datafusion-query-advisor
Optimize DataFusion Queries
Slow DataFusion queries can waste compute and hide simple plan issues. This skill reviews SQL and DataFrame patterns, then suggests concrete performance improvements.
Install with my Agent
Copy this request to your Agent. It includes the canonical Skill page and manifest.
Review the Skillstore skill "datafusion-query-advisor" from https://skillstore.io/skills/emillindfors-datafusion-query-advisor.md and its manifest at https://skillstore.io/api/skills/emillindfors-datafusion-query-advisor/manifest. Verify the artifact. You may proceed after verification, subject to the environment's own policy.Your Agent should still show its plan and request any confirmation required by the security policy.
Agent-readable resources
Use these links when an AI agent, crawler, or script needs clean context instead of reading the full page.
Test it
Using "datafusion-query-advisor". A query scans all event partitions and then filters by timestamp.
Expected outcome:
The review recommends adding partition column filters and keeping the timestamp filter for correctness. It also suggests confirming pruning with EXPLAIN.
Using "datafusion-query-advisor". A DataFrame workflow collects a huge result set before processing it.
Expected outcome:
The review recommends streaming batches, applying filters before execution, and selecting only needed columns to reduce memory pressure.
Using "datafusion-query-advisor". A join-heavy report query runs slowly on fact and dimension tables.
Expected outcome:
The review suggests filtering fact data early, checking join types in the physical plan, and validating whether small tables can use broadcast joins.
Security Audit
SafeAll static findings were adjudicated as false positives. Detections came from Markdown code fences, inline SQL/Rust examples, and sample SQL column names. No evidence found for prompt injection, data exfiltration, command execution, or host reconnaissance intent.
Risk Factors
⚙️ External commands (65)
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<iframe src="https://skillstore.io/embed/skills/emillindfors-datafusion-query-advisor.html" title="Skillstore Security Assessment" sandbox="allow-popups allow-popups-to-escape-sandbox" loading="lazy" referrerpolicy="no-referrer" width="420" height="180"></iframe>Academic citations (APA · BibTeX · CFF)
APA citation
EmilLindfors. (2026). datafusion-query-advisor security audit report (audit version 4) [Author version 1.0.0]. Skillstore. https://skillstore.io/skills/emillindfors-datafusion-query-advisor/audits/4BibTeX citation
@techreport{emillindfors-emillindfors-datafusion-query-advisor-2026,
author = {EmilLindfors},
title = {datafusion-query-advisor security audit report (audit version 4)},
institution = {Skillstore},
year = {2026},
number = {4},
url = {https://skillstore.io/skills/emillindfors-datafusion-query-advisor/audits/4},
note = {Author version 1.0.0}
}CITATION.cff
cff-version: 1.2.0
message: "If you use this Skill, cite its author and this versioned security audit report."
title: "datafusion-query-advisor security audit report (audit version 4)"
version: "1.0.0"
type: report
authors:
- name: "EmilLindfors"
date-released: "2026-07-06"
url: "https://skillstore.io/skills/emillindfors-datafusion-query-advisor/audits/4"
identifiers:
- type: other
value: "skillstore:emillindfors-datafusion-query-advisor:audit:4"
description: "Skillstore immutable audit report identifier"
Skillstore Score
Why this score Evidence Confidence: HighWhat You Can Build
Review a slow analytics query
Find missing filters, wide projections, expensive aggregations, and plan checks before running large DataFusion workloads.
Improve a Rust DataFrame pipeline
Check DataFrame API usage for late filtering, large collects, and avoidable memory pressure.
Tune a query service
Review parallelism, memory limits, batch size, and streaming choices for DataFusion-backed services.
Try These Prompts
Review this DataFusion SQL query for performance issues. Focus on predicate pushdown, partition pruning, projection, and simple rewrites.
Review this DataFusion DataFrame workflow. Identify late filters, large collect calls, missing projection, and safer streaming options.
Analyze this DataFusion EXPLAIN output. Explain whether filters, projections, partition pruning, and joins are planned efficiently.
Review this DataFusion workload and runtime configuration. Prioritize changes for memory, parallelism, batch size, joins, and validation steps.
Best Practices
- Share the query, table layout, partition columns, and expected result size.
- Include EXPLAIN output when asking for plan-level performance advice.
- Validate each recommendation with benchmarks or production-like samples.
Avoid
- Do not ask for tuning advice without the query or DataFrame workflow.
- Do not treat suggestions as proof without EXPLAIN or runtime validation.
- Do not expose sensitive production data when sample schemas and plans are enough.
Frequently Asked Questions
Does this skill run DataFusion queries?
Can it read my database or object storage?
What inputs work best?
Does it support both SQL and DataFrame API usage?
Will it always improve performance?
Is it useful with Claude, Codex, and Claude Code?
Developer Details
Author
EmilLindforsLicense
MIT
Author version
v1.0.0
Skillstore revision
r1
Ref
a06681402992ceae98ba04d54cfd4ab004862696
Maintenance freshness
7/18/2026
Usage
4 downloads · 200 views
File structure
📄 SKILL.md