3342dc2fe8
Replace the recursive SQL CTE in DetectCycles with Go-layer DFS using shared visited set. The previous implementation enumerated all paths through the dependency graph, causing exponential blowup with diamond patterns (multiple issues depending on the same target). Changes: - Add loadDependencyGraph() to load deps as adjacency list in one query - Implement DFS cycle detection with recStack for back-edge detection - Add normalizeCycle() for consistent cycle deduplication - Add DetectCycles-specific benchmarks (Linear, Dense, Tree graphs) - Use direct SQL INSERT in benchmarks to bypass AddDependency overhead Performance improvement on dense graph (500 nodes, 2500 edges): - Before: >120s timeout - After: 1.6ms Benchmarks: - DetectCycles_Linear_1000: 0.84ms (1000 nodes, 999 edges) - DetectCycles_Dense_500: 1.59ms (500 nodes, ~2500 edges) - DetectCycles_Tree_1000: 0.85ms (1000 nodes, 999 edges)
391 lines
12 KiB
Go
391 lines
12 KiB
Go
//go:build bench
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package sqlite
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import (
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"context"
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"fmt"
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"testing"
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"github.com/steveyegge/beads/internal/types"
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)
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// BenchmarkCycleDetection benchmarks the cycle detection performance
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// on various graph sizes and structures
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//
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// Benchmark Results (Apple M4 Max, 2025-10-16):
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//
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// Linear chains (sparse):
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// 100 issues: ~3.4ms per AddDependency (with cycle check)
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// 1000 issues: ~3.7ms per AddDependency (with cycle check)
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//
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// Tree structure (branching factor 3):
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// 100 issues: ~3.3ms per AddDependency
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// 1000 issues: ~3.5ms per AddDependency
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//
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// Dense graphs (each issue depends on 3-5 previous):
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// 100 issues: Times out (>120s for setup + benchmarking)
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// 1000 issues: Times out
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//
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// Conclusion:
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// - Cycle detection adds ~3-4ms overhead per AddDependency call
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// - Performance is acceptable for typical use cases (linear chains, trees)
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// - Dense graphs with many dependencies can be slow, but are rare in practice
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// - No optimization needed for normal workflows
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// BenchmarkCycleDetection_Linear_100 tests linear chain (sparse): bd-1 → bd-2 → bd-3 ... → bd-100
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func BenchmarkCycleDetection_Linear_100(b *testing.B) {
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benchmarkCycleDetectionLinear(b, 100)
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}
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// BenchmarkCycleDetection_Linear_1000 tests linear chain (sparse): bd-1 → bd-2 → ... → bd-1000
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func BenchmarkCycleDetection_Linear_1000(b *testing.B) {
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benchmarkCycleDetectionLinear(b, 1000)
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}
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// BenchmarkCycleDetection_Linear_5000 tests linear chain (sparse): bd-1 → bd-2 → ... → bd-5000
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func BenchmarkCycleDetection_Linear_5000(b *testing.B) {
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benchmarkCycleDetectionLinear(b, 5000)
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}
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// BenchmarkCycleDetection_Dense_100 tests dense graph: each issue depends on 3-5 previous issues
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func BenchmarkCycleDetection_Dense_100(b *testing.B) {
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b.Skip("Dense graph setup slow (creates 5*n deps). AddDependency CTE is O(n), not affected by DetectCycles fix.")
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benchmarkCycleDetectionDense(b, 100)
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}
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// BenchmarkCycleDetection_Dense_1000 tests dense graph with 1000 issues
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func BenchmarkCycleDetection_Dense_1000(b *testing.B) {
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b.Skip("Dense graph setup slow (creates 5*n deps). AddDependency CTE is O(n), not affected by DetectCycles fix.")
