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wifi-densepose/vendor/ruvector/docs/postgres/postgres-zero-copy-quick-reference.md

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PostgreSQL Zero-Copy Memory - Quick Reference

Quick Start

Import

use ruvector_postgres::types::{
    RuVector, VectorData,
    HnswSharedMem, IvfFlatSharedMem,
    ToastStrategy, estimate_compressibility,
    get_memory_stats, palloc_vector_aligned,
};

Common Operations

1. Zero-Copy Vector Access

let vec = RuVector::from_slice(&[1.0, 2.0, 3.0]);

// Get pointer (zero-copy)
unsafe {
    let ptr = vec.data_ptr();
    let dims = vec.dimensions();
}

// Get slice (zero-copy)
let slice = vec.as_slice();

// Check alignment
if vec.is_simd_aligned() {
    // Use AVX-512 operations
}

2. PostgreSQL Memory Allocation

unsafe {
    // Allocate (auto-freed at transaction end)
    let ptr = palloc_vector_aligned(1536);

    // Use ptr...

    // Optional manual free
    pfree_vector(ptr, 1536);
}

3. HNSW Shared Memory

let shmem = HnswSharedMem::new(16, 64);

// Read (concurrent-safe)
shmem.lock_shared();
let entry = shmem.entry_point.load(Ordering::Acquire);
shmem.unlock_shared();

// Write (exclusive)
if shmem.try_lock_exclusive() {
    shmem.entry_point.store(42, Ordering::Release);
    shmem.increment_version();
    shmem.unlock_exclusive();
}

4. TOAST Strategy

let data = vec![1.0; 10000];
let comp = estimate_compressibility(&data);
let strategy = ToastStrategy::for_vector(10000, comp);
// PostgreSQL applies automatically

5. Memory Monitoring

let stats = get_memory_stats();
println!("Memory: {:.2} MB", stats.current_mb());
println!("Peak: {:.2} MB", stats.peak_mb());

SQL Functions

-- Memory stats
SELECT ruvector_memory_detailed();

-- Reset peak tracking
SELECT ruvector_reset_peak_memory();

-- Vector operations
SELECT ruvector_dims(vector);
SELECT ruvector_norm(vector);
SELECT ruvector_normalize(vector);

API Reference

VectorData Trait

Method Description Zero-Copy
data_ptr() Get raw pointer ✅ Yes
data_ptr_mut() Get mutable pointer ✅ Yes
dimensions() Get dimensions ✅ Yes
as_slice() Get slice ✅ Yes (RuVector)
memory_size() Total memory size ✅ Yes
is_simd_aligned() Check alignment ✅ Yes
is_inline() Check TOAST status ✅ Yes

Memory Context

Function Purpose
palloc_vector(dims) Allocate vector
palloc_vector_aligned(dims) Allocate aligned
pfree_vector(ptr, dims) Free vector

Shared Memory - HnswSharedMem

Method Purpose
new(m, ef_construction) Create structure
lock_shared() Acquire read lock
unlock_shared() Release read lock
try_lock_exclusive() Try write lock
unlock_exclusive() Release write lock
increment_version() Increment version

TOAST Strategy

Strategy Size Range Condition
Inline < 512B Always inline
Compressed 512B-2KB comp > 0.3
External > 2KB comp ≤ 0.2
ExtendedCompressed > 8KB comp > 0.15

Memory Statistics

Method Returns
get_memory_stats() MemoryStats
stats.current_mb() Current MB
stats.peak_mb() Peak MB
stats.cache_mb() Cache MB
stats.total_mb() Total MB

Constants

const TOAST_THRESHOLD: usize = 2000;      // 2KB
const INLINE_THRESHOLD: usize = 512;      // 512B
const ALIGNMENT: usize = 64;              // AVX-512

Performance Tips

✅ DO

// Use aligned allocation
let ptr = palloc_vector_aligned(dims);

// Check alignment before SIMD
if vec.is_simd_aligned() {
    // Use aligned operations
}

// Lock properly
shmem.lock_shared();
let data = /* read */;
shmem.unlock_shared();

// Let TOAST decide
let strategy = ToastStrategy::for_vector(dims, comp);

❌ DON'T

// Don't use unaligned allocations for SIMD
let ptr = palloc_vector(dims);  // May not be aligned

// Don't read without locking
let data = shmem.entry_point.load(Ordering::Relaxed);  // Race!

