JAVA collection foundation (1)

I. Introduction

A. What is a collection

        Collection (Collection) is a container for storing and manipulating a set of objects in the Java programming language. It is the core part of the Java collection framework, providing a set of interfaces and classes for processing different types of collection data.

        In programming, we often need to deal with a group of related objects, such as storing user lists, product information, log records, etc. Collections provide a convenient way to organize and manipulate these objects, allowing us to easily add, delete, search, sort, etc., as well as interact and convert between collections.

        The collection framework provides various types of collection classes, each of which has its own characteristics and applicable scenarios. Common collection classes include List (list), Set (collection), Map (mapping) and Queue (queue). They can store different types of objects and have different properties and performance characteristics.

        Using collections can help us improve the readability, flexibility and maintainability of our code. They provide a series of methods and algorithms that allow us to easily operate and process the elements in the collection. In addition, collections also provide some convenient functions, such as traversing collections, filtering elements, sorting and searching, etc.

        All in all, a collection is a container for storing and manipulating a group of objects, which provides a wealth of functions and methods for us to organize and process data. By using collections, we can deal with various data structure and algorithm problems more efficiently and flexibly.

B. Why use collections

1. Data organization and management: Collections provide a convenient way to organize and manage a group of related data objects. They allow us to group objects together in logically related ways, forming more structured collections of data. With collections, we can represent and manipulate data more clearly, making code more readable and maintainable.

2. Rich in functions: The collection framework provides many built-in methods and algorithms, allowing us to conveniently perform common operations on collections, such as adding, deleting, searching, sorting, and traversing. These features greatly simplify working with collections, saving time and effort in writing repetitive code.

3. Scalability and flexibility: collections provide multiple types of collection classes, each with different characteristics and applicable scenarios. This allows us to choose the most appropriate collection class based on our needs, and extend and customize the collection as needed. The flexibility of collections enables us to adapt to different business needs and data structures, and to deal with various complex algorithms and problems.

4. Improved performance: The various collection classes in the collections framework have been optimized and tuned to provide efficient data storage and access. For example, ArrayList provides fast random access, LinkedList provides efficient insertion and deletion operations, HashMap provides fast key-value pair lookup, etc. By choosing the appropriate collection class, we can improve the performance and efficiency of the program.

5. Data structure and algorithm support: The collection framework provides a variety of commonly used data structures and algorithm support, such as lists, collections, maps, queues, etc. These data structures and algorithms are the basis for solving many programming problems. By using collections, we can more easily implement and apply these data structures and algorithms, improving the quality and maintainability of the code.

        All in all, the use of collections can simplify the organization and management of data, provide rich functions and methods, have scalability and flexibility, and can improve the performance and efficiency of programs. By choosing and using collections reasonably, we can better handle and solve various data structure and algorithm problems.

II. Overview of the Java Collections Framework

A. Architecture of the Collections Framework

The architecture of the Java collection framework is built on the core of the interface, which mainly includes the following key interfaces and classes:

1. Collection interface: The Collection interface is the root interface of the collection framework, which defines common methods for operating on a set of objects. It derives commonly used sub-interfaces, such as List, Set, and Queue.

2. List interface: The List interface inherits from the Collection interface and represents an ordered collection of elements, which can contain repeated elements. Common implementation classes of the List interface include ArrayList, LinkedList, and Vector.

3. Set interface: The Set interface inherits from the Collection interface and represents an unordered collection of elements, and duplicate elements are not allowed. Common implementation classes of the Set interface include HashSet, TreeSet, and LinkedHashSet.

4. Queue interface: The Queue interface inherits from the Collection interface, which represents the queue data structure and supports adding elements at the end of the queue and removing elements from the head of the queue. Common implementation classes of the Queue interface include ArrayDeque and PriorityQueue.

5. Map interface: The Map interface is a collection of key-value pairs used to store a set of unique keys and corresponding values. The implementation class of the Map interface allows both the key and the value to be null, but the key must be unique. Common implementation classes include HashMap, TreeMap, and LinkedHashMap.

        In the collection framework, there are some other interfaces and classes for extending and enhancing collection functions, such as Iterator interface for traversing collection elements, Comparable interface for sorting, Comparator interface for custom comparators, etc.

        The design of the collection framework follows some design principles, such as the interface isolation principle, the single responsibility principle, and the opening and closing principle, which make the collection class highly scalable and flexible. By using these interfaces and classes, we can easily select and combine different types of collections to meet different business needs and algorithm requirements.