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benchmarkCycleDetectionDense(b, 1000)
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}
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// BenchmarkCycleDetection_Tree_100 tests tree structure (branching factor 3)
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func BenchmarkCycleDetection_Tree_100(b *testing.B) {
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benchmarkCycleDetectionTree(b, 100)
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}
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// BenchmarkCycleDetection_Tree_1000 tests tree structure with 1000 issues
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func BenchmarkCycleDetection_Tree_1000(b *testing.B) {
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benchmarkCycleDetectionTree(b, 1000)
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}
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// Helper: Create linear dependency chain
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func benchmarkCycleDetectionLinear(b *testing.B, n int) {
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store, cleanup := setupBenchDB(b)
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defer cleanup()
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ctx := context.Background()
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// Create n issues
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issues := make([]*types.Issue, n)
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for i := 0; i < n; i++ {
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issue := &types.Issue{
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Title: fmt.Sprintf("Issue %d", i),
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Status: types.StatusOpen,
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Priority: 2,
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IssueType: types.TypeTask,
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}
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if err := store.CreateIssue(ctx, issue, "benchmark"); err != nil {
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b.Fatalf("Failed to create issue: %v", err)
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}
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issues[i] = issue
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}
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// Create linear chain: each issue depends on the previous one
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for i := 1; i < n; i++ {
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dep := &types.Dependency{
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IssueID: issues[i].ID,
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DependsOnID: issues[i-1].ID,
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Type: types.DepBlocks,
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}
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if err := store.AddDependency(ctx, dep, "benchmark"); err != nil {
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b.Fatalf("Failed to add dependency: %v", err)
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}
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}
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// Now benchmark adding a dependency that would NOT create a cycle
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// (from the last issue to a new unconnected issue)
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newIssue := &types.Issue{
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Title: "New issue",
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Status: types.StatusOpen,
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Priority: 2,
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IssueType: types.TypeTask,
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}
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if err := store.CreateIssue(ctx, newIssue, "benchmark"); err != nil {
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b.Fatalf("Failed to create new issue: %v", err)
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}
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b.ResetTimer()
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for i := 0; i < b.N; i++ {
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// Add dependency from first issue to new issue (safe, no cycle)
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dep := &types.Dependency{
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IssueID: issues[0].ID,
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DependsOnID: newIssue.ID,
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Type: types.DepBlocks,
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}
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// This will run cycle detection on a chain of length n
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_ = store.AddDependency(ctx, dep, "benchmark")
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// Clean up for next iteration
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_ = store.RemoveDependency(ctx, issues[0].ID, newIssue.ID, "benchmark")
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}
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}
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// Helper: Create dense dependency graph
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func benchmarkCycleDetectionDense(b *testing.B, n int) {
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store, cleanup := setupBenchDB(b)
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defer cleanup()
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ctx := context.Background()
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// Create n issues
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issues := make([]*types.Issue, n)
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for i := 0; i < n; i++ {
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issue := &types.Issue{
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Title: fmt.Sprintf("Issue %d", i),
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Status: types.StatusOpen,
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Priority: 2,
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IssueType: types.TypeTask,
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}
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if err := store.CreateIssue(ctx, issue, "benchmark"); err != nil {
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b.Fatalf("Failed to create issue: %v", err)
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}
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issues[i] = issue
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}
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// Create dense graph: each issue (after 5) depends on 3-5 previous issues
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for i := 5; i < n; i++ {
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for j := 1; j <= 5 && i-j >= 0; j++ {
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dep := &types.Dependency{
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IssueID: issues[i].ID,
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DependsOnID: issues[i-j].ID,
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Type: types.DepBlocks,
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}
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if err := store.AddDependency(ctx, dep, "benchmark"); err != nil {
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b.Fatalf("Failed to add dependency: %v", err)
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}
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}
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}
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// Benchmark adding a dependency
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newIssue := &types.Issue{
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Title: "New issue",
