at the same in which case it appears an appropriate message). At merging, we have to apply techniques of path compression and height reduction.How could we do this? (Thinking)
 
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  • #2
This is the algorithm that merges two up trees, applying the technique of path compression:
Code:
pointer Union(S,T){
  if (S==NULL or T==NULL) return;
  if (S->count>=T->count){
      S->count=S->count+T->count;
      T->parent=S;
      return S;
  }
  else {
      T->count=T->count+S->count;
      S->parent=T;
      return T;
  }
}
 
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  • #3
What do we have to do in this case, where we have a hash table? (Thinking)
 

Related to Union of Disjoint Sets with at Most k Sets - Algorithm

What is the Union of Disjoint Sets with at Most k Sets - Algorithm?

The Union of Disjoint Sets with at Most k Sets - Algorithm is a data structure and algorithm used to combine multiple sets into a single set while ensuring that the resulting set contains no overlapping elements.

What is the purpose of this algorithm?

The purpose of this algorithm is to efficiently merge sets and eliminate any duplicate elements in order to optimize data storage and retrieval processes.

What is the time complexity of this algorithm?

The time complexity of the Union of Disjoint Sets with at Most k Sets - Algorithm is O(klogn), where k is the maximum number of sets and n is the total number of elements in all the sets.

When is this algorithm most useful?

This algorithm is most useful when dealing with large sets of data that may contain duplicate elements, such as in database management or network routing applications.

What are some drawbacks of this algorithm?

One drawback of this algorithm is that it requires additional memory to store the sets and their elements, which can be a limitation in memory-constrained systems. Additionally, the algorithm may not be as efficient when dealing with very large values of k, as the time complexity can increase significantly.

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