HashMap enables efficient storage and search through hash tables in Java. It uses an array linked list (or red and black tree) structure, first obtain the hash value through the hashCode of the key, and then map it to the array index after processing by the hash function to reduce conflicts; 1. When a hash collision occurs, use the linked list to connect multiple key-value pairs; 2. Since JDK 8, when the length of the linked list exceeds 8, it is converted to a red and black tree to improve search efficiency; 3. The default initial capacity is 16 and the load factor is 0.75. When the number of elements exceeds the threshold, the capacity expansion is triggered, the array is doubled and the element position is recalculated; 4. Multithreaded capacity expansion may cause dead loops or data confusion, and it is recommended to use ConcurrentHashMap in a concurrent environment.
HashMap is a very commonly used collection class in Java, used to store key-value pairs. The reason why it is efficient is that it uses hash table implementation internally, which can quickly locate the location of data.
Hash functions and array structures
HashMap is actually a combination structure of an array linked list (or red and black trees). When we put a key-value pair, HashMap will first use hashCode()
method of the key (Key) to get a hash value, and then further process this value through its own hash function, with the purpose of reducing the probability of hash collision.
Then, this final hash value is "map" to a position in the array. For example, if the length of the array is 16, then the hash value will be used to modulo 16 and determine which index to put. This step is called hash addressing .
What should be noted is:
- If the positions calculated by different keys are the same, a hash collision occurs
- The initial capacity is 16, the default load factor is 0.75, and capacity expansion will be triggered when the number of elements exceeds the capacity × load factor.
How to resolve hash conflicts?
Java's HashMap uses linked lists to handle conflicts. That is, when multiple keys are mapped to the same array position, they are stringed in a linked list. Each array element (also called bucket) stores a node object (Node), which contains key, value, hash and next pointers.
However, there is another optimization starting from JDK 8: when the length of the linked list in a bucket exceeds the threshold (the default is 8), the linked list will be converted into a red and black tree, and the search efficiency will be improved from O(n) to O(log n). If the number of red and black tree nodes is less than 6, it will degenerate back to the linked list.
What's going on with the expansion mechanism?
When more and more data in HashMap reaches the threshold (threshold = capacity × load factor), it will automatically double the array and then recalculate the positions of all elements. This process is called rehashing (re-hashing) .
This operation is relatively performance-consuming, so if you know how much data you want to store, it is best to specify the initial capacity from the beginning to avoid frequent expansion.
For example:
Map<String, Integer> map = new HashMap<>(32); // Set initial capacity to 32
When expanding capacity, you need to pay attention to the problems under multi-threading. In older versions of HashMap, if multiple threads operate simultaneously during capacity expansion, it may lead to dead loops or data disorders. Therefore, it is recommended to use ConcurrentHashMap
in a concurrent environment.
Basically that's it. Although HashMap looks simple, the details are still very particular. Hash optimization, link list to red and black tree, and expansion strategies are all to ensure efficient read and write performance.
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