521 lines
16 KiB
Go
521 lines
16 KiB
Go
package main
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import (
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"context"
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"fmt"
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"sort"
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"sync"
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"time"
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"git.mleku.dev/mleku/nostr/encoders/event"
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"git.mleku.dev/mleku/nostr/encoders/filter"
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"git.mleku.dev/mleku/nostr/encoders/hex"
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"git.mleku.dev/mleku/nostr/encoders/kind"
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"git.mleku.dev/mleku/nostr/encoders/tag"
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"git.mleku.dev/mleku/nostr/interfaces/signer/p8k"
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"lukechampine.com/frand"
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"next.orly.dev/pkg/database"
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)
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const (
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// GraphBenchNumPubkeys is the number of pubkeys to generate for graph benchmark
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GraphBenchNumPubkeys = 100000
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// GraphBenchMinFollows is the minimum number of follows per pubkey
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GraphBenchMinFollows = 1
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// GraphBenchMaxFollows is the maximum number of follows per pubkey
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GraphBenchMaxFollows = 1000
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// GraphBenchSeed is the deterministic seed for frand PRNG (fits in uint64)
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GraphBenchSeed uint64 = 0x4E6F737472 // "Nostr" in hex
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// GraphBenchTraversalDepth is the depth of graph traversal (3 = third degree)
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GraphBenchTraversalDepth = 3
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)
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// GraphTraversalBenchmark benchmarks graph traversal using NIP-01 style queries
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type GraphTraversalBenchmark struct {
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config *BenchmarkConfig
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db *database.D
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results []*BenchmarkResult
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mu sync.RWMutex
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// Cached data for the benchmark
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pubkeys [][]byte // 100k pubkeys as 32-byte arrays
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signers []*p8k.Signer // signers for each pubkey
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follows [][]int // follows[i] = list of indices that pubkey[i] follows
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rng *frand.RNG // deterministic PRNG
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}
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// NewGraphTraversalBenchmark creates a new graph traversal benchmark
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func NewGraphTraversalBenchmark(config *BenchmarkConfig, db *database.D) *GraphTraversalBenchmark {
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return &GraphTraversalBenchmark{
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config: config,
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db: db,
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results: make([]*BenchmarkResult, 0),
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rng: frand.NewCustom(make([]byte, 32), 1024, 12), // ChaCha12 with seed buffer
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}
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}
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// initializeDeterministicRNG initializes the PRNG with deterministic seed
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func (g *GraphTraversalBenchmark) initializeDeterministicRNG() {
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// Create seed buffer from GraphBenchSeed (uint64 spread across 8 bytes)
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seedBuf := make([]byte, 32)
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seed := GraphBenchSeed
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seedBuf[0] = byte(seed >> 56)
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seedBuf[1] = byte(seed >> 48)
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seedBuf[2] = byte(seed >> 40)
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seedBuf[3] = byte(seed >> 32)
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seedBuf[4] = byte(seed >> 24)
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seedBuf[5] = byte(seed >> 16)
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seedBuf[6] = byte(seed >> 8)
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seedBuf[7] = byte(seed)
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g.rng = frand.NewCustom(seedBuf, 1024, 12)
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}
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// generatePubkeys generates deterministic pubkeys using frand
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func (g *GraphTraversalBenchmark) generatePubkeys() {
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fmt.Printf("Generating %d deterministic pubkeys...\n", GraphBenchNumPubkeys)
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start := time.Now()
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g.initializeDeterministicRNG()
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g.pubkeys = make([][]byte, GraphBenchNumPubkeys)
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g.signers = make([]*p8k.Signer, GraphBenchNumPubkeys)
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for i := 0; i < GraphBenchNumPubkeys; i++ {
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// Generate deterministic 32-byte secret key from PRNG
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secretKey := make([]byte, 32)
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g.rng.Read(secretKey)
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// Create signer from secret key
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signer := p8k.MustNew()
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if err := signer.InitSec(secretKey); err != nil {
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panic(fmt.Sprintf("failed to init signer %d: %v", i, err))
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}
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g.signers[i] = signer
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g.pubkeys[i] = make([]byte, 32)
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copy(g.pubkeys[i], signer.Pub())
