Add ctu-restbase
Browse files- ctu-restbase/README.md +34 -0
- ctu-restbase/db/generalinfo.parquet +3 -0
- ctu-restbase/db/geographic.parquet +3 -0
- ctu-restbase/db/location.parquet +3 -0
- ctu-restbase/manifest.yaml +21 -0
- ctu-restbase/schema.svg +77 -0
- ctu-restbase/tasks/restbase-original/manifest.yaml +9 -0
- ctu-restbase/tasks/restbase-original/test.parquet +3 -0
- ctu-restbase/tasks/restbase-original/train.parquet +3 -0
- ctu-restbase/tasks/restbase-original/val.parquet +3 -0
ctu-restbase/README.md
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---
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tags:
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- relbench
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- relational-deep-learning
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pretty_name: ctu-restbase
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---
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# ctu-restbase
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A database of restaurants in the San Francisco Bay Area. Sourced from the CTU Prague Relational Learning Repository (https://relational.fel.cvut.cz/).
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## Schema
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Open [`schema.svg`](schema.svg) for a zoomable view: each table lists all of its columns and types, with primary keys, foreign keys, and the foreign-key edges between tables.
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Splits: validation `2262-04-11`, test `2262-04-11` (rows up to a split's timestamp are the inputs for that split).
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## Tasks
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| task | kind | type | description |
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|---|---|---|---|
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| `restbase-original` | external | regression | Predict the `review` of each `generalinfo`. (random split) |
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## Loading
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```python
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import relbench
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ds = relbench.load_dataset("ctu-restbase")
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task = relbench.load_task("ctu-restbase", "<task>")
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```
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Manifest layout (`manifest.yaml` + plain parquet); see the RelBench [CONTRIBUTING guide](https://github.com/snap-stanford/relbench/blob/main/CONTRIBUTING.md).
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ctu-restbase/db/generalinfo.parquet
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version https://git-lfs.github.com/spec/v1
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oid sha256:bef60a17fdc721ff3561625f328078195890f5ab5adb1cb4e1932775ada90a4f
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size 185925
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ctu-restbase/db/geographic.parquet
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version https://git-lfs.github.com/spec/v1
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oid sha256:3101b4d70cb88eba3545c60b51574d4f94781fa9735b20d7e3aa24c63a9a9d27
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size 6050
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ctu-restbase/db/location.parquet
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version https://git-lfs.github.com/spec/v1
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oid sha256:b1a3cb8390ebdd48843958160f175056a3eef5c5a838df09b0ea66389126587e
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size 208982
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ctu-restbase/manifest.yaml
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name: ctu-restbase
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manifest_version: 1
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description: A database of restaurants in the San Francisco Bay Area. Sourced from the CTU Prague Relational Learning Repository (https://relational.fel.cvut.cz/).
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val_timestamp: '2262-04-11'
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test_timestamp: '2262-04-11'
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tables:
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generalinfo:
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pkey: __PK__
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time_col: null
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fkeys:
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FK_geographic_city: geographic
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location:
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pkey: __PK__
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time_col: null
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fkeys:
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FK_geographic_city: geographic
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FK_generalinfo_id_restaurant: generalinfo
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geographic:
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pkey: __PK__
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time_col: null
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fkeys: {}
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ctu-restbase/schema.svg
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ctu-restbase/tasks/restbase-original/manifest.yaml
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name: restbase-original
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kind: external
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task_type: regression
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description: Predict the `review` of each `generalinfo`. (random split)
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entity_table: generalinfo
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entity_col: __PK__
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target_col: review
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timedelta: 0 days
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manifest_version: 1
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ctu-restbase/tasks/restbase-original/test.parquet
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version https://git-lfs.github.com/spec/v1
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oid sha256:7db016b99f1d7da392c896e6a4118ba2be521e795c154beaf64ef938fabac185
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size 7535
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ctu-restbase/tasks/restbase-original/train.parquet
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version https://git-lfs.github.com/spec/v1
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oid sha256:68fa3881cb8e6c5af5c2d4fe18f4c15788216bd2dece60f7b7f6dec895a478f5
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size 49969
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ctu-restbase/tasks/restbase-original/val.parquet
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version https://git-lfs.github.com/spec/v1
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oid sha256:c1638e9955deeee1ac842ebfb41859c7d6ab648f9aff0839df57f71e38fdd2f9
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size 7582
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