Avoid expensive operations in frequently executed code paths by implementing performance optimizations such as lookup tables, result caching, conditional initialization, and object reuse.

Key optimization strategies:

Replace expensive algorithms with faster alternatives: Use lookup tables instead of linear searches like std::find_first_of when checking for special characters in strings.
Cache redundant computations: Avoid performing the same expensive checks multiple times by caching results in appropriate data structures like unsafe_unique_array<bool>.
Minimize initialization overhead: Only perform expensive initialization when necessary (e.g., after state changes) rather than on every iteration or function call.
Reuse expensive objects: Make costly-to-create objects like compiled regex patterns static to avoid recreation overhead.

Example of lookup table optimization:

// Instead of: std::find_first_of(string_data, string_end, special_chars, special_chars + special_chars_length)
// Use a lookup table for O(1) character checking:
static bool special_char_lookup[256] = {false}; // Initialize once
// Check: if (special_char_lookup[static_cast<unsigned char>(ch)])

Example of conditional initialization:

// Instead of initializing on every chunk:
static void MultiFileScan(...) {
    InitializeFileScanState(context, data, gstate.projection_ids); // Every call
}

// Initialize only when needed:
static void MultiFileScan(...) {
    if (file_changed || !initialized) {
        InitializeFileScanState(context, data, gstate.projection_ids);
    }
}

These optimizations can provide significant performance improvements, with reported speedups of 2x or more in critical code paths.

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