Issue: Improve Python Model Support in Incremental Materialization

[ReemaAlzaid]

Description

The current implementation of incremental materialization has limited and problematic support for Python models. This issue proposes improvements to make Python models work more seamlessly with incremental materializations.

Current Situation

• The code contains a comment describing the Python model handling as "yucky"
• There are issues with temporary views and Python models
• The current workaround uses direct SQL statements instead of adapter methods:

  {% call statement('drop_relation') -%}
    drop table if exists {{ tmp_relation }}
  {%- endcall %}

• Limited documentation on how to effectively use Python models with incremental materializations
• No clear guidance on best practices for Python models in incremental scenarios

Proposed Changes

1. Fix the issues with temporary views and Python models:

   {%- if language == 'python' -%}
     {#--
     This is yucky.
     See note in dbt-spark/dbt/include/spark/macros/adapters.sql
     re: python models and temporary views.
   
     Also, why do neither drop_relation or adapter.drop_relation work here?!
     --#}
     {% call statement('drop_relation') -%}
       drop table if exists {{ tmp_relation }}
     {%- endcall %}
   {%- endif -%}

2. Implement proper adapter methods for handling Python models:

   • Fix the issue with drop_relation not working for Python models
   • Implement a cleaner approach for temporary relations with Python models
   • Add proper error handling specific to Python models

3. Enhance the Python model integration:

   • Add support for Python-specific optimizations
   • Implement better handling of PySpark DataFrames
   • Add support for Python UDFs in incremental models

4. Improve documentation and examples:

   • Add clear documentation on how to use Python models with incremental materializations
   • Provide examples of common patterns and best practices
   • Document limitations and workarounds

Specific Areas to Improve

1. Fix the temporary view handling for Python models:

   {%- if language == 'python' -%}
     {# Implement proper handling of temporary relations for Python models #}
   {%- endif -%}

2. Add better support for PySpark operations:

   {%- if language == 'python' -%}
     {# Add support for PySpark-specific optimizations #}
   {%- endif -%}

3. Implement proper adapter methods for Python models:

   {%- if language == 'python' -%}
     {# Use proper adapter methods instead of direct SQL #}
     {% do adapter.drop_relation(tmp_relation) %}
   {%- endif -%}

Benefits

• Cleaner and more maintainable code
• Better support for Python models in incremental materializations
• Improved user experience for data scientists using Python models
• More consistent behavior between SQL and Python models
• Reduced need for workarounds and hacks

Implementation Details

1. Investigate why adapter.drop_relation doesn't work for Python models
2. Implement proper handling of temporary relations for Python models
3. Add support for PySpark-specific optimizations
4. Improve documentation and examples
5. Add tests specifically for Python models with incremental materializations