Agent skill · data analytics · aiskillstore
datafusion-query-advisor
Reviews SQL queries and DataFrame operations for optimization opportunities including predicate pushdown, partition pruning, column projection, and join ordering. Activates when users write DataFusion queries or experience slow query performance.
Why this skill is useful
Provides specific optimization patterns and suggestions for DataFusion SQL queries that the AI wouldn't reliably generate on its own.
What it needs
About 6k tokens when loaded. Last updated 2026-08-07. 405 stars on the source repository.
What this skill does
DataFusion Query Advisor Skill You are an expert at optimizing DataFusion SQL queries and DataFrame operations. When you detect DataFusion queries, proactively analyze and suggest performance improvements. When to Activate Activate this skill when you notice: SQL queries using ctx.sql(...) or DataFrame API Discussion about slow DataFusion query performance Code registering tables or data sources Questions about query optimization or EXPLAIN plans Mentions of partition pruning, predicate pushdown, or column projection Query Optimization Checklist 1. Predicate Pushdown What to Look For: WHERE clauses that can be pushed to storage layer Filters applied after data is loaded Good Pattern: Bad Pattern: Suggestion: 2. Partition Pruning What to Look For: Queries on partitioned tables without partition filters Filters on non-partition columns only Good Pattern: Bad Pattern: Suggestion: 3. Column Projection What to Look For: SELECT on wide tables Reading more columns than needed Good Pattern: Bad Pattern: Suggestion: 4. Join Optimization What to Look For: Large table joined to small table (wrong order) Multiple joins without understanding order Missing EXPLAIN analysis Good Pattern: Optimization Principles: DataFusion automatically optimizes join order, but verify with EXPLAIN For multi-way joins, filter early and join late Use broadcast joins for small tables (<100MB) Suggestion: 5. Aggregation Performance What to Look For: GROUP BY on high-cardinality columns Aggregations without filters Missing LIMIT on exploratory queries Good Pattern: Suggestion: 6. Window Functions What to Look For: Window functions on large partitions Missing PARTITION BY or ORDER BY optimization Good Pattern: Suggestion: Configuration Optimization 1. Parallelism What to Look For: Default parallelism on large queries Missing .withtargetpartitions() configuration Suggestion: 2. Memory Management What to Look For: OOM errors Large .collect() operations Missing memory limits Suggestion: 3. …
How to use it
Reference it in AdaL, Claude Code, Cursor or any coding agent — nothing to install:
@skills aiskillstore/datafusion-query-advisor