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Stream Processing Windowing Designer

// Designs optimal windowing strategies for stream processing

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stars:384
forks:73
updated:March 4, 2026
SKILL.mdreadonly
SKILL.md Frontmatter
nameStream Processing Windowing Designer
descriptionDesigns optimal windowing strategies for stream processing
version1.0.0
categoryStreaming
skillIdSK-DEA-018
allowed-toolsRead,Write,Edit,Glob,Grep,Bash

Stream Processing Windowing Designer

Overview

Designs optimal windowing strategies for stream processing. This skill provides expertise in window types, watermarks, and trigger strategies for streaming applications.

Capabilities

  • Window type selection (tumbling, sliding, session, global)
  • Watermark strategy design
  • Late data handling
  • Trigger configuration
  • Window aggregation optimization
  • State management recommendations
  • Exactly-once semantics configuration

Input Schema

{
  "useCase": "string",
  "eventTimeField": "string",
  "latencyRequirements": {
    "maxLatencyMs": "number",
    "allowedLateMs": "number"
  },
  "aggregations": ["object"]
}

Output Schema

{
  "windowConfig": {
    "type": "string",
    "size": "string",
    "slide": "string"
  },
  "watermarkConfig": "object",
  "triggerConfig": "object",
  "lateDataHandling": "object"
}

Target Processes

  • Streaming Pipeline
  • Feature Store Setup

Usage Guidelines

  1. Define use case and event time field
  2. Specify latency requirements
  3. List aggregation operations needed
  4. Consider late data arrival patterns

Best Practices

  • Choose window type based on business requirements
  • Configure watermarks based on expected lateness
  • Use appropriate triggers for latency vs completeness tradeoff
  • Plan state management for long windows
  • Test with realistic event time distributions