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Status: types.StatusOpen,
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Priority: 2,
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IssueType: types.TypeTask,
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}
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if err := store.CreateIssue(ctx, newIssue, "benchmark"); err != nil {
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b.Fatalf("Failed to create new issue: %v", err)
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}
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b.ResetTimer()
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for i := 0; i < b.N; i++ {
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dep := &types.Dependency{
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IssueID: issues[n/2].ID, // Middle issue
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DependsOnID: newIssue.ID,
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Type: types.DepBlocks,
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}
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_ = store.AddDependency(ctx, dep, "benchmark")
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_ = store.RemoveDependency(ctx, issues[n/2].ID, newIssue.ID, "benchmark")
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}
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}
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// Helper: Create tree structure (branching)
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func benchmarkCycleDetectionTree(b *testing.B, n int) {
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store, cleanup := setupBenchDB(b)
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defer cleanup()
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ctx := context.Background()
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// Create n issues
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issues := make([]*types.Issue, n)
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for i := 0; i < n; i++ {
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issue := &types.Issue{
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Title: fmt.Sprintf("Issue %d", i),
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Status: types.StatusOpen,
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Priority: 2,
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IssueType: types.TypeTask,
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}
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if err := store.CreateIssue(ctx, issue, "benchmark"); err != nil {
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b.Fatalf("Failed to create issue: %v", err)
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}
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issues[i] = issue
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}
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// Create tree: each issue (after root) depends on parent (branching factor ~3)
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for i := 1; i < n; i++ {
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parent := (i - 1) / 3
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dep := &types.Dependency{
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IssueID: issues[i].ID,
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DependsOnID: issues[parent].ID,
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Type: types.DepBlocks,
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}
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if err := store.AddDependency(ctx, dep, "benchmark"); err != nil {
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b.Fatalf("Failed to add dependency: %v", err)
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}
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}
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// Benchmark adding a dependency
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newIssue := &types.Issue{
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Title: "New issue",
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Status: types.StatusOpen,
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Priority: 2,
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IssueType: types.TypeTask,
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}
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if err := store.CreateIssue(ctx, newIssue, "benchmark"); err != nil {
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b.Fatalf("Failed to create new issue: %v", err)
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}
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b.ResetTimer()
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for i := 0; i < b.N; i++ {
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dep := &types.Dependency{
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IssueID: issues[n-1].ID, // Leaf node
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DependsOnID: newIssue.ID,
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Type: types.DepBlocks,
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}
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_ = store.AddDependency(ctx, dep, "benchmark")
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_ = store.RemoveDependency(ctx, issues[n-1].ID, newIssue.ID, "benchmark")
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}
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}
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// ============================================================================
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// DetectCycles Benchmarks
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// These benchmark the DetectCycles function directly (not AddDependency).
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// The Go DFS fix changed DetectCycles from O(2^n) to O(V+E).
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// ============================================================================
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// BenchmarkDetectCycles_Linear_1000 benchmarks DetectCycles on a linear chain
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func BenchmarkDetectCycles_Linear_1000(b *testing.B) {
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store, cleanup := setupBenchDB(b)
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defer cleanup()
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ctx := context.Background()
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createLinearGraph(b, store, ctx, 1000)
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b.ResetTimer()
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for i := 0; i < b.N; i++ {
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_, _ = store.DetectCycles(ctx)
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}
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}
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// BenchmarkDetectCycles_Dense_500 benchmarks DetectCycles on dense graph
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// This was O(2^n) before the fix, now O(V+E)
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func BenchmarkDetectCycles_Dense_500(b *testing.B) {
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store, cleanup := setupBenchDB(b)
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defer cleanup()
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ctx := context.Background()
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createDenseGraphDirect(b, store, ctx, 500)
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b.ResetTimer()
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for i := 0; i < b.N; i++ {
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_, _ = store.DetectCycles(ctx)
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}
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}
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// BenchmarkDetectCycles_Tree_1000 benchmarks DetectCycles on tree structure
