CQL Type System & Schema Handling

Deserialize Cassandra CQL types using schema-provided information.

17|5|Updated Jul 14, 2025

Search Tags:#schema #cql #collection #deserialization #udt #type-system #frozen

Ready to run

npx skills add https://github.com/pmcfadin/cqlite --skill cql-type-system-schema-handling

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: CQL Type System & Schema Handling
Source: https://github.com/pmcfadin/cqlite/tree/main/.claude/skills/cql-type-system
Command: npx skills add https://github.com/pmcfadin/cqlite --skill cql-type-system-schema-handling

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Provide a robust, schema-driven foundation for deserializing all Cassandra CQL types (primitives, collections, UDTs, tuples), including frozen versus non-frozen semantics and proper null handling.

Core Features & Use Cases

Schema-provided deserialization for primitive, collection, and complex types.
Support for lists, sets, maps, tuples, UDTs, and frozen types.
Strong schema validation and type-safe data generation.

Quick Start

Supply a CQL schema file and a sample data row, then deserialize values using the schema-provided types. Use the parser to validate support for new types and CI test data.

Frequently Asked Questions about CQL Type System & Schema Handling

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

FAQPage Schema

How do I deserialize CQL types correctly from raw Cassandra data?▼

Schema-driven CQL deserialization interprets raw data using type information from your schema to correctly parse primitive types, collections, UDTs, and tuples. This ensures type-safe data generation across simple and nested contexts, handling both frozen and non-frozen variants with proper null semantics.

What's the difference between frozen and non-frozen collections in CQL schemas?▼

Frozen types are immutable and stored as binary blobs, while non-frozen types allow updates to individual elements. Deserialization must parse them differently: frozen types skip element-level parsing, whereas non-frozen collections require length-prefix parsing for each element.

Can I deserialize nested UDTs and complex collection types?▼

Yes. CQL deserialization supports nested user-defined types within collections and tuples, plus maps with complex value types. Schema validation ensures correct interpretation of all nesting levels through recursive type resolution and proper length-prefix handling.

How do I validate that my CQL schema supports a particular data type?▼

Supply your CQL schema file and use the parser to validate type support before processing rows. Schema validation checks primitive, collection, tuple, and UDT definitions against your data, catching unsupported types early in CI test data workflows.

What deserialization patterns does this support for production use?▼

Zero-copy and length-prefix deserialization patterns are built in, supporting both schema statistics and system table sources. This enables efficient production deserialization across Cassandra clusters without data copying overhead.