| --- |
| license: cc-by-nc-4.0 |
| tags: |
| - tsfile |
| - time-series |
| - recommendation |
| - taac2026 |
| modality: timeseries |
| pretty_name: TAAC2026 Data Sample 1000 TsFile |
| configs: |
| - config_name: default |
| data_files: |
| - split: train |
| path: data/*.tsfile |
| --- |
| |
| # TAAC2026 Data Sample 1000 TsFile |
|
|
| This dataset is a TsFile conversion of |
| [`TAAC2026/data_sample_1000`](https://huggingface.co/datasets/TAAC2026/data_sample_1000), |
| the TAAC2026 demo recommendation dataset with 1,000 user-item interaction |
| records. |
|
|
| Modalities: Time-series. The source dataset is a flat Parquet file where all |
| features are top-level columns. Some top-level columns are variable-length list |
| features, so the conversion stores scalar interaction features and sequence |
| features in separate TsFile tables instead of expanding the lists into more than |
| 130,000 wide columns. |
|
|
| ## Source Dataset |
|
|
| - Original dataset: [`TAAC2026/data_sample_1000`](https://huggingface.co/datasets/TAAC2026/data_sample_1000) |
| - Source file: `demo_1000.parquet` |
| - Source license: `cc-by-nc-4.0` |
| - Source tags: `TAAC2026`, `recommendation` |
| - Source scale: 1,000 rows, 120 top-level columns, about 39 MB |
| - Source schema groups: 5 ID/label columns, 46 user integer features, 10 user dense features, 14 item integer features, and 45 domain sequence features |
|
|
| ## Converted Files |
|
|
| The upload contains 9 TsFile files under `data/`. |
|
|
| | File | Table | Rows | Notes | |
| |---|---|---:|---| |
| | `data/data_sample_1000_scalar.tsfile` | `data_sample_1000_scalar` | 1,000 | Scalar interaction features | |
| | `data/data_sample_1000_user_int_lists.tsfile` | `data_sample_1000_user_int_lists` | 11,560 | 11 user integer list features | |
| | `data/data_sample_1000_user_dense_lists.tsfile` | `data_sample_1000_user_dense_lists` | 318,538 | 10 user dense list features | |
| | `data/data_sample_1000_item_lists.tsfile` | `data_sample_1000_item_lists` | 2,086 | 1 item list feature | |
| | `data/data_sample_1000_domain_a_seq.tsfile` | `data_sample_1000_domain_a_seq` | 701,086 | 9 domain A sequence features | |
| | `data/data_sample_1000_domain_b_seq.tsfile` | `data_sample_1000_domain_b_seq` | 570,758 | 14 domain B sequence features | |
| | `data/data_sample_1000_domain_c_seq.tsfile` | `data_sample_1000_domain_c_seq` | 449,431 | 12 domain C sequence features | |
| | `data/data_sample_1000_domain_d_seq_1.tsfile` | `data_sample_1000_domain_d_seq` | 1,048,576 | Domain D sequence shard 1 | |
| | `data/data_sample_1000_domain_d_seq_2.tsfile` | `data_sample_1000_domain_d_seq` | 51,283 | Domain D sequence shard 2 | |
|
|
| The sequence tables contain 3,153,318 rows in total. `domain_d_seq` was split |
| into two TsFile shards by the TsFile conversion tool. |
|
|
| ## Schema Design |
|
|
| Scalar event table: |
|
|
| - `Time`: epoch milliseconds derived from source `timestamp * 1000` |
| - TAG columns: `event_index`, `user_id` |
| - FIELD columns: `item_id`, `label_type`, `label_time`, `event_timestamp`, and all source scalar user/item features |
|
|
| Sequence tables: |
|
|
| - `Time`: `sequence_index` within each source interaction event |
| - TAG columns: `event_index`, `user_id`, `item_id` |
| - FIELD columns: `event_timestamp`, `label_time`, `label_type`, plus the list feature values for that sequence family |
| - `event_timestamp` preserves the source `timestamp` value in seconds |
|
|
| ## Conversion Notes |
|
|
| - No source columns are intentionally dropped. |
| - Source `timestamp` is renamed to `event_timestamp` and also used to create |
| the scalar event table's TsFile `Time`. |
| - Variable-length list columns are reshaped into per-family sequence tables. |
| This preserves list positions while avoiding an extremely wide table. |
| - Missing list positions caused by unequal sequence lengths are stored as nulls. |
| - The converted layout keeps one `event_index` per original source row so users |
| can join scalar and sequence tables back to the original interaction record. |
|
|
| ## Validation |
|
|
| Local validation confirmed that all 9 TsFile files are non-empty. TsFile |
| metadata row counts match the staged Parquet row counts for every table, |
| including both shards of `data_sample_1000_domain_d_seq`. |
|
|
| ## Minimal Read Example |
|
|
| ```python |
| from tsfile import TsFileReader |
| |
| path = "data/data_sample_1000_scalar.tsfile" |
| with TsFileReader(path) as reader: |
| schemas = reader.get_all_table_schemas() |
| print(schemas.keys()) |
| ``` |
|
|
