| --- |
| license: cc-by-4.0 |
| pretty_name: Retail star schema with a verified answer key |
| language: |
| - en |
| size_categories: |
| - 1M<n<10M |
| task_categories: |
| - table-question-answering |
| tags: |
| - synthetic |
| - retail |
| - star-schema |
| - olap |
| - clickhouse |
| - duckdb |
| - text-to-sql |
| - benchmark |
| - evaluation |
| configs: |
| - config_name: questions |
| data_files: answer_key/answer_key.csv |
| default: true |
| - config_name: orders |
| data_files: data/parquet/orders.parquet |
| - config_name: order_lines |
| data_files: data/parquet/order_lines.parquet |
| - config_name: returns |
| data_files: data/parquet/returns.parquet |
| - config_name: dim_date |
| data_files: data/parquet/dim_date.parquet |
| - config_name: dim_product |
| data_files: data/parquet/dim_product.parquet |
| - config_name: dim_customer |
| data_files: data/parquet/dim_customer.parquet |
| - config_name: dim_store |
| data_files: data/parquet/dim_store.parquet |
| --- |
| |
| # Retail star schema with an answer key |
|
|
| A synthetic retail sales star schema for ClickHouse (1.2 million orders, 3 million order lines, January 2023 to June |
| 2026) and 60 questions, each with its SQL and one checked answer. It tests whether an agent, a cube or a model |
| computes the right number. Read `DATASET_CARD.md` first: the tables, the measure definitions the answers use, and how the |
| data was made and checked. |
|
|
| ## Download |
|
|
| The whole package as one file: [`retail_star_v1.zip`](https://huggingface.co/datasets/misatadata/retail-star-answer-key/resolve/main/retail_star_v1.zip) (128 MB). |
| The same files, laid out as below, with the Hugging Face CLI: |
|
|
| ```bash |
| hf download misatadata/retail-star-answer-key --repo-type dataset --local-dir retail-star |
| ``` |
|
|
| ## What is in the package |
|
|
| | Path | What | |
| |---|---| |
| | `data/parquet/*.parquet` | one file per table, zstd, exact decimals | |
| | `data/csv/*.csv` | the same tables as CSVWithNames, `\N` for NULL | |
| | `data/ROWCOUNTS`, `data/MANIFEST.json` | rows per table; every file's rows, size and SHA-256 | |
| | `clickhouse/ddl.sql`, `clickhouse/load.sh` | the tables (MergeTree, pinned types) and a loader that checks row counts | |
| | `answer_key/questions.jsonl` | one record per question: the question, the measure definitions it uses, SQL for ClickHouse and DuckDB, the expected value, its tolerance, the traps it tests | |
| | `answer_key/answer_key.md`, `answer_key.csv` | the same, as a table | |
| | `DATASET_CARD.md` | tables, definitions, as-of date, how it was made and verified | |
| | `PATTERNS.md` | the planted patterns and traps, measured; for the person grading, not for agents | |
| | `calibration/` | the price calibration: aggregates of US retail listings per kind of product, and the script that makes them | |
| | `LICENSE` | CC BY 4.0: use, share and adapt it for any purpose, with credit | |
|
|
| ## Load into ClickHouse |
|
|
| With ClickHouse running in Docker as `clickhouse`: |
|
|
| ```bash |
| CLICKHOUSE_CLIENT="docker exec -i clickhouse clickhouse-client" clickhouse/load.sh parquet |
| ``` |
|
|
| With `clickhouse-client` on the path, `clickhouse/load.sh parquet` is enough. `clickhouse/load.sh csv` loads the CSV |
| files instead. The loader creates the tables, loads each one, and checks every table's row count against |
| `data/ROWCOUNTS`. It skips tables it has already loaded; `--reset` drops them and starts over. `CH_DATABASE` picks a |
| database other than `default`. |
|
|
| Plain `INSERT ... FORMAT Parquet` works as well; keep `input_format_null_as_default=0` so NULL customer ids and segments |
| stay NULL instead of becoming 0 and ''. |
|
|
| ## Query without loading |
|
|
| DuckDB reads the Parquet files directly, and every question has DuckDB SQL beside the ClickHouse SQL: |
|
|
| ```sql |
| CREATE VIEW order_lines AS SELECT * FROM 'data/parquet/order_lines.parquet'; |
| ``` |
|
|
| ## Grading |
|
|
| Compare an answer with `expected` within `tolerance` (`questions.jsonl`): money exact to the cent, averages of money |
| within ±0.01, ratios within ±0.0001, members by exact name. Every answer was computed on ClickHouse 24.3, 26.8 and 26.9 |
| and on DuckDB and checked equal, and a sample was recomputed without SQL. `PATTERNS.md` lists what a wrong answer |
| usually looks like, so a failure can be put down to the agent, the model or the dataset. |
|
|
| ## License |
|
|
| [CC BY 4.0](https://creativecommons.org/licenses/by/4.0/) (`LICENSE`). Credit it as "Retail star schema with a verified |
| answer key, generated with Misata Studio (misata.studio), CC BY 4.0". |
|
|
