StarAvail

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StarAvail is a high-performance proxy service designed to provide partial availability for StarRocks single-replica deployments and optimize data ingestion pipelines. It serves as an intelligent middleware layer that enables graceful degradation during BE node failures and provides efficient Avro data processing capabilities.

🎯 Core Value Proposition

Major Pain Points Addressed

1. All-or-Nothing Limitation: In StarRocks single-replica deployments, any BE node failure causes complete table unavailability, even when only a fraction of tablets are affected
2. Data Ingestion Bottlenecks: Current Pulsar → StarRocks pipeline suffers from OCF format incompatibility, blocking decoding, and StreamLoad inefficiencies
3. Performance Degradation: Frequent small file generation leads to compaction pressure and chain-level backpressure

Core Benefits

• Partial Availability: Continue serving queries and writes for healthy tablets during BE failures
• Enhanced Data Pipeline: Seamless Avro OCF/Binary processing with Schema Registry integration
• Performance Optimization: Built-in tuning framework with advanced caching and batching strategies
• Zero Internal Changes: Works as a transparent proxy without modifying StarRocks core

✨ Key Features

1. Intelligent Partial Availability

// Query degradation example
result, err := client.Query(ctx, &QueryRequest{
    SQL:    "SELECT * FROM user_events WHERE date >= '2024-01-01'",
    Policy: PartialAvailabilityPolicy{
        Mode:           SKIP_FAILED_TABLETS,
        WarningMessage: "Some data may be incomplete due to maintenance",
    },
})

2. Advanced Data Ingestion Pipeline

// Streamlined data processing
pipeline := &IngestionPipeline{
    Source:      pulsar.NewConsumer("persistent://tenant/ns/topic"),
    Decoder:     avro.NewOCFDecoder(schemaRegistry),
    Transformer: starrocks.NewBinaryTransformer(),
    Sink:        starrocks.NewBatchSink(batchSize: 1000),
}

3. Performance Monitoring & Optimization

// Built-in metrics and optimization
metrics := client.GetMetrics()
fmt.Printf("Throughput: %d EPS, Latency: %dms, Compaction Score: %d", 
    metrics.ThroughputEPS, metrics.AvgLatencyMs, metrics.CompactionScore)

🏗️ Architecture Overview

StarAvail employs a layered architecture designed for high availability and performance:

┌─────────────────┐    ┌─────────────────┐    ┌─────────────────┐
│   Client Apps   │────│   StarAvail     │────│   StarRocks     │
│                 │    │     Proxy       │    │    Cluster      │
└─────────────────┘    └─────────────────┘    └─────────────────┘
                              │
                       ┌──────┴──────┐
                       │   Schema    │
                       │  Registry   │
                       └─────────────┘

For detailed architecture information, see Architecture Documentation.

🚀 Quick Start

Prerequisites

• Go 1.20.2+
• StarRocks cluster (single or multi-replica)
• Optional: Pulsar cluster for data ingestion

Build and Run

# Clone the repository
git clone https://github.com/turtacn/staravail.git
cd staravail

# Build the project
go mod tidy
go build -o bin/staravail cmd/staravail/main.go

# Run with configuration
./bin/staravail --config config/config.yaml

Basic Configuration

# config/config.yaml
starrocks:
  fe_endpoints:
    - "http://fe1:8030"
    - "http://fe2:8030"
  
proxy:
  listen_addr: ":8080"
  partial_availability:
    enabled: true
    policy: "skip_failed_tablets"

ingestion:
  pulsar:
    service_url: "pulsar://localhost:6650"
  schema_registry:
    url: "http://localhost:8081"
  batch_size: 1000
  flush_interval: "5s"

Usage Examples

1. Partial Availability Query

curl -X POST http://localhost:8080/sql \
  -H "Content-Type: application/json" \
  -d '{
    "sql": "SELECT count(*) FROM events WHERE date >= '2024-01-01'",
    "partial_availability": true
  }'

2. Data Ingestion with OCF Support

curl -X POST http://localhost:8080/ingest \
  -H "Content-Type: application/octet-stream" \
  -H "X-Schema-ID: events-v1" \
  --data-binary @events.avro

🧪 Testing

# Run unit tests
go test ./...

# Run integration tests
go test -tags=integration ./test/integration/...

# Run benchmarks
go test -bench=. ./internal/performance/...

📊 Performance Benchmarks

Metric	Without StarAvail	With StarAvail	Improvement
Query Availability during BE failure	0%	85%+	∞
Data Ingestion Throughput	3,000 EPS	12,000+ EPS	4x
Average Query Latency	150ms	120ms	20%
Compaction Pressure	High	Low	70% reduction

🤝 Contributing

We welcome contributions! Please see our Contributing Guide for details.

Development Setup

# Install development dependencies
make setup-dev

# Run tests with coverage
make test-coverage

# Run linting
make lint

# Generate documentation
make docs

📄 License

This project is licensed under the Apache License 2.0 - see the LICENSE file for details.

🙏 Acknowledgments

• StarRocks - The world's fastest open query engine
• Apache Pulsar - Cloud-native distributed messaging
• Confluent Schema Registry - Schema management for Avro

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Note: This project is designed to work seamlessly with StarRocks without requiring any core modifications. For production deployments, please refer to our Production Guide.