view-matching-literature

view-matching-literature is a Databases & SQL skill for AI agents, published by ila in the openivm repository on GitHub. Skillspace rates view-matching-literature F (52/100) and it passed the safety scan; the rating is based on static analysis only.

Deep research reference on view matching (answering queries using views, materialized-view query rewriting, subsumption-based rewriting) spanning classical PODS/SIGMOD theory, the Goldstein-Larson matcher, Calcite's implementation, commercial systems (Oracle, SQL Server, DB2, Snowflake, BigQuery, Redshift, Databricks, Firebolt, ClickHouse), adjacent result/semantic caching, and Microsoft/Google computation-reuse work. Auto-loaded when discussing view matching, query rewriting with MVs, subsumption, cache-aware optimization, or integrating a matcher into OpenIVM.

Grade
F
Quality
52 / 100
Safety
Passed
GitHub stars
24

Unproven: rated by static analysis only, not yet compared head-to-head.

This rating describes the version of the repository we crawled; it may have changed since, so go by its current files.

View source on GitHubila/openivm

Our review

Architecture
70 / 100
Maturity
Basic: a single SKILL.md
Security scan
No issues found
License
MIT
Adoption
Adopted by 0 other repositories, in 0 collections

Not checked yet

  • Not judged on the rubric yet (not a contender in its category)
  • No blind task eval yet
  • Scope (portable / vendor / repo-internal) not assessed; only the top of each category is read for scope
  • Sibling files (scripts, references) not fetched; security scan covers SKILL.md only

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