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Dht reduction methods

DavidCary ( talk ) 15:52, (UTC) Confusing a hash inscription concours agent finances publiques table and a hash map edit The intro to gagner des jeux sur internet this article is severely misguided and confusing.
Edit Hi, a recent edit claims that hash tables (HT) allow aritrary insertions and deletions in O(1) worst-case sense.
It barely explains anything at first.Any more than that and you could chance drying your hair and scalp out.The cost is O(1) only if averaged over a long sequence of operations.Josh 08:11, (UTC) In my experience the O notation usually refers to expected runtime, unless otherwise stated, but feel free to disambiguate.However, a real hash function takes the input data to get the key!"Given a key, the algorithm computes an index that suggests where the entry can be found:." "Suggests"?As the article says, "For all records in a cluster, there must be no vacant slots between their natural hash position and their current position (else lookups will terminate before finding the record)." The application needs to scan through *all* the records between the record.Those would indeed have O(1) worst-case insertion cost in theory, but the overhead seems quite large, and I wonder whether such solutions are really practical.Adrianwn ( talk ) 17:22, (UTC) You should add a comment explaining why it is that, I misread the termination condition myself.- ( User ) Wolfkeeper ( Talk ) 17:33, (UTC) Yes, that is probably a good idea; I will think of something.I would be more concerned about the simplicity claim.Dcoetzee 23:41, (UTC) People want to know how hash tables behave in the real world.S:, Akash Gokhale, Maharashtra one per line.One might distinguish between 'adequate' and 'bad' functions, where 'bad' might run slowly and produce uneven distributions, but if your problems are going undetected, I'd say you've at least struck 'adequate and improving to 'good' would be an exercise in lily-gilding.In that case you can wipe out the record by marking that record as not occupied - overwriting the key with a null byte - and you are done.
It makes more sense to contrast "closed hashing" with "open hashing".
Additionally, the concept of "buckets" is not intrinsic to a hash table.

(Alternately, if the attacker adds enough entries to be able to work out the size, it's also likely to force a rehash.) Ralphmerridew 00:51, (UTC) Well yes, if secrecy is a choice, it's a good idea to choose a large prime as the hash table.Those references recommend temporary secret algorithms, which generally guarantee O(1) lookup times even in the worst case under active attack, at the cost of making the worst-case insertion time slower.Kang Preceding unsigned comment added by ( talk ) 04:50, (UTC) It would be good to add to this an example of how the hash function might be constructed.Adrianwn ( talk ) 05:34, (UTC) I rewrote it and tried to clearly distinguish between the ops for the resizing and the ops for adding elements to the table.18:47, (UTC) But O(n) on a 50 full table with 1000 entries and a good hash function, it's not just "very rare" as in the text, it just never happens and never would happen before the end of the universe.Its DHT binder not 5ar inhibitor in theory, Cannot be shipped overseas at present).Josh 01:24, (UTC) I agree with Josh here.Of course you are correct in that one algorithm may perform well with a certain kind of input and badly with other kinds of input, but if one algorithm always works in O(n) time, it is, after certain point, always faster than an algorithm that.Hair functions a related way; this is why you need to have to consume about 8 eyeglasses of drinking water a day.Perhaps the editor is thinking of implementations that keep 2 (or 3) arrays and spread out the copying load over many ops?And hash_map permits these operations in constant time on average.
All the best, - Jorge Stolfi ( talk ) 02:21, (UTC) At forum concours adjoint administratif insee work I regularly explain to new developers the implementation of hash tables in our software product.
As it happens, the size of the hashkey (and the time it takes to compute it) grows with log n, where n is the number of buckets.

( talk ) 14:01, (UTC) The Load Factor page defines it as: Load factor (computer science the ratio of the number of records to the number of addresses or indexes within a data structure - Yitscar ( talk ) 17:38, (UTC) Info about multiplicative hashing.
23:24, 2 November 2007 (UTC) The probability of n collisions by sheer chance is pn where p is a number usually well under.8.