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if (i+1)%10000 == 0 {
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fmt.Printf(" Generated %d/%d pubkeys...\n", i+1, GraphBenchNumPubkeys)
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}
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}
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fmt.Printf("Generated %d pubkeys in %v\n", GraphBenchNumPubkeys, time.Since(start))
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}
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// generateFollowGraph generates the random follow graph with deterministic PRNG
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func (g *GraphTraversalBenchmark) generateFollowGraph() {
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fmt.Printf("Generating follow graph (1-%d follows per pubkey)...\n", GraphBenchMaxFollows)
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start := time.Now()
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// Reset RNG to ensure deterministic follow graph
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g.initializeDeterministicRNG()
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// Skip the bytes used for pubkey generation
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skipBuf := make([]byte, 32*GraphBenchNumPubkeys)
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g.rng.Read(skipBuf)
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g.follows = make([][]int, GraphBenchNumPubkeys)
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totalFollows := 0
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for i := 0; i < GraphBenchNumPubkeys; i++ {
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// Determine number of follows for this pubkey (1 to 1000)
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numFollows := int(g.rng.Uint64n(uint64(GraphBenchMaxFollows-GraphBenchMinFollows+1))) + GraphBenchMinFollows
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// Generate random follow indices (excluding self)
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followSet := make(map[int]struct{})
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for len(followSet) < numFollows {
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followIdx := int(g.rng.Uint64n(uint64(GraphBenchNumPubkeys)))
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if followIdx != i {
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followSet[followIdx] = struct{}{}
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}
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}
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// Convert to slice
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g.follows[i] = make([]int, 0, numFollows)
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for idx := range followSet {
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g.follows[i] = append(g.follows[i], idx)
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}
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totalFollows += numFollows
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if (i+1)%10000 == 0 {
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fmt.Printf(" Generated follow lists for %d/%d pubkeys...\n", i+1, GraphBenchNumPubkeys)
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}
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}
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avgFollows := float64(totalFollows) / float64(GraphBenchNumPubkeys)
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fmt.Printf("Generated follow graph in %v (avg %.1f follows/pubkey, total %d follows)\n",
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time.Since(start), avgFollows, totalFollows)
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}
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// createFollowListEvents creates kind 3 follow list events in the database
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func (g *GraphTraversalBenchmark) createFollowListEvents() {
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fmt.Println("Creating follow list events in database...")
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start := time.Now()
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ctx := context.Background()
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baseTime := time.Now().Unix()
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var mu sync.Mutex
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var wg sync.WaitGroup
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var successCount, errorCount int64
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latencies := make([]time.Duration, 0, GraphBenchNumPubkeys)
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// Use worker pool for parallel event creation
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numWorkers := g.config.ConcurrentWorkers
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if numWorkers < 1 {
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numWorkers = 4
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}
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workChan := make(chan int, numWorkers*2)
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// Rate limiter: cap at 20,000 events/second
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perWorkerRate := 20000.0 / float64(numWorkers)
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for w := 0; w < numWorkers; w++ {
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wg.Add(1)
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go func() {
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defer wg.Done()
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workerLimiter := NewRateLimiter(perWorkerRate)
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for i := range workChan {
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workerLimiter.Wait()
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ev := event.New()
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ev.Kind = kind.FollowList.K
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ev.CreatedAt = baseTime + int64(i)
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ev.Content = []byte("")
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ev.Tags = tag.NewS()
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// Add p tags for all follows
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for _, followIdx := range g.follows[i] {
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pubkeyHex := hex.Enc(g.pubkeys[followIdx])
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ev.Tags.Append(tag.NewFromAny("p", pubkeyHex))
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}
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// Sign the event
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if err := ev.Sign(g.signers[i]); err != nil {
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mu.Lock()
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errorCount++
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mu.Unlock()
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ev.Free()
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continue
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}
