Skip Lists — ever used them? [closed]

Answer 1

My understanding is that they're not so much a useful alternative to binary trees (e.g. red-black trees) as they are to B-trees for database use, so that you can keep the # of levels down to a feasible minimum and deal w/ base-K logs rather than base-2 logs for performance characteristics. The algorithms for probabilistic skip-lists are (IMHO) easier to get right than the corresponding B-tree algorithms. Plus there's some literature on lock-free skip lists. I looked at using them a few months ago but then abandoned the effort on discovering the HDF5 library.

literature on the subject:

Papers by Bill Pugh:

• A skip list cookbook
• Skip lists: A probabilistic alternative to balanced trees
• Concurrent Maintenance of Skip Lists

non-academic papers/tutorials:

• Eternally Confuzzled (has some discussion on several data structures)
• "Skip Lists" by Thomas A. Anastasio

Answer 2

The skip list has the same logarithmic time bounds for searching as is achieved by the binary search algorithm, yet it extends that performance to update methods when inserting or deleting entries. Nevertheless, the bounds are expected for the skip list, while binary search of a sorted table has a worst-case bound.

Answer 3

Skip Lists are easy to implement. But, adjusting the pointers on a skip list in case of insertion and deletion you have to be careful. Have not used this in a real program but, have doen some runtime profiling. Skip lists are different from search trees. The similarity is that, it gives average log(n) for a period of dictionary operations just like the splay tree. It is better than an unbalanced search tree but is not better than a balanced tree.

Every skip list node has forward pointers which represent the current->next() connections to the different levels of the skip list. Typically this level is bounded at a maximum of ln(N). So if N = 1million the level is 13. There will be that much pointers and in Java this means twie the number of pointers for implementing reference data types. where as a balanced search tree has less and it gives same runtime!!.

SkipList Vs Splay Tree Vs Hash As profiled for dictionary look up ops a lock stripped hashtable will give result in under 0.010 ms where as a splay tree gives ~ 1 ms and skip list ~720ms.

Answer 4

Years ago I implemented my own for a probabilistic algorithms class. I'm not aware of any library implementations, but it's been a long time. It is pretty simple to implement. As I recall they had some really nice properties for large data sets and avoided some of the problems of rebalancing. I think the implementation is also simpler than binary tries in general. There is a nice discussion and some sample c++ code here:

http://www.ddj.us/cpp/184403579?pgno=1

There's also an applet with a running demonstration. Cute 90's Java shininess here:

http://www.geocities.com/siliconvalley/network/1854/skiplist.html

Answer 5

I implemented a variant that I termed a Reverse Skip List for a rules engine a few years ago. Much the same, but the reference links run backward from the last element.

This is because it was faster for inserting sorted items that were most likely towards the back-end of the collection.

It was written in C# and took a few iterations to get working successfully.

Answer 6

Actually, for one of my projects, I am implementing my own full STL. And I used a skiplist to implement my std::map. The reason I went with it is that it is a simple algorithm which is very close to the performance of a balanced tree but has much simpler iteration capabilities.

Also, Qt4's QMap was a skiplist as well which was the original inspiration for my using it in my std::map.