Search code examples
javaarraylistdata-structures

Can ArrayList handle big datasets in java?


I have a requirement to store around 100000 - 200000 records in a collection object. As of now, I am planning to use ArrayList, but I am interested to know the best way to store such a huge list.

Can any one of you help me come up with some thoughts on how to store large amounts of data into Collection? Which one is efficient, affordable in terms of performing well when it lands up in place?

ArrayList: Grows dynamically by allocating new memory chunks, potentially causing fragmentation. Is there any way we can define the size while creating the object itself? Is it the correct way to define ? Also do I need to change the java heap size ?

Is there any other data structure I should consider?

Note - I have decided to go with arraylist as order and index does not matter. I am fine with random access. I just want to know what are the best practice and other alternative approach.


Solution

  • Handling a large number of records efficiently involves choosing the right data structure. Here are simplified options:

    ArrayList:

    • Good for easy access by index.
    • Set initial size to reduce resizing overhead: ArrayList<Type> list = new ArrayList<>(initialCapacity);
    • Increase Java heap size if memory errors occur.

    LinkedList:

    • Efficient for adding/removing in the middle, but slow for random access.

    HashSet/TreeSet:

    • HashSet ensures uniqueness, TreeMap stores in sorted order.
    • Useful for fast lookup but no inherent ordering in HashSet.

    HashMap/TreeMap:

    • Key-value pairs for fast retrieval by keys.

    ArrayDeque:

    • Good for queue (FIFO) or stack (LIFO) operations.

    Considerations:

    • Choose based on what you'll do most with the data.
    • Think about memory usage versus performance.
    • Check if you need to optimize for specific operations like lookup or insertion/removal.

    Some insights you can consider:

    • Preallocate space to reduce resizing.
    • Increase Java heap size if needed for large datasets.