Skip to main content

Aggregate Time Windows

Transform high-frequency event streams into meaningful analytics by grouping data into time buckets.

The Problem​

IoT devices and sensors generate continuous high-frequency events:

  • 60 events/minute per sensor creates overwhelming data volume
  • Raw streams generate 98% redundant data
  • No actionable insights from individual readings
  • Expensive cloud ingestion and storage costs

The Solution​

Learn 5 time-windowed aggregation techniques:

  1. Tumbling Windows - Fixed-size, non-overlapping buckets with timestamp rounding
  2. Sliding Windows - Overlapping windows for smoothed moving averages and trending
  3. Session Windows - Dynamic windows based on activity gaps for behavioral analytics
  4. Multi-Level Aggregation - Simultaneous aggregation at sensor, location, and global levels
  5. Production Buffering - Memory management, late arrivals, and network outage handling

Get Started​

Choose your path:

Interactive Explorer​

See each windowing technique with side-by-side before/after views

Step-by-Step Tutorial​

Build the pipeline incrementally:

  1. Tumbling Windows
  2. Sliding Windows
  3. Session Windows
  4. Multi-Level Aggregation
  5. Production Optimization

Complete Pipeline​

Download the production-ready solution