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Looking at the use of a tuple to store the computed Prime and to load them from storage, it seems apparent that the program operation would benefit through increased speed from the use of LevelDB. The use of a tuple is faster than a list however, as the size of the tuple grows past 10,000 Prime the speed slows from 6 seconds to many days for computing 10,000,000 Prime. LevelDB allows for lookup and storage in memory of only the relevant Prime needed for computation an optimisation designed to increase the speed average of searching for more Prime.

LevelDB Features:

• Key-Value Store: Data is stored as key-value pairs, where both keys and values are arbitrary byte arrays.
• Ordered Data: The data is stored sorted by key, which allows for efficient range queries.
• Atomic Batches: Multiple changes can be made in one atomic batch, ensuring data integrity.
• Compression: Supports compression of the data via Google's Snappy compression library, reducing storage space. (although we should not use it)
• Simple API: Offers basic operations like Get, Put, and Delete, making it easy to use.

A statistical analysis using an online tool shows it is very likely the first 1,000,000 numbers found in _data release WIPPPING IT are Prime both that they are and the 1,000,000th number 15485863 is the 1,000,000th Prime.

If anybody wants to perform some sort of empirical validation it is a worthwhile assignment I can include your comments.

Professor. Damian A. James Williamson