hashtable

问题 I am new to programming language and I am using PHP and mysql. I got an assignment to do a hashtables in php. What I need to do is, store items that a user collected and then display it. After do some research over the internet, I will do the following steps when implement the hashtable, please correct me if I am wrong: Set up the tables: -> Users Table: uid(int[5]), username(varchar[128]), item_id(int[8], items_id_hash(int[50]) -> Items Table: item_id(int[5]), item_name(varchar[128]), items

问题 I have two hash tables and I need to compare them. Let me explain my problem : [hashtable]$User = @{ "Jack" = "AdminLA, AdminUSA"; "John" = "AdminAustralia"; "Sarah" = "AdminIceland"; "Arnold" = "AdminUSA"; "Maurice" = "AdminAustralia, AdminCanada"; } [hashtable]$Profil = @{ "AdminLA" = "P1"; "AdminIceland" = "P2"; "AdminUSA" = "P3"; "AdminCanada" = "P4"; "AdminAustralia" = "P5" ; "AdminCroatia" = "P6"; } I want to have this kind of result : Key Value --- ----- Jack P1, P3 John P5 Sarah P2

问题 The following code gives me the output in the same order of insertion. I read the javadoc and they did not even talk about the insertion order. Can someone help me to get the right information. import java.util.*; public class hash { public static void main(String[] args) { String str[] = { "japan", "usa", "japan", "russia", "usa", "japan", "japan", "australia"}; int len = 8; Hashtable ht = new Hashtable(); int i = 0; while (i < len) { String c = str[i]; System.out.println("c :" + c); Integer

问题 Are hashtables always faster than trees? Though Hashtables have O(1) search complexity but suppose if due to badly designed hash function lot of collisions happen and if we handle collisions using chained structure (say a balanced tree) then the worst case running time for search would be O(log n). So can I conclude for big or small data sets even in case of worst case scenarios hash tables will always be faster than trees? Also If I have ample memory and I dont want range searches can I

问题 There are two basic methods for implementing a hash function that are cited in pretty much every text book and CS courses: Division method where we simply do k mod m essentially picking m as prime not too close to power of 2. Multiplication method where we multiply k with some well-chosen irrational number (Knuth suggests using number based on Golden ratio) between 0 to 1, take the fractional part of the product and use desired number of most significant bits from it. Most text books and

问题 There are two basic methods for implementing a hash function that are cited in pretty much every text book and CS courses: Division method where we simply do k mod m essentially picking m as prime not too close to power of 2. Multiplication method where we multiply k with some well-chosen irrational number (Knuth suggests using number based on Golden ratio) between 0 to 1, take the fractional part of the product and use desired number of most significant bits from it. Most text books and

问题 This question already has answers here : How can Python dict have multiple keys with same hash? (5 answers) Closed 5 years ago . How Python stores the dict key, values when collision occurs in hash table? Whats the hash algorithm used to get the hash value here? 回答1: For the "normal" Python, this great writeup by Praveen Gollakota explains it very well, here are the important bits: Python dictionaries are implemented as hash tables. Hash tables consist of slots, and keys are mapped to the

问题 I'm trying to create a Hashtable as in the following: Hashtable<int, ArrayList<byte>> block = new Hashtable<int, ArrayList<byte>>(); but I am getting an error on both int and byte saying "Dimensions expected after this token". If I use something like: Hashtable<String, byte[]> - all is good. Can someone explain why? Thanks. 回答1: In Java's core collection classes you can only store reference types (something that extends a java.lang.Object). You cannot store primitives like int and byte . Note

问题 I'm writing a Haxe C# target, and I've been studying performance differences for Haxe's std library so we can provide the best performance possible through its cross platform code. One very good example is for the hash table code. I was a little reluctant about using .NET's Dictionary, as it seems bulky (structs for key/value pairs can take up a huge amount of memory because of memory alignment issues, besides from unnecessary information held by it), and since on the std library there is no

问题 Is there any way to implement hash tables efficiently in a purely functional language? It seems like any change to the hash table would require creating a copy of the original hash table. I must be missing something. Hash tables are pretty darn important data structures, and a programming language would be limited without them. 回答1: Is there any way to implement hash tables efficiently in a purely functional language? Hash tables are a concrete implementation of the abstract "dictionary" or