File Organization and Processing

Alan L. Tharp

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The many and powerful data structures for representing information physically (in contrast to a database management system that represents information with logical structures) are introduced by this book. Specialized data structures are covered, and there is an explanation of how to choose the appropriate algorithm or data structure for the job at hand. The four sections treat primary file organizations, bit level and related structures, tree structures, and file sorting. The opening chapters cover sequential file organization, direct file organization, indexed sequential file organization, bits of information, secondary key retrieval, and bits and hashing.

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What's a correct and good way to implement __hash__()?

I am talking about the function that returns a hashcode that is then used to insert objects into hashtables aka dictionaries.

As __hash__() returns an integer and is used for "binning" objects into hashtables I assume that the values of the returned integer should be uniformly distributed for common data (to minimize collisions). What's a good practice to get such values? Are collisions a problem? In my case I have a small class which acts as a container class holding some ints, some floats and a string.

I can try to answer the second part of your question.

The collisions will probably result not from the hash code itself, but from mapping the hash code to an index in a collection. So for example your hash function could return random values from 1 to 10000, but if your hash table only has 32 entries you'll get collisions on insertion.

In addition, I would think that collisions would be resolved by the collection internally, and there are many methods to resolve collisions. The simplest (and worst) is, given an entry to insert at index i, add 1 to i until you find an empty spot and insert there. Retrieval then works the same way. This results in inefficient retrievals for some entries, as you could have an entry that requires traversing the entire collection to find!

Other collision resolution methods reduce the retrieval time by moving entries in the hash table when an item is inserted to spread things out. This increases the insertion time but assumes you read more than you insert. There are also methods that try and branch different colliding entries out so that entries to cluster in one particular spot.

Also, if you need to resize the collection you will need to rehash everything or use a dynamic hashing method.

In short, depending on what you're using the hash code for you may have to implement your own collision resolution method. If you're not storing them in a collection, you can probably get away with a hash function that just generates hash codes in a very large range. If so, you can make sure your container is bigger than it needs to be (the bigger the better of course) depending on your memory concerns.

Here are some links if you're interested more:

coalesced hashing on wikipedia

Wikipedia also has a summary of various collision resolution methods:

Also, "File Organization And Processing" by Tharp covers alot of collision resolution methods extensively. IMO it's a great reference for hashing algorithms.