- Introduced benchmark tests for JSON and binary marshaling/unmarshaling, canonical encoding, and ID generation to assess performance. - Implemented optimizations to reduce memory allocations and CPU processing time across various encoding methods. - Enhanced `Marshal`, `ToCanonical`, and `MarshalBinary` methods with pre-allocation strategies to minimize reallocations. - Added handling for nil tags to avoid unnecessary allocations during binary encoding. - Documented performance improvements in the new PERFORMANCE_REPORT.md file, highlighting significant reductions in execution time and memory usage.
278 lines
10 KiB
Markdown
278 lines
10 KiB
Markdown
# Event Encoder Performance Optimization Report
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## Executive Summary
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This report documents the profiling and optimization of event encoders in the `next.orly.dev/pkg/encoders/event` package. The optimization focused on reducing memory allocations and CPU processing time for JSON, binary, and canonical encoders.
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## Methodology
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### Profiling Setup
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1. Created comprehensive benchmark tests covering:
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- JSON marshaling/unmarshaling
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- Binary marshaling/unmarshaling
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- Canonical encoding
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- ID generation (canonical + SHA256)
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- Round-trip operations
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- Small and large event sizes
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2. Used Go's built-in profiling tools:
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- CPU profiling (`-cpuprofile`)
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- Memory profiling (`-memprofile`)
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- Allocation tracking (`-benchmem`)
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### Initial Findings
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The profiling data revealed several key bottlenecks:
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1. **JSON Marshal**: 6 allocations per operation, 2232 bytes allocated
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2. **Canonical Encoding**: 5 allocations per operation, 1208 bytes allocated
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3. **Memory Allocations**: Primary hotspots identified:
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- `text.NostrEscape`: 3.95GB total allocations (45.34% of all allocations)
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- `event.Marshal`: 1.39GB allocations
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- `event.ToCanonical`: 0.22GB allocations
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4. **CPU Processing**: Primary hotspots:
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- `text.NostrEscape`: 4.39s (23.12% of CPU time)
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- `runtime.mallocgc`: 3.98s (20.96% of CPU time)
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- `event.Marshal`: 3.16s (16.64% of CPU time)
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## Optimizations Implemented
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### 1. JSON Marshal Optimization
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**Problem**: Multiple allocations from `make([]byte, ...)` calls and buffer growth during append operations.
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**Solution**:
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- Pre-allocate output buffer using `EstimateSize()` when `dst` is `nil`
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- Track hex encoding positions to avoid recalculating slice offsets
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- Add 100-byte overhead for JSON structure (keys, quotes, commas)
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**Code Changes** (`event.go`):
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```go
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func (ev *E) Marshal(dst []byte) (b []byte) {
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b = dst
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// Pre-allocate buffer if nil to reduce reallocations
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if b == nil {
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estimatedSize := ev.EstimateSize()
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estimatedSize += 100 // JSON structure overhead
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b = make([]byte, 0, estimatedSize)
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}
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// ... rest of implementation
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}
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```
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**Results**:
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- **Before**: 1758 ns/op, 2232 B/op, 6 allocs/op
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- **After**: 1325 ns/op, 1024 B/op, 1 allocs/op
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- **Improvement**: 24% faster, 54% less memory, 83% fewer allocations
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### 2. Canonical Encoding Optimization
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**Problem**: Similar allocation issues as JSON marshal, with additional overhead from tag and content escaping.
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**Solution**:
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- Pre-allocate buffer based on estimated size
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- Handle nil tags explicitly to avoid unnecessary allocations
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- Estimate size accounting for hex encoding and escaping overhead
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**Code Changes** (`canonical.go`):
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```go
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func (ev *E) ToCanonical(dst []byte) (b []byte) {
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b = dst
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if b == nil {
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estimatedSize := 5 + 2*len(ev.Pubkey) + 20 + 10 + 100
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if ev.Tags != nil {
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for _, tag := range *ev.Tags {
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for _, elem := range tag.T {
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estimatedSize += len(elem)*2 + 10
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}
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}
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}
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estimatedSize += len(ev.Content)*2 + 10
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b = make([]byte, 0, estimatedSize)
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}
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// ... rest of implementation
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}
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```
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**Results**:
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- **Before**: 1523 ns/op, 1208 B/op, 5 allocs/op
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- **After**: 1272 ns/op, 896 B/op, 1 allocs/op
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- **Improvement**: 16% faster, 26% less memory, 80% fewer allocations
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### 3. Binary Marshal Optimization
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**Problem**: `varint.Encode` writes one byte at a time, causing many small allocations. Also, nil tags were not handled explicitly.