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// Save to database
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eventStart := time.Now()
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_, err := g.db.SaveEvent(ctx, ev)
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latency := time.Since(eventStart)
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mu.Lock()
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if err != nil {
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errorCount++
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} else {
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successCount++
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latencies = append(latencies, latency)
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}
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mu.Unlock()
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ev.Free()
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}
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}()
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}
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// Send work
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for i := 0; i < GraphBenchNumPubkeys; i++ {
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workChan <- i
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if (i+1)%10000 == 0 {
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fmt.Printf(" Queued %d/%d follow list events...\n", i+1, GraphBenchNumPubkeys)
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}
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}
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close(workChan)
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wg.Wait()
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duration := time.Since(start)
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eventsPerSec := float64(successCount) / duration.Seconds()
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// Calculate latency stats
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var avgLatency, p95Latency, p99Latency time.Duration
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if len(latencies) > 0 {
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sort.Slice(latencies, func(i, j int) bool { return latencies[i] < latencies[j] })
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avgLatency = calculateAvgLatency(latencies)
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p95Latency = calculatePercentileLatency(latencies, 0.95)
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p99Latency = calculatePercentileLatency(latencies, 0.99)
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}
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fmt.Printf("Created %d follow list events in %v (%.2f events/sec, errors: %d)\n",
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successCount, duration, eventsPerSec, errorCount)
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fmt.Printf(" Avg latency: %v, P95: %v, P99: %v\n", avgLatency, p95Latency, p99Latency)
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// Record result for event creation phase
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result := &BenchmarkResult{
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TestName: "Graph Setup (Follow Lists)",
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Duration: duration,
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TotalEvents: int(successCount),
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EventsPerSecond: eventsPerSec,
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AvgLatency: avgLatency,
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P95Latency: p95Latency,
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P99Latency: p99Latency,
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ConcurrentWorkers: numWorkers,
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MemoryUsed: getMemUsage(),
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SuccessRate: float64(successCount) / float64(GraphBenchNumPubkeys) * 100,
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}
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g.mu.Lock()
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g.results = append(g.results, result)
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g.mu.Unlock()
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}
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// runThirdDegreeTraversal runs the third-degree graph traversal benchmark
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func (g *GraphTraversalBenchmark) runThirdDegreeTraversal() {
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fmt.Printf("\n=== Third-Degree Graph Traversal Benchmark ===\n")
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fmt.Printf("Traversing 3 degrees of follows for each of %d pubkeys...\n", GraphBenchNumPubkeys)
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start := time.Now()
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ctx := context.Background()
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var mu sync.Mutex
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var wg sync.WaitGroup
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var totalQueries int64
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var totalPubkeysFound int64
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queryLatencies := make([]time.Duration, 0, GraphBenchNumPubkeys*3)
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traversalLatencies := make([]time.Duration, 0, GraphBenchNumPubkeys)
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// Sample a subset for detailed traversal (full 100k would take too long)
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sampleSize := 1000
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if sampleSize > GraphBenchNumPubkeys {
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sampleSize = GraphBenchNumPubkeys
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}
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// Deterministic sampling
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g.initializeDeterministicRNG()
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sampleIndices := make([]int, sampleSize)
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for i := 0; i < sampleSize; i++ {
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sampleIndices[i] = int(g.rng.Uint64n(uint64(GraphBenchNumPubkeys)))
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}
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fmt.Printf("Sampling %d pubkeys for traversal...\n", sampleSize)
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numWorkers := g.config.ConcurrentWorkers
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if numWorkers < 1 {
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numWorkers = 4
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}
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workChan := make(chan int, numWorkers*2)
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for w := 0; w < numWorkers; w++ {
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wg.Add(1)
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go func() {