// Don't force inline for large vectors
// This wastes space

// Don't forget to unlock
shmem.lock_shared();
// ... forgot to unlock_shared()!

Error Handling

// Always check dimension limits
if dims > MAX_DIMENSIONS {
    pgrx::error!("Dimension {} exceeds max", dims);
}

// Handle lock acquisition
if !shmem.try_lock_exclusive() {
    // Handle failure (retry, error, etc.)
}

// Validate data
if val.is_nan() || val.is_infinite() {
    pgrx::error!("Invalid value");
}

Common Patterns

Pattern 1: Index Search

fn search(shmem: &HnswSharedMem, query: &[f32]) -> Vec<u32> {
    shmem.lock_shared();
    let entry = shmem.entry_point.load(Ordering::Acquire);
    let results = hnsw_search(entry, query);
    shmem.unlock_shared();
    results
}

Pattern 2: Index Insert

fn insert(shmem: &HnswSharedMem, vec: &[f32]) {
    while !shmem.try_lock_exclusive() {
        std::hint::spin_loop();
    }

    let node_id = insert_node(vec);
    shmem.node_count.fetch_add(1, Ordering::Relaxed);
    shmem.increment_version();

    shmem.unlock_exclusive();
}

Pattern 3: Memory Monitoring

fn check_memory() {
    let stats = get_memory_stats();
    if stats.current_mb() > THRESHOLD {
        trigger_cleanup();
    }
}

Pattern 4: SIMD Processing

unsafe fn process(vec: &RuVector) {
    let ptr = vec.data_ptr();
    let dims = vec.dimensions();

    if vec.is_simd_aligned() {
        simd_process_aligned(ptr, dims);
    } else {
        simd_process_unaligned(ptr, dims);
    }
}

Benchmarks (Quick Reference)

Operation Performance vs. Copy-based
Vector read 2.1 ns 21.6x faster
SIMD distance 128 ns 4.0x faster
Batch scan 1.2 s 4.0x faster
Concurrent reads (100) 9,200 QPS 18.9x faster
Storage Original Compressed Savings
Sparse (10K) 40 KB 2.1 KB 94.8%
Quantized 8.2 KB 4.3 KB 47.6%
Dense 6.1 KB 6.1 KB 0%

Troubleshooting

Issue: Slow SIMD Operations

// Check alignment
if !vec.is_simd_aligned() {
    // Use palloc_vector_aligned instead
}

Issue: High Memory Usage

// Monitor and cleanup
let stats = get_memory_stats();
if stats.peak_mb() > threshold {
    // Consider increasing TOAST threshold
    // or compressing more aggressively
}

Issue: Lock Contention

// Use read locks when possible
shmem.lock_shared();  // Multiple readers OK
// vs
shmem.try_lock_exclusive();  // Only one writer

Issue: TOAST Not Compressing

// Check compressibility
let comp = estimate_compressibility(data);
if comp < 0.15 {
    // Data is not compressible
    // External storage will be used
}

SQL Examples

-- Create table
CREATE TABLE vectors (
    id SERIAL PRIMARY KEY,
    embedding ruvector(1536)
);

-- Create index (uses shared memory)
CREATE INDEX ON vectors
USING hnsw (embedding vector_l2_ops)
WITH (m = 16, ef_construction = 64);

-- Query
SELECT id FROM vectors
ORDER BY embedding <-> '[0.1, 0.2, ...]'::ruvector
LIMIT 10;

-- Monitor
SELECT ruvector_memory_detailed();

File Locations

crates/ruvector-postgres/src/types/
├── mod.rs          # Core: VectorData, memory context, TOAST
├── vector.rs       # RuVector with zero-copy
├── halfvec.rs      # HalfVec (f16)
└── sparsevec.rs    # SparseVec

docs/
├── postgres-zero-copy-memory.md           # Full documentation
├── postgres-memory-implementation-summary.md
├── postgres-zero-copy-examples.rs         # Code examples
└── postgres-zero-copy-quick-reference.md  # This file

Links

Version Info

  • Implementation Version: 1.0.0
  • PostgreSQL Compatibility: 12+
  • Rust Version: 1.70+
  • pgrx Version: 0.11+

Quick Help: For detailed information, see postgres-zero-copy-memory.md

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