databricks-system-tables

Extract operational insights from Databricks Unity Catalog system tables via SQL queries.

1|Updated Jan 6, 2026

Search Tags:#cost-analysis #audit-logs #databricks #unity-catalog #data-lineage #system-tables #query-history

Ready to run

npx skills add https://github.com/mats16/briclaude --skill databricks-system-tables

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: databricks-system-tables
Source: https://github.com/mats16/briclaude/tree/main/skills/databricks-system-tables
Command: npx skills add https://github.com/mats16/briclaude --skill databricks-system-tables

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Databricks System Tables は Unity Catalog の system カタログに格納された運用データを分析・調査するための分析支援ツールです。コスト分析、監査ログ調査、ジョブ実行履歴、テーブルリネージュ、クエリ履歴の分析など、運用データを横断的に読み解く目的で活用されます。

Core Features & Use Cases

コスト分析と課金見積もり: system.billing の usage と list_prices を組み合わせてコスト動向を分析。
監査とセキュリティ調査: system.access の audit や table_lineage でユーザー操作を追跡。
ジョブ・リネージュ/パフォーマンス: system.lakeflow の job_run_timeline などと連携してジョブ実行履歴を把握。
クエリ履歴とパフォーマンス: system.query.history を用いた長時間クエリの特定と最適化提案。
リネージュとリソース追跡: system.compute の clusters/warehouses の変更履歴と資源利用の関係を把握。

Quick Start

Analyze the Unity Catalog system tables to surface cost, audit, and lineage insights from your workspace.

Frequently Asked Questions about databricks-system-tables

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

FAQPage Schema

How do I analyze Databricks Unity Catalog system tables for cost and audit insights?▼

You can analyze Databricks Unity Catalog system tables by running deterministic SQL queries against schemas like system.billing and system.access. This approach extracts operational insights for cost analysis, audit investigations, and data lineage tracking to produce structured reports.

What is the best way to track long-running queries in Databricks?▼

The best way to track long-running queries in Databricks is by querying the system.query.history table. This identifies prolonged query executions and supports performance optimization suggestions based on historical execution metadata.

Can I use system tables to investigate user access and table lineage in Unity Catalog?▼

Yes, you can use system tables to investigate user access and table lineage in Unity Catalog. Querying system.access provides audit logs of user operations, while table_lineage tracks data flow across your workspace.

Does this approach require external tools to generate billing estimates from Databricks usage data?▼

No external tools are required to generate billing estimates from Databricks usage data. You can directly join the system.billing usage table with list_prices using standard SQL to analyze cost trends within your environment.

How do I monitor job run timelines and compute resource changes in Databricks?▼

You monitor job run timelines and compute resource changes in Databricks by querying system.lakeflow and system.compute. This reveals job execution history and correlates cluster or warehouse modifications with resource utilization.