We present a new class of resizable sequential and concurrent hash map algorithms directed at both uni-processor and multicore machines. The new hopscotch. I am currently experimenting with various hash table algorithms, and I stumbled upon an approach called hopscotch hashing. Hopscotch. We present a new resizable sequential and concurrent hash map algorithm directed at both uniprocessor and multicore machines. The algorithm is based on a.

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Figure 2 below shows the hash table presented in Figure 1, and along with it the bitmaps for each of the buckets.

My choice for hash function was the following: Starting at 4, the size of the neighborhood would be doubling until it reaches Robin Hood Hashing vs. However, this does not prevent multiple buckets to cluster the overlapping area of their respective neighborhoods.

What it appears is that with neighborhoods of size 64, the load factor at which clustering prevents inserting is around 0. I am a software engineer at Booking.

Hopscotch hashing – Wikipedia

In hopscotch hashing, as in cuckoo hashingand unlike in linear probinga given item will always be inserted-into and found-in the neighborhood of its hashed bucket. The original paper was using the bitmap representation to present the algorithm, and I believe that things are simpler without it.

This is a major improvement compared to basic open addressing that uses only probing. Indeed, when looking up a key, this allows to quickly compare its hash with the ones in the bucket array, and only retrieve data from the secondary storage when the hash values are matching.


Insertion time is much faster than std:: This may come across as I am picking on the paper, but I am not, I am just pointing out something I find to be inconsistent. Here is my reasoning: The advantage of a bitmap or a linked list, as presented in the original paper, is that you only compare to keys of the items that landed in the same original bucket as the query key.

Home About Me Keto Calculator. As I am researching collision resolution methods to store hash tables on disk, storing the hashed key of each entry in the bucket array is something I am strongly considering. Due to the hopscotch method, an entry may not be in the bucket it was hashed to, its initial bucket, but most likely in a bucket in the neighborhood of its initial bucket.

When querying for an element, we just need to sequentially check the offsets. As for the linked-list neighborhood, I was referring to cache prefetching more specifically.

Hopscotch Hashing

Wikipedia has a nice representation:. Regarding storing the hashed keys in the bucket array, the main advantage is for when the data is stored in secondary storage HDD, SSD, etc. Also, the first search will terminate prior to bucket 6 if it finds either an empty bucket or a bucket whose initial bucket is hopscohch than or equal to 3.

This clustering behavior occurs around load factors of 0. As the table fills up, this prevents the lookup method from doing many random reads on the secondary storage, which are costly.


Part of this efficiency is due to using a linear probe only to find an empty slot during insertion, not for every lookup as in the original linear probing hash table algorithm. Proceedings of the 22nd international symposium on Distributed Computing. Instead, I am presenting the insertion process of hopscotch hashing with a diagram, in Figure 1 below. From there, the neighborhood to which the entry belongs can be determined, which is the hashjng bucket that was just derived and the next H-1 buckets.

The offset at index 6 is 0: The bitmap for bucket 5 is thereforewith a bit set to 1 at index 1, because bucket 6 is at an offset of 1 from bucket 5. Since it is taken by something else, it will hashiny a higher value, so we are certain this is not the bucket we are looking for. Whenever a jump occurs, the hashmap got too full and it is reallocating.

The desired property of the neighborhood is that the cost of finding an item in the buckets of the neighborhood is close to the cost of finding it in the bucket itself for example, by having buckets in the neighborhood fall within the same cache line. The first step to retrieve an entry is to determine its initial bucket.

Russell A Brown permalink. From Wikipedia, the free encyclopedia. I am using Visual Studio Update 3, 64 bit, Intel i 3.