In the blog Map classes, we discussed the map classes in java.util package. In blog ConcurrentHashMap, we ventured into concurrent collections and discussed the features of ConcurrentHashMap, which offers much superior concurrency than a conventional HashMap.

In this blog we discuss another concurrent map, the ConcurrentSkipListMap and compare it with ConcurrentHashMap. Package java.util has a HashMap and TreeMap. Have you ever wondered why java.util.concurrent has a ConcurrentHashMap, but no ConcurrentTreeMap and why there is a ConcurrentSkipListMap ?

In the non concurrent Collections, there is a HashMap and TreeMap. HashMap for O(1) time complexity and TreeMap for maintaining a sorted order but O(logn) complexity. The implementation of a tree map is not a ordinary binary search tree(BST), because a BST that is not balanced degrades in performance to O(n) for input that is already sorted. TreeMap is implemented as a Red black tree, whose implementation is complex and involves balancing the tree (moving the nodes around) when nodes are added or removed. The complexity is even more when you try to make the implementation concurrent (safe for concurrent use). For that reason there is no ConcurrentTreeMap in java.util.concurrent.

A concurrent implementation of SkipList is simpler. Hence, for a Map that is ordered and concurrent,the implementators choose SkipList.

A skiplist is an ordered linked list with o(log n) worst case search time. An ordinary linked list has o(n) worst case search time. A skip list provides faster search by maintaining layers of links, allowing the search to skip nodes. As shown in the figure, the lowest layer is an ordinary linked list. But each higher layer skips some (more) nodes.

level4 10-------------------------------------100-null

level3 10-----------------50-----------------100-null

level2 10-------30------ 50-----70---------100-null

level1 10 -20 -30 -40 -50 -60-70-80-90-100-null

Let us you need to find 80 in the list.

Start are highest level 4. Search linearly to find the node that is equal to or whose next node is greater than 80. At level 4, 100 is greater than 80. So at node 10, move down to level 3.

At level 3, node 10, 50 is less than 80. Move to node 50. Next node 100 is greater that 50. Move down to level 2 at node 50.

At level 2 node 50, next node is 70 which is less than 80. Move to node 70. Next node is 100 which is greater than 80. Move to level 1 at node 70.

At level 1, this is the last level. Keep going forward from 70 till you find 80 or reach end of the list.

Adding more levels can leads to faster search.

Skiplist has O(logn) performance for search, insert and delete. Depending on number of levels, it does use some extra space. Space complexity is O(nlogn).

In general, you will use a ConcurrentHashMap, if you must have O(1) for both get and put operations, but do not care about the ordering in the collection. You will use a ConcurrentSkipListMap if you need an ordered collection (sorted), but can tolerate O(logn) performance for get and put.

Lastly, SkipList is easier to implement than a balanced tree and is become the data structure of choice for ordered concurrent Map.

In this blog we discuss another concurrent map, the ConcurrentSkipListMap and compare it with ConcurrentHashMap. Package java.util has a HashMap and TreeMap. Have you ever wondered why java.util.concurrent has a ConcurrentHashMap, but no ConcurrentTreeMap and why there is a ConcurrentSkipListMap ?

In the non concurrent Collections, there is a HashMap and TreeMap. HashMap for O(1) time complexity and TreeMap for maintaining a sorted order but O(logn) complexity. The implementation of a tree map is not a ordinary binary search tree(BST), because a BST that is not balanced degrades in performance to O(n) for input that is already sorted. TreeMap is implemented as a Red black tree, whose implementation is complex and involves balancing the tree (moving the nodes around) when nodes are added or removed. The complexity is even more when you try to make the implementation concurrent (safe for concurrent use). For that reason there is no ConcurrentTreeMap in java.util.concurrent.

A concurrent implementation of SkipList is simpler. Hence, for a Map that is ordered and concurrent,the implementators choose SkipList.

**What is a Skip List ?**A skiplist is an ordered linked list with o(log n) worst case search time. An ordinary linked list has o(n) worst case search time. A skip list provides faster search by maintaining layers of links, allowing the search to skip nodes. As shown in the figure, the lowest layer is an ordinary linked list. But each higher layer skips some (more) nodes.

level4 10-------------------------------------100-null

level3 10-----------------50-----------------100-null

level2 10-------30------ 50-----70---------100-null

level1 10 -20 -30 -40 -50 -60-70-80-90-100-null

Let us you need to find 80 in the list.

Start are highest level 4. Search linearly to find the node that is equal to or whose next node is greater than 80. At level 4, 100 is greater than 80. So at node 10, move down to level 3.

At level 3, node 10, 50 is less than 80. Move to node 50. Next node 100 is greater that 50. Move down to level 2 at node 50.

At level 2 node 50, next node is 70 which is less than 80. Move to node 70. Next node is 100 which is greater than 80. Move to level 1 at node 70.

At level 1, this is the last level. Keep going forward from 70 till you find 80 or reach end of the list.

Adding more levels can leads to faster search.

Skiplist has O(logn) performance for search, insert and delete. Depending on number of levels, it does use some extra space. Space complexity is O(nlogn).

In general, you will use a ConcurrentHashMap, if you must have O(1) for both get and put operations, but do not care about the ordering in the collection. You will use a ConcurrentSkipListMap if you need an ordered collection (sorted), but can tolerate O(logn) performance for get and put.

Lastly, SkipList is easier to implement than a balanced tree and is become the data structure of choice for ordered concurrent Map.