How is HashMap internally implemented? I read somewhere that it uses LinkedList while other places it mentions Arrays. I tried studying the code for HashSet and found Entry array. Then where is More on stackoverflow.com

In a Map, there is only one value for a key -- if you put a new value for the same key, the old value will be replaced. HashMaps are implemented using 'buckets' -- an array of cells of finite size, indexed by the hashCode of the key. More on stackoverflow.com

For my data structures class, we had to build our own array-based hash map. Best I can explain what I know is that you’re putting hashed key-value pairs into the array. Let’s say the initial length of the backing array is 5 and the load factor is .75 like you say. That means on the 4th add (4/5 > .75) the array will be resized into a new array (my class used 2*length +1 for this operation, something about prime numbers reduce the chances of hashing collisions) and all the values will be rehashed. Then if you assume a number’s hash code is itself for simplicity (I don’t understand how the actual .hashcode() method works internally, generates some big number), start by adding 11 to the hashmap. The haschode is 11, and that’s not a valid index value in the map. What we’d do is always % by the length of the map. 11%5 = 1, so check the hash map to see if there’s anything at index 1, there’s not, so add it there. Then you’d add let’s say 7. 7%5 is 2, there’s nothing in the map at 2, so you add 7 at 2. Backing array rn would look something like this [null, 11, 7, null, null] Then let’s say you add 16 to the map. 16%5 is 1, so you try and add it at index 1. There is already a value there, this is called a collision. There are a couple ways of dealing with this, I think linear probing is probably the most basic, but you can look into chaining too, basically creates a linked list at each index so you’d add 16 to 11’s next pointer. But with linear probing you’d see that there is a value there, so you’d move to the next index. You’d see that there is also a value there (7) so you’d again move to the next index. Now you’re at index 3, there’s nothing there, you’d put 16 there and your backing array would look like [null, 11, 7, 16 null] Notice the num of items in there / total spots (3/5) is still less than .75 Then let’s say you add 10. The condition where size / array.length() >.75 is trigged and the resizeArray method is called. For my class we’d resize this to 2*length+1, so the new array size would be 11. Now you’d iterate through the original and add the elements to the new spot in the new backing array. So, 11 % 11 = 0 (11 at index 0), 7 % 11= index 7, 16%11 = index 5, and now you add 10 (10%11= 10.) So your new resized backingArray would be [11, null, null, null, null, 16, null, 7, null, null, 10, null] A collision could occur there too though so you have to make sure to include a way of handling that in there. And then I forgot to mention but in adding you also have to check if the actual keys are the same, in which case you’d update the key with the new value you’re adding in because hash maps can’t have duplicate keys. Removing can be a little tricky but there’s tons on YouTube about it, if you find the pair you’re looking for in the map if you’re using linear probing as the collision method you sometimes have to set a marker on the index you’re removing from so it doesn’t affect a later search method. Hope all that helps and there’s plenty of stuff out there too to help with coding all that once you’re actually implementing it, good luck M8. And re firstFreeIndex, I haven’t seen that before but it looks like a more efficient way to do linear probing. In my class we’d manually iterate until we found an empty spot in the HashMap to add the pair, but that would be O(n) in worst cases and having firstFreeIndex keep track of that index seems helpful. So if there was a collision you would just put your pair at firstFreeIndex rather than iterating until you find an empty space, that’s my impression of it at least More on reddit.com

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