B. Introduction to Core Interfaces and Classes

1. Collection interface and its implementation class

        The Collection interface is one of the root interfaces of the Java collection framework, which defines a set of common methods for manipulating a set of objects. It is the parent interface of all collection classes and provides some basic collection operations, such as adding, deleting, traversing, etc. The following is an introduction to the implementation classes of some common Collection interfaces:

1. ArrayList：

   • ArrayList is a dynamic array based on arrays, which can be automatically expanded as needed.
   • It allows random access to elements, fast access and modification of elements through indexing.
   • It is suitable for scenarios where elements are frequently accessed and modified.

2. LinkedList：

   • LinkedList is a doubly linked list implemented based on linked list.
   • It allows efficient insertion and deletion of elements at the beginning and end of the collection.
   • It is suitable for scenarios where elements are frequently inserted and deleted.

3. HashSet：

   • HashSet is implemented based on a hash table, which uses a hash algorithm to store and retrieve elements.
   • It does not guarantee the order of elements and does not allow duplicate elements.
   • It is suitable for scenarios where you need to find elements quickly and don't care about the order.

4. TreeSet：

   • TreeSet is implemented based on red-black tree, which sorts and stores elements.
   • It maintains the sort order of elements and does not allow duplicate elements.
   • Suitable for scenarios that require ordered collections.

5. LinkedHashSet：

   • LinkedHashSet is a subclass of HashSet, which is implemented by hash table and linked list.
   • It maintains the insertion order of elements and does not allow duplicate elements.
   • Suitable for scenarios where insertion order needs to be maintained.

6. PriorityQueue：

   • PriorityQueue is a queue implemented based on a priority heap.
   • It sorts the elements according to their priority, and when getting an element returns the element with the highest priority.
   • Applicable to scenarios that require element processing according to priority.

        The above are some common implementation classes of the Collection interface, and each implementation class has its own characteristics and applicable scenarios. Choosing an appropriate implementation class depends on specific requirements and operations, such as requirements for order, frequency of insertion/deletion, handling of repeated elements, etc.

2. Map interface and its implementation class

        The Map interface is an interface used to store key-value pairs in the Java collection framework, and it provides a set of methods for manipulating key-value pairs. The following is an introduction to some common implementation classes of the Map interface:

1. HashMap：

   • HashMap is a Map implemented based on a hash table, which uses a hash algorithm to store and retrieve key-value pairs.
   • It does not guarantee the order of key-value pairs, allowing nulls as keys and values.
   • It is suitable for scenarios that need to quickly find key-value pairs and do not care about the order.

2. TreeMap：

   • TreeMap is implemented based on a red-black tree, which stores keys in sorted order.
   • It maintains the sort order of the keys, allowing nulls as values.
   • Applicable to scenarios that require ordered key-value pairs.

3. LinkedHashMap：

   • LinkedHashMap is a subclass of HashMap, which is implemented through a hash table and a doubly linked list.
   • It maintains insertion order or access order (optional), allowing nulls as keys and values.
   • Suitable for scenarios where insertion or access order needs to be maintained.

4. Hashtable：

   • Hashtable is a thread-safe Map implementation class, similar to HashMap.
   • It does not guarantee the order of key-value pairs and does not allow null as key and value.
   • It is suitable for scenarios that require thread safety in a multi-threaded environment.

5. ConcurrentHashMap：

   • ConcurrentHashMap is a thread-safe and efficient Map implementation class.
   • It uses a segmented lock mechanism for thread safety, allowing concurrent reads and writes.
   • It is suitable for scenarios that require high performance and thread safety in a high-concurrency environment.

        The above are some common implementation classes of the Map interface, and each implementation class has its own characteristics and applicable scenarios. Choosing an appropriate implementation class depends on specific requirements and operations, such as the order requirements for key-value pairs, requirements for thread safety, support for null values, and so on.

III. Characteristics and applicable scenarios of commonly used collection classes

A. List

1. ArrayList

ArrayList is the implementation class of the List interface in the Java collection framework. It is implemented based on an array and has the following characteristics:

1. Dynamic array: The underlying implementation of ArrayList is a variable-length array that can be automatically expanded as needed. When the number of elements exceeds the current capacity, ArrayList will automatically increase the capacity to accommodate more elements.