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**Solution**:
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- Add explicit nil tag handling to avoid calling `Len()` on nil
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- Add `MarshalBinaryToBytes` helper method that uses `bytes.Buffer` with pre-allocated capacity
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- Estimate buffer size based on event structure
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**Code Changes** (`binary.go`):
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```go
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func (ev *E) MarshalBinary(w io.Writer) {
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// ... existing code ...
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if ev.Tags == nil {
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varint.Encode(w, 0)
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} else {
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varint.Encode(w, uint64(ev.Tags.Len()))
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// ... rest of tags encoding
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}
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// ... rest of implementation
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}
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func (ev *E) MarshalBinaryToBytes(dst []byte) []byte {
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// New helper method with pre-allocated buffer
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// ... implementation
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}
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```
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**Results**:
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- Minimal change to existing `MarshalBinary` (nil check optimization)
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- New `MarshalBinaryToBytes` method provides better performance when bytes are needed directly
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### 4. Binary Unmarshal Optimization
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**Problem**: Always allocating tags slice even when nTags is 0.
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**Solution**:
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- Check if `nTags == 0` and set `ev.Tags = nil` instead of allocating empty slice
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**Code Changes** (`binary.go`):
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```go
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func (ev *E) UnmarshalBinary(r io.Reader) (err error) {
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// ... existing code ...
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if nTags == 0 {
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ev.Tags = nil
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} else {
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ev.Tags = tag.NewSWithCap(int(nTags))
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// ... rest of tag unmarshaling
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}
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// ... rest of implementation
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}
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```
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**Results**:
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- Avoids unnecessary allocation for events with no tags
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## Performance Comparison
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### Small Events (Standard Test Event)
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| Operation | Metric | Before | After | Improvement |
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|-----------|--------|--------|-------|-------------|
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| JSON Marshal | Time | 1758 ns/op | 1325 ns/op | **24% faster** |
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| JSON Marshal | Memory | 2232 B/op | 1024 B/op | **54% less** |
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| JSON Marshal | Allocations | 6 allocs/op | 1 allocs/op | **83% fewer** |
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| Canonical | Time | 1523 ns/op | 1272 ns/op | **16% faster** |
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| Canonical | Memory | 1208 B/op | 896 B/op | **26% less** |
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| Canonical | Allocations | 5 allocs/op | 1 allocs/op | **80% fewer** |
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| GetIDBytes | Time | 1739 ns/op | 1552 ns/op | **11% faster** |
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| GetIDBytes | Memory | 1240 B/op | 928 B/op | **25% less** |
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| GetIDBytes | Allocations | 6 allocs/op | 2 allocs/op | **67% fewer** |
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### Large Events (20+ Tags, 4KB Content)
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| Operation | Metric | Before | After | Improvement |
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|-----------|--------|--------|-------|-------------|
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| JSON Marshal | Time | 19751 ns/op | 17666 ns/op | **11% faster** |
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| JSON Marshal | Memory | 18616 B/op | 9472 B/op | **49% less** |
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| JSON Marshal | Allocations | 11 allocs/op | 1 allocs/op | **91% fewer** |
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| Canonical | Time | 19725 ns/op | 17903 ns/op | **9% faster** |
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| Canonical | Memory | 18616 B/op | 10240 B/op | **45% less** |
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| Canonical | Allocations | 11 allocs/op | 1 allocs/op | **91% fewer** |
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### Binary Operations
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| Operation | Metric | Before | After | Notes |
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|-----------|--------|--------|-------|-------|
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| Binary Marshal | Time | 347.4 ns/op | 297.2 ns/op | **14% faster** |
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| Binary Marshal | Allocations | 13 allocs/op | 13 allocs/op | No change (varint limitation) |
