spark-structured-streaming
CommunityBuild robust streaming pipelines.
Software Engineering#real-time data#kafka#data pipelines#spark streaming#delta lake#structured streaming
AuthorLaurentPRAT-DB
Version1.0.0
Installs0
System Documentation
What problem does it solve?
This Skill provides comprehensive guidance and patterns for building production-ready streaming data pipelines using Spark Structured Streaming, enabling real-time data processing and analysis.
Core Features & Use Cases
- Real-time Data Ingestion: Connect to sources like Kafka and ingest data into Delta Lake.
- Stateful Operations: Implement complex logic like stream-stream joins, windowed aggregations, and deduplication.
- Production Optimization: Learn best practices for checkpointing, watermarking, and performance tuning.
- Use Case: Process clickstream data from Kafka in real-time, enrich it with user dimension data, and aggregate session activity into a Delta table for immediate dashboarding.
Quick Start
Use the spark-structured-streaming skill to build a Kafka to Delta pipeline with a 30-second trigger interval.
Dependency Matrix
Required Modules
None requiredComponents
references
💻 Claude Code Installation
Recommended: Let Claude install automatically. Simply copy and paste the text below to Claude Code.
Please help me install this Skill: Name: spark-structured-streaming Download link: https://github.com/LaurentPRAT-DB/LPT_claude_config/archive/main.zip#spark-structured-streaming Please download this .zip file, extract it, and install it in the .claude/skills/ directory.
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