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defer wg.Done()
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for startIdx := range workChan {
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traversalStart := time.Now()
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foundPubkeys := make(map[string]struct{})
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// Start with the initial pubkey
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currentLevel := [][]byte{g.pubkeys[startIdx]}
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startPubkeyHex := hex.Enc(g.pubkeys[startIdx])
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foundPubkeys[startPubkeyHex] = struct{}{}
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// Traverse 3 degrees
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for depth := 0; depth < GraphBenchTraversalDepth; depth++ {
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if len(currentLevel) == 0 {
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break
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}
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nextLevel := make([][]byte, 0)
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// Query follow lists for all pubkeys at current level
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// Batch queries for efficiency
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batchSize := 100
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for batchStart := 0; batchStart < len(currentLevel); batchStart += batchSize {
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batchEnd := batchStart + batchSize
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if batchEnd > len(currentLevel) {
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batchEnd = len(currentLevel)
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}
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batch := currentLevel[batchStart:batchEnd]
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// Build filter for kind 3 events from these pubkeys
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f := filter.New()
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f.Kinds = kind.NewS(kind.FollowList)
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f.Authors = tag.NewWithCap(len(batch))
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for _, pk := range batch {
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// Authors.T expects raw byte slices (pubkeys)
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f.Authors.T = append(f.Authors.T, pk)
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}
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queryStart := time.Now()
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events, err := g.db.QueryEvents(ctx, f)
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queryLatency := time.Since(queryStart)
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mu.Lock()
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totalQueries++
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queryLatencies = append(queryLatencies, queryLatency)
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mu.Unlock()
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if err != nil {
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continue
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}
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// Extract followed pubkeys from p tags
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for _, ev := range events {
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for _, t := range *ev.Tags {
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if len(t.T) >= 2 && string(t.T[0]) == "p" {
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pubkeyHex := string(t.ValueHex())
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if _, exists := foundPubkeys[pubkeyHex]; !exists {
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foundPubkeys[pubkeyHex] = struct{}{}
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// Decode hex to bytes for next level
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if pkBytes, err := hex.Dec(pubkeyHex); err == nil {
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nextLevel = append(nextLevel, pkBytes)
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}
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}
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}
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}
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ev.Free()
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}
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}
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currentLevel = nextLevel
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}
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traversalLatency := time.Since(traversalStart)
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mu.Lock()
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totalPubkeysFound += int64(len(foundPubkeys))
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traversalLatencies = append(traversalLatencies, traversalLatency)
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mu.Unlock()
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}
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}()
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}
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// Send work
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for _, idx := range sampleIndices {
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workChan <- idx
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}
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close(workChan)
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wg.Wait()
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duration := time.Since(start)
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// Calculate statistics
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var avgQueryLatency, p95QueryLatency, p99QueryLatency time.Duration
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if len(queryLatencies) > 0 {
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sort.Slice(queryLatencies, func(i, j int) bool { return queryLatencies[i] < queryLatencies[j] })
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avgQueryLatency = calculateAvgLatency(queryLatencies)
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p95QueryLatency = calculatePercentileLatency(queryLatencies, 0.95)
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p99QueryLatency = calculatePercentileLatency(queryLatencies, 0.99)
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}
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var avgTraversalLatency, p95TraversalLatency, p99TraversalLatency time.Duration
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if len(traversalLatencies) > 0 {
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sort.Slice(traversalLatencies, func(i, j int) bool { return traversalLatencies[i] < traversalLatencies[j] })
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avgTraversalLatency = calculateAvgLatency(traversalLatencies)
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p95TraversalLatency = calculatePercentileLatency(traversalLatencies, 0.95)