2. Random access: Since the bottom layer is implemented based on arrays, ArrayList supports fast access and modification of elements through indexes. The element at the specified position can be directly accessed according to the index, and the time complexity is O(1).

3. Allow repeated elements: ArrayList allows to store repeated elements, and the same element can appear multiple times.

4. Non-thread-safe: ArrayList is not thread-safe and is not suitable for concurrent access in a multi-threaded environment. If you need to use it in a multi-threaded environment, consider using a thread-safe alternative class, such as CopyOnWriteArrayList or Vector.

5. Suitable for frequently accessing and modifying elements: Because it supports random access and modifying elements, ArrayList performs well in scenarios where elements need to be frequently searched, traversed, and modified.

Based on the above characteristics, ArrayList is suitable for the following scenarios:

1. Need to access elements randomly: ArrayList is a good choice if you need to quickly access elements in the collection by index.

2. Elements need to be modified frequently: Since the bottom layer of ArrayList is implemented based on arrays, the insertion, deletion, and modification operations on elements are more efficient, and are suitable for scenarios where elements are frequently modified.

3. The number of elements is variable: When the number of elements in the collection changes dynamically, the dynamic expansion mechanism of ArrayList can automatically adapt to the increase or decrease of elements without manually adjusting the capacity.

4. Does not involve multi-threaded concurrent operations: If it is a single-threaded environment, or to ensure that access operations in a multi-threaded environment are synchronized, ArrayList can meet the requirements.

        It should be noted that if the insertion and deletion operations on elements are frequent and the collection is large, it may cause frequent array copies and affect performance. In this case, you can consider using LinkedList as an alternative, which has better performance on insertion and deletion operations, but less efficient random access.

2. LinkedList

LinkedList is another implementation class of the List interface in the Java collection framework. It is implemented based on a linked list and has the following characteristics:

1. Linked list structure: LinkedList stores elements in the form of a doubly linked list, and each node contains references to the previous node and the next node. Compared with ArrayList based on array implementation, LinkedList's insertion and deletion operations are more efficient.

2. High insertion and deletion efficiency: Due to the characteristics of the linked list, only the reference of the node needs to be modified when inserting and deleting elements, and there is no need to expand the array and copy data. Therefore, LinkedList performs better in scenarios that require frequent insertion and deletion of elements.

3. Does not support random access: LinkedList does not support direct access to elements through indexes, but needs to traverse from the head or tail of the linked list. Therefore, the efficiency of random access is low, and the time complexity is O(n).

4. Allows storing duplicate elements: Like ArrayList, LinkedList also allows storing duplicate elements.

5. Non-thread-safe: LinkedList is not thread-safe and is not suitable for concurrent access in a multi-threaded environment. If you need to use it in a multi-threaded environment, consider using a thread-safe alternative class, such as CopyOnWriteArrayList or Vector.

Based on the above characteristics, LinkedList is suitable for the following scenarios:

1. Frequent insertion and deletion of elements: Due to the high efficiency of LinkedList's insertion and deletion operations, it is suitable for scenarios that require frequent element insertion and deletion.

2. Queues or stacks need to be implemented: Due to the structural characteristics of linked lists, LinkedList can easily implement the data structure of queues (FIFO) or stacks (LIFO).

3. Sequential or reverse access to elements: LinkedList provides methods for obtaining the first element, the last element, and sequential or reverse traversal of elements, suitable for scenarios that require sequential or reverse access to elements.

4. Does not involve multi-threaded concurrent operations: If it is a single-threaded environment, or to ensure that access operations in a multi-threaded environment are synchronized, LinkedList can meet the requirements.

        It should be noted that since LinkedList does not support random access, it may be more appropriate to use ArrayList for scenarios that require frequent access based on indexes. In addition, LinkedList has a slight increase in memory usage compared to ArrayList due to the need for additional memory space to store node references.

3. Vector

Vector is another implementation class of the List interface in the Java collection framework. It is similar to ArrayList, but has the following characteristics:

1. Thread safety: Vector is thread safe, and it ensures thread safety by adding synchronization locks on each method. Multiple threads can operate on Vector at the same time without data inconsistency.

2. Dynamic array: The underlying implementation of Vector is also based on arrays, similar to ArrayList, it has the feature of automatic expansion. When the number of elements exceeds the current capacity, Vector will automatically increase the capacity to accommodate more elements.

