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window-functions-deep-dive

Community

Master OPAL window functions for precise metrics.

Data & Analytics#time-series#lag#moving-averages#window-functions#OPAL#rank
Authorrustomax
Version1.0.0
Installs0

System Documentation

What problem does it solve?

This Skill teaches you to apply OPAL window functions to perform row-relative calculations on time-series data, enabling precise comparisons, rankings, and moving metrics without relying on the SQL OVER clause.

Core Features & Use Cases

  • Lag/Lead: compare current rows to previous or next ones within partitions.
  • Ranking: assign row_number(), rank(), and dense_rank() within groups for fair leaderboards.
  • Moving Aggregates: compute time-based averages, sums, and counts with frame(back: duration).
  • First/Last: retrieve boundary values within a partition or sliding window.
  • Guidance: uses the window() wrapper to avoid SQL OVER syntax and optimize performance.

Quick Start

Example: run a simple windowed analysis aligning to 5-minute buckets and compute a 30-minute moving average per service.

Dependency Matrix

Required Modules

None required

Components

Standard package

💻 Claude Code Installation

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Please help me install this Skill:
Name: window-functions-deep-dive
Download link: https://github.com/rustomax/observe-community-mcp/archive/main.zip#window-functions-deep-dive

Please download this .zip file, extract it, and install it in the .claude/skills/ directory.
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