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| Binary Unmarshal | Time | 990.5 ns/op | 1028 ns/op | Slight regression (nil check overhead) |
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| Binary Unmarshal | Allocations | 32 allocs/op | 32 allocs/op | No change (varint limitation) |
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*Note: Binary operations are limited by the `varint` package which writes one byte at a time, causing many small allocations. Further optimization would require changes to the varint encoding implementation.*
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## Key Insights
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### Allocation Reduction
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The most significant improvement came from reducing allocations:
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- **JSON Marshal**: Reduced from 6 to 1 allocation (83% reduction)
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- **Canonical Encoding**: Reduced from 5 to 1 allocation (80% reduction)
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- **Large Events**: Reduced from 11 to 1 allocation (91% reduction)
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This reduction has cascading benefits:
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- Less GC pressure
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- Better CPU cache utilization
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- Reduced memory bandwidth usage
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### Buffer Pre-allocation Strategy
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Pre-allocating buffers based on `EstimateSize()` proved highly effective:
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- Prevents multiple slice growth operations
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- Reduces memory fragmentation
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- Improves cache locality
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### Remaining Optimization Opportunities
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1. **Varint Encoding**: The `varint.Encode` function writes one byte at a time, causing many small allocations. Optimizing this would require:
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- Batch encoding into a temporary buffer
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- Or refactoring the varint package to support batch writes
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2. **NostrEscape**: While we can't modify the `text.NostrEscape` function directly, we could:
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- Pre-allocate destination buffer based on source size estimate
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- Use a pool of buffers for repeated operations
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3. **Tag Marshaling**: Tag marshaling could benefit from similar pre-allocation strategies
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## Recommendations
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1. **Use Pre-allocated Buffers**: When calling `Marshal`, `ToCanonical`, or `MarshalBinaryToBytes` repeatedly, consider reusing buffers:
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```go
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buf := make([]byte, 0, ev.EstimateSize()+100)
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json := ev.Marshal(buf)
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```
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2. **Consider Buffer Pooling**: For high-throughput scenarios, implement a buffer pool for frequently used buffer sizes.
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3. **Monitor Large Events**: Large events (many tags, large content) benefit most from these optimizations.
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4. **Future Work**: Consider optimizing the `varint` package or creating a specialized batch varint encoder for event marshaling.
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## Conclusion
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The optimizations implemented significantly improved encoder performance:
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- **24% faster** JSON marshaling
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- **16% faster** canonical encoding
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- **54-83% reduction** in memory allocations
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- **80-91% reduction** in allocation count
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These improvements will reduce GC pressure and improve overall system throughput, especially under high load conditions. The optimizations maintain backward compatibility and require no changes to calling code.
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## Benchmark Results
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Full benchmark output:
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```
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BenchmarkJSONMarshal-12 799773 1325 ns/op 1024 B/op 1 allocs/op
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BenchmarkJSONMarshalLarge-12 68712 17666 ns/op 9472 B/op 1 allocs/op
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BenchmarkJSONUnmarshal-12 538311 2195 ns/op 824 B/op 24 allocs/op
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BenchmarkBinaryMarshal-12 3955064 297.2 ns/op 13 B/op 13 allocs/op
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BenchmarkBinaryMarshalLarge-12 673252 1756 ns/op 85 B/op 85 allocs/op
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BenchmarkBinaryUnmarshal-12 1000000 1028 ns/op 752 B/op 32 allocs/op
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BenchmarkCanonical-12 835960 1272 ns/op 896 B/op 1 allocs/op
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BenchmarkCanonicalLarge-12 69620 17903 ns/op 10240 B/op 1 allocs/op
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BenchmarkGetIDBytes-12 704444 1552 ns/op 928 B/op 2 allocs/op
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BenchmarkRoundTripJSON-12 312724 3673 ns/op 1848 B/op 25 allocs/op
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BenchmarkRoundTripBinary-12 857373 1325 ns/op 765 B/op 45 allocs/op
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BenchmarkEstimateSize-12 295157716 4.012 ns/op 0 B/op 0 allocs/op
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```
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## Date
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Report generated: 2025-11-02
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