The key to optimizing Java program performance lies in the rational selection of data structures and algorithms. 1. Select appropriate collection classes according to the scene, such as frequent access to intermediate elements, use ArrayList, and use LinkedList to operate head or tail, find multi-priority HashMap or HashSet, and avoid thread-safe classes and capacity expansion losses. 2. Avoid repeated calculations, use memory cache results to reduce time complexity. 3. Master efficient sorting search algorithms, such as insertion sorting, counting sorting, binary search, KMP, etc., and select according to data characteristics. 4. Reduce GC pressure, avoid creating objects in loops, use object pools, StringBuilder and use Stream API with caution.

The performance optimization of Java programs often depends not on the language itself, but on what data structures and algorithms you use. If you choose the right structure and write the right logic, the program will naturally be faster. Let’s talk about how to use Java data structures and algorithms to improve performance from several common perspectives.

1. Choose the collection class reasonably to avoid unnecessary overhead

Java provides many built-in data structures, such as ArrayList , LinkedList , HashMap , TreeMap , HashSet , etc. Their performance varies greatly in different scenarios.

• If you need to access intermediate elements frequently, ArrayList is more appropriate than LinkedList because the time complexity of random access is O(1).
• LinkedList may be more efficient if it is often inserted and deleted at the head or tail.
• When there are many search operations, we give priority to HashMap or HashSet . They are implemented based on a hash table, and the search time is close to O(1), which is much faster than TreeMap (unless you need sorting function).

Small suggestions:

• When thread-safe is not required, do not use Vector or Hashtable , use ArrayList and HashMap instead.
• If you know the size of the collection, specifying the capacity during initialization can reduce the performance loss caused by expansion.

2. Avoid repeated calculations and make good use of cache and memory

Some algorithms repeatedly calculate the same problem, such as the Fibonacci sequence implemented in recursively. In this case, "memorization" can be used to optimize - cache the calculated results.

For example:

 int[] memo = new int[n 1];
Arrays.fill(memo, -1);

public int fib(int n) {
    if (n <= 1) return n;
    if (memo[n] != -1) return memo[n];
    memo[n] = fib(n - 1) fib(n - 2);
    return memo[n];
}

This method greatly reduces repeated calls, and the time complexity drops from exponential to O(n).

Similar techniques can also be used in:

• Store sub-solutions in dynamic programming problems;
• Database query results cache;
• The result cache when the method parameters are fixed (you can use frameworks such as Spring Cache);

3. Use efficient sorting and search algorithms

Arrays.sort() in Java has been optimized very well, but you need to know that behind it is Dual-Pivot Quicksort (base type) and TimSort (object). These are already relatively fast general sorting algorithms.

If you are facing:

• Almost ordered data, insert sorting can be considered;
• When the data range is limited, count sorting may be faster;
• For multiple rounds of sorting requirements, remember to sort them stably (such as TimSort);

For search:

• Ordered arrays are searched in binary ( Arrays.binarySearch() );
• String matching can be considered as KMP or Boyer-Moore algorithms;
• BFS/DFS is commonly used in the graph structure, and decide which one is more suitable based on the problem;

4. Minimize garbage recycling pressure

Java automatically manages memory, but frequent creation of short-lifetime objects will increase pressure on GC and affect performance.

Some practical practices:

• Avoid creating new objects in loops, such as new String() or new ArrayList() ;
• Use object pools to handle expensive objects (such as database connections, threads, etc.);
• For large number of string splicing, use StringBuilder instead of ;
• Be careful with the Stream API, which can sometimes bring additional overhead;

Basically that's it. The selection of data structures and algorithms directly affects the efficiency of code operation. Don’t just pursue “elegance”, it depends on the actual scenario and performance bottlenecks.

The above is the detailed content of Java Data Structures and Algorithms for Performance. For more information, please follow other related articles on the PHP Chinese website!