Modular C++ ETL Framework

A modular C++ ETL (Extract, Transform, Load) framework designed for scalable data processing. Supports JSON input, flexible transformation pipelines, and output management, built with clear separation of layers for extensibility and integration.

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Features

• JSON input support: Seamless ingestion of JSON data with robust parsing and validation.
• Flexible transformation pipelines: Compose reusable transformation stages to build complex ETL workflows.
• Output management: Flexible sinks for writing results to files, databases, or messaging systems.
• Layered architecture: Clear separation of concerns to maximize extensibility and testability.
• Scalability: Designed for large data volumes with efficient streaming and parallelism capabilities.
• Extensibility: Easily add new data sources, transformers, and sinks with well-defined interfaces.
• Config-driven: Pipelines configured via JSON or YAML, enabling dynamic workflow changes without recompilation.
• Type safety: Modern C++ practices with strong type guarantees and compile-time checks where possible.

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Why this framework

• Reduces boilerplate for common ETL tasks by providing building blocks that can be stitched together.
• Enables clean separation between data extraction, transformation, and loading logic.
• Facilitates testing and maintenance through modular design and dependency injection-friendly patterns.
• Supports a variety of data sources and sinks with minimal coupling.

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Architecture Overview

• Source Layer: Abstractions for data input (e.g., JSON files, streams, REST endpoints).
• Transformation Layer: Pipeline stages that transform, filter, aggregate, or enrich data.
• Sink Layer: Output destinations (e.g., files, databases, queues).
• Orchestrator / Engine: Coordinates extraction, transformation, and loading, manages concurrency and error handling.
• Config & Metadata: Centralized configuration for pipelines, schemas, and runtime parameters.

[ Source ] --> [ Transform 1 ] --> [ Transform 2 ] --> ... --> [ Sink ]

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Getting Started

Prerequisites

• C++17 or newer (C++20 is supported)
• CMake (3.16+ recommended)
• JSON library (e.g., nlohmann/json or your preferred JSON parser)
• Build system capable of linking the framework

Quickstart

1. Clone the repository
2. Create a build directory and configure with CMake
3. Build and run a sample ETL job

git clone https://github.com/your-organization/etl-framework-cpp.git
cd etl-framework-cpp
mkdir build && cd build
cmake .. -DCMAKE_BUILD_TYPE=Release
make -j$(nproc)
./etl-framework-sample --config sample_pipeline.json

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Usage

• Define pipelines: Create a configuration (JSON/YAML) describing sources, transforms, and sinks.
• Extend: Implement new Source, Transform, or Sink plugins by following the provided interfaces.
• Configure parallelism: Tune thread pools, batch sizes, and backpressure to scale with data volume.
• Error handling: Customize retry policies and dead-letter queues as needed.

Example Configuration (Pseudo)

{
  "pipeline": {
    "name": "customer-analytics",
    "source": {
      "type": "json_file",
      "path": "data/input/customers.json",
      "schema": "schemas/customer_schema.json"
    },
    "transforms": [
      { "type": "filter", "condition": "record.active == true" },
      { "type": "normalize", "fields": ["name", "email"] },
      { "type": "enrich", "lookup": "customer_master" }
    ],
    "sink": {
      "type": "parquet_file",
      "path": "data/output/customers.parquet"
    }
  }
}

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Extensibility & API

• Interfaces: Abstract base classes for Source, Transform, and Sink.
• Plugins: Lightweight plugin mechanism to plug in new data sources and destinations.
• Dependency Injection: Optional DI container to manage lifetimes and dependencies.
• Testing: Unit tests and integration tests designed around isolated components and end-to-end pipelines.

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Build & Integration

• Supported platforms: Linux, macOS, Windows (where applicable)
• Dependency management: External JSON library, optional third-party plugins
• CI: CI pipelines available for builds and tests (GitHub Actions, etc.)

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Documentation

• API reference for core components
• Developer guide for creating new Sources, Transforms, and Sinks
• Tutorials and example pipelines
• Testing and debugging tips

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Contributing

We welcome contributions. Please see:

• CONTRIBUTING.md for guidelines
• CODE_OF_CONDUCT.md for community standards
• ISSUE_TEMPLATE.md and PULL_REQUEST_TEMPLATE.md for contribution process

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License

MIT License

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Contact

• Repository maintainers: your name or team
• Support: issues page

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If you’d like, I can tailor this README to your exact project layout, add a detailed API section with class diagrams, or generate a sample CMake configuration and a minimal runnable example. Just share any specifics you want included (e.g., exact module names, plugin system details, or preferred JSON library).