feat: export to parquet #424
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mikeldking
reviewed
Mar 23, 2023
mikeldking
approved these changes
Mar 28, 2023
src/phoenix/core/model.py
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| def export_events_as_parquet_file( | ||
| self, | ||
| rows: Mapping[DatasetType, Iterable[int]], | ||
| parquet_file: BinaryIO, | ||
| ) -> None: | ||
| """ | ||
| Given row numbers, exports dataframe subset into parquet file. | ||
| Duplicate rows are removed. | ||
|
|
||
| Parameters | ||
| ---------- | ||
| rows: Mapping[DatasetType, Iterable[int]] | ||
| mapping of dataset type to list of row numbers | ||
| parquet_file: file handle | ||
| output parquet file handle | ||
| """ | ||
| pd.concat( | ||
| dataset.export_events(rows.get(dataset_type, ())) | ||
| for dataset_type, dataset in self.__datasets.items() | ||
| if dataset is not None | ||
| ).to_parquet(parquet_file, index=False) |
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It might be important to encode the dataset type into the parquet file itself so that if the user is exporting a cluster that has both, they can distinguish them. I posed a similar question on the main platform ticket and I think that makes sense.
Context: https://github.com/Arize-ai/arize/issues/19710
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thanks for the heads-up. will revisit in a future PR
src/phoenix/datasets/dataset.py
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| self.__original_column_indices = [ | ||
| dataframe.columns.get_loc(column_name) for column_name in original_column_names | ||
| ] |
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How is this information passed back to the server runtime?
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good call out. currently this does nothing given that datasets are initialized (and validated) twice. will remove from this PR and revisit in the future
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resolves #417
resolves #432
clean-ups:
os.pathwithpathlibEvents.py