Inspect time windows

Compare the authored record shape at each window stage.

Interactive pipeline

TIME WINDOWS

Curated aggregation walkthrough

Stage1. Original High-Frequency Events2. Tumbling Window Aggregation3. Sliding Window Trends4. Session-Based Activity Clustering5. Multi-Level Configuration

Stage 1 of 5

Original High-Frequency Events

A synthetic sensor record before any window key or aggregate field is added.

0HighlightsAuthored emphasis only—not a computed diff.

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Input

 { "sensor_id": "temp_001", "temperature": 72.3, "humidity": 45.2, "timestamp": "2025-01-15T10:23:45.123Z" }

Output

 { "sensor_id": "temp_001", "temperature": 72.3, "humidity": 45.2, "timestamp": "2025-01-15T10:23:45.123Z" }

Stage configuration01-original-high-frequency-events.yaml

# No processing - just input pass-through
input:
  file:
    paths: ["sensor-data.jsonl"]

pipeline:
  processors: []  # No transformation

output:
  stdout:
    codec: lines