3. Allow repeated elements: Vector allows to store repeated elements, and the same element can appear multiple times.

4. Relatively inefficient: Since Vector is thread-safe, it needs to perform synchronization operations on each method, which will bring additional performance overhead. Compared with ArrayList, the performance of Vector may be slightly lower in a single-threaded environment.

Based on the above characteristics, Vector is suitable for the following scenarios:

1. Multi-threaded environment: Since Vector is thread-safe, it is suitable for scenarios that require concurrent access and modification of collections in a multi-threaded environment. Multiple threads can operate on Vector at the same time without additional synchronization measures.

2. Collections that need to grow dynamically: If the number of elements in the collection changes dynamically and needs to be operated in a multi-threaded environment, Vector can automatically expand and ensure thread safety.

3. Allows to store repeated elements: If you need to store repeated elements, Vector is an optional choice.

        It should be noted that because of the synchronous operation of Vector on every method, it is relatively low in terms of performance. In a single-threaded environment, if you don't need thread-safe operations, you can consider using ArrayList as an alternative. In addition, Java 1.2 introduced more efficient thread-safe classes, such as CopyOnWriteArrayList and ConcurrentLinkedDeque, which may be more suitable for use in high-concurrency scenarios.

B. Set

1. HashSet

HashSet is the implementation class of the Set interface in the Java collection framework, which has the following characteristics:

1. Based on hash table: The underlying implementation of HashSet is based on hash table (HashMap), which uses hash algorithm to store and retrieve elements. Each element is stored as part of the key, while the value is a fixed placeholder.

2. Duplicate elements are not allowed: HashSet does not allow to store duplicate elements. If you try to add duplicate elements to the HashSet, it will be ignored.

3. Unordered collection: The elements in HashSet have no fixed order, that is, the storage and traversal order of elements is unpredictable.

4. Efficient insertion and search: Since HashSet is implemented based on a hash table, the time complexity of insertion and search operations is O(1). This makes HashSet perform well in insertion and lookup scenarios of large amounts of data.

5. Not thread-safe: HashSet is not thread-safe. If concurrent access to HashSet is required in a multi-threaded environment, external synchronization control is required.

Based on the above characteristics, HashSet is suitable for the following scenarios:

1. Deduplication storage: Since HashSet does not allow the storage of duplicate elements, it is often used for deduplication operations. The elements that need to be deduplicated can be added to the HashSet to achieve fast deduplication.

2. Find and determine whether an element exists: Due to the efficient search feature of HashSet, it can be used to quickly determine whether an element exists in the set. The contains() method of HashSet can quickly determine whether an element exists without traversing the entire collection.

3. Store elements that do not require a fixed order: If you do not need to maintain a specific order of elements, but only care about the uniqueness of elements and efficient insertion and lookup, HashSet is a suitable choice.

        It should be noted that since HashSet is implemented based on a hash table, its order of elements is unpredictable. If you need to store elements in an orderly manner, you can consider using LinkedHashSet, which maintains the insertion order of elements based on HashSet.

2. TreeSet

TreeSet is the implementation class of the Set interface in the Java collection framework, and it has the following characteristics:

1. Based on red-black tree: The underlying implementation of TreeSet is based on the red-black tree data structure. A red-black tree is a self-balancing binary search tree that maintains the order of elements and provides efficient insertion, deletion, and search operations.

2. Sorted collection: The elements in the TreeSet are ordered, sorted according to the natural sorting of elements or custom sorting rules. By default, a TreeSet is sorted according to the natural order of the elements, or according to the passed comparator.

3. Duplicate elements are not allowed: TreeSet does not allow to store duplicate elements. Attempts to add duplicate elements to the TreeSet will be ignored.

4. Efficient insertion, deletion and search: Since the bottom layer of TreeSet is a red-black tree, the time complexity of insertion, deletion and search operations is O(log n). This makes TreeSet perform well in storage and retrieval scenarios of sorted collections.

5. Not thread-safe: TreeSet is not thread-safe. If you need to access TreeSet concurrently in a multi-threaded environment, you need to perform external synchronization control.

Based on the above characteristics, TreeSet is suitable for the following scenarios:

1. Sorted storage: Since TreeSet is ordered, it is often used in scenarios where elements need to be stored in a certain order. Elements can be stored in a specific order according to their natural order or a custom comparator.

2. Range search: Since TreeSet is ordered, it is very convenient to perform range search. The subset within the specified range can be obtained through the subSet() method of TreeSet.

3. Store elements that need to be sorted: If you need to store a set of elements and sort them, TreeSet is a suitable choice.