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p99TraversalLatency = calculatePercentileLatency(traversalLatencies, 0.99)
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}
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avgPubkeysPerTraversal := float64(totalPubkeysFound) / float64(sampleSize)
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traversalsPerSec := float64(sampleSize) / duration.Seconds()
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queriesPerSec := float64(totalQueries) / duration.Seconds()
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fmt.Printf("\n=== Graph Traversal Results ===\n")
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fmt.Printf("Traversals completed: %d\n", sampleSize)
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fmt.Printf("Total queries: %d (%.2f queries/sec)\n", totalQueries, queriesPerSec)
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fmt.Printf("Avg pubkeys found per traversal: %.1f\n", avgPubkeysPerTraversal)
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fmt.Printf("Total duration: %v\n", duration)
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fmt.Printf("\nQuery Latencies:\n")
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fmt.Printf(" Avg: %v, P95: %v, P99: %v\n", avgQueryLatency, p95QueryLatency, p99QueryLatency)
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fmt.Printf("\nFull Traversal Latencies (3 degrees):\n")
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fmt.Printf(" Avg: %v, P95: %v, P99: %v\n", avgTraversalLatency, p95TraversalLatency, p99TraversalLatency)
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fmt.Printf("Traversals/sec: %.2f\n", traversalsPerSec)
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// Record result for traversal phase
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result := &BenchmarkResult{
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TestName: "Graph Traversal (3 Degrees)",
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Duration: duration,
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TotalEvents: int(totalQueries),
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EventsPerSecond: traversalsPerSec,
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AvgLatency: avgTraversalLatency,
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P90Latency: calculatePercentileLatency(traversalLatencies, 0.90),
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P95Latency: p95TraversalLatency,
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P99Latency: p99TraversalLatency,
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Bottom10Avg: calculateBottom10Avg(traversalLatencies),
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ConcurrentWorkers: numWorkers,
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MemoryUsed: getMemUsage(),
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SuccessRate: 100.0,
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}
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g.mu.Lock()
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g.results = append(g.results, result)
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g.mu.Unlock()
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// Also record query performance separately
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queryResult := &BenchmarkResult{
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TestName: "Graph Queries (Follow Lists)",
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Duration: duration,
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TotalEvents: int(totalQueries),
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EventsPerSecond: queriesPerSec,
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AvgLatency: avgQueryLatency,
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P90Latency: calculatePercentileLatency(queryLatencies, 0.90),
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P95Latency: p95QueryLatency,
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P99Latency: p99QueryLatency,
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Bottom10Avg: calculateBottom10Avg(queryLatencies),
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ConcurrentWorkers: numWorkers,
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MemoryUsed: getMemUsage(),
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SuccessRate: 100.0,
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}
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g.mu.Lock()
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g.results = append(g.results, queryResult)
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g.mu.Unlock()
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}
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// RunSuite runs the complete graph traversal benchmark suite
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func (g *GraphTraversalBenchmark) RunSuite() {
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fmt.Println("\n╔════════════════════════════════════════════════════════╗")
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fmt.Println("║ GRAPH TRAVERSAL BENCHMARK (100k Pubkeys) ║")
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fmt.Println("╚════════════════════════════════════════════════════════╝")
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// Step 1: Generate pubkeys
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g.generatePubkeys()
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// Step 2: Generate follow graph
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g.generateFollowGraph()
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// Step 3: Create follow list events in database
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g.createFollowListEvents()
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// Step 4: Run third-degree traversal benchmark
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g.runThirdDegreeTraversal()
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fmt.Printf("\n=== Graph Traversal Benchmark Complete ===\n\n")
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}
|
|
|
|
// GetResults returns the benchmark results
|
|
func (g *GraphTraversalBenchmark) GetResults() []*BenchmarkResult {
|
|
g.mu.RLock()
|
|
defer g.mu.RUnlock()
|
|
return g.results
|
|
}
|
|
|
|
// PrintResults prints the benchmark results
|
|
func (g *GraphTraversalBenchmark) PrintResults() {
|
|
g.mu.RLock()
|
|
defer g.mu.RUnlock()
|
|
|
|
for _, result := range g.results {
|
|
fmt.Printf("\nTest: %s\n", result.TestName)
|
|
fmt.Printf("Duration: %v\n", result.Duration)
|
|
fmt.Printf("Total Events/Queries: %d\n", result.TotalEvents)
|
|
fmt.Printf("Events/sec: %.2f\n", result.EventsPerSecond)
|
|
fmt.Printf("Success Rate: %.1f%%\n", result.SuccessRate)
|
|
fmt.Printf("Concurrent Workers: %d\n", result.ConcurrentWorkers)
|
|
fmt.Printf("Memory Used: %d MB\n", result.MemoryUsed/(1024*1024))
|
|
fmt.Printf("Avg Latency: %v\n", result.AvgLatency)
|
|
fmt.Printf("P90 Latency: %v\n", result.P90Latency)
|
|
fmt.Printf("P95 Latency: %v\n", result.P95Latency)
|
|
fmt.Printf("P99 Latency: %v\n", result.P99Latency)
|
|
fmt.Printf("Bottom 10%% Avg Latency: %v\n", result.Bottom10Avg)
|
|
}
|
|
}
|