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f73bbdb510
* bals * refs * . * final QA updates * remove ref * final upds * move the daily back a bit
77 lines
3.1 KiB
Plaintext
77 lines
3.1 KiB
Plaintext
---
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description:
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globs:
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alwaysApply: true
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---
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# dbt Model Standards for Flipside Crypto
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## General Rules
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- Follow the existing code style and patterns in the codebase
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- Write clear, concise, and well-documented code
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- Use meaningful variable, function, column and model names
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- Handle errors gracefully and provide helpful error messages
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- Test your code thoroughly before submitting
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- Follow the existing project structure and conventions
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## Code Quality
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- Write self-documenting code with clear and consistent names
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- Use consistent formatting and indentation
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- Implement proper error handling and logging
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- Follow DRY (Don't Repeat Yourself) principles
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- Use meaningful commit messages
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- Use snake_case for all objects (tables, columns, models)
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- Maintain column naming consistency through the pipeline
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## dbt Model Structure
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- Models are connected through ref() and source() functions
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- Data flows from source -> bronze -> silver -> gold layers
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- Each model has upstream dependencies and downstream consumers
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- Column-level lineage is maintained through transformations
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- Parse ref() and source() calls to identify direct dependencies
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- Track column transformations from upstream models
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- Consider impact on downstream consumers
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- Preserve business logic across transformations
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## Model Naming and Organization
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- Follow naming patterns: bronze__, silver__, core__, fact_, dim__, ez__, where a double underscore indicates a break between a model schema and object name. I.e. core__fact_blocks equates to <database>.core.fact_blocks.
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- Organize by directory structure: bronze/, silver/, gold/, etc.
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- Upstream models appear on the LEFT side of the DAG
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- Current model is the focal point
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- Downstream models appear on the RIGHT side of the DAG
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## Modeling Standards
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- Use snake_case for all objects
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- Prioritize incremental processing always
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- Follow source/bronze/silver/gold layering
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- Document chain-specific assumptions
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- Include incremental predicates to improve performance
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- For gold layer models, include search optimization following Snowflake's recommended best practices
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- Cluster models on appropriate fields
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## Testing Requirements
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- Ensure proper token decimal handling
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- Implement unique tests for primary keys
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- Implement recency tests for tables that are expected to have frequent data updates
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- Add not_null tests for required columns
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- Use relationships tests for foreign keys
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## Performance Guidelines
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- Optimize for high TPS (blockchain data)
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- Handle large state change volumes efficiently
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- Index frequently queried dimensions
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- Consider partition pruning strategies
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- Implement appropriate clustering keys
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- Optimize database queries for large datasets
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- Use appropriate indexing strategies
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- Monitor resource usage and optimize accordingly
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- Consider the impact of changes on existing systems
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## Documentation
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- Document data sources
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- Map entity relationships
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- Include model descriptions in yml files per expanded rule [dbt-documentation-standards.mdc](mdc:.cursor/rules/dbt-documentation-standards.mdc)
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- Document column descriptions and business logic
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- Explain incremental logic and predicates
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- Note any data quality considerations
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