        It should be noted that since TreeSet is implemented based on a red-black tree, it has high performance for insertion, deletion, and search operations. But compared to HashSet, it has a higher memory footprint because each element requires additional storage space to maintain the tree structure. In addition, the sorting of elements may add a certain amount of time overhead, especially for the case of custom collations. Therefore, in scenarios with high performance requirements, it is necessary to carefully evaluate whether to choose TreeSet.

3. LinkedHashSet

LinkedHashSet is the implementation class of the Set interface in the Java collection framework. It is a subclass of HashSet, has the characteristics of HashSet, and additionally maintains the insertion order of elements. The following are the characteristics and applicable scenarios of LinkedHashSet:

1. Maintain insertion order: LinkedHashSet internally uses a doubly linked list to maintain the insertion order of elements. Therefore, when traversing the LinkedHashSet, the order of the elements is consistent with the insertion order.

2. Duplicate elements are not allowed: Like HashSet, LinkedHashSet does not allow to store duplicate elements. If you try to add duplicate elements to LinkedHashSet, it will be ignored.

3. Based on hash table: The underlying implementation of LinkedHashSet is still based on hash table (HashMap). In addition to using a hash table to store elements, a linked list is also used to maintain the insertion order of elements.

4. Ordered collection: Since LinkedHashSet maintains the insertion order of elements, it is ordered. The traversal order of elements is consistent with the insertion order.

5. Slightly lower performance than HashSet: Since LinkedHashSet needs to maintain an additional linked list structure to maintain the insertion order, its performance on insertion and deletion operations is slightly lower than that of HashSet. But compared with ArrayList and LinkedList, LinkedHashSet has higher performance on lookup operations.

Based on the above characteristics, LinkedHashSet is suitable for the following scenarios:

1. Need to maintain the insertion order of elements: If you need to store and traverse elements in the order of insertion, LinkedHashSet is a suitable choice.

2. De-duplicate storage and maintain insertion order: Since LinkedHashSet does not allow to store duplicate elements and maintains the insertion order, it can be used for de-duplication storage and maintains the order in which elements are added.

3. Cached LRU (Least Recently Used) strategy: Since LinkedHashSet maintains the insertion order, it can be used to implement a cache based on the LRU strategy, that is, the least recently used strategy. When the cache runs out of space, the element that has not been accessed for the longest time can be removed.

        It should be noted that LinkedHashSet will occupy more memory space while maintaining the insertion order of elements, because an additional linked list structure needs to be maintained. Therefore, in scenarios with high memory usage requirements, you need to choose carefully.

C. Map

1. HashMap

HashMap is an implementation class of the Map interface in the Java collection framework, and it has the following characteristics:

1. Key-value pair storage: HashMap is a storage structure based on key-value pairs (key-value), and each element consists of a key and a value. Values ​​are uniquely identified and accessed by keys.

2. Based on Hash Table: The underlying implementation of HashMap is based on Hash Table. Hash tables use a hash function to map keys to array index positions for fast insertion, deletion, and lookup operations.

3. Unordered collection: The elements in HashMap have no fixed order, that is, the storage and traversal order of elements is unpredictable.

4. Allow to store null key and null value: HashMap allows to store null as key and value.

5. Efficient insertion, deletion and search: Since HashMap is implemented based on a hash table, the average time complexity of insertion, deletion and search operations is O(1). This makes HashMap perform well in scenarios of insertion, deletion and lookup of large amounts of data.

6. Non-thread-safe: HashMap is not thread-safe. If concurrent access to HashMap is required in a multi-threaded environment, external synchronization control is required.

Based on the above characteristics, HashMap is suitable for the following scenarios:

1. Key-value pair storage and retrieval: Since HashMap provides fast key-value pair storage and retrieval capabilities, it is often used in scenarios where the corresponding value needs to be quickly obtained according to the key.

2. Deduplication storage: Since the key of HashMap is unique, HashMap can be used for deduplication storage. Store the elements to be deduplicated as keys in the HashMap, and the value can be empty or a placeholder object.

3. Cache implementation: Due to the fast storage and retrieval characteristics of HashMap, it can be used to implement cache. Store the cached key as the key of the HashMap, and store the cached value as the value of the HashMap.

4. Storage without a fixed order: If you do not need to maintain a specific order of elements, but only care about the storage and retrieval of key-value pairs, HashMap is a suitable choice.

