How slices affect the performance of your code in go? How can they be mitigated?

Quick tech learn
2 min readAug 25, 2023

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To know more about slices in go, read my blog about slices in go.

In Go, appending to a slice can potentially decrease performance, if the underlying array needs to be resized. However, the impact on performance depends on various factors, including the size of the slice, the frequency of appends, and how the slice is managed.

Here are some key areas where you should take care while implementing slices in go,

  1. Resizing: When you append to a slice and the underlying array doesn’t have enough capacity to accommodate the new element, a new larger array is allocated, and the existing elements are copied to the new slice. This is not a problem when the slice length is small like 5. Think when the length is about 1000+. This resizing operation has a time complexity of O(n), where n is the length of the slice.
  2. Amortized Constant Time: Although appending an element to a slice involves resizing, Go uses an amortized constant-time strategy to minimize the time taken. That is, over a series of append operations, the average time per append is constant, but individual appends may be slower due to occasional resizing.
  3. Preallocating Capacity: To improve performance, you can preallocate capacity for a slice using the make() function with a specified capacity. This can reduce the number of reallocations and copying operations. For example:
slice := make([]int, 0, 100) // Allocate capacity for 100 elements

4. Copy vs. Reference: Slices are passed as reference to functions instead of sending a copy. So, modifying the argument will change original array itself.

5. Append Frequency: If you frequently append small numbers of elements, the overhead of resizing may be negligible. However, if you’re appending a large number of elements in a loop, it’s more efficient to preallocate capacity.

6. Sharing among goroutines: Be careful when the slices are shared across multiple goroutines. Concurrent append operations can lead to race conditions and unpredictable behaviour. Sync properly and carefully the threads.

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Quick tech learn

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