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DM-13876: implement ParquetStorage butler storage mechanism #89

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May 1, 2018
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11 changes: 6 additions & 5 deletions policy/datasets.yaml
Original file line number Diff line number Diff line change
Expand Up @@ -806,14 +806,15 @@ deepCoadd_obj: #consolidated multi-band object tables from coadd
description: >
Consolidated coadd multi-band object table, a merge of
deepCoadd_meas, deepCoadd_forced_src and deepCoadd_ref tables for multiple bands.
This is a pandas DataFrame with a multi-level column index; access a particular
subcatalog as df['meas']['HSC-R'], e.g.
This is stored as a DataFrame with a multi-level column index; access a particular
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DataFrame -> ParquetTable?

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Not really; the comment here regards the fact that it is actually a multilevel pandas DataFrame that is stored in the parquet file.

subtable with, e.g. catalog.to_df(columns=dict(dataset='meas', filter='HSC-G'));
see MultilevelParquetTable documentation for more.
persistable: ignored
storage: FitsCatalogStorage
python: lsst.qa.explorer.table.ParquetTable
storage: ParquetStorage
python: lsst.qa.explorer.parquetTable.MultilevelParquetTable # pandas.DataFrame to write
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template: deepCoadd-results/merged/%(tract)d/%(patch)s/obj-%(tract)d-%(patch)s.parq
writeObjectTable_config:
persistable: Config
python: lsst.qa.explorer.writeParquet.WriteObjectTableConfig
python: lsst.qa.explorer.writeObjectTable.WriteObjectTableConfig
storage: ConfigStorage
template: config/writeObjectTable.py