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Maps are data structures that associate a key with an element. This lets the map be very flexible. If the key is the hash code of the element, the Map is essentially a Set. If it's just an increasing number, it becomes a list. Examples of Map implementations include java.util.HashMap, java.util.LinkedHashMap, and java.util.TreeMap.
For ordered access as defined by the java.util.NavigableMap interface, java.util.concurrent.ConcurrentSkipListMap was added in Java 1.6, [1] and implements java.util.concurrent.ConcurrentMap and also java.util.concurrent.ConcurrentNavigableMap. It is a Skip list which uses Lock-free techniques to make a tree. Performance is O(log(n)).
This is a list of the instructions that make up the Java bytecode, an abstract machine language that is ultimately executed by the Java virtual machine. [1] The Java bytecode is generated from languages running on the Java Platform, most notably the Java programming language.
To create a treemap, one must define a tiling algorithm, that is, a way to divide a region into sub-regions of specified areas.Ideally, a treemap algorithm would create regions that satisfy the following criteria:
Depending on the problem at hand, pre-order, post-order, and especially one of the number of subtrees − 1 in-order operations may be optional. Also, in practice more than one of pre-order, post-order, and in-order operations may be required. For example, when inserting into a ternary tree, a pre-order operation is performed by comparing items.
A level-order walk effectively performs a breadth-first search over the entirety of a tree; nodes are traversed level by level, where the root node is visited first, followed by its direct child nodes and their siblings, followed by its grandchild nodes and their siblings, etc., until all nodes in the tree have been traversed.
Merge sort. In computer science, a sorting algorithm is an algorithm that puts elements of a list into an order.The most frequently used orders are numerical order and lexicographical order, and either ascending or descending.
Each node in a min-max heap has a data member (usually called key) whose value is used to determine the order of the node in the min-max heap. The root element is the smallest element in the min-max heap. One of the two elements in the second level, which is a max (or odd) level, is the greatest element in the min-max heap