Pipeline Specifications

Technical specifications and requirements for building production-ready data pipelines.

Pipeline Types

ETL (Extract, Transform, Load)

• Data is extracted from source
• Transformed in the pipeline
• Loaded into destination
• Best for: Complex transformations, data cleansing

ELT (Extract, Load, Transform)

• Data is extracted from source
• Loaded into destination as-is
• Transformed in the destination system
• Best for: Cloud data warehouses, simple transformations

Reverse ETL

• Data flows from warehouse back to operational systems
• Syncs analytical insights to business tools
• Best for: Customer data activation, operational analytics

Streaming

• Real-time or near-real-time data processing
• Continuous data flow
• Best for: Event data, monitoring, real-time analytics

CDC (Change Data Capture)

• Captures only changed data from source
• Maintains data freshness with minimal load
• Best for: Database replication, incremental updates

Required Components

1. Pipeline Metadata

{
  "$schema": "https://registry.514.ai/schemas/pipeline.json",
  "name": "Google Analytics to ClickHouse",
  "identifier": "google-analytics-to-clickhouse",
  "description": "Sync Google Analytics data to ClickHouse for analysis",
  "type": "elt",
  "schedule": {
    "cron": "0 */6 * * *",
    "timezone": "UTC"
  }
}

2. Source Configuration

{
  "source": {
    "connector": {
      "name": "google-analytics",
      "version": "v4",
      "author": "514-labs",
      "language": "typescript",
      "implementation": "default"
    },
    "config": {
      "propertyId": "{{GA_PROPERTY_ID}}",
      "startDate": "30daysAgo",
      "dimensions": ["date", "country", "deviceCategory"],
      "metrics": ["sessions", "users", "pageviews"]
    }
  }
}

3. Transformation Rules

{
  "transformations": [
    {
      "type": "rename",
      "field": "ga:date",
      "to": "event_date"
    },
    {
      "type": "cast",
      "field": "sessions",
      "to": "UInt32"
    },
    {
      "type": "derive",
      "field": "bounce_rate",
      "expression": "bounces / sessions"
    }
  ]
}

4. Destination Configuration

{
  "destination": {
    "system": "clickhouse",
    "config": {
      "host": "{{CLICKHOUSE_HOST}}",
      "database": "analytics",
      "table": "ga_events",
      "engine": "MergeTree()",
      "orderBy": ["event_date", "country"]
    }
  }
}

5. Schema Definitions

• Source schema (from connector)
• Transformation schema
• Destination schema
• Lineage manifest

6. Error Handling

• Retry logic with exponential backoff
• Dead letter queues for failed records
• Alerting on failures
• Data quality checks

7. Monitoring & Observability

• Execution logs
• Performance metrics
• Data volume tracking
• Lineage visualization

Best Practices

Performance

• Batch data appropriately
• Use incremental loads where possible
• Implement proper indexing
• Monitor memory usage

Reliability

• Make transformations idempotent
• Handle schema evolution
• Implement checkpointing
• Test failure scenarios

Security

• Encrypt data in transit
• Mask sensitive fields
• Use secure credential storage
• Implement access controls

Testing Requirements

• Unit tests for transformations
• Integration tests with sample data
• Schema validation tests
• Performance benchmarks
• End-to-end pipeline tests