expalin hash table

[bady1985]

hi ever one , can explain hashtable ,how can use it, what is the better (linkedlist or hash table)

[nuzzle]

hi ever one , can explain hashtable ,how can use it, what is the better (linkedlist or hash table)

What's better - a hammer or a saw? That depends on what you want to do.

Same here and there's no shortcut really. You simply have to bite the bullet and open a textbook (for example on Java and data structures, or Java and the collections).

I found this quite good. It covers generics in the first part and the collections in the second. They kind of go hand in hand.

http://www.amazon.com/Java-Generics-...34602&sr=8-3#_

[bady1985]

can you explain it ,is it kind of tree or like linkedlist?

[nuzzle]

can you explain it ,is it kind of tree or like linkedlist?

It's more like an array actually. In an array you get the element at a certain index position in just one access and accesses to a hash table is almost as fast.

The idea behind a hash table is that the value of an element determines the position of that element in the table. A hash function is used to define the mapping between the value and the position, like

index_position = hash_function(element_value)

Java has two major hash based data structures, the HashSet and the HashMap. The details of the hash function is hidden but you still have to supply part of it by overriding the hashCode() and equals() methods for the classes you want to store. But if you stick to standard types such as Integer and String you don't even have to do that because it's done for you already.

So you can think of a hash table as a kind of array. It has very fast accesses independent of how many elements are stored just like an array. It's called O(1). Accesses to a tree is slower. They're proportional to the logarithm of how many elements are stored, called O(log N)). Accesses to a linked list is slower still. They're proportional to the number of elements, called O(N).

These are some of the differences but as I recommended get a textbook because there's a lot more to it and a thorough understanding is very important. Picking the wrong data structures is a sure way to inefficient and slow code.