As I mentioned before, it is vital to read code with prepared questions. Hum, How about reading code with answers? The differences between Hashtable and HashMap have been explained many times including, null key & null value synchronized or not Enumeration and Iterator hash method I am wondering how these arguments are supported by code. This post will give a view of code illustrating the above confusion. ...
For those who has no patience to look through this post, I conclude it in a word: HashSet is backed by HashMap. Set is a collection in which every element is unique. So does the keys in HashMap. It is reasonable to infer that the implementation of HashSet is based on HashMap, so it is. Remember resize of HashMap? it makes no guarantees as to the iteration order of the set. With the help of HashMap, HashSet offers constant time performance for the basic operations, like add, remove, contains and size. Iterating over this set requires time proportional to the sum of the HashSet instance’s size (the number of elements) plus the “capacity” of the backing HashMap instance (the number of buckets). ...
After joining the workforce, I have coded with various programming languages, like C++, Objective-C, Ruby, Python, Scala, Java, Go, etc. I ask to myself spontaneously, which language am I most skillful at? This question dismay me because I cannot answer it immediately. Since I choice to focus on Big Data, it’s pragmatic to equipped with Java and Python, two powerful weapons in this field. Reading the source code of java.util is a good start. The leading actor of this post is TreeMap, a Red-Black tree based NavigableMap implementation. It has no array underneath, as many of you think. Because TreeMap inherits directly AbstractMap, in contrast with LinkedHashMap. Performances differ on account of distinctive data structures. This implementation provides guaranteed log(n) time cost for the containsKey, get, put and remove operations. Now allow me to show you a close look. ...
As its name implies, LinkedHashMap is a hash table and linked list implementation of the Map interface, with predictable iteration order. Different with HashMap, it maintains a doubly-linked list running through all of its entries, which also defines the iteration ordering, same as the order in which keys were inserted into the map. This order remains if a key is re-inserted into the map. Like HashMap, LinkedHashMap provides constant-time performance for the basic operations add, contains and remove, assuming the hash function disperses elements properly among the buckets. Performance is likely to be just slightly below that of HashMap, due to the added expense of maintaining the linked list, Thanks to the linked list, this kind of map is well-suited to building LRU caches. So my questions is how LinkedHashMap preserves the linked list when key changes. ...
It’s necessary to learn with questions. Otherwise, you may distract your focus when something you don’t know appears, whether should I go deeper or not. With preliminary doubts in your mind, this would not be a problem. Learning can be direct, clear and fruitful, which brings you more sense of achievement. For this post about the source code of HashMap, few questions need answers: data structure underneath why HashMap permits nulls and unsynchronized does it make guarantees as to the order of the map what happens when I put and get a key with value, and time complexity how the map shrink or expand when size changes ...
LinkedList is a doubly-linked list implementation of the List and Deque interfaces. By “doubly-linked”, it means we can traverse the list from the beginning to the end, and vice versa. This class is a member of Java Collections Framework, located in java.util. Let’s go straight to the source code. ...