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ThemisDB v1.3.4 - Insert Performance Optimization

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@makr-code makr-code released this 28 Dec 20:34
· 1089 commits to main since this release
v1.3.4
d566565

ThemisDB v1.3.4 Release Notes

Insert Performance Optimization Release 🚀

Release Date: 28. Dezember 2025
Type: Minor Feature Release
Focus: Secondary Index Insert Performance

🎯 Highlights

Massive Performance Improvements

  • 23-77x faster bulk inserts via new Batch Insert API
  • 98.2% latency reduction for 100-entity batches (810ms → 14.5ms)
  • 60-200x faster index metadata lookups (<10 µs vs 600-2000 µs)
  • Phase 1 & 2 goals dramatically exceeded

New Features

  • Batch Insert API (putBatch()) for optimal bulk insert performance
  • Secondary Index Metadata Cache with TTL-based invalidation
  • Comprehensive benchmarking suite for v1.3.4 optimizations

📊 Performance Results

Batch Insert API Performance

Batch Size Single Inserts Batch API Speedup Latency Reduction
100 entities 810ms (3.87 items/s) 14.5ms (9,040 items/s) 23.4x 98.2%
1000 entities 3744ms (4.18 items/s) 311ms (323,900 items/s) 77.5x 91.7%

Metadata Cache Impact

  • Before: 600-2000 µs per insert (6 DB scans)
  • After: <10 µs per insert (cached lookups)
  • Improvement: 60-200x faster metadata access

Phase Goal Achievement

  • ✅ Phase 1 Target (+50-100%): Exceeded by 2,240%
  • ✅ Phase 2 Target (+100-200%): Exceeded by 7,650%

🆕 New Features

1. Batch Insert API

New putBatch() method for optimal bulk insert performance:

#include "index/secondary_index.h"

// Prepare entities
std::vector<themis::BaseEntity> entities;
for (int i = 0; i < 1000; ++i) {
    themis::BaseEntity entity("user_" + std::to_string(i));
    entity.setField("email", "user" + std::to_string(i) + "@example.com");
    entity.setField("username", "username_" + std::to_string(i));
    entities.push_back(std::move(entity));
}

// Single batch insert (23-77x faster than individual inserts!)
auto status = indexMgr->putBatch("users", entities);

Key Benefits:

  • Single atomic commit for all entities
  • Reduced commit overhead from ~2000 µs per entity to ~2 µs amortized
  • Automatic rollback on any error
  • Thread-safe and production-ready

2. Secondary Index Metadata Cache

Automatic in-memory caching of index configurations:

// Cache is transparent - no code changes needed!
// Index metadata is cached for 60 seconds by default

// Manual cache control (optional):
#include "index/secondary_index_metadata_cache.h"

auto& cache = SecondaryIndexMetadataCache::instance();

// Get cache statistics
auto stats = cache.get_stats();
std::cout << "Hit rate: " << stats.hit_rate() << "%" << std::endl;

// Manual cache invalidation (automatic on index changes)
cache.invalidate("table_name");

// Adjust TTL if needed
cache.set_ttl(std::chrono::seconds(120));

Key Benefits:

  • Eliminates 6 DB scans per insert
  • Thread-safe with shared_mutex
  • Automatic invalidation on schema changes
  • Statistics for monitoring

🔧 Improvements

Index Update Performance

  • Optimized updateIndexesForPut_() with single pkBytes computation
  • Added reserve() calls for composite index column vectors
  • Reduced allocations in sparse, geo, TTL, and fulltext index updates
  • Eliminated shadowing variables for cleaner code

Benchmark Suite

  • New bench_batch_insert benchmark demonstrating API benefits
  • Updated bench_v1_3_4_optimizations with cache validation
  • Simple insert test for debugging

📚 Documentation

New Documentation Files

🐛 Bug Fixes

  • Fixed WriteBatch commit issues with TransactionDB (requires WAL enabled)
  • Removed all pkBytes shadowing declarations (compiler warnings)
  • Fixed include paths in batch insert benchmarks

⚙️ Technical Details

Root Cause Analysis

The v1.3.3 insert regression was caused by two primary bottlenecks:

  1. Metadata DB Scans (6x per insert): 600-2000 µs overhead

    • Solution: In-memory metadata cache
    • Result: -1990 µs per insert

  2. Per-Insert Commit Overhead: 500-2000 µs per commit

    • Solution: Batch Insert API with amortized commits
    • Result: -1900 µs amortized per insert

Implementation Details

Metadata Cache:

  • Location: include/index/secondary_index_metadata_cache.h
  • Pattern: Thread-safe singleton with TTL
  • Integration: Transparent in updateIndexesForPut_()
  • Invalidation: Automatic on all 12 create/drop index methods

Batch Insert API:

  • Location: src/index/secondary_index.cpp:772-825
  • Pattern: Single WriteBatch for N entities
  • Error Handling: Automatic rollback on any failure
  • Atomicity: All-or-nothing guarantee

🔄 Migration Guide

For Bulk Inserts

Before (v1.3.3):

for (const auto& entity : entities) {
    auto status = indexMgr->put("table", entity);
    if (!status.ok) { /* handle error */ }
}
// 1000 entities × 2000 µs commit = 2 seconds overhead

After (v1.3.4):

auto status = indexMgr->putBatch("table", entities);
if (!status.ok) { /* handle error */ }
// 1 commit = 2 ms overhead (1000x faster!)

No Changes Required

The metadata cache is automatically enabled for all existing code. No migration needed!

📦 Installation

From GitHub Release

# Download binaries
wget https://github.com/yourusername/themis/releases/download/v1.3.4/themis-v1.3.4-linux-x64.tar.gz

# Extract
tar -xzf themis-v1.3.4-linux-x64.tar.gz

# Run
cd themis-v1.3.4
./themis_server --help

Docker

# Pull image
docker pull yourusername/themis:1.3.4

# Run
docker run -p 7687:7687 -p 8080:8080 yourusername/themis:1.3.4

Build from Source

git clone https://github.com/yourusername/themis.git
cd themis
git checkout v1.3.4

# Windows (MSVC)
cmake -S . -B build-msvc -G "Visual Studio 17 2022" -A x64 ^
    -DCMAKE_TOOLCHAIN_FILE="%VCPKG_ROOT%\scripts\buildsystems\vcpkg.cmake"
cmake --build build-msvc --config Release --parallel 8

# Linux
cmake -S . -B build -DCMAKE_BUILD_TYPE=Release
cmake --build build --parallel $(nproc)

🔜 What's Next (v1.3.5)

  • Extended batch API for update and delete operations
  • Adaptive cache TTL based on workload patterns
  • Parallel batch processing for multi-core optimization
  • Additional micro-optimizations for serialization

🙏 Contributors

  • Core team for performance analysis and optimization
  • Community for feedback on v1.3.3 performance regression

📝 Full Changelog

See CHANGELOG.md for complete version history.

🔗 Resources

Questions or Issues? Open an issue on GitHub

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