        It should be noted that due to the unordered nature of HashMap, if you need to store elements in an orderly manner, you can consider using LinkedHashMap, which maintains the insertion order of elements on the basis of HashMap. In addition, in a multi-threaded environment, if you need to access HashMap concurrently, you can consider using thread-safe ConcurrentHashMap.

2. TreeMap

TreeMap is an implementation class of the Map interface in the Java collection framework, and it has the following characteristics:

1. Sorted storage: The key-value pairs in TreeMap are ordered, and it sorts the keys according to their natural order or a custom comparator. By default, the TreeMap is sorted according to the natural order of the keys, or according to the passed comparator.

2. Based on red-black tree: The underlying implementation of TreeMap is based on the red-black tree (Red-Black Tree) data structure. A red-black tree is a self-balancing binary search tree that maintains the order of elements and provides efficient insertion, deletion, and search operations.

3. Keys are not allowed to be null: TreeMap does not allow keys to be null because it needs the keys to be sorted.

4. Efficient insertion, deletion and search: Since the bottom layer of TreeMap is a red-black tree, the time complexity of insertion, deletion and search operations is O(log n). This makes TreeMap perform well in ordered storage and retrieval scenarios.

5. Non-thread-safe: TreeMap is not thread-safe. If you need to access TreeMap concurrently in a multi-threaded environment, you need to perform external synchronization control.

Based on the above characteristics, TreeMap is suitable for the following scenarios:

1. Ordered storage and retrieval: Since the elements in TreeMap are ordered, it is often used in scenarios that require storage and retrieval in the order of keys. Keys can be sorted according to their natural order or a custom comparator.

2. Range search: Since the elements in TreeMap are ordered, range search can be easily performed. The subMap within the specified range can be obtained through the subMap() method of TreeMap.

3. Store key-value pairs that need to be sorted: If you need to store a set of key-value pairs and sort them according to the order of the keys, TreeMap is a suitable choice.

        It should be noted that since TreeMap is implemented based on a red-black tree, it has high performance for insertion, deletion, and search operations. But compared to HashMap, it has a higher memory footprint because each element requires additional storage space to maintain the tree structure. In addition, the sorting of elements may add a certain amount of time overhead, especially for the case of custom collations. Therefore, in scenarios with high performance requirements, it is necessary to carefully evaluate whether to choose TreeMap.

3. LinkedHashMap

LinkedHashMap is an implementation class of the Map interface in the Java collection framework. It inherits from HashMap and additionally maintains the insertion order of elements. The following are the characteristics and applicable scenarios of LinkedHashMap:

1. Maintain insertion order: LinkedHashMap internally uses a doubly linked list to maintain the insertion order of elements. Therefore, when traversing LinkedHashMap, the order of elements is consistent with the insertion order.

2. Based on hash table: The underlying implementation of LinkedHashMap is still based on hash table (HashMap). In addition to using a hash table to store elements, a linked list is also used to maintain the insertion order of elements.

3. Allows storing null key and null value: Like HashMap, LinkedHashMap allows storing null as key and value.

4. Ordered collection: Since LinkedHashMap maintains the insertion order of elements, it is ordered. The traversal order of elements is consistent with the insertion order.

5. The performance is similar to HashMap: LinkedHashMap's insertion, deletion and search operation performance is similar to that of HashMap, and the average time complexity is O(1). However, due to the maintenance of the linked list structure, LinkedHashMap has a slightly higher memory footprint than HashMap.

Based on the above characteristics, LinkedHashMap is suitable for the following scenarios:

1. Maintain element insertion order: LinkedHashMap is a suitable choice if you need to store and traverse elements in the order in which they are inserted.

2. Record access order: In addition to insertion order, LinkedHashMap can also be stored in order of access. By setting the accessOrder parameter in the constructor to true, the most recently accessed element can be placed at the end of the linked list. This can be used to implement a cache based on the LRU (Least Recently Used) strategy.

3. Ordered storage and retrieval: Since LinkedHashMap maintains the insertion order, it can be used in scenarios that require ordered storage and retrieval of elements. Elements can be obtained in insertion order or access order by traversing LinkedHashMap.

        It should be noted that LinkedHashMap has a slightly higher memory footprint than HashMap because of the need to maintain the linked list structure. In scenarios with high memory usage requirements, you need to choose carefully. In addition, in a multi-threaded environment, if you need to access LinkedHashMap concurrently, you can consider using thread-safe ConcurrentLinkedHashMap.

