Test Data Generation & Validation

Generate Cassandra 5.0 test data and validate parsing against sstabledump.

17|5|Updated Jul 14, 2025
One-click install
npx skills add https://github.com/pmcfadin/cqlite --skill test-data-generation-validation
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: Test Data Generation & Validation
Source: https://github.com/pmcfadin/cqlite/tree/main/.claude/skills/test-data-management
Command: npx skills add https://github.com/pmcfadin/cqlite --skill test-data-generation-validation

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Generate real Cassandra 5.0 test data using Docker containers, export SSTables with proper directory structure, validate parsing against sstabledump, and manage test datasets. Use this Skill to create reproducible test fixtures for parser validation and CI regression suites.

Core Features & Use Cases

  • End-to-end test data generation: from fresh Cassandra 5.0 instances to ready-to-export SSTables.
  • Validation workflow: compare cqlite output against sstabledump references to ensure parsing correctness.
  • Fixture management: organize datasets with metadata for repeatable tests, benchmarks, and demos.

Quick Start

Start with a clean test-data workspace and follow the documented workflow:

  • Start Cassandra 5.0 and apply schemas using the provided script.
  • Generate data with the ROWS setting and the generate.sh script.
  • Export SSTables to datasets with export.sh.
  • Shutdown and clean volumes with shutdown-clean.sh.

Frequently Asked Questions about Test Data Generation & Validation

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I generate and validate Cassandra test data in Docker?

Generate Cassandra test data by spinning up a Docker container with Cassandra 5.0, applying your schema, populating rows with generate.sh, exporting SSTables with export.sh, then validating the parsed output against sstabledump references to confirm correctness.

What's the best way to create reproducible test datasets for Cassandra parsing?

Export SSTables with preserved directory structure and metadata from Docker-based Cassandra instances, organize them as fixtures, and run automated sstabledump comparisons to ensure parsing consistency across test runs and CI regression suites.

Can I use Docker to manage Cassandra test fixtures for parser validation?

Yes. Docker containers let you start clean Cassandra 5.0 instances, generate type-correct data per schema, export SSTables with proper structure, and manage datasets with metadata for repeatable parser validation and benchmarks.

How do I export Cassandra SSTables while preserving directory structure?

Use export.sh to extract SSTables from Docker-based Cassandra 5.0 instances with their original directory layout intact, producing organized datasets and metadata needed for downstream parsing validation and test fixture reuse.

What happens when I compare cqlite output against sstabledump?

Validation workflow compares your parser's output directly against sstabledump references to detect parsing errors, ensuring generated test data correctly represents Cassandra's internal format and catches regressions early.

Do I need to manually manage Cassandra volumes for test data cleanup?

No. Use shutdown-clean.sh to automate volume teardown after exporting SSTables, eliminating manual cleanup and ensuring each test run starts with a fresh Cassandra 5.0 instance.