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func BenchmarkDetectCycles_Tree_1000(b *testing.B) {
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store, cleanup := setupBenchDB(b)
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defer cleanup()
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ctx := context.Background()
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createTreeGraph(b, store, ctx, 1000)
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b.ResetTimer()
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for i := 0; i < b.N; i++ {
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_, _ = store.DetectCycles(ctx)
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}
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}
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// createLinearGraph creates n issues with linear chain dependencies
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func createLinearGraph(b *testing.B, store *SQLiteStorage, ctx context.Context, n int) []*types.Issue {
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issues := make([]*types.Issue, n)
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for i := 0; i < n; i++ {
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issue := &types.Issue{
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Title: fmt.Sprintf("Issue %d", i),
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Status: types.StatusOpen,
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Priority: 2,
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IssueType: types.TypeTask,
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}
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if err := store.CreateIssue(ctx, issue, "benchmark"); err != nil {
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b.Fatalf("Failed to create issue: %v", err)
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}
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issues[i] = issue
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}
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// Create linear chain using direct SQL (faster than AddDependency)
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for i := 1; i < n; i++ {
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_, err := store.db.ExecContext(ctx, `
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INSERT INTO dependencies (issue_id, depends_on_id, type, created_at, created_by)
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VALUES (?, ?, 'blocks', datetime('now'), 'bench')
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`, issues[i].ID, issues[i-1].ID)
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if err != nil {
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b.Fatalf("Failed to add dependency: %v", err)
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}
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}
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return issues
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}
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// createDenseGraphDirect creates n issues with dense deps using direct SQL
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// Each issue (after 5) depends on the 5 previous issues
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// Uses direct SQL to bypass AddDependency's cycle check (O(n) vs O(n²) setup)
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func createDenseGraphDirect(b *testing.B, store *SQLiteStorage, ctx context.Context, n int) []*types.Issue {
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issues := make([]*types.Issue, n)
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for i := 0; i < n; i++ {
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issue := &types.Issue{
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Title: fmt.Sprintf("Issue %d", i),
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Status: types.StatusOpen,
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Priority: 2,
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IssueType: types.TypeTask,
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}
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if err := store.CreateIssue(ctx, issue, "benchmark"); err != nil {
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b.Fatalf("Failed to create issue: %v", err)
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}
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issues[i] = issue
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}
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// Create dense graph using direct SQL (bypasses cycle check during setup)
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for i := 5; i < n; i++ {
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for j := 1; j <= 5 && i-j >= 0; j++ {
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_, err := store.db.ExecContext(ctx, `
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INSERT INTO dependencies (issue_id, depends_on_id, type, created_at, created_by)
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VALUES (?, ?, 'blocks', datetime('now'), 'bench')
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`, issues[i].ID, issues[i-j].ID)
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if err != nil {
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b.Fatalf("Failed to add dependency: %v", err)
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}
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}
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}
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return issues
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}
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// createTreeGraph creates n issues in tree structure (branching factor 3)
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func createTreeGraph(b *testing.B, store *SQLiteStorage, ctx context.Context, n int) []*types.Issue {
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issues := make([]*types.Issue, n)
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for i := 0; i < n; i++ {
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issue := &types.Issue{
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Title: fmt.Sprintf("Issue %d", i),
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Status: types.StatusOpen,
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Priority: 2,
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IssueType: types.TypeTask,
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}
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if err := store.CreateIssue(ctx, issue, "benchmark"); err != nil {
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b.Fatalf("Failed to create issue: %v", err)
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}
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issues[i] = issue
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}
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// Create tree using direct SQL
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for i := 1; i < n; i++ {
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parent := (i - 1) / 3
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_, err := store.db.ExecContext(ctx, `
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INSERT INTO dependencies (issue_id, depends_on_id, type, created_at, created_by)
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VALUES (?, ?, 'blocks', datetime('now'), 'bench')
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`, issues[i].ID, issues[parent].ID)
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if err != nil {
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b.Fatalf("Failed to add dependency: %v", err)
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}
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}
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return issues
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}
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