I have a number of data sets that have key-value pattern – i.e. a string key and a pointer to the data. Right now it is stored in hashtables, each table having array of slots corresponding to hash keys, and on collision forming a linked list under each slot that has collision (direct chaining). All implemented in C (and should stay in C) if it matters.
Now, the data is actually 3 slightly different types of data sets:
- Some sets can be changed (keys added, removed, replaced, etc.) at will
- For some sets data can be added but almost never replaced/removed (i.e. it can happen, but in practice it is very rare)
- For some sets the data is added once and then only looked up, it is never changed once the whole set is loaded.
All sets of course have to support lookups as fast as possible, and consume minimal amounts of memory (though lookup speed is more important than size).
So the question is – is there some better hashtable structure/implementation that would suit the specific cases better? I suspect for the first case the chaining is the best, but not sure about two other cases.
If you are using linked lists for each bucket in your hashtable, you have already accepted relatively poor performance on modern CPUs (linked lists have poor locality and therefore poor CPU cache interaction). So I probably wouldn’t worry about optimizing the other special cases. However, here are a few tips if you want to continue down the path you are using:
For the ‘frequent changes’ data set and the ‘almost never change’ cases, every time you read an item from the hash table, move it to the front of the linked list chain for that bucket. For some even better ideas this paper, even though it focus on fixed size keys, is a good staring point Fast and Compact Hash Tables for Integer Keys.
For the ‘data set never changes’ case you should look into the perfect hash generators. If you know your keys at compile time I’ve had good results with gperf. If your keys are not available until run-time try the C Minimal Perfect Hashing Library.