Feat (AINode): Add timexl and sundial in create model (test)

[Alchuang22-dev]

Description

This PR implements support for CREATE MODEL statements in Apache IoTDB, enabling users to register and manage AI/ML models within the IoTDB ecosystem. The implementation includes model registration, lifecycle management, and integration with the AI Node component.

The PR is used for showing the changes in our code, SO PLEASE DO NOT PASS THE PR !

If you find that there are comments or output in Chinese in the code, this is just for easy testing on different machines. The release version will not include these notes.

Model Registration and Management

The implementation introduces a comprehensive model management system that allows users to register models using URI-based references. The system supports various model types including user-defined models, with built-in support for TimerXL and Sundial forecasting models. The design emphasizes flexibility by allowing external model repositories and local file system references.

Key design decisions:

• URI-based model registration: Models are registered using URIs to support both local and remote model storage, providing flexibility for different deployment scenarios
• Asynchronous model loading: Models are loaded asynchronously to prevent blocking the main database operations during potentially time-consuming model initialization
• State-based lifecycle management: Models progress through LOADING → ACTIVE → INACTIVE states with proper error handling for each transition

SQL Grammar and Parsing

The SQL grammar has been extended to support CREATE MODEL, DROP MODEL, and SHOW MODELS statements. The parser integrates seamlessly with IoTDB's existing SQL infrastructure while maintaining backward compatibility.

Design considerations:

• Consistent syntax: The CREATE MODEL syntax follows IoTDB's existing patterns (similar to CREATE TIMESERIES)
• Flexible parameter passing: Support for both URI-based and inline configuration parameters
• Error-first parsing: Comprehensive syntax validation with clear error messages

Alternative considered: We evaluated using a JSON-based configuration approach but chose the URI pattern for consistency with IoTDB's existing LOAD/REMOVE commands.

AI Node Integration

The implementation leverages IoTDB's AI Node component for actual model execution and inference. The DataNode acts as a coordinator, delegating model operations to appropriate AI Nodes while maintaining metadata consistency.

Architecture decisions:

• Separation of concerns: Model metadata management in DataNode, execution in AI Node
• Distributed model registry: Models can be deployed across multiple AI Nodes for scalability
• Fault tolerance: Graceful handling of AI Node failures with automatic retry mechanisms

Error Handling and Resource Management

The system implements comprehensive error handling for various failure scenarios including network issues, insufficient resources, and invalid model configurations.

Error handling strategies:

• Graceful degradation: System remains operational even when individual models fail to load
• Resource cleanup: Automatic cleanup of partially loaded models on failure
• User-friendly error messages: Clear error reporting for common issues like missing files or invalid URIs

---

This PR has:

• been self-reviewed.
  • concurrent read
  • concurrent write
  • concurrent read and write
• added documentation for new or modified features or behaviors.
• added Javadocs for most classes and all non-trivial methods.
• added or updated version, license, or notice information
• added comments explaining the "why" and the intent of the code wherever would not be obvious
  for an unfamiliar reader.
• added unit tests or modified existing tests to cover new code paths, ensuring the threshold
  for code coverage.
• added integration tests.
• been tested in a test IoTDB cluster.

---

Key changed/added classes (or packages if there are too many classes) in this PR

org.apache.iotdb.ainode.model.ModelLoader
org.apache.iotdb.it.ainode.CreateModelIT

[github-actions]

Hi, this is your first pull request in IoTDB project. Thanks for your contribution! IoTDB will be better because of you.