Prompt
Avoid unnecessary memory allocations in performance-critical code paths. These allocations not only consume memory but also trigger expensive CPU operations that can significantly impact system performance.
Key optimization techniques:
- Use efficient data structures:
- Box large enum variants to reduce memory footprint
```rust
// Before
enum Schedule {
Cron(OwnedScheduleIterator
), // 288 bytes Every(Duration), // 16 bytes }
// After enum Schedule { Cron(Box<OwnedScheduleIterator
>), // 16 bytes Every(Duration), // 16 bytes } ``` - Prefer
HashMapoverBTreeMapfor lookup-heavy operations - Consider
Arc<str>or&stroverStringwhen appropriate
- Box large enum variants to reduce memory footprint
```rust
// Before
enum Schedule {
Cron(OwnedScheduleIterator
- Optimize container operations:
- Use
contains()instead ofiter().any()for membership checks ```rust // Less efficient if paths_without_authz.iter().any(|disabled_authz_path| *disabled_authz_path == path) { // … }
// More efficient if paths_without_authz.contains(&path) { // … } ```
- Consider how you handle capacity in vectors (clear vs. take)
- Use iterators for lazy evaluation rather than materializing full collections
- Use
- Avoid string overhead:
- Use
to_string()instead offormat!()for simple conversions ```rust // Less efficient let partition_key = data_types::PartitionKey::from(format!(“{}”, parquet_file.chunk_time));
// More efficient let partition_key = data_types::PartitionKey::from(parquet_file.chunk_time.to_string()); ```
- Avoid rebuilding schemas or data structures repeatedly in hot paths
- Use
Remember that even small allocations can have a significant impact when they occur frequently in critical code paths, particularly in high-throughput systems handling many requests or processing large datasets.