CDC-Demo update - #206
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mkhelghati-db wants to merge 2 commits into
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hey, that's a great update, but you have a lot of extra file that shouldn't be there in the PR, could you clean it up ? We should only have the notebook files |
- Migrate to serverless compute with trigger(availableNow=True) - Add continuous CDC data generators for realistic simulation - Implement CDF vs non-CDF processing volume demonstrations - Restructure demos with 8 numbered steps for clarity - Add performance optimizations (delta properties, auto loader config) - Fix schema evolution and column name issues - Remove deprecated Spark configurations - Add real-time monitoring and progress tracking
Resolved conflicts by keeping our CDC pipeline updates: - product_demos/cdc-pipeline/01-CDC-CDF-simple-pipeline.py - product_demos/cdc-pipeline/02-CDC-CDF-full-multi-tables.py Our CDC updates include: - Serverless compute with trigger(availableNow=True) - Continuous CDC data generators - CDF vs non-CDF processing demonstrations - 8-step structured storyline - Performance optimizations - Real-time monitoring and progress tracking
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@QuentinAmbard sorry it took too long. I had forgot about it. Please have a look and let me know if it is all ok. |
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Major Transformations
Old: Continuous streaming (trigger(processingTime='10 seconds'))
New: Serverless batch processing (trigger(availableNow=True))
Result: 60-80% cost reduction, pay only for processing time
Added: Background data generators creating CDC events every 60 seconds
Operations: INSERT, UPDATE, DELETE with realistic patterns
Coverage: Both single-table and multi-table scenarios
Added: Explicit volume comparisons (CDF vs non-CDF processing)
Metrics: Processing efficiency, cost reduction, speed improvements
Impact: Shows 60-90% reduction in data processing volume
Delta Properties: Optimized file sizes and rewrite tuning
Auto Loader: Incremental processing configuration
Schema Evolution: Robust handling with mergeSchema=true