Chunked data processing

When processing large arrays or data structures, implement chunked processing to avoid stack size limitations and optimize performance. Break operations into manageable chunks rather than processing everything at once.

Key practices:

1. Use appropriate chunk sizes (typically 100KB or less) when dealing with large binary data or strings
2. Choose the right collection operation for your use case:
   • Use reduce() when accumulating or combining values across collections
   • Use map() when transforming elements without combining them
   • Consider recursion for nested structures with appropriate base cases

Example:

// Process large binary data in chunks to avoid stack overflow
async asString(): Promise<string> {
  const data = this.data ?? new Blob([]);
  const dataBuffer = await data.arrayBuffer();
  const dataArray = new Uint8Array(dataBuffer);

  // Need to handle the array in smaller chunks to deal with stack size limits
  let ret = "";
  const chunkSize = 102400;
  for (let i = 0; i < dataArray.length; i += chunkSize) {
    const chunk = dataArray.subarray(i, i + chunkSize);
    ret += String.fromCharCode(...chunk);
  }

  return ret;
}

Implementing chunked processing improves application stability by preventing stack overflows and can improve performance by managing memory more efficiently. This pattern is especially important when handling user-generated content, large API responses, or binary data operations.