D. Tail

1. ArrayDeque

ArrayDeque is an implementation class of the Deque interface in the Java collection framework, which has the following characteristics:

1. Double-ended queue: ArrayDeque is a double-ended queue that can insert and delete elements at both ends of the queue. This means that elements can be inserted and removed from the head of the queue, and elements can be inserted and removed from the tail of the queue.

2. Dynamic array: The bottom layer of ArrayDeque is implemented with a circular array, which can dynamically adjust the size of the array as needed. This makes ArrayDeque more efficient in insertion and deletion operations.

3. Null elements are not allowed to be stored: ArrayDeque does not allow to store null elements. If you try to store null elements, a NullPointerException will be thrown.

4. Efficient operations: Since ArrayDeque is implemented based on dynamic arrays, it provides efficient insertion and deletion operations. The average time complexity of inserting and deleting operations at both ends of the queue is O(1).

5. Non-thread-safe: ArrayDeque is not thread-safe. If ArrayDeque needs to be accessed concurrently in a multi-threaded environment, external synchronization control is required.

Based on the above characteristics, ArrayDeque is suitable for the following scenarios:

1. Efficient double-ended queue operation: Since ArrayDeque supports insertion and deletion operations at the head and tail of the queue, it is very suitable for use as a double-ended queue. It can be used in scenarios that require frequent operations on the head and tail of the queue at the same time.

2. Efficient stack operation: Since ArrayDeque has the characteristics of a double-ended queue, it can also be used as a stack. Elements can be inserted at the end of the queue through the push() method, and elements can be deleted from the end of the queue through the pop() method to achieve efficient stack operations.

3. Temporary buffer: Due to ArrayDeque's dynamic array implementation, it can be used as a temporary buffer. Data that needs to be temporarily stored can be put into ArrayDeque and processed in insertion order without a fixed-size buffer.

        It should be noted that ArrayDeque is not thread-safe. If ArrayDeque needs to be accessed concurrently in a multi-threaded environment, external synchronization control is required. In addition, compared to LinkedList, ArrayDeque has better performance in insertion and deletion operations, but poor performance in random access elements. Therefore, ArrayDeque can be selected in scenarios where frequent insertion and deletion operations are required without random access to elements.

2. PriorityQueue

PriorityQueue is an implementation class of the Queue interface in the Java collection framework, which has the following characteristics:

1. Priority Queue: PriorityQueue is a special queue that sorts elements according to their priority. In PriorityQueue, elements are sorted in natural order or by a custom comparator.

2. Heap-based: The underlying implementation of PriorityQueue is based on the heap (Heap) data structure. A heap is a complete binary tree, which can ensure that the value of each node is greater than (or less than) the value of its child nodes, so as to achieve the order of elements.

3. Fast insertion and deletion operations: Since PriorityQueue is implemented based on a heap, the average time complexity of insertion and deletion operations is O(log n). This makes PriorityQueue have high performance in scenarios where insertion and deletion operations need to be performed according to priority.

4. Storage of null elements is not allowed: PriorityQueue does not allow storage of null elements. If you try to store null elements, a NullPointerException will be thrown.

5. Non-thread-safe: PriorityQueue is not thread-safe. If you need to access PriorityQueue concurrently in a multi-threaded environment, you need to perform external synchronization control.

Based on the above characteristics, PriorityQueue is suitable for the following scenarios:

1. Priority processing: Since PriorityQueue is sorted according to the priority of elements, it is very suitable for scenarios that need to be processed according to priority. Elements with different priorities can be put into PriorityQueue and processed according to priority order.

2. Heap sorting: Since the underlying implementation of PriorityQueue is based on the heap, it can be used to implement the heap sorting algorithm. Heap sorting is an efficient sorting algorithm. By inserting the elements to be sorted into PriorityQueue in sequence, and then taking them out in order of priority, you can get ordered results.

3. Task scheduling: PriorityQueue can be used to implement task scheduling queues. The tasks that need to be executed can be put into the PriorityQueue and scheduled according to the priority of the tasks.

        It should be noted that PriorityQueue is not thread-safe. If you need to access PriorityQueue concurrently in a multi-threaded environment, you need to perform external synchronization control. In addition, since PriorityQueue is implemented based on a heap, it has good performance in sorting and inserting large-scale data, but has poor performance in random access elements. Therefore, evaluation and selection are required in scenarios with high requirements for random access elements.

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