| ---
|
| license: cc-by-nc-4.0
|
| task_categories:
|
| - text-generation
|
| - question-answering
|
| language:
|
| - en
|
| tags:
|
| - sql
|
| - database
|
| - query-optimization
|
| - explain-analyze
|
| - postgresql
|
| - mysql
|
| - clickhouse
|
| - cockroachdb
|
| - dba
|
| - fine-tuning
|
| pretty_name: "Enterprise Database Query Plan Optimization & Remediation Traces"
|
| size_categories:
|
| - 100<n<1K
|
| ---
|
|
|
| # Enterprise Database Query Plan Optimization & Remediation Traces (Community Preview)
|
|
|
| <p align="center">
|
| <img src="dataset_product_cover_1024.png" alt="Dataset Banner" width="700"/>
|
| </p>
|
|
|
| ## Overview
|
| High-concurrency database workloads frequently degrade due to optimizer plan misestimations, unindexed correlated joins, merge-sort memory spills, and non-sargable expressions.
|
|
|
| This repository hosts the **Community Preview (250 verified traces)** of an architectural fine-tuning dataset spanning **PostgreSQL 16, MySQL 8.0, ClickHouse 24, CockroachDB, MariaDB, and SQLite**. Each record pairs an authentic production query regression and raw execution plan (`EXPLAIN ANALYZE`) with chain-of-thought architectural diagnosis, actionable remediation DDL, and dialect-compliant optimized queries.
|
|
|
| ---
|
|
|
| ## Dataset Splits & Commercial Licensing
|
|
|
| | Split | Records | Format | Primary Use Case | License |
|
| | :--- | :--- | :--- | :--- | :--- |
|
| | **Community Evaluation** (This Repo) | 250 | Parquet | Benchmarking, zero-shot eval, research | **CC BY-NC 4.0** |
|
| | **Enterprise Commercial Corpus** | 2,500 | Parquet + JSONL | Production fine-tuning (SFT/DPO), commercial DBA agents | **Commercial Enterprise License** |
|
|
|
| ### Complete Enterprise Corpus (2,500 Records)
|
| For production model deployment, proprietary agent training, or private RAG pipelines without non-commercial restrictions:
|
|
|
| 👉 **[Acquire Enterprise Commercial License & Dataset via Dodo Payments](https://checkout.dodopayments.com/buy/pdt_0NqD7nyGBW7fVDMd1Fm2l)**
|
|
|
| ---
|
|
|
| ## Data Structure & Schema
|
|
|
| ```json
|
| {
|
| "database_engine": "string",
|
| "slow_query": "string",
|
| "execution_plan": "string",
|
| "diagnostic_thought": "string",
|
| "remediation_ddl": "string",
|
| "optimized_query": "string"
|
| }
|
| ```
|
|
|
| ### Field Definitions
|
|
|
| | Field | Data Type | Description |
|
| | :--- | :--- | :--- |
|
| | `database_engine` | `string` | Target engine dialect & exact version (e.g., `PostgreSQL 16.2`, `ClickHouse 24.3`). |
|
| | `slow_query` | `string` | Realistic unoptimized SQL query triggering runtime performance degradation. |
|
| | `execution_plan` | `string` | Raw optimizer output (`EXPLAIN (ANALYZE, BUFFERS)` or JSON plan) exposing node bottlenecks. |
|
| | `diagnostic_thought` | `string` | Step-by-step reasoning diagnosing node cost, row estimate deltas, and I/O buffer behavior. |
|
| | `remediation_ddl` | `string` | Executable DDL statements (`CREATE INDEX CONCURRENTLY`, table parameter tuning). |
|
| | `optimized_query` | `string` | Performant rewritten query strictly adhering to engine dialect grammar. |
|
|
|
| ---
|
|
|
| ## Quickstart (Hugging Face Datasets)
|
|
|
| ```python
|
| from datasets import load_dataset
|
|
|
| # Load Community Preview
|
| dataset = load_dataset("ayushjoshi2012/sql-optimization-diagnostic-traces", split="train")
|
|
|
| # Inspect a single diagnostic trace
|
| sample = dataset[0]
|
| print(f"Engine: {sample['database_engine']}")
|
| print(f"Slow Query:\n{sample['slow_query']}")
|
| print(f"Diagnosis:\n{sample['diagnostic_thought']}")
|
| print(f"Remediation DDL:\n{sample['remediation_ddl']}")
|
| print(f"Rewritten Query:\n{sample['optimized_query']}")
|
| ```
|
|
|
| ---
|
|
|
| ## Core Domain Taxonomy
|
|
|
| Traces are generated across representative enterprise schema designs:
|
| * **Fintech & Ledger Core:** Double-entry ledger scans, implicit UUID-to-integer type coercion, balance aggregations.
|
| * **IoT & Telematics:** Granule skip-index mismatches, partition decompression stalls, time-bucket groupings.
|
| * **B2B SaaS & Security:** High-offset tenant audit logs, soft-delete booleans, unindexed RBAC joins.
|
| * **Healthcare & EHR:** Unindexed composite foreign keys, leading-wildcard text filters, outdated optimizer statistics.
|
| * **Freight & Global Logistics:** Disk-spilling merge joins on departure timestamps, Cartesian row multiplication.
|
| * **AdTech & Gaming Telemetry:** Unindexed streaming click joins, unbounded window function sorts, leaderboard lock contention.
|
|
|
| ---
|
|
|
| ## Citation & Contact
|
| For inquiries regarding custom synthetic domain generation, enterprise site licenses, or data additions, please commentinitiate a new discussion. |
