Is String Concatenation in Go Really O(n)? A Look at Amortized Costs and Efficient Alternatives.

Efficient String Concatenation in Go

The article begins by describing a common problem encountered when processing large log files: the need to efficiently collect regex matches and store them in a container for subsequent processing and serialization. The questioner expresses concerns about the potential performance issues associated with appending to slices, citing the doubling of capacity for smaller slices and 1.25x capacity increase for larger ones, especially given the potentially high number of regex matches.

The questioner then proposes an alternative solution involving a doubly-linked list of matches, followed by preallocation of a slice based on the list's length and subsequent copying of string pointers to this slice. They inquire if there are more efficient ways to achieve this in Go, with a focus on achieving an average O(1) append complexity.

The response addresses the concerns raised by the questioner, explaining that the append() operation in Go actually has an amortized cost of O(1). This means that while the cost of individual append() operations may vary, the average cost over a large number of operations remains constant. The response attributes this to the fact that the array used to store the strings grows proportionally to its size, with the increasing cost of growing the array being balanced out by the decreasing frequency of such growth.

The response also provides empirical evidence to support this claim, citing a benchmark that shows a million append() operations taking 77ms on a laptop. It emphasizes that the cost of "copying" strings is primarily the cost of copying string headers (a pointer/length pair) rather than the entire string contents.

The response then compares the performance of linked lists (container/list) with slices, indicating that slices may be more appropriate for this particular scenario due to their lower overhead. However, the response also acknowledges that pre-allocating space for the slice can further improve performance in certain cases.

Finally, recognizing the specific context of a grep-like application, the response recommends against buffering the entire output in RAM. Instead, it suggests streaming the results as a single function, avoiding the need to store large amounts of data in memory. The response also discusses the potential implications of keeping string references, highlighting the impact on garbage collection and suggesting the use of []byte instead of string for efficiency in certain scenarios.

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