High performance library for set operations?

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For efficient set operations like union, intersection, and difference on sets of integers, performance is a key concern, especially with hundreds of elements and sets. While the Java Collections Framework can handle these operations, alternative frameworks may offer better performance for large datasets. Custom implementations can significantly enhance efficiency, particularly when dealing with limited integer ranges, such as 1-300, where bitstring operations outperform general-purpose methods. Using bitwise operations can lead to faster calculations for unions, intersections, and differences. Ultimately, the choice of approach should prioritize performance based on specific data characteristics.
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I need to perform standard set theory operations such as union, intersection, difference on sets of integer numbers. Each set can have a few hundred elements and each operation can involve a few hundred sets.

The operations can easily be written in Java using the Java Collections Framework, but I am very concerned about the performance. There are several other similar frameworks in all kinds of programming languages, but which one is really suitable for processing massive amounts of data?
 
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Depending on exactly what you're doing, it could be most efficient to write your own program. If you had a large number of sets containing only integers 1-300, for example, boolean operations on bitstrings would be much faster than general-purpose implementations. A union B = A|B, A intersect B = A&B, A setminus B = A&(!B), etc.
 
The standard _A " operator" maps a Null Hypothesis Ho into a decision set { Do not reject:=1 and reject :=0}. In this sense ( HA)_A , makes no sense. Since H0, HA aren't exhaustive, can we find an alternative operator, _A' , so that ( H_A)_A' makes sense? Isn't Pearson Neyman related to this? Hope I'm making sense. Edit: I was motivated by a superficial similarity of the idea with double transposition of matrices M, with ## (M^{T})^{T}=M##, and just wanted to see if it made sense to talk...

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