feat(executors): Add Java connector support to PyAirbyte

[aaronsteers]

Summary

This PR implements Java connector support for PyAirbyte by copying and enhancing the implementation from PR #719. The key addition is a dual-parameter API that provides fine-grained control over Java connector execution:

• use_java: Controls Java execution mode (None/True/False/Path to JRE)
• use_java_tar: Specifies connector TAR file location (None for auto-detect, Path for specific file)

The implementation includes automatic JRE management, connector TAR extraction, and intelligent fallback logic (Docker when available, Java when not). A complete example script demonstrates usage with source-snowflake, including Google Drive TAR download and credential handling patterns.

Core changes:

• New JavaExecutor class with automatic JRE download from Azul API
• Updated get_source() API to include both Java parameters
• Enhanced executor factory with dual-parameter fallback logic
• Created examples/run_source_snowflake_java.py demonstrating real-world usage

Review & Testing Checklist for Human

• [ ] End-to-end testing: Test the Java connector with real Snowflake credentials to verify the complete data reading flow works correctly
• [ ] JRE platform compatibility: Verify JRE download and execution works on different OS/architecture combinations (the current implementation supports Linux/macOS with x64/aarch64)
• [ ] Dual parameter logic: Test various combinations of use_java and use_java_tar parameters to ensure the interaction logic works as expected and documented
• [ ] Error handling robustness: Test failure scenarios (missing JRE, corrupted TAR files, network issues) to ensure graceful error handling
• [ ] Google Drive dependency: Verify the source-snowflake TAR file download from Google Drive still works and consider hosting alternatives for production use

Recommended test plan: Run the example script with real Snowflake test credentials, then try variations with different parameter combinations and intentional failure scenarios.

---

Diagram

%%{ init : { "theme" : "default" }}%%
graph TD
    A["airbyte/sources/util.py<br/>get_source()"]:::minor-edit --> B["airbyte/_executors/util.py<br/>get_connector_executor()"]:::minor-edit
    B --> C["airbyte/_executors/java.py<br/>JavaExecutor"]:::major-edit
    D["examples/run_source_snowflake_java.py<br/>Demo script"]:::major-edit --> A
    C --> E["JRE Download<br/>Azul API"]:::context
    C --> F["TAR Extraction<br/>~/.airbyte/connectors/"]:::context
    C --> G["Java Process<br/>Connector execution"]:::context
    
    subgraph Legend
        L1[Major Edit]:::major-edit
        L2[Minor Edit]:::minor-edit  
        L3[Context/No Edit]:::context
    end

classDef major-edit fill:#90EE90
classDef minor-edit fill:#87CEEB  
classDef context fill:#FFFFFF

Notes

• Implementation source: Based on PR #719 with enhanced dual-parameter API as requested
• Testing limitation: Successfully tested Java connector execution and TAR extraction, but full end-to-end data reading requires real Snowflake credentials
• Platform support: Currently supports Linux/macOS with x64/aarch64 architectures for JRE auto-download
• Fallback behavior: When Java is not explicitly requested, falls back to Docker if available, otherwise uses Java execution

Link to Devin run: https://app.devin.ai/sessions/e9a8bcdfcab246f0857ac38f3755296f
Requested by: @aaronsteers

Summary by CodeRabbit

• New Features

  • Run Java-based connectors with automatic JRE download/management and lifecycle handling.
  • New options to select Java execution or provide a connector tarball for sources and destinations (use_java, use_java_tar).
  • Simplified access to executors via package-level imports.

• Documentation

  • Added an example demonstrating a Java connector workflow (install, spec, check, discover, read) using a downloaded tarball and the new Java options.